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Yousefian M, Hashemi M, Eskandarpour V, Zarghi A, Hadizadeh F, Ghodsi R. New indolin-2-ones, possessing sunitinib scaffold as HDAC inhibitors and anti-cancer agents with potential VEGFR inhibition activity; design, synthesis and biological evaluation. Bioorg Chem 2025; 156:108231. [PMID: 39904079 DOI: 10.1016/j.bioorg.2025.108231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2024] [Revised: 01/23/2025] [Accepted: 01/29/2025] [Indexed: 02/06/2025]
Abstract
New series of indolin-2-ones possessing sunitinib scaffold and a hydroxamic acid moiety were designed and synthesized as inhibitors of HDAC, demonstrating significant anti-cancer properties with potential VEGFR inhibition, using sunitinib and vorinostat as the lead compounds. The newly synthesized compounds incorporate the sunitinib framework along with functional groups derived from vorinostat, thus they can be named the rigid analogs of vorinostat. The cytotoxic effects of these compounds were assessed against two cancer cell lines, HCT116 (human colon cancer) and HT29 (human colon adenocarcinoma), as well as NIH (a normal fibroblast cell line). A majority of the compounds displayed notable cytotoxicity towards HT-29 and HCT-116, with IC50 values ranging from 1.78 to 38.54 µM notably, compound 13c exhibited the highest anti-proliferative effect against HT-29, with an IC50 of 1.78 µM, comparable to or exceeding that of the reference drugs, sunitinib and vorinostat. This compound reduced the expression levels of VEGFR-2 and phosphorylated VEGFR-2 (pVEGFR-2) by approximately 80 % and inhibited the HDAC1 enzyme (IC50 = 1.07 µM), indicating its anticancer activity through the targeting of these enzymes. Further cellular mechanism investigations revealed that compound 13c induced substantial apoptosis in HCT-116 cells, with a total apoptotic cell percentage of 41.1 % in treated cells (2.59 µM), compared to negative control (3.68 %)). The CAM assay also indicated that 13c possesses antiangiogenic property similar to that of sunitinib. Additionally, a molecular docking simulation supported the initial design strategy and suggested a common mode of interaction of compound 13c at the binding sites of VEGFR-2 and HDAC1. These findings suggested that 13c could be as a promising lead targeting VEGFR-2 and HDAC1. Therefore, it deserved further investigation for cancer treatment.
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Affiliation(s)
- Mozhdeh Yousefian
- Biotechnology Research Center Pharmaceutical Technology Institute Mashhad University of Medical Sciences Mashhad Iran; Department of Medicinal Chemistry School of Pharmacy Mashhad University of Medical Sciences Mashhad Iran
| | - Maryam Hashemi
- Nanotechnology Research Center Pharmaceutical Technology Institute Mashhad University of Medical Sciences Mashhad Iran; Department of Pharmaceutical Biotechnology School of Pharmacy Mashhad University of Medical Sciences Iran
| | - Vahid Eskandarpour
- Department of Medicinal Chemistry School of Pharmacy Mashhad University of Medical Sciences Mashhad Iran
| | - Afshin Zarghi
- Department of Medicinal Chemistry School of Pharmacy Shaheed Beheshti University of Medical Sciences Tehran Iran
| | - Farzin Hadizadeh
- Biotechnology Research Center Pharmaceutical Technology Institute Mashhad University of Medical Sciences Mashhad Iran; Department of Medicinal Chemistry School of Pharmacy Mashhad University of Medical Sciences Mashhad Iran
| | - Razieh Ghodsi
- Biotechnology Research Center Pharmaceutical Technology Institute Mashhad University of Medical Sciences Mashhad Iran; Department of Medicinal Chemistry School of Pharmacy Mashhad University of Medical Sciences Mashhad Iran.
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102
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Ali S, Shaikh S, Ahmad K, Choi I. Identification of active compounds as novel dipeptidyl peptidase-4 inhibitors through machine learning and structure-based molecular docking simulations. J Biomol Struct Dyn 2025; 43:1611-1620. [PMID: 38100571 DOI: 10.1080/07391102.2023.2292299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 11/23/2023] [Indexed: 12/17/2023]
Abstract
The enzyme dipeptidyl peptidase 4 (DPP4) is a potential therapeutic target for type 2 diabetes (T2DM). Many synthetic anti-DPP4 medications are available to treat T2DM. The need for secure and efficient medicines has been unmet due to the adverse side effects of existing DPP4 medications. The present study implemented a combined approach to machine learning and structure-based virtual screening to identify DPP4 inhibitors. Two ML models were trained based on DPP4 IC50 datasets. The ML models random forest (RF) and multilayer perceptron (MLP) neural network showed good accuracy, with the area under the curve being 0.93 and 0.91, respectively. The natural compound library was screened through ML models, and 1% (217) of compounds were selected for further screening. Structure-based virtual screening was performed along with positive control sitagliptin to obtain more specific and selective leads for DPP4. Based on binding affinity, drug-likeness properties, and interaction with DPP4, Z-614 and Z-997 compounds showed high binding affinity and specificity in the catalytic pocket of DPP4. Finally, the stability conformation of the DPP4 enzyme complex was checked by a molecular dynamics (MD) simulation. The MD simulation showed that both compounds bind better in the catalytic pocket, but the Z-614 compound altered the DPP4 native conformation. Therefore, Z-614 showed a high deviation in the backbone. This combined approach (ML and structure-based) study reported that Z-997 binds most stably to DPP4 in their catalytic pocket with a binding free energy of -70.3 kJ/mol, suggesting its therapeutic potential as a treatment option for T2DM disease.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Shahid Ali
- Department of Medical Biotechnology, Yeungnam University, Gyeongsan, South Korea
- Research Institute of Cell Culture, Yeungnam University, Gyeongsan, South Korea
| | - Sibhghatulla Shaikh
- Department of Medical Biotechnology, Yeungnam University, Gyeongsan, South Korea
- Research Institute of Cell Culture, Yeungnam University, Gyeongsan, South Korea
| | - Khurshid Ahmad
- Department of Medical Biotechnology, Yeungnam University, Gyeongsan, South Korea
- Research Institute of Cell Culture, Yeungnam University, Gyeongsan, South Korea
| | - Inho Choi
- Department of Medical Biotechnology, Yeungnam University, Gyeongsan, South Korea
- Research Institute of Cell Culture, Yeungnam University, Gyeongsan, South Korea
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103
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Rasul HO, Ghafour DD, Aziz BK, Hassan BA, Rashid TA, Kivrak A. Decoding Drug Discovery: Exploring A-to-Z In Silico Methods for Beginners. Appl Biochem Biotechnol 2025; 197:1453-1503. [PMID: 39630336 DOI: 10.1007/s12010-024-05110-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/19/2024] [Indexed: 03/29/2025]
Abstract
The drug development process is a critical challenge in the pharmaceutical industry due to its time-consuming nature and the need to discover new drug potentials to address various ailments. The initial step in drug development, drug target identification, often consumes considerable time. While valid, traditional methods such as in vivo and in vitro approaches are limited in their ability to analyze vast amounts of data efficiently, leading to wasteful outcomes. To expedite and streamline drug development, an increasing reliance on computer-aided drug design (CADD) approaches has merged. These sophisticated in silico methods offer a promising avenue for efficiently identifying viable drug candidates, thus providing pharmaceutical firms with significant opportunities to uncover new prospective drug targets. The main goal of this work is to review in silico methods used in the drug development process with a focus on identifying therapeutic targets linked to specific diseases at the genetic or protein level. This article thoroughly discusses A-to-Z in silico techniques, which are essential for identifying the targets of bioactive compounds and their potential therapeutic effects. This review intends to improve drug discovery processes by illuminating the state of these cutting-edge approaches, thereby maximizing the effectiveness and duration of clinical trials for novel drug target investigation.
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Affiliation(s)
- Hezha O Rasul
- Department of Pharmaceutical Chemistry, College of Science, Charmo University, Peshawa Street, Chamchamal, 46023, Sulaimani, Iraq.
| | - Dlzar D Ghafour
- Department of Medical Laboratory Science, College of Science, Komar University of Science and Technology, 46001, Sulaimani, Iraq
- Department of Chemistry, College of Science, University of Sulaimani, 46001, Sulaimani, Iraq
| | - Bakhtyar K Aziz
- Department of Nanoscience and Applied Chemistry, College of Science, Charmo University, Peshawa Street, Chamchamal, 46023, Sulaimani, Iraq
| | - Bryar A Hassan
- Computer Science and Engineering Department, School of Science and Engineering, University of Kurdistan Hewler, KRI, Iraq
- Department of Computer Science, College of Science, Charmo University, Peshawa Street, Chamchamal, 46023, Sulaimani, Iraq
| | - Tarik A Rashid
- Computer Science and Engineering Department, School of Science and Engineering, University of Kurdistan Hewler, KRI, Iraq
| | - Arif Kivrak
- Department of Chemistry, Faculty of Sciences and Arts, Eskisehir Osmangazi University, Eskişehir, 26040, Turkey
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Chowdhury R, Bhuia S, Rakib AI, Al Hasan S, Shill MC, El-Nashar HAS, El-Shazly M, Islam MT. Gigantol, a promising natural drug for inflammation: a literature review and computational based study. Nat Prod Res 2025; 39:1241-1257. [PMID: 38623737 DOI: 10.1080/14786419.2024.2340042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 03/18/2024] [Accepted: 03/26/2024] [Indexed: 04/17/2024]
Abstract
Gigantol, a bibenzyl compound extracted from various medicinal plants, has shown a number of biological activities, making it an attractive candidate for potential medical applications. This systematic review aims to shed light on gigantol's promising role in inflammation treatment and its underlying mechanisms. Gigantol exhibits potential anti-inflammatory properties in pre-clinical pharmacological test systems. It effectively reduced the levels of pro-inflammatory markers and arachidonic acid metabolites through various pathways, such as NF-κB, AKT, PI3K, and JNK/cPLA2/12-LOX. The in-silico investigations demonstrated that the MMP-13 enzyme served as the most promising target for gigantol with highest binding affinity (docking score = -8.8 kcal/mol). Encouragingly, the absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis of gigantol confirmed its compatibility with the necessary physiochemical, pharmacokinetic, and toxicity properties, bolstering its potential as a drug candidate. Gigantol, with its well-documented anti-inflammatory properties, could be a promising agent for treating inflammation in the near future.
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Affiliation(s)
- Raihan Chowdhury
- Department of Pharmacy, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
- Bioluster Research Center, Dhaka, Bangladesh
| | - Shimul Bhuia
- Department of Pharmacy, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
- Bioluster Research Center, Dhaka, Bangladesh
| | - Asraful Islam Rakib
- Department of Pharmacy, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
| | - Sakib Al Hasan
- Department of Pharmacy, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
| | - Manik Chandra Shill
- Department of Pharmaceutical Sciences, North South University, Dhaka, Bangladesh
| | - Heba A S El-Nashar
- Department of Pharmacognosy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt
| | - Mohamed El-Shazly
- Department of Pharmacognosy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt
| | - Muhammad Torequl Islam
- Department of Pharmacy, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh
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105
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Avolio E, Bassani B, Campanile M, Mohammed KA, Muti P, Bruno A, Spinetti G, Madeddu P. Shared molecular, cellular, and environmental hallmarks in cardiovascular disease and cancer: Any place for drug repurposing? Pharmacol Rev 2025; 77:100033. [PMID: 40148035 DOI: 10.1016/j.pharmr.2024.100033] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2024] [Accepted: 12/17/2024] [Indexed: 03/29/2025] Open
Abstract
Cancer and cardiovascular disease (CVD) are the 2 biggest killers worldwide. Specific treatments have been developed for the 2 diseases. However, mutual therapeutic targets should be considered because of the overlap of cellular and molecular mechanisms. Cancer research has grown at a fast pace, leading to an increasing number of new mechanistic treatments. Some of these drugs could prove useful for treating CVD, which realizes the concept of cancer drug repurposing. This review provides a comprehensive outline of the shared hallmarks of cancer and CVD, primarily ischemic heart disease and heart failure. We focus on chronic inflammation, altered immune response, stromal and vascular cell activation, and underlying signaling pathways causing pathological tissue remodeling. There is an obvious scope for targeting those shared mechanisms, thereby achieving reciprocal preventive and therapeutic benefits. Major attention is devoted to illustrating the logic, advantages, challenges, and viable examples of drug repurposing and discussing the potential influence of sex, gender, age, and ethnicity in realizing this approach. Artificial intelligence will help to refine the personalized application of drug repurposing for patients with CVD. SIGNIFICANCE STATEMENT: Cancer and cardiovascular disease (CVD), the 2 biggest killers worldwide, share several underlying cellular and molecular mechanisms. So far, specific therapies have been developed to tackle the 2 diseases. However, the development of new cardiovascular drugs has been slow compared with cancer drugs. Understanding the intersection between pathological mechanisms of the 2 diseases provides the basis for repurposing cancer therapeutics for CVD treatment. This approach could allow the rapid development of new drugs for patients with CVDs.
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Affiliation(s)
- Elisa Avolio
- Bristol Heart Institute, Laboratory of Experimental Cardiovascular Medicine, Translational Health Sciences, Bristol Medical School, University of Bristol, United Kingdom.
| | - Barbara Bassani
- Laboratory of Innate Immunity, Unit of Molecular Pathology, Biochemistry, and Immunology, IRCCS MultiMedica, Milan, Italy
| | - Marzia Campanile
- Laboratory of Cardiovascular Pathophysiology - Regenerative Medicine, IRCCS MultiMedica, Milan, Italy; Department of Biosciences, University of Milan, Milan, Italy
| | - Khaled Ak Mohammed
- Bristol Heart Institute, Laboratory of Experimental Cardiovascular Medicine, Translational Health Sciences, Bristol Medical School, University of Bristol, United Kingdom; Department of Cardiothoracic Surgery, Faculty of Medicine, Assiut University, Assiut, Egypt
| | - Paola Muti
- IRCCS MultiMedica, Milan, Italy; Department of Biomedical, Surgical and Dental Health Sciences, University of Milan, Italy
| | - Antonino Bruno
- Laboratory of Innate Immunity, Unit of Molecular Pathology, Biochemistry, and Immunology, IRCCS MultiMedica, Milan, Italy; Laboratory of Immunology and General Pathology, Department of Biotechnology and Life Sciences, University of Insubria, Varese, Italy.
| | - Gaia Spinetti
- Laboratory of Cardiovascular Pathophysiology - Regenerative Medicine, IRCCS MultiMedica, Milan, Italy.
| | - Paolo Madeddu
- Bristol Heart Institute, Laboratory of Experimental Cardiovascular Medicine, Translational Health Sciences, Bristol Medical School, University of Bristol, United Kingdom.
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106
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Guan H, Chen J, Yin H, Feng X, Liu C, Liu S, Li J, Li J, Cao Y, Ma C. A UHPLC-MS/MS Method Reveals the Pharmacokinetics of Deacetyl Asperulosidic Acid Methyl Ester in Rats. Biomed Chromatogr 2025; 39:e70001. [PMID: 39917783 DOI: 10.1002/bmc.70001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2024] [Revised: 12/08/2024] [Accepted: 01/03/2025] [Indexed: 05/08/2025]
Abstract
In the current study, a simple ultra-high performance liquid chromatography-tandem mass spectrometry method was developed and fully validated for the quantitation of deacetyl asperulosidic acid methyl ester in rat plasma. The plasma sample was precipitated with acetonitrile and then separated on the Waters ACQUITY UPLC HSS T3 column. The mobile phases, water and acetonitrile, were added with 0.1% formic acid. The mass spectrometry detection was performed in negative-ion multiple reaction monitoring. In the range of 1-1000 ng/mL, the linearity meets the requirements with correlation coefficient more than 0.99. The parameters of accuracy, precision, carryover, matrix effect, extraction recovery, stability, and dilution integrity are within accepted ranges. The validated method has been successfully used for pharmacokinetic study of deacetyl asperulosidic acid methyl ester in rats. After oral administration, deacetyl asperulosidic acid methyl ester was quickly absorbed into blood and reached the maximum plasma drug concentration of 4047.49 ng/mL at 2 h. The half-life of deacetyl asperulosidic acid methyl ester is 5.6 h, which suggests that it has a moderate metabolic process. Since the absolute bioavailability of deacetyl asperulosidic acid methyl ester is only 3.74%, its gastrointestinal stability, first-pass effect, and transmembrane properties remain to be studied.
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Affiliation(s)
- Huida Guan
- Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jian Chen
- Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Hao Yin
- Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xia Feng
- Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Chang Liu
- Department of Chinese Medicine Authentication, Faculty of Pharmacy, Naval Medical University, People's Liberation Army Navy, Shanghai, China
| | - Shanshan Liu
- Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jiacheng Li
- Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jingchu Li
- Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yongbing Cao
- Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Chao Ma
- Shanghai TCM-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
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107
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Wu Y, Tang K, Wang C, Song H, Zhou F, Guo Y. Establishment of interpretable cytotoxicity prediction models using machine learning analysis of transcriptome features. Acta Pharm Sin B 2025; 15:1344-1358. [PMID: 40370539 PMCID: PMC12069252 DOI: 10.1016/j.apsb.2025.02.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Revised: 09/13/2024] [Accepted: 09/14/2024] [Indexed: 05/16/2025] Open
Abstract
Cytotoxicity, usually represented by cell viability, is a crucial parameter for evaluating drug safety in vitro. Accurate prediction of cell viability/cytotoxicity could accelerate drug development in the early stage. In this study, by integrating cellular transcriptome and cell viability data using four machine learning algorithms (support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM)) and two ensemble algorithms (voting and stacking), highly accurate prediction models of 50% and 80% cell viability were developed with area under the receiver operating characteristic curve (AUROC) of 0.90 and 0.84, respectively; these models also showed good performance when utilized for diverse cell lines. Concerning the characterization of the employed Feature Genes, the models were interpreted, and the mechanisms of bioactive compounds with a narrow therapeutic index (NTI) can also be analyzed. In summary, the models established in this research exhibit superior capacity to those of previous studies; these models enable accurate high-safety substance screening via cytotoxicity prediction across cell lines. Moreover, for the first time, Cytotoxicity Signature (CTS) genes were identified, which could provide additional clues for further study of mechanisms of action (MOA), especially for NTI compounds.
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Affiliation(s)
- You Wu
- Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
- Department of Pharmacology, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Ke Tang
- Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
- Department of Pharmacology, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Chunzheng Wang
- Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
- Department of Pharmacology, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Hao Song
- Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
- Department of Pharmacology, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Fanfan Zhou
- Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
- Department of Pharmacology, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Ying Guo
- Beijing Key Laboratory of New Drug Mechanisms and Pharmacological Evaluation Study, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
- Department of Pharmacology, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
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108
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Lin JZ, Kominia M, Doorduin J, de Vries EFJ. PET imaging of the anticancer drug candidate [ 11C]trimebutine in a rat glioma model. Nucl Med Biol 2025; 142-143:108985. [PMID: 39662136 DOI: 10.1016/j.nucmedbio.2024.108985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2024] [Revised: 11/22/2024] [Accepted: 11/29/2024] [Indexed: 12/13/2024]
Abstract
PURPOSE Preclinical studies suggest that trimebutine could be a potential treatment for glioblastoma. The aim of this study was to investigate the distribution, kinetics and tumor accumulation of [11C]trimebutine. METHOD A proliferation assay and cell scratch healing assay were performed to confirm the antitumor effects of trimebutine on C6 glioma cells in-vitro. Trimebutine was subsequently labeled with 11C. The distribution and kinetics of [11C]trimebutine in health rats and rats with an orthotopic C6 glioma were evaluated by ex-vivo gamma counting and positron emission tomography, respectively. Blocking experiments with an excess of unlabeled trimebutine or the μ-opioid receptor ligand cyprodime were employed to determine if trimebutine exhibits saturable binding in the brain. In addition, plasma stability of the tracer was assessed. RESULTS The proliferation assay and cell scratch healing assay confirmed that trimebutine has anti-tumor effects in-vitro. [11C]Trimebutine with a radiochemical purity >98 % was synthesized in 15 ± 5 % radiochemical yield. In peripheral organs, the highest accumulation of the tracer was detected in excretion organs. In the brain, the highest tracer uptake was observed in the brainstem and the lowest in the hypothalamus, although differences between regions were small. PET imaging showed rapid brain uptake of [11C]trimebutine, followed by a gradual washout. Administration of an intravenous dose of trimebutine (10 mg/kg) significantly decreased the uptake in all brain regions (p < 0.05), except midbrain. Likewise, administration of cyprodime (2 mg/kg) significantly reduced [11C]trimebutine uptake in the brain (p < 0.01). However, uptake of [11C]trimebutine in the tumor was not significantly different from its brain uptake in rats bearing an orthotopic C6 glioma. The percentage of intact [11C]trimebutine at 60 min post injection was only 1.7 ± 0.6 %. CONCLUSION Trimebutine exhibits inhibitory effects on the growth and migration of glioma cells in a dose- and time-dependent manner. [11C]Trimebutine was able to penetrate the blood-brain barrier in rats and tracer uptake could be significantly reduced by administration of a μ-opioid receptor antagonist. However, [11C]trimebutine failed to selectively accumulate in orthotopic C6 glioma, which could be caused by low expression levels of the drug target in these tumors, or by fast metabolism of the tracer.
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Affiliation(s)
- Jia-Zhe Lin
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center, Groningen, the Netherlands; Department of Neurosurgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515041, China
| | - Maria Kominia
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center, Groningen, the Netherlands
| | - Janine Doorduin
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center, Groningen, the Netherlands
| | - Erik F J de Vries
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center, Groningen, the Netherlands.
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109
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Truong L, Bieberich AA, Fatig RO, Rajwa B, Simonich MT, Tanguay RL. Accelerating antiviral drug discovery: early hazard detection with a dual zebrafish and cell culture screen of a 403 compound library. Arch Toxicol 2025; 99:1029-1041. [PMID: 39730949 PMCID: PMC11821682 DOI: 10.1007/s00204-024-03948-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2024] [Accepted: 12/17/2024] [Indexed: 12/29/2024]
Abstract
The constant emergence of new viral pathogens underscores the need for continually evolving, effective antiviral drugs. A key challenge is identifying compounds that are both efficacious and safe, as many candidates fail during development due to unforeseen toxicity. To address this, the embryonic zebrafish morphology, mortality, and behavior (ZBE) screen and the SYSTEMETRIC® Cell Health Screen (CHS) were employed to evaluate the safety of 403 compounds from the Cayman Antiviral Screening Library. Of these compounds, 114 were FDA-approved, 17 were discontinued, and 97 remained on the market. CHS identified 25% (104 compounds) as toxic, with a Cell Health Index™ (CHI) > 0.5. The embryonic zebrafish model identified an additional 20% as toxic (79), bringing the total to 183. ZBEscreen flagged 19 toxic hits among compounds still on the market, seven of which were also identified by CHS. The combined use of CHS and zebrafish models enhanced hazard detection. Together, CHS and ZBEscreen identified 45.5% of the library as potentially hazardous. Notably, the zebrafish non-hazardous compounds correlated strongly with over-the-counter or prescribed antiviral drugs, confirming their known safety profile. Over 130 hazard-associated compounds warranted further investigation. Using self-organizing maps, six distinct neighborhoods of compound similarity were identified. This dual approach streamlined the early detection of hazards associated with promising leads and is expected to facilitate faster, safer antiviral discovery.
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Affiliation(s)
- Lisa Truong
- Department of Environmental and Molecular Toxicology, Sinnhuber Aquatic Research Laboratory, Oregon State University, Corvallis, OR, 97333, USA
| | | | | | - Bartek Rajwa
- AsedaSciences Inc., West Lafayette, IN, USA
- Bindley Bioscience Center, Purdue University, West Lafayette, IN, 47907, USA
| | - Michael T Simonich
- Department of Environmental and Molecular Toxicology, Sinnhuber Aquatic Research Laboratory, Oregon State University, Corvallis, OR, 97333, USA
| | - Robyn L Tanguay
- Department of Environmental and Molecular Toxicology, Sinnhuber Aquatic Research Laboratory, Oregon State University, Corvallis, OR, 97333, USA.
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Lomash RM, Dehdashti J, Shchelochkov OA, Chandler RJ, Li L, Manoli I, Sloan JL, Terse P, Xu X, Saade D, Stan R, Brooks PJ, Lo DC, Bönnemann CG, Venditti CP, Pariser AR, Ottinger EA. Adeno-Associated Virus Gene Therapy Development: Early Planning and Regulatory Considerations to Advance the Platform Vector Gene Therapy Program. Hum Gene Ther 2025; 36:653-662. [PMID: 39976996 PMCID: PMC11971537 DOI: 10.1089/hum.2024.230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2024] [Accepted: 12/24/2024] [Indexed: 03/14/2025] Open
Abstract
Gene therapy development presents multiple challenges, and early planning is vital in the successful implementation of such programs. The Platform Vector Gene Therapy (PaVe-GT) program is a National Institutes of Health (NIH) initiative developing adeno-associated virus (AAV) gene therapies for four low-prevalence rare diseases. Utilizing the platform-based approach, the program aims to incorporate efficiencies throughout the preclinical and clinical development processes followed by public dissemination of scientific and regulatory learnings. Early in development, the establishment of a Target Product Profile (TPP) by the research team is a critical step to guide product development and align preclinical studies to clinical objectives. Based on the specific needs of the investigational product as defined in the TPP, an overall regulatory strategy can then be outlined to meet the regulatory requirements for the first-in-human clinical trials. During the preclinical phase of development, sponsors may request meetings with the Food and Drug Administration (FDA) to gather feedback on the planned studies and regulatory strategy. To pave the way for PaVe-GT's first investigational AAV gene therapy lead candidate, AAV9-hPCCA, we sought early feedback from the FDA utilizing an INitial Targeted Engagement for Regulatory Advice on CBER/CDER ProducTs (INTERACT) meeting. Here, we elaborate on the value of establishing a TPP and the FDA INTERACT meeting by including our initial AAV9-hPCCA TPP, detailing our INTERACT meeting experience, providing all corresponding regulatory documentation, and highlighting lessons learned. The regulatory documents along with templates developed by our program can also be found on the PaVe-GT website (https://pave-gt.ncats.nih.gov/). This communication aims to provide stakeholders with resources that can be applied to drug development programs in establishing a viable regulatory path to clinical trial initiation.
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Affiliation(s)
- Richa Madan Lomash
- Therapeutic Development Branch, Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), NIH, Rockville, Maryland, USA
| | - Jean Dehdashti
- Division of Rare Diseases Research and Innovation, NCATS, NIH, Rockville, Maryland, USA
| | - Oleg A. Shchelochkov
- Organic Acid Research Section, Metabolic Medicine Branch, National Human Genome Research Institute (NHGRI), NIH, Bethesda, Maryland, USA
| | - Randy J. Chandler
- Organic Acid Research Section, Metabolic Medicine Branch, National Human Genome Research Institute (NHGRI), NIH, Bethesda, Maryland, USA
| | - Lina Li
- Organic Acid Research Section, Metabolic Medicine Branch, National Human Genome Research Institute (NHGRI), NIH, Bethesda, Maryland, USA
| | - Irini Manoli
- Organic Acid Research Section, Metabolic Medicine Branch, National Human Genome Research Institute (NHGRI), NIH, Bethesda, Maryland, USA
| | - Jennifer L. Sloan
- Organic Acid Research Section, Metabolic Medicine Branch, National Human Genome Research Institute (NHGRI), NIH, Bethesda, Maryland, USA
| | - Pramod Terse
- Therapeutic Development Branch, Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), NIH, Rockville, Maryland, USA
| | - Xin Xu
- Therapeutic Development Branch, Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), NIH, Rockville, Maryland, USA
| | - Dimah Saade
- Neuromuscular and Neurogenetic Disorders of Childhood Section, National Institute of Neurological Disorders and Stroke (NINDS), NIH, Bethesda, Maryland, USA
| | - Rodica Stan
- Therapeutic Development Branch, Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), NIH, Rockville, Maryland, USA
| | - Philip J. Brooks
- Division of Rare Diseases Research and Innovation, NCATS, NIH, Rockville, Maryland, USA
| | - Donald C. Lo
- Therapeutic Development Branch, Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), NIH, Rockville, Maryland, USA
| | - Carsten G. Bönnemann
- Neuromuscular and Neurogenetic Disorders of Childhood Section, National Institute of Neurological Disorders and Stroke (NINDS), NIH, Bethesda, Maryland, USA
| | - Charles P. Venditti
- Organic Acid Research Section, Metabolic Medicine Branch, National Human Genome Research Institute (NHGRI), NIH, Bethesda, Maryland, USA
| | - Anne R. Pariser
- Division of Rare Diseases Research and Innovation, NCATS, NIH, Rockville, Maryland, USA
| | - Elizabeth A. Ottinger
- Therapeutic Development Branch, Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), NIH, Rockville, Maryland, USA
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Menestrina L, Parrondo-Pizarro R, Gómez I, Garcia-Serna R, Boyer S, Mestres J. Refined ADME Profiles for ATC Drug Classes. Pharmaceutics 2025; 17:308. [PMID: 40142973 PMCID: PMC11944659 DOI: 10.3390/pharmaceutics17030308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2024] [Revised: 02/18/2025] [Accepted: 02/26/2025] [Indexed: 03/28/2025] Open
Abstract
Background: Modern generative chemistry initiatives aim to produce potent and selective novel synthetically feasible molecules with suitable pharmacokinetic properties. General ranges of physicochemical properties relevant for the absorption, distribution, metabolism, and excretion (ADME) of drugs have been used for decades. However, the therapeutic indication, dosing route, and pharmacodynamic response of the individual drug discovery program may ultimately define a distinct desired property profile. Methods: A methodological pipeline to build and validate machine learning (ML) models on physicochemical and ADME properties of small molecules is introduced. Results: The analysis of publicly available data on several ADME properties presented in this work reveals significant differences in the property value distributions across the various levels of the anatomical, therapeutic, and chemical (ATC) drug classification. For most properties, the predicted data distributions agree well with the corresponding distributions derived from experimental data across fourteen drug classes. Conclusions: The refined ADME profiles for ATC drug classes should be useful to guide the de novo generation of advanced lead structures directed toward specific therapeutic indications.
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Affiliation(s)
- Luca Menestrina
- Chemotargets SL, Parc Cientific de Barcelona, Baldiri Reixac 4 (TR-03), 08028 Barcelona, Catalonia, Spain
| | - Raquel Parrondo-Pizarro
- Chemotargets SL, Parc Cientific de Barcelona, Baldiri Reixac 4 (TR-03), 08028 Barcelona, Catalonia, Spain
- Institut de Quimica Computacional i Catalisi, Facultat de Ciencies, Universitat de Girona, Maria Aurelia Capmany 69, 17003 Girona, Catalonia, Spain
| | - Ismael Gómez
- Chemotargets SL, Parc Cientific de Barcelona, Baldiri Reixac 4 (TR-03), 08028 Barcelona, Catalonia, Spain
| | - Ricard Garcia-Serna
- Chemotargets SL, Parc Cientific de Barcelona, Baldiri Reixac 4 (TR-03), 08028 Barcelona, Catalonia, Spain
| | - Scott Boyer
- Chemotargets SL, Parc Cientific de Barcelona, Baldiri Reixac 4 (TR-03), 08028 Barcelona, Catalonia, Spain
| | - Jordi Mestres
- Chemotargets SL, Parc Cientific de Barcelona, Baldiri Reixac 4 (TR-03), 08028 Barcelona, Catalonia, Spain
- Institut de Quimica Computacional i Catalisi, Facultat de Ciencies, Universitat de Girona, Maria Aurelia Capmany 69, 17003 Girona, Catalonia, Spain
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Thakur GS, Gupta AK, Pal D, Vaishnav Y, Kumar N, Annadurai S, Jain SK. Designing novel cabozantinib analogues as p-glycoprotein inhibitors to target cancer cell resistance using molecular docking study, ADMET screening, bioisosteric approach, and molecular dynamics simulations. Front Chem 2025; 13:1543075. [PMID: 40084274 PMCID: PMC11903459 DOI: 10.3389/fchem.2025.1543075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2024] [Accepted: 02/04/2025] [Indexed: 03/16/2025] Open
Abstract
Introduction One of the foremost contributors to mortality worldwide is cancer. Chemotherapy remains the principal strategy for cancer treatment. A significant factor leading to the failure of cancer chemotherapy is the phenomenon of multidrug resistance (MDR) in cancer cells. The primary instigator of MDR is the over expression of P-glycoprotein (P-gp), a protein that imparts resistance and facilitates the ATP-dependent efflux of various anticancer agents. Numerous efforts have been made to inhibit P-gp function with the aim of restoring the effectiveness of chemotherapy due to its broad specificity. The main objective has been to create compounds that either serve as direct P-gp inhibitors or interact with cancer therapies to modulate transport. Despite substantial in vitro achievements, there are currently no approved drugs available that can effectively "block" P-gp mediated resistance. Cabozantinib (CBZ), a multi-kinase inhibitor, is utilized in the treatment of various carcinomas. CBZ has been shown to inhibit P-gp efflux activity, thereby reversing P-gp mediated MDR. Consequently, P-gp has emerged as a critical target for research in anti-cancer therapies. Methods The purpose of this study was to computationally identify new andsafer analogues of CBZ using bioisosteric approach, focusing on improved pharmacokinetic properties andreduced toxicity. The physicochemical, medicinal, and ADMET profiles of generated analogues were computed using the ADMETLab 3.0 server. We also predicted the drug likeness (DL) and drug score (DS) of analogues. The molecular docking studies of screened analogues against the protein (PDB ID: 3G5U) were conducted using AutoDock Vina flowing by BIOVIA Discovery Studio for visualizing interactions.Molecular dynamics (MD) simulation of docked ligands was done using Schrödinger suite. Results and Discussion The docking scores for the ligands CBZ01, CBZ06, CBZ11, CBZ13, CBZ25, CBZ34, and CBZ38 ranged from -8.0 to -6.4 kcal/mol against the protein (PDB ID: 3G5U). A molecular dynamics (MD) simulation of CBZ01, CBZ13, and CBZ38 was conducted using the Schrödinger suite, revealing that these complexesmaintained stability throughout the 100 ns simulation. Conclusion An integrated computational approach combining bioisosteric approach, molecular docking, drug likeness calculations, and MD simulations highlights the promise of ligands CBZ01 and CBZ13 as candidates for the development of potential anticancer agents for the treatment of various cancers.
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Affiliation(s)
- Gajendra Singh Thakur
- Drug Discovery and Research Laboratory, Department of Pharmacy, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur, Chhattisgarh, India
| | - Ajay Kumar Gupta
- Drug Discovery and Research Laboratory, Department of Pharmacy, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur, Chhattisgarh, India
| | - Dipti Pal
- Drug Discovery and Research Laboratory, Department of Pharmacy, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur, Chhattisgarh, India
| | - Yogesh Vaishnav
- Drug Discovery and Research Laboratory, Department of Pharmacy, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur, Chhattisgarh, India
| | - Neeraj Kumar
- Department of Pharmaceutical Chemistry, Bhupal Nobles’ College of Pharmacy, Udaipur, Rajasthan, India
| | - Sivakumar Annadurai
- Department of Pharmacognosy, College of Pharmacy, King Khalid University, Abha, Saudi Arabia
| | - Sanmati Kumar Jain
- Drug Discovery and Research Laboratory, Department of Pharmacy, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur, Chhattisgarh, India
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Yang Q, Yao L, Chen Z, Wang X, Jia F, Pang G, Huang M, Li J, Fan L. Exploring a new paradigm for serum-accessible component rules of natural medicines using machine learning and development and validation of a direct predictive model. Int J Pharm 2025; 671:125207. [PMID: 39826781 DOI: 10.1016/j.ijpharm.2025.125207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2024] [Revised: 12/30/2024] [Accepted: 01/08/2025] [Indexed: 01/22/2025]
Abstract
In the field of pharmaceutical research, Lipinski's Rule of Five (RO5) was once widely regarded as the prevailing standard for the development of novel drugs. Despite the fact that an increasing number of recently approved drugs no longer adhere to this rule, it continues to serve as a valuable guiding principle in the field of drug discovery. The present study aims to establish a set of rules specifically for the serum-accessible components of natural medicines. A comprehensive literature review was conducted to collect data on serum-accessible components of natural medicines, and machine learning methods were then applied to analyse and screen molecular features distinguishing serum-accessible components from non-serum-accessible ones. The most critical rules for serum-accessible components of natural medicines were identified, and these were named the "Natural Medicine's Rule of 5 (NMRO5)." We then compared the molecular property distributions and predictive performance of NMRO5 with RO5. Then, we developed a predictive model capable of directly assessing the possibility of a molecule being serum-accessible. This model was validated using in vivo experiments on multiple natural medicines. Furthermore, we performed molecular modifications on serum-accessible components to "violate" NMRO5, conducting both forward and reverse validations to confirm the reliability of NMRO5. The results obtained revealed that NMRO5 is characterised by the following: higher TPSA, MaxEState, and PEOE VSA1 values, and lower LogP and MinEState values. This indicates that natural medicine components with these properties are more likely to be serum-accessible or remain in plasma rather than being rapidly eliminated. The investigation revealed significant disparities among the five molecular properties of NMRO5, and the predictive performance of eight models based on NMRO5 consistently outperformed those based on RO5. This finding suggests that NMRO5 provides a more reliable framework for determining whether a molecule is serum-accessible compared to RO5. Finally, we developed a direct predictive model for serum-accessible components, achieving an accuracy of 0.7257, an F1 score of 0.7223, and an AUC of 0.7553.
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Affiliation(s)
- Qi Yang
- Faculty of Pharmacy, Guangxi University of Chinese Medicine, Nanning 530200, China; Guangxi Key Laboratory of Efficacy Study on Chinese Materia Medica, Guangxi University of Chinese Medicine, Nanning 530200, China
| | - Lihao Yao
- Faculty of Pharmacy, Guangxi University of Chinese Medicine, Nanning 530200, China; Guangxi Key Laboratory of Efficacy Study on Chinese Materia Medica, Guangxi University of Chinese Medicine, Nanning 530200, China
| | - Zhiyang Chen
- Suzhou TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Suzhou 215009, China
| | - Xiaopeng Wang
- Suzhou TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Suzhou 215009, China
| | - Fang Jia
- Faculty of Pharmacy, Guangxi University of Chinese Medicine, Nanning 530200, China; Guangxi Key Laboratory of Efficacy Study on Chinese Materia Medica, Guangxi University of Chinese Medicine, Nanning 530200, China
| | - Guiyuan Pang
- Faculty of Pharmacy, Guangxi University of Chinese Medicine, Nanning 530200, China; Guangxi Key Laboratory of Efficacy Study on Chinese Materia Medica, Guangxi University of Chinese Medicine, Nanning 530200, China
| | - Meiyu Huang
- Faculty of Pharmacy, Guangxi University of Chinese Medicine, Nanning 530200, China; Guangxi Key Laboratory of Efficacy Study on Chinese Materia Medica, Guangxi University of Chinese Medicine, Nanning 530200, China
| | - Jiacheng Li
- Suzhou TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Suzhou 215009, China.
| | - Lili Fan
- Faculty of Pharmacy, Guangxi University of Chinese Medicine, Nanning 530200, China.
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114
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Soundara Pandi SP, Winter H, Smith MR, Harkin K, Bojdo J. Preclinical Retinal Disease Models: Applications in Drug Development and Translational Research. Pharmaceuticals (Basel) 2025; 18:293. [PMID: 40143072 PMCID: PMC11944893 DOI: 10.3390/ph18030293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2025] [Revised: 02/10/2025] [Accepted: 02/18/2025] [Indexed: 03/28/2025] Open
Abstract
Retinal models play a pivotal role in translational drug development, bridging preclinical research and therapeutic applications for both ocular and systemic diseases. This review highlights the retina as an ideal organ for studying advanced therapies, thanks to its immune privilege, vascular and neuronal networks, accessibility, and advanced imaging capabilities. Preclinical retinal disease models offer unparalleled insights into inflammation, angiogenesis, fibrosis, and hypoxia, utilizing clinically translatable bioimaging tools like fundoscopy, optical coherence tomography, confocal scanning laser ophthalmoscopy, fluorescein angiography, optokinetic tracking, and electroretinography. These models have driven innovations in anti-inflammatory, anti-angiogenic, and neuroprotective strategies, with broader implications for systemic diseases such as rheumatoid arthritis, Alzheimer's, and fibrosis-related conditions. By emphasizing the integration of the 3Rs principles and novel imaging modalities, this review highlights how retinal research not only enhances therapeutic precision but also minimizes ethical concerns, paving the way for more predictive and human-relevant approaches in drug development.
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Affiliation(s)
| | - Hanagh Winter
- Medinect Bioservices Ltd., Belfast BT7 1NF, UK; (S.P.S.P.); (H.W.); (M.R.S.); (K.H.)
| | - Madeleine R. Smith
- Medinect Bioservices Ltd., Belfast BT7 1NF, UK; (S.P.S.P.); (H.W.); (M.R.S.); (K.H.)
| | - Kevin Harkin
- Medinect Bioservices Ltd., Belfast BT7 1NF, UK; (S.P.S.P.); (H.W.); (M.R.S.); (K.H.)
- Wellcome-Wolfson Institute for Experimental Medicine, Queen’s University Belfast, Belfast BT9 7BL, UK
| | - James Bojdo
- Medinect Bioservices Ltd., Belfast BT7 1NF, UK; (S.P.S.P.); (H.W.); (M.R.S.); (K.H.)
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Kovari D, Male L, Roper KA, Mang CP, Kunz O, Cox LR. Short Scalable Route to Bis-morpholine Spiroacetals and Oxazepane Analogues: Useful 3D-Scaffolds for Compound Library Assembly. J Org Chem 2025; 90:2652-2661. [PMID: 39927818 PMCID: PMC11852203 DOI: 10.1021/acs.joc.4c02690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2024] [Revised: 01/19/2025] [Accepted: 01/23/2025] [Indexed: 02/11/2025]
Abstract
sp3-Rich molecular scaffolds incorporating nitrogen heterocycles represent important starting points for assembling compound screening libraries and drug discovery. Herein, we report a four-step synthesis of a conformationally well-defined sp3-rich scaffold incorporating two morpholine rings embedded within a spiroacetal framework. The synthesis involves the intermediacy of a 2-chloromethyl-substituted morpholine, accessed from epichlorohydrin and readily available β-aminoalcohols. Base-mediated dehydrochlorination affords an exocyclic enol ether, from which the second morpholine ring is constructed in two steps. Scaffold synthesis is high-yielding and can be performed on a large scale. The methodology allows ready substitution of one-or both- of the morpholine rings for 1,4-oxazepanes and the generation of 6,7- and 7,7-spiroacetal analogues, which are virtually unexplored in drug discovery. Substituted 6,6-systems can be prepared and, in some instances, undergo acid-mediated anomerization to deliver the scaffolds in high diastereoselectivity. The two amine functionalities embedded in the 6,6- and 6,7-spiroacetal scaffolds were sequentially functionalized to provide a diverse physical compound library. These library compounds occupy a similar chemical space to small-molecule drugs that have been approved for clinical application by the Food and Drug Administration yet are structurally dissimilar and may therefore act upon novel targets, representing attractive starting materials for drug discovery.
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Affiliation(s)
- Daniel Kovari
- School
of Chemistry, The University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K.
- AnalytiCon
Discovery GmbH, Hermannswerder 17, 14473 Potsdam, Germany
| | - Louise Male
- School
of Chemistry, The University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K.
| | - Kimberley A. Roper
- School
of Pharmacy, The University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K.
| | - Christian P. Mang
- AnalytiCon
Discovery GmbH, Hermannswerder 17, 14473 Potsdam, Germany
| | - Oliver Kunz
- AnalytiCon
Discovery GmbH, Hermannswerder 17, 14473 Potsdam, Germany
| | - Liam R. Cox
- School
of Chemistry, The University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K.
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116
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Han W, Zhou Q, Wang MW. Current challenges and future perspectives of drug discovery in China. Expert Opin Drug Discov 2025:1-10. [PMID: 39953852 DOI: 10.1080/17460441.2025.2468290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2024] [Revised: 02/03/2025] [Accepted: 02/13/2025] [Indexed: 02/17/2025]
Abstract
INTRODUCTION China's pharmaceutical industry, which is historically centered around generic medicines, has largely transformed from imitation to innovation over the past three decades. Despite unprecedented progress, critical challenges remain such as insufficient indigenous research funding, underdeveloped academia-industry relationships, and significant barriers to market access. AREAS COVERED This perspective examines the evolving pharmaceutical landscape of China, focusing on its participation in global clinical trials and the resultant new drug approvals. Data for this analysis was sourced from several databases (e.g. PharmCube, NextPharma, and PharmaGO), academic reports, and published literature, covering data up to 2024 (unless otherwise specified). This perspective highlights ongoing regulatory challenges, such as inconsistencies in product standards, and the approval processes relative to the U.S.A. and the European Union. There is also an urgent demand for sustained international investment and recognition, partially due to the recent changes in the geopolitical environment. This perspective also discusses China's efforts to implement accelerated approval pathways and foster multilateral development collaborations. EXPERT OPINION China must align its regulatory policies more closely to the international norm to generate robust trial data that will be readily acceptable to the FDA and EMA. Continued investment in biologics as well as cell and gene therapy and artificial intelligence will drive innovation and enhance competitiveness. Additionally, strengthening the academia-industry collaboration is crucial to obtaining new leads through translational research. Ultimately, structural reforms are required to solidify the country's goal of becoming a major player in the global pharmaceutical market.
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Affiliation(s)
- Wei Han
- Research Center for Medicinal Structural Biology, National Research Center for Translational Medicine at Shanghai, State Key Laboratory of Medical Genomics, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qingtong Zhou
- Research Center for Medicinal Structural Biology, National Research Center for Translational Medicine at Shanghai, State Key Laboratory of Medical Genomics, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ming-Wei Wang
- Research Center for Medicinal Structural Biology, National Research Center for Translational Medicine at Shanghai, State Key Laboratory of Medical Genomics, Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Pharmacology Division, Research Center for Deepsea Bioresources, Sanya, China
- Engineering Research Center of Tropical Medicine Innovation and Transformation of Ministry of Education, School of Pharmacy, Hainan Medical University, Haikou, China
- Department of Pharmacology, School of Basic Medical Sciences, Fudan University, Shanghai, China
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Wang L, Gao Y, Chen Y, Tang Z, Lin X, Bai M, Cao P, Liu K. Discovery of Novel Pyridin-2-yl Urea Inhibitors Targeting ASK1 Kinase and Its Binding Mode by Absolute Protein-Ligand Binding Free Energy Calculations. Int J Mol Sci 2025; 26:1527. [PMID: 40003993 PMCID: PMC11854949 DOI: 10.3390/ijms26041527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2024] [Revised: 01/30/2025] [Accepted: 02/08/2025] [Indexed: 02/27/2025] Open
Abstract
Apoptosis signal-regulating kinase 1 (ASK1), a key component of the mitogen-activated protein kinase (MAPK) cascades, has been identified as a promising therapeutic target owing to its critical role in signal transduction pathways. In this study, we proposed novel pyridin-2-yl urea inhibitors exhibiting favorable physicochemical properties. The potency of these compounds was validated through in vitro protein bioassays. The inhibition (IC50) of compound 2 was 1.55 ± 0.27 nM, which was comparable to the known clinical inhibitor, Selonsertib. To further optimize the hit compounds, two possible binding modes were initially predicted by molecular docking. Absolute binding free energy (BFE) calculations based on molecular dynamics simulations further discriminated the binding modes, presenting good tendency with bioassay results. This strategy, underpinned by BFE calculations, has the great potential to expedite the drug discovery process in the targeting of ASK1 kinase.
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Affiliation(s)
- Lingzhi Wang
- Guangxi Key Laboratory of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China; (L.W.); (Y.G.); (Y.C.); (Z.T.); (X.L.); (M.B.)
- Institute of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China
| | - Yalei Gao
- Guangxi Key Laboratory of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China; (L.W.); (Y.G.); (Y.C.); (Z.T.); (X.L.); (M.B.)
- Institute of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China
| | - Yuying Chen
- Guangxi Key Laboratory of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China; (L.W.); (Y.G.); (Y.C.); (Z.T.); (X.L.); (M.B.)
- Institute of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China
| | - Zhenzhou Tang
- Guangxi Key Laboratory of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China; (L.W.); (Y.G.); (Y.C.); (Z.T.); (X.L.); (M.B.)
- Institute of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China
| | - Xiao Lin
- Guangxi Key Laboratory of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China; (L.W.); (Y.G.); (Y.C.); (Z.T.); (X.L.); (M.B.)
- Institute of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China
| | - Meng Bai
- Guangxi Key Laboratory of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China; (L.W.); (Y.G.); (Y.C.); (Z.T.); (X.L.); (M.B.)
- Institute of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China
| | - Pei Cao
- Guangxi Key Laboratory of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China; (L.W.); (Y.G.); (Y.C.); (Z.T.); (X.L.); (M.B.)
- Institute of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China
| | - Kai Liu
- Guangxi Key Laboratory of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China; (L.W.); (Y.G.); (Y.C.); (Z.T.); (X.L.); (M.B.)
- Institute of Marine Drugs, Guangxi University of Chinese Medicine, Nanning 530200, China
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Wang N, Dong J, Ouyang D. AI-directed formulation strategy design initiates rational drug development. J Control Release 2025; 378:619-636. [PMID: 39719215 DOI: 10.1016/j.jconrel.2024.12.043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2024] [Revised: 11/27/2024] [Accepted: 12/18/2024] [Indexed: 12/26/2024]
Abstract
Rational drug development would be impossible without selecting the appropriate formulation route. However, pharmaceutical scientists often rely on limited personal experiences to perform trial-and-error tests on diverse formulation strategies. Such an inefficient screening manner not only wastes research investments but also threatens the safety of clinical volunteers and patients. A design-oriented paradigm for formulation strategy determination is urgently needed to initiate rational drug development. Herein, we introduce FormulationDT, the first data-driven and knowledge-guided artificial intelligence (AI) platform for rational formulation strategy design. Learning from approved drug formulations, FormulationDT devised a comprehensive formulation strategy design system containing 12 decisions for both oral and injectable administration. Utilizing PU-Decide, our specialized partially supervised learning framework designed for positive-unlabeled (PU) scenarios, FormulationDT developed precise and interpretable classification models for each decision, achieving area under the receiver operating characteristic curve (ROC_AUC) scores ranging from 0.78 to 0.98, with an average above 0.90. Incorporating extensive domain knowledge, FormulationDT is now accessible through a user-friendly web platform (http://formulationdt.computpharm.org/). Moreover, FormulationDT demonstrates its value by showcasing its application in proteolysis targeting chimeras (PROTACs) and recent drug approvals. Overall, this study created the first approved drug formulation dataset and tailored the PU-Decide framework to develop a high-performance, interpretable, and user-friendly AI formulation strategy design platform, which holds promise for driving risk reduction and efficiency gains across the life cycle of drug discovery and development.
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Affiliation(s)
- Nannan Wang
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences (ICMS), University of Macau, Macau, China
| | - Jie Dong
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, China.
| | - Defang Ouyang
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences (ICMS), University of Macau, Macau, China; Department of Public Health and Medicinal Administration, Faculty of Health Sciences (FHS), University of Macau, Macau, China.
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Alanazi M, Alanazi J, Alharby TN, Huwaimel B. Correlation of rivaroxaban solubility in mixed solvents for optimization of solubility using machine learning analysis and validation. Sci Rep 2025; 15:4725. [PMID: 39922955 PMCID: PMC11807219 DOI: 10.1038/s41598-025-89093-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2024] [Accepted: 02/03/2025] [Indexed: 02/10/2025] Open
Abstract
In this study, the solubility of rivaroxaban, a poorly water-soluble drug, was investigated in mixed solvent systems to address challenges in pharmaceutical formulation and bioavailability enhancement. Solubility optimization is essential for the effective delivery and therapeutic performance of rivaroxaban, as its low aqueous solubility limits oral bioavailability and necessitates innovative approaches for drug formulation. The study explored the role of primary alcohols combined with dichloromethane in improving solubility, emphasizing their industrial relevance in crystallization, purification, and drug manufacturing processes. To complement experimental insights, machine learning models were employed to predict rivaroxaban solubility based on temperature, solvent type, and mass fraction of dichloromethane. Three models-AdaBoost Gaussian process regression (ADAGPR), AdaBoost multilayer perceptron (ADAMLP), and AdaBoost LASSO regression (ADALASSO)-were evaluated using [Formula: see text], RMSE, and MAPE metrics. Among these, ADAGPR demonstrated superior performance with an R² score of [Formula: see text], outperforming ADAMLP [Formula: see text] and [Formula: see text]. It also achieved the lowest total RMSE [Formula: see text] and MAPE [Formula: see text], confirming its predictive precision and reliability. Optimal solubility conditions were identified at [Formula: see text] with a mass fraction of 0.8190 in a dichloromethane-methanol mixture, yielding a predicted solubility of [Formula: see text]. These findings highlight the potential of combining chemical engineering principles with advanced predictive modeling to optimize solubility in complex solvent systems, offering significant value to pharmaceutical development and process optimization.
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Affiliation(s)
- Muteb Alanazi
- Department of Clinical Pharmacy, College of Pharmacy, University of Ha'il, Ha'il, 81442, Saudi Arabia.
| | - Jowaher Alanazi
- Department of Pharmacology and Toxicology, College of Pharmacy, University of Ha'il, Ha'il, 81442, Saudi Arabia
| | - Tareq Nafea Alharby
- Department of Clinical Pharmacy, College of Pharmacy, University of Ha'il, Ha'il, 81442, Saudi Arabia
| | - Bader Huwaimel
- Department of Pharmaceutical Chemistry, College of Pharmacy, University of Ha'il, Hail, 81442, Saudi Arabia
- Medical and Diagnostic Research Center, University of Ha'il, Hail, 55473, Saudi Arabia
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Cook RL, Martelly W, Agu CV, Gushgari LR, Moreno S, Kesiraju S, Mohan M, Takulapalli B. An approach to produce thousands of single-chain antibody variants on a SPR biosensor chip for measuring target binding kinetics and for deep characterization of antibody paratopes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.01.11.632576. [PMID: 39868233 PMCID: PMC11760398 DOI: 10.1101/2025.01.11.632576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2025]
Abstract
Drug discovery continues to face a staggering 90% failure rate, with many setbacks occurring during late-stage clinical trials. To address this challenge, there is an increasing focus on developing and evaluating new technologies to enhance the "design" and "test" phases of antibody-based drugs (e.g., monoclonal antibodies, bispecifics, CAR-T therapies, ADCs) and biologics during early preclinical development, with the goal of identifying lead molecules with a higher likelihood of clinical success. Artificial intelligence (AI) is becoming an indispensable tool in this domain, both for improving molecules identified through traditional approaches and for the de novo design of novel therapeutics. However, critical bottlenecks persist in the "build" and "test" phases of AI-designed antibodies and protein binders, impeding early preclinical evaluation. While AI models can rapidly generate thousands to millions of putative drug designs, technological and cost limitations mean that only a few dozen candidates are typically produced and tested. Drug developers often face a tradeoff between ultra-high-throughput wet lab methods that provide binary yes/no binding data and biophysical methods that offer detailed characterization of a limited number of drug-target pairs. To address these bottlenecks, we previously reported the development of the Sensor-integrated Proteome On Chip (SPOC®) platform, which enables the production and capture-purification of 1,000 - 2,400 folded proteins directly onto a surface plasmon resonance (SPR) biosensor chip for measuring kinetic binding rates with picomolar affinity resolution. In this study, we extend the SPOC technology to the expression of single-chain antibodies (sc-antibodies), specifically scFv and VHH constructs. We demonstrate that these constructs are capture-purified at high levels on SPR biosensors and retain functionality as shown by the binding specificity to their respective target antigens, with affinities comparable to those reported in the literature. SPOC outputs comprehensive kinetic data including quantitative binding (R max ), on-rate ( k a ), off-rate ( k d ), affinity ( K D ), and half-life ( t 1/2 ), for each of thousands of on-chip sc-antibodies. Additionally, we present a case study showcasing single amino acid mutational scan of the complementarity-determining regions (CDRs) of a HER2 VHH (nanobody) paratope. Using 92 unique mutated variants from four different amino acid substitutions, we pinpoint critical residues within the paratope that could further enhance binding affinity. This study serves as a demonstration of a novel high-throughput approach for biophysical screening of hundreds to thousands of single chain antibody sequences in a single assay, generating high affinity resolution kinetic data to support antibody discovery and AI-enabled pipelines.
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Ruankham W, Pingaew R, Prachayasittikul V, Worachartcheewan A, Sathuphong S, Apiraksattayakul S, Tantimongcolwat T, Prachayasittikul V, Prachayasittikul S, Phopin K. Neuroprotective thiazole sulfonamides against 6-OHDA-induced Parkinsonian model: in vitro biological and in silico pharmacokinetic assessments. RSC Adv 2025; 15:4281-4295. [PMID: 39931414 PMCID: PMC11809491 DOI: 10.1039/d4ra04941a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2024] [Accepted: 01/14/2025] [Indexed: 02/13/2025] Open
Abstract
The limitations of currently existing medications in delaying or halting the development of Parkinson's disease (PD) remain dramatically problematic, making it the second most prevalent neurodegenerative disorder. Moreover, it is expected that the number of PD cases will double within the next 30 years. Herein, to discover a novel neuroprotective therapeutic strategy, a series of multifunctional thiazole sulfonamides underwent preliminary assessment owing to their neuroprotective capabilities against 6-hydroxydopamine (6-OHDA)-induced damage in human neuronal SH-SY5Y cells. Pretreatment with novel synthetic hybrids, including 1, 2, and 8, significantly improved cell viability, reduced lactate dehydrogenase (LDH) leakage, prevented mitochondrial dysfunction, and mitigated intracellular oxidative stress. Insight molecular mechanisms and potential targets of these compounds were elucidated through their activation and binding interaction with sirtuin 1 (SIRT1), suggesting their influencing roles on relevant downstream cascades of PD. Furthermore, in silico pharmacokinetic analysis revealed the drug-likeness of these three hybrids, which are capable of being distributed into the central nervous system (CNS) with slight toxicity. Therefore, these novel neuroprotective thiazole sulfonamides are promising candidates for further development (i.e., in vivo and clinical trials) of effective PD therapy.
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Affiliation(s)
- Waralee Ruankham
- Center for Research Innovation and Biomedical Informatics, Faculty of Medical Technology, Mahidol University Bangkok 10700 Thailand +66 2 441 4380 +66 2 441 4376
- Department of Clinical Chemistry, Faculty of Medical Technology, Mahidol University Bangkok 10700 Thailand
| | - Ratchanok Pingaew
- Department of Chemistry, Faculty of Science, Srinakharinwirot University Bangkok 10110 Thailand
| | - Veda Prachayasittikul
- Center for Research Innovation and Biomedical Informatics, Faculty of Medical Technology, Mahidol University Bangkok 10700 Thailand +66 2 441 4380 +66 2 441 4376
| | - Apilak Worachartcheewan
- Department of Community Medical Technology, Faculty of Medical Technology, Mahidol University Bangkok 10700 Thailand
| | - Suphissara Sathuphong
- Center for Research Innovation and Biomedical Informatics, Faculty of Medical Technology, Mahidol University Bangkok 10700 Thailand +66 2 441 4380 +66 2 441 4376
| | - Setthawut Apiraksattayakul
- Center for Research Innovation and Biomedical Informatics, Faculty of Medical Technology, Mahidol University Bangkok 10700 Thailand +66 2 441 4380 +66 2 441 4376
| | - Tanawut Tantimongcolwat
- Center for Research Innovation and Biomedical Informatics, Faculty of Medical Technology, Mahidol University Bangkok 10700 Thailand +66 2 441 4380 +66 2 441 4376
| | - Virapong Prachayasittikul
- Department of Clinical Microbiology and Applied Technology, Faculty of Medical Technology, Mahidol University Bangkok 10700 Thailand
| | - Supaluk Prachayasittikul
- Center for Research Innovation and Biomedical Informatics, Faculty of Medical Technology, Mahidol University Bangkok 10700 Thailand +66 2 441 4380 +66 2 441 4376
| | - Kamonrat Phopin
- Center for Research Innovation and Biomedical Informatics, Faculty of Medical Technology, Mahidol University Bangkok 10700 Thailand +66 2 441 4380 +66 2 441 4376
- Department of Clinical Microbiology and Applied Technology, Faculty of Medical Technology, Mahidol University Bangkok 10700 Thailand
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Das SK, Mishra R, Samanta A, Shil D, Roy SD. Deep learning: A game changer in drug design and development. ADVANCES IN PHARMACOLOGY (SAN DIEGO, CALIF.) 2025; 103:101-120. [PMID: 40175037 DOI: 10.1016/bs.apha.2025.01.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2025]
Abstract
The lengthy and costly drug discovery process is transformed by deep learning, a subfield of artificial intelligence. Deep learning technologies expedite the procedure, increasing treatment success rates and speeding life-saving procedures. Deep learning stands out in target identification and lead selection. Deep learning greatly accelerates initial stage by analyzing large datasets of biological data to identify possible therapeutic targets and rank targeted drug molecules with desired features. Predicting possible adverse effects is another significant challenge. Deep learning offers prompt and efficient assistance with toxicology prediction in a very short time, deep learning algorithms can forecast a new drug's possible harm. This enables to concentrate on safer alternatives and steer clear of late-stage failures brought on by unanticipated toxicity. Deep learning unlocks the possibility of drug repurposing; by examining currently available medications, it is possible to find whole new therapeutic uses. This method speeds up development of diseases that were previously incurable. De novo drug discovery is made possible by deep learning when combined with sophisticated computational modeling, it can create completely new medications from the ground. Deep learning can recommend and direct towards new drug candidates with high binding affinities and intended therapeutic effects by examining molecular structures of disease targets. This provides focused and personalized medication. Lastly, drug characteristics can be optimized with aid of deep learning. Researchers can create medications with higher bioavailability and fewer toxicity by forecasting drug pharmacokinetics. In conclusion, deep learning promises to accelerate drug development, reduce costs, and ultimately save lives.
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Affiliation(s)
- Sushanta Kumar Das
- Mata Gujri College of Pharmacy, Mata Gujri University, Kishanganj, Bihar, India.
| | - Rahul Mishra
- Pharmacokinetics Scientist, Phase 1 Clinical Trial, Celerion IMC, Rose Street, Lincoln, NE, United States
| | - Amit Samanta
- Mata Gujri College of Pharmacy, Mata Gujri University, Kishanganj, Bihar, India
| | - Dibyendu Shil
- Mata Gujri College of Pharmacy, Mata Gujri University, Kishanganj, Bihar, India
| | - Saumendu Deb Roy
- Mata Gujri College of Pharmacy, Mata Gujri University, Kishanganj, Bihar, India
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Zhang C, Dong YX, Gao LX, Gan S, Gao W, Li J, Xiang DJ, Wang X, Zhou YB, Wang WL. 6 H-Indolo-[2,3- b]-quinoxaline derivatives as promising bifunctional SHP1 inhibitors. Org Biomol Chem 2025; 23:1394-1405. [PMID: 39744882 DOI: 10.1039/d4ob01492h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2025]
Abstract
Dysfunction in the SHP1 enzyme can cause cancers and many diseases, so it is of great significance to develop novel small molecule SHP1 inhibitors. Through continuous monitoring of metabolic and targeted processes of SHP1 inhibitors in real-time, we can evaluate the effectiveness and toxicity of the inhibitors, further optimize drug design, and explore SHP1 biology. Indoloquinoxaline is an important class of N-containing heterocycle, which has been studied and applied in the pharmacological field and in optoelectronic materials. In this work, the potential Src homology 2 domain-containing phosphatase 1 (SHP1) inhibitor 5a was developed with the help of the structural fusion and scaffold hop of a fluorophore, 6H-indolo-[2,3-b]-quinoxaline, and a bio-active skeleton, thieno[2,3-b]quinoline-procaine. Compound 5a selectively inhibited the SHP1PTP enzyme abilities (IC50 = 2.34 ± 0.06 μM), exhibited a significant fluorescence response (P = 0.007) in response to SHP1PTP activity, and emitted strong blue/green fluorescence in MDA-MB-231 cells. Furthermore, compound 5a showed irreversible binding with SHP1PTP in simulations and dialysis experiments. Altogether, compound 5a serves as a bifunctional SHP1 inhibitor, combining imaging and therapeutic functionalities, enhancing our understanding of SHP1 biological mechanisms, and positively impacting novel drug development.
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Affiliation(s)
- Chun Zhang
- School of Life Sciences and Health Engineering, Jiangnan University, Jiangsu, 214122, China.
| | - Yi-Xin Dong
- School of Life Sciences and Health Engineering, Jiangnan University, Jiangsu, 214122, China.
| | - Li-Xin Gao
- School of Life Sciences and Health Engineering, Jiangnan University, Jiangsu, 214122, China.
| | - Suya Gan
- School of Life Sciences and Health Engineering, Jiangnan University, Jiangsu, 214122, China.
| | - Wenran Gao
- Joint International Research Laboratory of Biomass Energy and Materials, Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing 210037, China
| | - Jia Li
- National Center for Drug Screening, State key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China.
- Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, SSIP Healthcare and Medicine Demonstration Zone, Zhongshan Tsuihang New District, Zhongshan, Guangdong 528400, China
| | - Da-Jun Xiang
- Xishan People's Hospital of Wuxi City, Wuxi, Jiangsu, 214105, China.
| | - Xin Wang
- Henan-Macquarie University Joint Centre for Biomedical Innovation, School of Life Sciences, Henan University, Kaifeng, Henan, 475004, China.
| | - Yu-Bo Zhou
- National Center for Drug Screening, State key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China.
- Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, SSIP Healthcare and Medicine Demonstration Zone, Zhongshan Tsuihang New District, Zhongshan, Guangdong 528400, China
| | - Wen-Long Wang
- School of Life Sciences and Health Engineering, Jiangnan University, Jiangsu, 214122, China.
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Namba S, Li C, Yuyama Otani N, Yamanishi Y. SSL-VQ: vector-quantized variational autoencoders for semi-supervised prediction of therapeutic targets across diverse diseases. Bioinformatics 2025; 41:btaf039. [PMID: 39880378 PMCID: PMC11842052 DOI: 10.1093/bioinformatics/btaf039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Revised: 01/14/2025] [Accepted: 01/25/2025] [Indexed: 01/31/2025] Open
Abstract
MOTIVATION Identifying effective therapeutic targets poses a challenge in drug discovery, especially for uncharacterized diseases without known therapeutic targets (e.g. rare diseases, intractable diseases). RESULTS This study presents a novel machine learning approach using multimodal vector-quantized variational autoencoders (VQ-VAEs) for predicting therapeutic target molecules across diseases. To address the lack of known therapeutic target-disease associations, we incorporate the information on uncharacterized diseases without known targets or uncharacterized proteins without known indications (applicable diseases) in the semi-supervised learning (SSL) framework. The method integrates disease-specific and protein perturbation profiles with genetic perturbations (e.g. gene knockdowns and gene overexpressions) at the transcriptome level. Cross-cell representation learning, facilitated by VQ-VAEs, was performed to extract informative features from protein perturbation profiles across diverse human cell types. Concurrently, cross-disease representation learning was performed, leveraging VQ-VAE, to extract informative features reflecting disease states from disease-specific profiles. The model's applicability to uncharacterized diseases or proteins is enhanced by considering the consistency between disease-specific and patient-specific signatures. The efficacy of the method is demonstrated across three practical scenarios for 79 diseases: target repositioning for target-disease pairs, new target prediction for uncharacterized diseases, and new indication prediction for uncharacterized proteins. This method is expected to be valuable for identifying therapeutic targets across various diseases. AVAILABILITY AND IMPLEMENTATION Code: github.com/YamanishiLab/SSL-VQ and Data: 10.5281/zenodo.14644837.
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Affiliation(s)
- Satoko Namba
- Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology, Kawazu, Iizuka, Fukuoka, 820-8502, Japan
- Department of Complex Systems Science, Graduate School of Informatics, Nagoya University, Chikusa, Nagoya, Aichi, 464-8601, Japan
| | - Chen Li
- Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology, Kawazu, Iizuka, Fukuoka, 820-8502, Japan
- Department of Complex Systems Science, Graduate School of Informatics, Nagoya University, Chikusa, Nagoya, Aichi, 464-8601, Japan
| | - Noriko Yuyama Otani
- Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology, Kawazu, Iizuka, Fukuoka, 820-8502, Japan
- Department of Complex Systems Science, Graduate School of Informatics, Nagoya University, Chikusa, Nagoya, Aichi, 464-8601, Japan
| | - Yoshihiro Yamanishi
- Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology, Kawazu, Iizuka, Fukuoka, 820-8502, Japan
- Department of Complex Systems Science, Graduate School of Informatics, Nagoya University, Chikusa, Nagoya, Aichi, 464-8601, Japan
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Wei X, Li M, Tu Y, Wang L. ROC-guided virtual screening, molecular dynamics simulation, and bioactivity validation assessment Z195914464 as a 3CL Mpro inhibitor. Biophys Chem 2025; 317:107357. [PMID: 39612624 DOI: 10.1016/j.bpc.2024.107357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2024] [Revised: 10/30/2024] [Accepted: 11/20/2024] [Indexed: 12/01/2024]
Abstract
Discovering novel class anti-SARS-CoV-2 compounds with novel backbones is essential for preventing and controlling SARS-CoV-2 transmission, which poses a substantial threat to the health and social sustainable development of the global population because of its high pathogenicity and high transmissibility. Although the potential mutation of SARS-CoV-2 might diminish the therapeutic efficacy of drugs, 3CL Mpro is the target highly conservative in contrast with other targets. It is an essential enzyme for coronavirus replication. Based on this, this study utilized the drug discovery strategy of Knime molecular filtering framework, ROC-guided virtual screening, clustering analysis, binding mode analysis, and activity evaluation approaches to identify compound Z195914464 (IC50: 7.19 μM) is a novel class inhibitor of anti-SARS-CoV-2 against the 3CL Mpro target. In addition, based on molecular dynamics simulations and MMPBSA analyses, discovered that compound Z195914464 can interact with more key residues and lower bonding energies, which explains why it exhibited more activity than the other three compounds. In summary, this study developed a method for the rapid and accurate discovery of active compounds and can also be applied in the discovery of active compounds in other targets.
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Affiliation(s)
- Xiongpiao Wei
- Jiangxi Provincial Key Laboratory of Drug Design and Evaluation, School of Pharmacy, Jiangxi Science & Technology Normal University, Economic Development Zone, 330013 Nanchang City, Jiangxi Province, China
| | - Min Li
- Jiangxi Provincial Key Laboratory of Drug Design and Evaluation, School of Pharmacy, Jiangxi Science & Technology Normal University, Economic Development Zone, 330013 Nanchang City, Jiangxi Province, China
| | - Yuanbiao Tu
- Cancer Research Center, Jiangxi University of Traditional Chinese Medicine, Meiling Avenue, Xinjian District, 330004 Nanchang City, Jiangxi Province, China
| | - Linxiao Wang
- Jiangxi Provincial Key Laboratory of Drug Design and Evaluation, School of Pharmacy, Jiangxi Science & Technology Normal University, Economic Development Zone, 330013 Nanchang City, Jiangxi Province, China.
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Abdelrady YA, Thabet HS, Sayed AM. The future of metronomic chemotherapy: experimental and computational approaches of drug repurposing. Pharmacol Rep 2025; 77:1-20. [PMID: 39432183 DOI: 10.1007/s43440-024-00662-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2024] [Revised: 09/30/2024] [Accepted: 10/01/2024] [Indexed: 10/22/2024]
Abstract
Metronomic chemotherapy (MC), long-term continuous administration of anticancer drugs, is gaining attention as an alternative to the traditional maximum tolerated dose (MTD) chemotherapy. By combining MC with other treatments, the therapeutic efficacy is enhanced while minimizing toxicity. MC employs multiple mechanisms, making it a versatile approach against various cancers. However, drug resistance limits the long-term effectiveness of MC, necessitating ongoing development of anticancer drugs. Traditional drug discovery is lengthy and costly due to processes like target protein identification, virtual screening, lead optimization, and safety and efficacy evaluations. Drug repurposing (DR), which screens FDA-approved drugs for new uses, is emerging as a cost-effective alternative. Both experimental and computational methods, such as protein binding assays, in vitro cytotoxicity tests, structure-based screening, and several types of association analyses (Similarity-Based, Network-Based, and Target Gene), along with retrospective clinical analyses, are employed for virtual screening. This review covers the mechanisms of MC, its application in various cancers, DR strategies, examples of repurposed drugs, and the associated challenges and future directions.
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Affiliation(s)
- Yousef A Abdelrady
- Institute of Pharmaceutical Sciences, University of Freiburg, 79104, Freiburg, Germany
| | - Hayam S Thabet
- Microbiology Department, Faculty of Veterinary Medicine, Assiut University, Asyut, 71526, Egypt
| | - Ahmed M Sayed
- Biochemistry Laboratory, Chemistry Department, Faculty of Science, Assiut University, Asyut, 71516, Egypt
- Bioscience Program, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955, Kingdom of Saudi Arabia
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Disha IJ, Hasan R, Bhuia S, Ansari SA, Ansari IA, Islam MT. Anxiolytic Efficacy of Indirubin: In Vivo Approach Along with Receptor Binding Profiling and Molecular Interaction with GABAergic Pathways. ChemistryOpen 2025; 14:e202400290. [PMID: 39460441 PMCID: PMC11808267 DOI: 10.1002/open.202400290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2024] [Revised: 09/03/2024] [Indexed: 10/28/2024] Open
Abstract
Anxiety is a natural response to stress, characterized by feelings of worry, fear, or unease. The current research was conducted to investigate the anxiolytic effect of indirubin (IND) in different behavioral paradigms in Swiss albino mice. To observe the animal's behavioural response to assess anxiolytic activity, different tests were performed, such as the open-field (square cross, grooming, and rearing), swing, dark-light, and hole cross tests. The experimental mice were administered IND (5 and 10 mg/kg, p.o.), where diazepam (DZP) and vehicle were used as positive and negative controls, respectively. In addition, a combination treatment (DZP+IND-10) was provided to the animals to determine the modulatory effect of IND on DZP. Molecular docking approach was also conducted to determine the binding energy of IND with the GABAA receptor (α2 and α3 subunits) and pharmacokinetics were also estimated. The findings revealed that IND dose-dependently significantly (p<0.05) reduced the animal's movement exerting calming behavior like DZP. IND also demonstrated the highest docking score (-7.7 kcal/mol) against the α3 subunit, while DZP showed a lower docking value (-6.4 kcal/mol) than IND. The ADMET analysis revealed that IND has proper drug-likeness and pharmacokinetic characteristics. In conclusion, IND exerted anxiolytic effects through GABAergic Pathways.
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Affiliation(s)
- Ishrat Jahan Disha
- Biochemistry and Molecular BiologyBangabandhu Sheikh Mujibur Rahman Science and Technology UniversityGopalganj8100Bangladesh
- Bioinformatics and Drug Innovation LaboratoryBioLuster Research Center Ltd.Gopalganj, Dhaka8100Bangladesh
| | - Rubel Hasan
- Bioinformatics and Drug Innovation LaboratoryBioLuster Research Center Ltd.Gopalganj, Dhaka8100Bangladesh
- Department of PharmacyBangabandhu Sheikh Mujibur Rahman Science and Technology UniversityGopalganj8100Bangladesh
| | - Shimul Bhuia
- Bioinformatics and Drug Innovation LaboratoryBioLuster Research Center Ltd.Gopalganj, Dhaka8100Bangladesh
- Department of PharmacyBangabandhu Sheikh Mujibur Rahman Science and Technology UniversityGopalganj8100Bangladesh
| | - Siddique Akber Ansari
- Department of Pharmaceutical ChemistryCollege of PharmacyKing Saud UniversityRiyadh11451Saudi Arabia
| | - Irfan Aamer Ansari
- Department of Drug Science and TechnologyUniversity of TurinTurin10124Italy
| | - Muhammad Torequl Islam
- Department of PharmacyBangabandhu Sheikh Mujibur Rahman Science and Technology UniversityGopalganj8100Bangladesh
- Pharmacy DisciplineKhulna UniversityKhulna9208Bangladesh
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Boonsom S, Chamnansil P, Boonseng S, Srisongkram T. ToxSTK: A multi-target toxicity assessment utilizing molecular structure and stacking ensemble learning. Comput Biol Med 2025; 185:109480. [PMID: 39644580 DOI: 10.1016/j.compbiomed.2024.109480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2024] [Revised: 11/04/2024] [Accepted: 11/25/2024] [Indexed: 12/09/2024]
Abstract
Drug registration requires risk assessment of new active pharmaceutical ingredients or excipients to ensure they are safe for human health and the environment. However, traditional risk assessment is expensive and relies heavily on animal testing. Machine learning (ML) has been used as a risk assessment tool, providing less time, money, and involved animals than in vivo experiments. Despite that, the ML models often rely on a single model, which may introduce bias and unreliable prediction. Stacking ensemble learning is an ML framework that makes predictions based on multimodal outcomes. This framework performs well in quantitative structure-activity relationship (QSAR) studies. In this study, we developed ToxSTK, a multi-target toxicity assessment using stacking ensemble learning. We aimed to create an ML tool that facilitates toxicity assessments more affordably with reduced reliance on animal models. We focused on four key targets generally assessed in early-stage drug development: hERG toxicity, mTOR toxicity, PBMCs toxicity, and mutagenicity. Our model integrated 12 molecular fingerprints with 3 ML algorithms, generating 36 novel predictive features (PFs). These PFs were then combined to construct the final meta-decision model. Our results demonstrated that the ToxSTK model surpasses standard regression and classification metrics, ensuring it is highly reliable and accurate in predicting chemical toxicities within its application domain. This model passed the y-randomization test, confirming that the identified QSAR is robust and not due to random chance. Additionally, this model outperforms the existing ML methods for these endpoints, suggesting its effectiveness for risk assessment applications. We recommend incorporating this stacking ensemble learning framework into the chemical risk assessment pipeline to improve model generalization, accuracy, robustness, and reliability.
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Affiliation(s)
- Surapong Boonsom
- Department of Chemistry, Mahidol Wittayanusorn School, Phutthamonthon, Nakhon Pathom, Thailand
| | - Panisara Chamnansil
- Department of Chemistry, Mahidol Wittayanusorn School, Phutthamonthon, Nakhon Pathom, Thailand
| | - Sarote Boonseng
- Department of Chemistry, Mahidol Wittayanusorn School, Phutthamonthon, Nakhon Pathom, Thailand
| | - Tarapong Srisongkram
- Division of Pharmaceutical Chemistry, Faculty of Pharmaceutical Sciences, Khon Kaen University, Thailand.
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Li T, Wan Z, Wang Q, Qiao F, Pan G, Zhao C, Zhu Y, Zhou H, Tan Y, Zhou Z, Zhang D. Utilizing Tissues Self-Assembled in Fiber Optic-Based "Chinese Guzheng Strings" for Contractility Sensing and Drug Efficacy Evaluation: A Practical Approach. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2025; 21:e2406144. [PMID: 39822158 DOI: 10.1002/smll.202406144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2024] [Revised: 12/25/2024] [Indexed: 01/19/2025]
Abstract
Recent advances in drug design and compound synthesis have highlighted the increasing need for effective methods of toxicity evaluation. A specialized force sensor, known as the light wavelength-encoded "Chinese guzheng" is developed. This innovative sensor is equipped with optical fiber strings and utilizes a wavelength-encoded fiber Bragg grating (FBG) that is chemically etched to reduce its diameter. This design allows the sensor to detect minimal forces as low as l µN. This sensor is successfully applied to monitor human-induced pluripotent stem cell-derived human-engineered heart tissue (hEHT) models that can self-assemble and contact optical fiber-based strings. The sensor detects micro newton contraction forces in real-time by measuring the wavelength drift resulting from hEHT contractions. In addition, the sensor is precise and durable, exhibiting a fatigue resistance of up to 800 000 cycles, making it suitable for long-term monitoring. The device effectively measured the contractile force of the hEHTs under various physiological conditions, including natural contraction, electrical stimulation, and stretching. Moreover, multichannel detection enables the study and demonstration of short- and long-term effectiveness of multiple drugs. This breakthrough sensor addresses the critical need for high-precision real-time monitoring in drug evaluation and provides a solid foundation for screening drugs to treat cardiomyopathy.
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Affiliation(s)
- Tianliang Li
- School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, Hubei, 430070, China
| | - Zhongjun Wan
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Stem Cells and Tissue Engineering Manufacture Center, School of Life Science, Hubei University, Wuhan, Hubei, 430062, China
| | - Qian'ao Wang
- School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, Hubei, 430070, China
| | - Feng Qiao
- School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, Hubei, 430070, China
| | - Ganlin Pan
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Stem Cells and Tissue Engineering Manufacture Center, School of Life Science, Hubei University, Wuhan, Hubei, 430062, China
| | - Chen Zhao
- School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, Hubei, 430070, China
| | - Yongwen Zhu
- School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, Hubei, 430070, China
| | - Haotian Zhou
- School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, Hubei, 430070, China
| | - Yuegang Tan
- School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, Hubei, 430070, China
| | - Zude Zhou
- School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, Hubei, 430070, China
| | - Donghui Zhang
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Stem Cells and Tissue Engineering Manufacture Center, School of Life Science, Hubei University, Wuhan, Hubei, 430062, China
- Cardiovascular Institute, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, China
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130
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Woodward DJ, Thorp JG, Middeldorp CM, Akóṣílè W, Derks EM, Gerring ZF. Leveraging pleiotropy for the improved treatment of psychiatric disorders. Mol Psychiatry 2025; 30:705-721. [PMID: 39390223 PMCID: PMC11746150 DOI: 10.1038/s41380-024-02771-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 09/23/2024] [Accepted: 09/25/2024] [Indexed: 10/12/2024]
Abstract
Over 90% of drug candidates fail in clinical trials, while it takes 10-15 years and one billion US dollars to develop a single successful drug. Drug development is more challenging for psychiatric disorders, where disease comorbidity and complex symptom profiles obscure the identification of causal mechanisms for therapeutic intervention. One promising approach for determining more suitable drug candidates in clinical trials is integrating human genetic data into the selection process. Genome-wide association studies have identified thousands of replicable risk loci for psychiatric disorders, and sophisticated statistical tools are increasingly effective at using these data to pinpoint likely causal genes. These studies have also uncovered shared or pleiotropic genetic risk factors underlying comorbid psychiatric disorders. In this article, we argue that leveraging pleiotropic effects will provide opportunities to discover novel drug targets and identify more effective treatments for psychiatric disorders by targeting a common mechanism rather than treating each disease separately.
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Affiliation(s)
- Damian J Woodward
- Brain and Mental Health, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
- School of Biomedical Science, Queensland University of Technology, Brisbane, QLD, Australia.
| | - Jackson G Thorp
- Brain and Mental Health, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Christel M Middeldorp
- Department of Child and Adolescent Psychiatry and Psychology, Amsterdam UMC, Amsterdam Reproduction and Development Research Institute, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Arkin Mental Health Care, Amsterdam, The Netherlands
- Levvel, Academic Center for Child and Adolescent Psychiatry, Amsterdam, The Netherlands
- Child Health Research Centre, University of Queensland, Brisbane, QLD, Australia
- Child and Youth Mental Health Service, Children's Health Queensland Hospital and Health Service, Brisbane, QLD, Australia
| | - Wọlé Akóṣílè
- Greater Brisbane Clinical School, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Eske M Derks
- Brain and Mental Health, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Zachary F Gerring
- Brain and Mental Health, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
- Healthy Development and Ageing, Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia.
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131
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Krendl FJ, Primavesi F, Oberhuber R, Neureiter D, Ocker M, Bekric D, Kiesslich T, Mayr C. The importance of preclinical models for cholangiocarcinoma drug discovery. Expert Opin Drug Discov 2025; 20:205-216. [PMID: 39840603 DOI: 10.1080/17460441.2025.2457637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2024] [Revised: 01/09/2025] [Accepted: 01/20/2025] [Indexed: 01/23/2025]
Abstract
INTRODUCTION Biliary tract cancer (BTC) comprises a clinically diverse and genetically heterogeneous group of tumors along the intra- and extrahepatic biliary system (intrahepatic and extrahepatic cholangiocarcinoma) and gallbladder cancer with the common feature of a poor prognosis, despite increasing molecular knowledge of associated genetic aberrations and possible targeted therapies. Therefore, the search for even more precise and individualized therapies is ongoing and preclinical tumor models are central to the development of such new approaches. AREAS COVERED The models described in the current review include simple and advanced in vitro and in vivo models, including cell lines, 2D monolayer, spheroid and organoid cultures, 3D bioprinting, patient-derived xenografts, and more recently, machine-perfusion platform-based models of resected liver specimens. All these models have individual advantages, disadvantages and limitations that need to be considered depending on the desired application. EXPERT OPINION In addition to potential cost limitations, availability of BTC cell types, time required for model establishment and growth success rate, the individual models differently reflect relevant characteristics such as tumor heterogeneity, spatial tumor-stroma microenvironment interactions, metabolic and nutritional gradients and immunological interactions. Therefore, a consequent combination of different models may be required to improve clinical study outcomes by strengthening the preclinical data basis.
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Affiliation(s)
- Felix J Krendl
- Department of Visceral, Transplant and Thoracic Surgery, Center for Operative Medicine, Medical University of Innsbruck, Innsbruck, Austria
| | - Florian Primavesi
- Department of Visceral, Transplant and Thoracic Surgery, Center for Operative Medicine, Medical University of Innsbruck, Innsbruck, Austria
| | - Rupert Oberhuber
- Department of Visceral, Transplant and Thoracic Surgery, Center for Operative Medicine, Medical University of Innsbruck, Innsbruck, Austria
| | - Daniel Neureiter
- Institute of Pathology, Paracelsus Medical University/University Hospital Salzburg (SALK), Salzburg, Austria
- Cancer Cluster Salzburg, Salzburg, Austria
| | - Matthias Ocker
- Medical Department, Division of Hematology, Oncology, and Cancer Immunology, Campus Charité Mitte, Charité University Medicine Berlin, Berlin, Germany
- EO Translational Insights Consulting GmbH, Berlin, Germany
- Tacalyx GmbH, Berlin, Germany
| | - Dino Bekric
- Center of Physiology, Pathophysiology and Biophysics, Institute of Physiology and Pathophysiology, Paracelsus Medical University, Salzburg, Austria
| | - Tobias Kiesslich
- Center of Physiology, Pathophysiology and Biophysics, Institute of Physiology and Pathophysiology, Paracelsus Medical University, Salzburg, Austria
- Department of Internal Medicine I, Paracelsus Medical University/University Hospital Salzburg (SALK), Salzburg, Austria
| | - Christian Mayr
- Center of Physiology, Pathophysiology and Biophysics, Institute of Physiology and Pathophysiology, Paracelsus Medical University, Salzburg, Austria
- Department of Internal Medicine I, Paracelsus Medical University/University Hospital Salzburg (SALK), Salzburg, Austria
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132
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Inal-Gültekin G, Çetin Z, Mangır N. Exploring Drug Repurposing for Interstitial Cystitis/Bladder Pain Syndrome: Defining Novel Therapeutic Targets. Neurourol Urodyn 2025; 44:496-503. [PMID: 39723619 DOI: 10.1002/nau.25651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2024] [Accepted: 12/04/2024] [Indexed: 12/28/2024]
Abstract
INTRODUCTION Interstitial cystitis/bladder pain syndrome (IC/BPS) is a debilitating pain condition of unknown etiology. Effective therapies for this condition could not have been developed in the last century. Drug repurposing is a practical strategy for enhancing patient access to successful therapies. It is an approach for discovering novel applications for licensed or investigational pharmaceuticals that extend beyond the initial medical indication. This work aims to identify repurposable medications through bioinformatics to discover potential drugs or compounds that can reverse the IC/BPS disease signature. METHODS AND MATERIAL The analysis involved examining the differentially expressed genes in IC/BPS patients with two distinct disease phenotypes (Hunner's lesion disease, non-Hunner's lesion disease) and controls using the datasets GSE11783, GSE28242, and GSE57560. The goal was to assess the reversal of the disease signature on the L1000CDS2 and cMAP platforms. RESULTS Twenty-one compounds were repurposed, consisting of 11 small molecules, 10 chemical compounds, 3 natural products, and 6 FDA-approved drugs, currently used for clinical indications such as cancer, myelofibrosis, and diabetes. DISCUSSION Bioinformatics can be useful for identifying therapeutic agents for IC/BPS by accessing and processing big data on molecular and cellular levels. Prospective in vivo experiments must validate repurposed drugs. The expansion of large-scale genome sequencing, gene expression studies, and clinical data for IC/BPS will improve successful drug selection.
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Affiliation(s)
- Güldal Inal-Gültekin
- Department of Physiology, Faculty of Medicine, Istanbul Okan University, Istanbul, Türkiye
| | - Zeliha Çetin
- Department of Bioinformatics, Bingen University of Applied Sciences, Bingen am Rhein, Germany
| | - Naşide Mangır
- Faculty of Medicine, Department of Urology, Hacettepe University, Ankara, Türkiye
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133
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van Bergen W, Nederstigt AE, Heck AJR, Baggelaar MP. Site-Specific Competitive Kinase Inhibitor Target Profiling Using Phosphonate Affinity Tags. Mol Cell Proteomics 2025; 24:100906. [PMID: 39826875 PMCID: PMC11889359 DOI: 10.1016/j.mcpro.2025.100906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2024] [Revised: 01/10/2025] [Accepted: 01/12/2025] [Indexed: 01/22/2025] Open
Abstract
Protein kinases are prime targets for drug development due to their involvement in various cancers. However, selective inhibition of kinases, while avoiding off-target effects remains a significant challenge for the development of protein kinase inhibitors. Activity-based protein profiling (ABPP), in combination with pan-kinase activity-based probes (ABPs) and mass spectrometry-based proteomics, enables the identification of kinase drug targets. Here, we extend existing ABPP strategies for kinase profiling with a site-specific analysis, allowing for protein kinase inhibitor target engagement profiling with amino acid specificity. The site-specific approach involves highly efficient enrichment of ABP-labeled peptides, resulting in a less complex peptide matrix, straightforward data analysis, and the screening of over ∼100 kinase active sites in a single LC-MS analysis. The complementary use of both trypsin and pepsin in parallel to generate the ABP-labeled peptides considerably expanded the coverage of kinases and pinpoint the exact binding sites. Using the site-specific strategy to examine the on- and off-targets of the Ephrin receptor (Eph) B4 inhibitor NVP-BHG712 showed binding to EphA2 with an IC50 of 17 nM and EphB4 with an IC50 of 20 nM. Next to the known targets, EphA2 and EphB4, NVP-BHG712 bound to the discoidin domain-containing receptor 1 with an IC50 of 2.1 nM, suggesting that a discoidin domain-containing receptor 1-targeting regio-isomer of NVP-BHG712 was used. The promiscuity of XO44 toward ATP-binding pockets on nonkinase proteins facilitated the screening of additional off-target sites, revealing inosine-5'-monophosphate dehydrogenase 2 as a putative off-target. Expanding the search to other amino acids revealed that XO44, in addition to 745 lysines, also covalently linked 715 tyrosines, which significantly expands the competitive ABPP search space and highlights the added value of the site-specific method. Therefore, the presented approach, which can be fully automated with liquid handling platforms, provides a straightforward, valuable new approach for competitive site-specific kinase inhibitor target profiling.
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Affiliation(s)
- Wouter van Bergen
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, CH, The Netherlands; Netherlands Proteomics Center, Utrecht, CH, The Netherlands
| | - Anneroos E Nederstigt
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, CH, The Netherlands; Netherlands Proteomics Center, Utrecht, CH, The Netherlands
| | - Albert J R Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, CH, The Netherlands; Netherlands Proteomics Center, Utrecht, CH, The Netherlands
| | - Marc P Baggelaar
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, CH, The Netherlands; Netherlands Proteomics Center, Utrecht, CH, The Netherlands.
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134
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Kim Y, Kang M, Mamo MG, Adisasmita M, Huch M, Choi D. Liver organoids: Current advances and future applications for hepatology. Clin Mol Hepatol 2025; 31:S327-S348. [PMID: 39722609 PMCID: PMC11925438 DOI: 10.3350/cmh.2024.1040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2024] [Revised: 12/13/2024] [Accepted: 12/24/2024] [Indexed: 12/28/2024] Open
Abstract
The creation of self-organizing liver organoids represents a significant, although modest, step toward addressing the ongoing organ shortage crisis in allogeneic liver transplantation. However, researchers have recognized that achieving a fully functional whole liver remains a distant goal, and the original ambition of organoid-based liver generation has been temporarily put on hold. Instead, liver organoids have revolutionized the field of hepatology, extending their influence into various domains of precision and molecular medicine. These 3D cultures, capable of replicating key features of human liver function and pathology, have opened new avenues for human-relevant disease modeling, CRISPR gene editing, and high-throughput drug screening that animal models cannot accomplish. Moreover, advancements in creating more complex systems have led to the development of multicellular assembloids, dynamic organoid-on-chip systems, and 3D bioprinting technologies. These innovations enable detailed modeling of liver microenvironments and complex tissue interactions. Progress in regenerative medicine and transplantation applications continues to evolve and strives to overcome the obstacles of biocompatibility and tumorigenecity. In this review, we examine the current state of liver organoid research by offering insights into where the field currently stands, and the pivotal developments that are shaping its future.
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Affiliation(s)
- Yohan Kim
- Department of MetaBioHealth, Sungkyunkwan University, Suwon, Korea
- Department of Biopharmaceutical Convergence, Sungkyunkwan University, Suwon, Korea
- Biomedical Institute for Convergence at SKKU, Sungkyunkwan University, Suwon, Korea
| | - Minseok Kang
- Department of Surgery, Hanyang University College of Medicine, Seoul, Korea
| | - Michael Girma Mamo
- Department of Surgery, Hanyang University College of Medicine, Seoul, Korea
- Research Institute of Regenerative Medicine and Stem Cells, Hanyang University, Seoul, Korea
| | - Michael Adisasmita
- Department of Surgery, Hanyang University College of Medicine, Seoul, Korea
- Research Institute of Regenerative Medicine and Stem Cells, Hanyang University, Seoul, Korea
| | - Meritxell Huch
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Dongho Choi
- Department of Surgery, Hanyang University College of Medicine, Seoul, Korea
- Research Institute of Regenerative Medicine and Stem Cells, Hanyang University, Seoul, Korea
- Hanyang Institute of Bioscience and Biotechnology, Hanyang University, Seoul, Korea
- Department of HY-KIST Bio-convergence, Hanyang University, Seoul, Korea
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135
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Debnath A, Singh RK, Mazumder R, Mazumder A, Srivastava S, Chaudhary H, Mangal S, Sanchitra J, Tyagi PK, Kumar Singh S, Singh AK. Quest for discovering novel CDK12 inhibitor. J Recept Signal Transduct Res 2025; 45:1-21. [PMID: 39697035 DOI: 10.1080/10799893.2024.2441185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Revised: 12/04/2024] [Accepted: 12/06/2024] [Indexed: 12/20/2024]
Abstract
CDK12 is essential for cellular processes like RNA processing, transcription, and cell cycle regulation, inhibiting cancer cell growth and facilitating macrophage invasion. CDK12 is a significant oncogenic factor in various cancers, including HER2-positive breast cancer, Anaplastic thyroid carcinoma, Hepatocellular carcinoma, prostate cancer, and Ewing sarcoma. It is also regarded as a potential biomarker, emphasizing its broader significance in oncology. Targeting CDK12 offers a promising strategy to develop therapy. Various monoclonal antibodies have drawn wide attention, but they are expensive compared to small-molecule inhibitors, limiting their accessibility and affordability for patients. Consequently, this research aims to identify effective CDK12 inhibitors using comprehensive high-throughput virtual screening. RASPD protocol has been employed to screen three different databases against the target followed by drug-likeness, molecular docking, ADME, toxicity, Consensus molecular docking, MD Simulation, and in-vitro studies MTT assay. The research conducted yielded one compound ZINC11784547 has demonstrated robust binding affinity, favorable ADME features, less toxicity, remarkable stability, and cytotoxic effect. The identified compound holds promise for promoting cancer cell death through CDK12 inhibition.
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Affiliation(s)
- Abhijit Debnath
- Noida Institute of Engineering and Technology (Pharmacy Institute), Greater Noida, India
| | - Rajesh Kumar Singh
- Department of Dravyaguna, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
| | - Rupa Mazumder
- Noida Institute of Engineering and Technology (Pharmacy Institute), Greater Noida, India
| | - Avijit Mazumder
- Noida Institute of Engineering and Technology (Pharmacy Institute), Greater Noida, India
| | - Shikha Srivastava
- Bhaskaracharya College of Applied Sciences, University of Delhi, Delhi, India
| | - Hema Chaudhary
- School of Medical & Allied Sciences, K R Mangalam University, Gurugram, India
| | - Saloni Mangal
- Noida Institute of Engineering and Technology (Pharmacy Institute), Greater Noida, India
| | - Jahanvi Sanchitra
- Noida Institute of Engineering and Technology (Pharmacy Institute), Greater Noida, India
| | | | - Sachin Kumar Singh
- School of Pharmaceutical Sciences, Lovely Professional University, Phagwara, India
| | - Anil Kumar Singh
- Department of Dravyaguna, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
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136
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Masand VH, Patil MK, Al-Hussain SA, Samad A, Rastija V, Jawarkar RD, Masand GS, Gawali RG, Zaki MEA. Analyzing Oxygen Atom Distribution in FDA-Approved Drugs to Enhance Drug Discovery Strategies. Chem Biol Drug Des 2025; 105:e70060. [PMID: 39912316 DOI: 10.1111/cbdd.70060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2024] [Revised: 12/26/2024] [Accepted: 01/22/2025] [Indexed: 02/07/2025]
Abstract
Despite advancements in molecular design rules and understanding biochemical processes, the field of drug design and discovery seeks to minimize the number and duration of synthesis-testing cycles to convert lead compounds into drug candidates. A promising strategy involves gaining insightful understanding of key heteroatoms such as oxygen and nitrogen. This work presents a comprehensive analysis of oxygen atoms in approved drugs, aiming to streamline drug design and discovery efforts. The study examines the frequency, distribution, prevalence, and diversity of oxygen atoms in a dataset of 2049 small molecules approved by the FDA and other agencies. The analysis focuses on various types of oxygen atoms, including sp3, sp2-hybridized, ring, and nonring. In general, existence of sp3-O slightly outperforms sp2-O, which is associated with balancing various factors such as flexibility, solubility, stability, and pharmacokinetics, in addition to activity and selectivity. In approved drugs, majority of oxygen atoms are present within 4 Å from the COM of the molecule. This analysis offers valuable understanding of oxygen distribution, which could be used during the multiparameter optimization process, facilitating the transformation of a hit/lead compound into a potential drug candidate.
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Affiliation(s)
- Vijay H Masand
- Department of Chemistry, Vidya Bharati Mahavidyalaya, Amravati, Maharashtra, India
| | - Meghshyam K Patil
- Department of Chemistry, Dr. Babasaheb Ambedkar Marathwada University, Sub-Campus, Dharashiv, Maharashtra, India
| | - Sami A Al-Hussain
- Department of Chemistry, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia
| | - Abdul Samad
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Tishk International University, Erbil, Kurdistan Region, Iraq
| | - Vesna Rastija
- Department of Agroecology and Environmental Protection, Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
| | - Rahul D Jawarkar
- Department of Medicinal Chemistry, Dr. Rajendra Gode Institute of Pharmacy, Amravati, Maharashtra, India
| | - Gaurav S Masand
- Dr. D. Y. Patil Unitech Society's Dr. D. Y. Patil Institute of Technology, Pune, Maharashtra, India
| | - Rakhi G Gawali
- Department of Chemistry, D.B.F. Dayanand College of Arts & Science, Solapur, India
| | - Magdi E A Zaki
- Department of Chemistry, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia
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137
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McGreevy O, Bosakhar M, Gilbert T, Quinn M, Fenwick S, Malik H, Goldring C, Randle L. The importance of preclinical models in cholangiocarcinoma. EUROPEAN JOURNAL OF SURGICAL ONCOLOGY 2025; 51:108304. [PMID: 38653585 DOI: 10.1016/j.ejso.2024.108304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Accepted: 03/23/2024] [Indexed: 04/25/2024]
Abstract
Cholangiocarcinoma (CCA) is an adenocarcinoma of the hepatobiliary system with a grim prognosis. Incidence is rising globally and surgery is currently the only curative treatment, but is only available for patients who are fit and diagnosed in an early-stage of disease progression. Great importance has been placed on developing preclinical models to help further our understanding of CCA and potential treatments to improve therapeutic outcomes. Preclinical models of varying complexity and cost have been established, ranging from more simplistic in vitro 2D CCA cell lines in culture, to more complex in vivo genetically engineered mouse models. Currently there is no single model that faithfully recaptures the complexities of human CCA and the in vivo tumour microenvironment. Instead a multi-model approach should be used when designing preclinical trials to study CCA and potential therapies.
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Affiliation(s)
- Owen McGreevy
- The Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, The University of Liverpool, Sherrington Building, Ashton Street, Liverpool, L69 3GE, UK
| | - Mohammed Bosakhar
- The Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, The University of Liverpool, Sherrington Building, Ashton Street, Liverpool, L69 3GE, UK
| | - Timothy Gilbert
- The Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, The University of Liverpool, Sherrington Building, Ashton Street, Liverpool, L69 3GE, UK; Hepatobiliary Surgery, Liverpool University Hospitals NHS Foundation Trust, Royal Liverpool University Hospital, Prescot Street, L7 8XP, Liverpool, UK
| | - Marc Quinn
- The Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, The University of Liverpool, Sherrington Building, Ashton Street, Liverpool, L69 3GE, UK; Hepatobiliary Surgery, Liverpool University Hospitals NHS Foundation Trust, Royal Liverpool University Hospital, Prescot Street, L7 8XP, Liverpool, UK
| | - Stephen Fenwick
- Hepatobiliary Surgery, Liverpool University Hospitals NHS Foundation Trust, Royal Liverpool University Hospital, Prescot Street, L7 8XP, Liverpool, UK
| | - Hassan Malik
- Hepatobiliary Surgery, Liverpool University Hospitals NHS Foundation Trust, Royal Liverpool University Hospital, Prescot Street, L7 8XP, Liverpool, UK
| | - Christopher Goldring
- The Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, The University of Liverpool, Sherrington Building, Ashton Street, Liverpool, L69 3GE, UK
| | - Laura Randle
- The Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, The University of Liverpool, Sherrington Building, Ashton Street, Liverpool, L69 3GE, UK.
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138
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Orszulak L, Włodarczyk P, Hachuła B, Lamrani T, Jurkiewicz K, Tarnacka M, Hreczka M, Kamiński K, Kamińska E. Inhibition of naproxen crystallization by polymers: The role of topology and chain length of polyvinylpyrrolidone macromolecules. Eur J Pharm Biopharm 2025; 207:114581. [PMID: 39608423 DOI: 10.1016/j.ejpb.2024.114581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2024] [Revised: 11/07/2024] [Accepted: 11/13/2024] [Indexed: 11/30/2024]
Abstract
This paper presents an innovative approach that utilizes self-synthesized homopolymers of polyvinylpyrrolidone (PVP) with different architectures as effective matrices for inhibiting the crystallization of naproxen (NAP). We have thoroughly investigated amorphous solid dispersions containing NAP and (i) self-synthesized linear PVP, (ii) self-synthesized three-armed star-shaped PVP, and (iii) self-synthesized linear PVP with a mass (Mn) corresponding to the length of one arm of the star polymer, as well as (iv) commercial linear PVP K30 as a reference. Differential scanning calorimetry, X-ray diffraction, and infrared spectroscopy studies, as well as molecular dynamics simulations were conducted to gain comprehensive insights into the thermal and structural properties, as well as intermolecular interactions in the NAP-PVP systems. The main purpose of all experiments was to assess the impact of macromolecule structure (topology, molecular weight) on the kinetics of the crystallization of NAP - a drug that is very difficult to vitrify. Our studies clearly showed that the most effective matrix in inhibiting the NAP crystallization is linear, self-synthesized PVP with higher molecular weight (Mn) similar to that of the commercial PVP K30, but lower, strictly controlled dispersity. We also found that crystallization of API proceeds at a similar pace for the binary mixture composed of a star-shaped PVP and linear polymer with Mn corresponding to Mn of one arm of the star-shaped macromolecule in the vicinity of the Tg. The obtained data highlight the key role of polymer structure in designing new pharmaceutical formulations.
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Affiliation(s)
- Luiza Orszulak
- Institute of Chemistry, Faculty of Science and Technology, University of Silesia in Katowice, Szkolna 9 40-007, Katowice, Poland.
| | - Patryk Włodarczyk
- Institute of Non Ferrous Metals, Sowinskiego 5 44-100, Gliwice, Poland
| | - Barbara Hachuła
- Institute of Chemistry, Faculty of Science and Technology, University of Silesia in Katowice, Szkolna 9 40-007, Katowice, Poland
| | - Taoufik Lamrani
- Institute of Physics, Faculty of Science and Technology, University of Silesia in Katowice, 75 Pulku Piechoty 1, 41-500 Chorzow, Poland
| | - Karolina Jurkiewicz
- Institute of Physics, Faculty of Science and Technology, University of Silesia in Katowice, 75 Pulku Piechoty 1, 41-500 Chorzow, Poland
| | - Magdalena Tarnacka
- Institute of Physics, Faculty of Science and Technology, University of Silesia in Katowice, 75 Pulku Piechoty 1, 41-500 Chorzow, Poland
| | - Marek Hreczka
- Institute of Non Ferrous Metals, Sowinskiego 5 44-100, Gliwice, Poland; Department of Mechatronics, Silesian University of Technology, Akademicka 10A 44-100, Gliwice, Poland
| | - Kamil Kamiński
- Institute of Physics, Faculty of Science and Technology, University of Silesia in Katowice, 75 Pulku Piechoty 1, 41-500 Chorzow, Poland
| | - Ewa Kamińska
- Department of Pharmacognosy and Phytochemistry, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia in Katowice, Jagiellonska 4 41-200, Sosnowiec, Poland.
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139
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Ireland D, Rabeler C, Rao S, Richardson RJ, Collins EMS. Distinguishing classes of neuroactive drugs based on computational physicochemical properties and experimental phenotypic profiling in planarians. PLoS One 2025; 20:e0315394. [PMID: 39883642 PMCID: PMC11781733 DOI: 10.1371/journal.pone.0315394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2024] [Accepted: 11/25/2024] [Indexed: 02/01/2025] Open
Abstract
Mental illnesses put a tremendous burden on afflicted individuals and society. Identification of novel drugs to treat such conditions is intrinsically challenging due to the complexity of neuropsychiatric diseases and the need for a systems-level understanding that goes beyond single molecule-target interactions. Thus far, drug discovery approaches focused on target-based in silico or in vitro high-throughput screening (HTS) have had limited success because they cannot capture pathway interactions or predict how a compound will affect the whole organism. Organismal behavioral testing is needed to fill the gap, but mammalian studies are too time-consuming and cost-prohibitive for the early stages of drug discovery. Behavioral medium-throughput screening (MTS) in small organisms promises to address this need and complement in silico and in vitro HTS to improve the discovery of novel neuroactive compounds. Here, we used cheminformatics and MTS in the freshwater planarian Dugesia japonica-an invertebrate system used for neurotoxicant testing-to evaluate the extent to which complementary insight could be gained from the two data streams. In this pilot study, our goal was to classify 19 neuroactive compounds into their functional categories: antipsychotics, anxiolytics, and antidepressants. Drug classification was performed with the same computational methods, using either physicochemical descriptors or planarian behavioral profiling. As it was not obvious a priori which classification method was most suited to this task, we compared the performance of four classification approaches. We used principal coordinate analysis or uniform manifold approximation and projection, each coupled with linear discriminant analysis, and two types of machine learning models-artificial neural net ensembles and support vector machines. Classification based on physicochemical properties had comparable accuracy to classification based on planarian profiling, especially with the machine learning models that all had accuracies of 90-100%. Planarian behavioral MTS correctly identified drugs with multiple therapeutic uses, thus yielding additional information compared to cheminformatics. Given that planarian behavioral MTS is an inexpensive true 3R (refine, reduce, replace) alternative to vertebrate testing and requires zero a priori knowledge about a chemical, it is a promising experimental system to complement in silico cheminformatics to identify new drug candidates.
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Affiliation(s)
- Danielle Ireland
- Department of Biology, Swarthmore College, Swarthmore, Pennsylvania, United States of America
| | - Christina Rabeler
- Department of Biology, Swarthmore College, Swarthmore, Pennsylvania, United States of America
| | - Sagar Rao
- Department of Biology, Swarthmore College, Swarthmore, Pennsylvania, United States of America
| | - Rudy J. Richardson
- Department of Environmental Health Sciences, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Neurology, University of Michigan, Ann Arbor, Michigan, United States of America
- Center of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America
- Michigan Institute for Computational Discovery and Engineering, University of Michigan, Ann Arbor, Michigan, United States of America
- Michigan Institute for Data and AI in Society, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Eva-Maria S. Collins
- Department of Biology, Swarthmore College, Swarthmore, Pennsylvania, United States of America
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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140
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Unlocking drug modes of action with multi-dimensional high-throughput metabolic profiling. Nat Biotechnol 2025:10.1038/s41587-024-02525-4. [PMID: 39875673 DOI: 10.1038/s41587-024-02525-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2025]
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141
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Testa M, Gaggianesi M, D’Accardo C, Porcelli G, Turdo A, Di Marco C, Patella B, Di Franco S, Modica C, Di Bella S, Lopresti F, Stassi G, La Carrubba V, Todaro M. A Novel Tumor on Chip Mimicking the Breast Cancer Microenvironment for Dynamic Drug Screening. Int J Mol Sci 2025; 26:1028. [PMID: 39940796 PMCID: PMC11816644 DOI: 10.3390/ijms26031028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2024] [Revised: 01/20/2025] [Accepted: 01/23/2025] [Indexed: 02/16/2025] Open
Abstract
In light of the emerging breakthroughs in cancer biology, drug discovery, and personalized medicine, Tumor-on-Chip (ToC) platforms have become pivotal tools in current biomedical research. This study introduced a novel rapid prototyping approach for the fabrication of a ToC device using laser-patterned poly(methyl methacrylate) (PMMA) layers integrated with a polylactic acid (PLA) electrospun scaffold, enabling dynamic drug delivery and the assessment of therapeutic efficacy in cancer cells. Traditional drug screening methods, such as conventional cell cultures, mimic certain aspects of cancer progression but fail to capture critical features of the tumor microenvironment (TME). While animal models offer a closer approximation of tumor complexity, they are limited in their ability to predict human drug responses. Here, we evaluated the ability of our ToC device to recapitulate the interactions between cancer and TME cells and its efficacy in evaluating the drug response of breast cancer cells. The functional design of the proposed ToC system offered substantial potential for a wide range of applications in cancer research, significantly accelerating the preclinical assessment of new therapeutic agents.
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Affiliation(s)
- Maria Testa
- Department of Biomedicina, Neuroscienze e Diagnostica avanzata (Bind), University of Palermo, 90127 Palermo, Italy;
- Department of Engineering, University of Palermo, 90128 Palermo, Italy; (C.D.M.); (B.P.); (V.L.C.)
| | - Miriam Gaggianesi
- Department of Precision Medicine in Medical, Surgical, and Critical Areas (Me.Pre.C.C.), University of Palermo, 90127 Palermo, Italy; (M.G.); (C.D.); (G.P.); (S.D.F.); (C.M.); (S.D.B.)
| | - Caterina D’Accardo
- Department of Precision Medicine in Medical, Surgical, and Critical Areas (Me.Pre.C.C.), University of Palermo, 90127 Palermo, Italy; (M.G.); (C.D.); (G.P.); (S.D.F.); (C.M.); (S.D.B.)
| | - Gaetana Porcelli
- Department of Precision Medicine in Medical, Surgical, and Critical Areas (Me.Pre.C.C.), University of Palermo, 90127 Palermo, Italy; (M.G.); (C.D.); (G.P.); (S.D.F.); (C.M.); (S.D.B.)
| | - Alice Turdo
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties (PROMISE), University of Palermo, 90127 Palermo, Italy; (A.T.); (M.T.)
| | - Chiara Di Marco
- Department of Engineering, University of Palermo, 90128 Palermo, Italy; (C.D.M.); (B.P.); (V.L.C.)
| | - Bernardo Patella
- Department of Engineering, University of Palermo, 90128 Palermo, Italy; (C.D.M.); (B.P.); (V.L.C.)
| | - Simone Di Franco
- Department of Precision Medicine in Medical, Surgical, and Critical Areas (Me.Pre.C.C.), University of Palermo, 90127 Palermo, Italy; (M.G.); (C.D.); (G.P.); (S.D.F.); (C.M.); (S.D.B.)
| | - Chiara Modica
- Department of Precision Medicine in Medical, Surgical, and Critical Areas (Me.Pre.C.C.), University of Palermo, 90127 Palermo, Italy; (M.G.); (C.D.); (G.P.); (S.D.F.); (C.M.); (S.D.B.)
| | - Sebastiano Di Bella
- Department of Precision Medicine in Medical, Surgical, and Critical Areas (Me.Pre.C.C.), University of Palermo, 90127 Palermo, Italy; (M.G.); (C.D.); (G.P.); (S.D.F.); (C.M.); (S.D.B.)
| | - Francesco Lopresti
- Department of Engineering, University of Palermo, 90128 Palermo, Italy; (C.D.M.); (B.P.); (V.L.C.)
| | - Giorgio Stassi
- Department of Precision Medicine in Medical, Surgical, and Critical Areas (Me.Pre.C.C.), University of Palermo, 90127 Palermo, Italy; (M.G.); (C.D.); (G.P.); (S.D.F.); (C.M.); (S.D.B.)
| | - Vincenzo La Carrubba
- Department of Engineering, University of Palermo, 90128 Palermo, Italy; (C.D.M.); (B.P.); (V.L.C.)
| | - Matilde Todaro
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties (PROMISE), University of Palermo, 90127 Palermo, Italy; (A.T.); (M.T.)
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142
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Srirangan P, Sabina EP. Protective effects of herbal compounds against cyclophosphamide-induced organ toxicity: a pathway-centered approach. Drug Chem Toxicol 2025:1-43. [PMID: 39847469 DOI: 10.1080/01480545.2025.2455442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2024] [Revised: 12/24/2024] [Accepted: 01/14/2025] [Indexed: 01/25/2025]
Abstract
Cyclophosphamide is a key component of numerous chemotherapeutic protocols, demonstrating broad-spectrum efficacy against various malignancies and non-cancerous conditions. This review examines CPM's metabolic pathways, therapeutic applications, and its resulting organ-specific toxicities. Despite its clinical benefits in treating nephrotic syndrome, encephalomyelitis, breast cancer, ovarian cancer, and other diseases, CPM is associated with significant adverse effects on the kidneys, liver, heart, lungs, and intestines. The discussion delves into the molecular mechanisms underlying these toxicities, highlighting dysregulation in key signaling pathways, including Nrf2, NF-κB, MAPK/ERK, and AKT. In addressing these challenges, recent studies have identified various herbal drugs and phytochemicals capable of mitigating CPM-induced toxicity. Notable compounds such as cinnamaldehyde, baicalin, quercetin, and curcumin have demonstrated protective effects. Integrating these herbal formulations with CPM therapy is proposed to enhance patient safety and treatment efficacy. This review underscores the influence of CPM on apoptosis and inflammation pathways, which lead to alterations in organ-specific biomarkers. Phytochemicals may exert protective effects by restoring disrupted signaling pathways and normalizing altered biomarkers. The compilation of phytochemicals presented in this review serves as a valuable resource for researchers exploring other herbal products with potential protective effects against CPM toxicity. A significant gap in the current literature is the lack of clinical trials evaluating phytochemicals that mitigate CPM toxicity in vivo. Rigorous clinical studies are necessary to establish the efficacy and safety of herbal formulations in cancer treatment. Such research will clarify the role of natural remedies in complementing conventional therapies, ultimately improving patient outcomes.
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Affiliation(s)
- Prathap Srirangan
- Department of Biotechnology, School of Biosciences and Technology, VIT University, Vellore, India
| | - Evan Prince Sabina
- Department of Biotechnology, School of Biosciences and Technology, VIT University, Vellore, India
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143
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Bois A, Grandela C, Gallant J, Mummery C, Menasché P. Revitalizing the heart: strategies and tools for cardiomyocyte regeneration post-myocardial infarction. NPJ Regen Med 2025; 10:6. [PMID: 39843488 PMCID: PMC11754855 DOI: 10.1038/s41536-025-00394-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Accepted: 01/13/2025] [Indexed: 01/24/2025] Open
Abstract
Myocardial infarction (MI) causes the loss of millions of cardiomyocytes, and current treatments do not address this root issue. New therapies focus on stimulating cardiomyocyte division in the adult heart, inspired by the regenerative capacities of lower vertebrates and neonatal mice. This review explores strategies for heart regeneration, offers insights into cardiomyocyte proliferation, evaluates in vivo models, and discusses integrating in vitro human cardiac models to advance cardiac regeneration research.
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Affiliation(s)
- Axelle Bois
- Department of Anatomy and Embryology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
- Department of Cardiovascular Surgery, Université Paris Cité, INSERM U970, PARCC Hôpital Européen Georges Pompidou, 75015, Paris, France
| | - Catarina Grandela
- Department of Anatomy and Embryology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| | - James Gallant
- Department of Anatomy and Embryology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Christine Mummery
- Department of Anatomy and Embryology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands.
| | - Philippe Menasché
- Department of Cardiovascular Surgery, Université Paris Cité, INSERM U970, PARCC Hôpital Européen Georges Pompidou, 75015, Paris, France
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144
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Ghazi Vakili M, Gorgulla C, Snider J, Nigam A, Bezrukov D, Varoli D, Aliper A, Polykovsky D, Padmanabha Das KM, Cox Iii H, Lyakisheva A, Hosseini Mansob A, Yao Z, Bitar L, Tahoulas D, Čerina D, Radchenko E, Ding X, Liu J, Meng F, Ren F, Cao Y, Stagljar I, Aspuru-Guzik A, Zhavoronkov A. Quantum-computing-enhanced algorithm unveils potential KRAS inhibitors. Nat Biotechnol 2025:10.1038/s41587-024-02526-3. [PMID: 39843581 DOI: 10.1038/s41587-024-02526-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Accepted: 12/06/2024] [Indexed: 01/24/2025]
Abstract
We introduce a quantum-classical generative model for small-molecule design, specifically targeting KRAS inhibitors for cancer therapy. We apply the method to design, select and synthesize 15 proposed molecules that could notably engage with KRAS for cancer therapy, with two holding promise for future development as inhibitors. This work showcases the potential of quantum computing to generate experimentally validated hits that compare favorably against classical models.
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Affiliation(s)
- Mohammad Ghazi Vakili
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
- Department of Chemistry, University of Toronto, Toronto, Ontario, Canada
| | - Christoph Gorgulla
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN, USA.
- Department of Physics, Harvard University, Cambridge, MA, USA.
| | - Jamie Snider
- Donnelly Centre, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - AkshatKumar Nigam
- Department of Computer Science, Stanford University, Stanford, CA, USA.
| | | | | | - Alex Aliper
- Insilico Medicine AI Limited, Abu Dhabi, UAE
| | | | - Krishna M Padmanabha Das
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Huel Cox Iii
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Anna Lyakisheva
- Donnelly Centre, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Ardalan Hosseini Mansob
- Donnelly Centre, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Zhong Yao
- Donnelly Centre, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Lela Bitar
- Donnelly Centre, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department for Lung Diseases Jordanovac, Clinical Hospital Centre Zagreb, University of Zagreb, Zagreb, Croatia
| | - Danielle Tahoulas
- Donnelly Centre, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Donnelly Centre, Department of Biochemistry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Dora Čerina
- Donnelly Centre, Department of Biochemistry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Oncology, University Hospital Center Split, School of Medicine, University of Split, Split, Croatia
| | | | - Xiao Ding
- Insilico Medicine AI Limited, Abu Dhabi, UAE
| | - Jinxin Liu
- Insilico Medicine AI Limited, Abu Dhabi, UAE
| | - Fanye Meng
- Insilico Medicine AI Limited, Abu Dhabi, UAE
| | - Feng Ren
- Insilico Medicine AI Limited, Abu Dhabi, UAE
| | | | - Igor Stagljar
- Donnelly Centre, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
- Donnelly Centre, Department of Biochemistry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
- Mediterranean Institute for Life Sciences (MedILS), School of Medicine, University of Split, Split, Croatia.
| | - Alán Aspuru-Guzik
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.
- Department of Chemistry, University of Toronto, Toronto, Ontario, Canada.
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario, Canada.
- Department of Materials Science and Engineering, University of Toronto, Toronto, Ontario, Canada.
- Vector Institute for Artificial Intelligence, Toronto, Ontario, Canada.
- Fellow, Canadian Institute for Advanced Research (CIFAR), Toronto, Ontario, Canada.
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145
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Réda C, Vie JJ, Wolkenhauer O. Comprehensive evaluation of pure and hybrid collaborative filtering in drug repurposing. Sci Rep 2025; 15:2711. [PMID: 39837888 PMCID: PMC11751339 DOI: 10.1038/s41598-025-85927-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2024] [Accepted: 01/07/2025] [Indexed: 01/23/2025] Open
Abstract
Drug development is known to be a costly and time-consuming process, which is prone to high failure rates. Drug repurposing allows drug discovery by reusing already approved compounds. The outcomes of past clinical trials can be used to predict novel drug-disease associations by leveraging drug- and disease-related similarities. To tackle this classification problem, collaborative filtering with implicit feedback (and potentially additional data on drugs and diseases) has become popular. It can handle large imbalances between negative and positive known associations and known and unknown associations. However, properly evaluating the improvement over the state of the art is challenging, as there is no consensus approach to compare models. We propose a reproducible methodology for comparing collaborative filtering-based drug repurposing. We illustrate this method by comparing 11 models from the literature on eight diverse drug repurposing datasets. Based on this benchmark, we derive guidelines to ensure a fair and comprehensive evaluation of the performance of those models. In particular, an uncontrolled bias on unknown associations might lead to severe data leakage and a misestimation of the model's true performance. Moreover, in drug repurposing, the ability of a model to extrapolate beyond its training distribution is crucial and should also be assessed. Finally, we identified a subcategory of collaborative filtering that seems efficient and robust to distribution shifts. Benchmarks constitute an essential step towards increased reproducibility and more accessible development of competitive drug repurposing methods.
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Affiliation(s)
- Clémence Réda
- Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, 18051, Germany.
| | | | - Olaf Wolkenhauer
- Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, 18051, Germany
- Leibniz-Institute for Food Systems Biology, Freising, 85354, Germany
- Stellenbosch Institute of Advanced Study, Wallenberg Research Centre, Stellenbosch, 7602, South Africa
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146
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Ana G, Malebari AM, Noorani S, Fayne D, O’Boyle NM, Zisterer DM, Pimentel EF, Endringer DC, Meegan MJ. ( E)-1-(3-(3-Hydroxy-4-Methoxyphenyl)-1-(3,4,5-Trimethoxyphenyl)allyl)-1 H-1,2,4-Triazole and Related Compounds: Their Synthesis and Biological Evaluation as Novel Antimitotic Agents Targeting Breast Cancer. Pharmaceuticals (Basel) 2025; 18:118. [PMID: 39861179 PMCID: PMC11769294 DOI: 10.3390/ph18010118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2024] [Revised: 12/31/2024] [Accepted: 01/02/2025] [Indexed: 01/27/2025] Open
Abstract
Background/Objectives: The synthesis of (E)-1-(1,3-diphenylallyl)-1H-1,2,4-triazoles and related compounds as anti-mitotic agents with activity in breast cancer was investigated. These compounds were designed as hybrids of the microtubule-targeting chalcones, indanones, and the aromatase inhibitor letrozole. Methods: A panel of 29 compounds was synthesized and examined by a preliminary screening in estrogen receptor (ER) and progesterone receptor (PR)-positive MCF-7 breast cancer cells together with cell cycle analysis and tubulin polymerization inhibition. Results: (E)-5-(3-(1H-1,2,4-triazol-1-yl)-3-(3,4,5-trimethoxyphenyl)prop-1-en-1-yl)-2-methoxyphenol 22b was identified as a potent antiproliferative compound with an IC50 value of 0.39 mM in MCF-7 breast cancer cells, 0.77 mM in triple-negative MDA-MB-231 breast cancer cells, and 0.37 mM in leukemia HL-60 cells. In addition, compound 22b demonstrated potent activity in the sub-micromolar range against the NCI 60 cancer cell line panel including prostate, melanoma, colon, leukemia, and non-small cell lung cancers. G2/M phase cell cycle arrest and the induction of apoptosis in MCF-7 cells together with inhibition of tubulin polymerization were demonstrated. Immunofluorescence studies confirmed that compound 22b targeted tubulin in MCF-7 cells, while computational docking studies predicted binding conformations for 22b in the colchicine binding site of tubulin. Compound 22b also selectively inhibited aromatase. Conclusions: Based on the results obtained, these novel compounds are suitable candidates for further investigation as antiproliferative microtubule-targeting agents for breast cancer.
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Affiliation(s)
- Gloria Ana
- School of Pharmacy and Pharmaceutical Sciences, Panoz Institute, Trinity College Dublin, D02 PN40 Dublin, Ireland
| | - Azizah M. Malebari
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Sara Noorani
- School of Pharmacy and Pharmaceutical Sciences, Panoz Institute, Trinity College Dublin, D02 PN40 Dublin, Ireland
| | - Darren Fayne
- Molecular Design Group, School of Chemical Sciences, Dublin City University, Glasnevin, D09 V209 Dublin, Ireland
- DCU Life Sciences Institute, Dublin City University, Glasnevin, D09 V209 Dublin, Ireland
| | - Niamh M. O’Boyle
- School of Pharmacy and Pharmaceutical Sciences, Panoz Institute, Trinity College Dublin, D02 PN40 Dublin, Ireland
| | - Daniela M. Zisterer
- School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, 152-160 Pearse Street, D02 R590 Dublin, Ireland
| | - Elisangela Flavia Pimentel
- Department of Pharmaceutical Sciences, University Vila Velha, Av. Comissário José Dantas de Melo, n°21, Boa Vista, Vila Velha CEP 29102-920, Brazil
| | - Denise Coutinho Endringer
- Department of Pharmaceutical Sciences, University Vila Velha, Av. Comissário José Dantas de Melo, n°21, Boa Vista, Vila Velha CEP 29102-920, Brazil
| | - Mary J. Meegan
- School of Pharmacy and Pharmaceutical Sciences, Panoz Institute, Trinity College Dublin, D02 PN40 Dublin, Ireland
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147
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Debnath A, Mazumder R, Singh AK, Singh RK. Identification of novel cyclin-dependent kinase 4/6 inhibitors from marine natural products. PLoS One 2025; 20:e0313830. [PMID: 39813224 PMCID: PMC11734976 DOI: 10.1371/journal.pone.0313830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2024] [Accepted: 10/31/2024] [Indexed: 01/18/2025] Open
Abstract
Cyclin-dependent kinases 4 and 6 (CDK4/6) are crucial regulators of cell cycle progression and represent important therapeutic targets in breast cancer. This study employs a comprehensive computational approach to identify novel CDK4/6 inhibitors from marine natural products. We utilized structure-based virtual screening of the CMNPD database and MNP library, followed by rigorous filtering based on drug-likeness criteria, PAINS filter, ADME properties, and toxicity profiles. From an initial hit of 9,497 compounds, 2,344 passed drug-likeness and PAINS filters. Further ADME filtering yielded 50 compounds, of which 25 exhibited non-toxic profiles. These 25 candidates underwent consensus molecular docking using seven distinct algorithms: AutoDockTools 4.2, idock, LeDock, Qvina 2, Smina, AutoDock Vina 1.2.0, PLANTS, and rDock. Based on these results, six top-scoring compounds were selected for comprehensive 500 nanosecond all-atom molecular dynamics simulations to evaluate their structural stability and interactions with CDK4/6. Our analysis revealed that compounds CMNPD11585 and CMNPD2744 demonstrated superior stability in their interactions with CDK4/6, exhibiting lower RMSD and RMSF values, more favorable binding free energies, and persistent hydrogen bonding patterns. These compounds also showed lower Solvent Accessible Surface Area values, indicating better compatibility with the CDK4/6 active site. Subsequent in-vitro studies using MTT assays on MCF-7 breast cancer cells confirmed the cytotoxic effects of these compounds, with CMNPD11585 showing the highest potency, followed by CMNPD2744.
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Affiliation(s)
- Abhijit Debnath
- Noida Institute of Engineering and Technology [Pharmacy Institute], Institutional Area, Greater Noida, Uttar Pradesh, India
| | - Rupa Mazumder
- Noida Institute of Engineering and Technology [Pharmacy Institute], Institutional Area, Greater Noida, Uttar Pradesh, India
| | - Anil Kumar Singh
- Department of Dravyaguna, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
| | - Rajesh Kumar Singh
- Department of Dravyaguna, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
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148
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Gao Y, Bissoyi A, Guo Q, Gibson MI. Induced Extracellular Ice Nucleation Protects Cocultured Spheroid Interior and Exterior during Cryopreservation. ACS Biomater Sci Eng 2025; 11:208-212. [PMID: 39315639 PMCID: PMC11733914 DOI: 10.1021/acsbiomaterials.4c00958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Revised: 09/09/2024] [Accepted: 09/10/2024] [Indexed: 09/25/2024]
Abstract
Spheroids and other 3D cellular models more accurately recapitulate physiological responses when compared to 2D models and represent potential alternatives to animal testing. The cryopreservation of spheroids remains challenging, limiting their wider use. Standard DMSO-only cryopreservation results in supercooling to low subzero temperatures, reducing viability, shedding surface cells, and perforating spheroid interiors. Here, cocultured spheroids with differentially labeled outer cell layers allow spatial evaluation of the protective effect of macromolecular ice nucleators by microscopy and histology. Extracellular nucleation is shown to reduce damage to both interior and exterior regions of the spheroids, which will support the development of "off-the-shelf" 3D models.
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Affiliation(s)
- Yanan Gao
- Department
of Chemistry, University of Warwick, Coventry CV4 7AL, United Kingdom
- Department
of Biomedical Engineering, Southern University
of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Akalabya Bissoyi
- Manchester
Institute of Biotechnology, University of
Manchester, 131 Princess
Street, Manchester M1 7DN, United Kingdom
| | - Qiongyu Guo
- Department
of Biomedical Engineering, Southern University
of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Matthew I. Gibson
- Department
of Chemistry, University of Warwick, Coventry CV4 7AL, United Kingdom
- Division
of Biomedical Sciences, Warwick Medical School, University of Warwick, Coventry CV4 7AL, United
Kingdom
- Department
of Chemistry, University of Manchester, Oxford Road, Manchester M13 9PL, United Kingdom
- Manchester
Institute of Biotechnology, University of
Manchester, 131 Princess
Street, Manchester M1 7DN, United Kingdom
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149
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Zhai Y, Liu L, Zhang F, Chen X, Wang H, Zhou J, Chai K, Liu J, Lei H, Lu P, Guo M, Guo J, Wu J. Network pharmacology: a crucial approach in traditional Chinese medicine research. Chin Med 2025; 20:8. [PMID: 39800680 PMCID: PMC11725223 DOI: 10.1186/s13020-024-01056-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2024] [Accepted: 12/28/2024] [Indexed: 01/16/2025] Open
Abstract
Network pharmacology plays a pivotal role in systems biology, bridging the gap between traditional Chinese medicine (TCM) theory and contemporary pharmacological research. Network pharmacology enables researchers to construct multilayered networks that systematically elucidate TCM's multi-component, multi-target mechanisms of action. This review summarizes key databases commonly used in network pharmacology, including those focused on herbs, components, diseases, and dedicated platforms for network pharmacology analysis. Additionally, we explore the growing use of network pharmacology in TCM, citing literature from Web of Science, PubMed, and CNKI over the past two decades with keywords like "network pharmacology", "TCM network pharmacology", and "herb network pharmacology". The application of network pharmacology in TCM is widespread, covering areas such as identifying the material basis of TCM efficacy, unraveling mechanisms of action, and evaluating toxicity, safety, and novel drug development. However, challenges remain, such as the lack of standardized data collection across databases and insufficient consideration of processed herbs in research. Questions also persist regarding the reliability of study outcomes. This review aims to offer valuable insights and reference points to guide future research in precision TCM network pharmacology.
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Affiliation(s)
- Yiyan Zhai
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Liu Liu
- School of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Fanqin Zhang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Xiaodong Chen
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Haojia Wang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Jiying Zhou
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Keyan Chai
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Jiangying Liu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Huiling Lei
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Peiying Lu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Meiling Guo
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Jincheng Guo
- School of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 100029, China.
| | - Jiarui Wu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China.
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150
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Ciccone L, Nencetti S. Special Issue "Advances in Drug Discovery and Synthesis". Int J Mol Sci 2025; 26:584. [PMID: 39859300 PMCID: PMC11765983 DOI: 10.3390/ijms26020584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2024] [Accepted: 01/08/2025] [Indexed: 01/27/2025] Open
Abstract
In modern medicinal chemistry, drug discovery is a long, difficult, highly expensive and highly risky process for the identification of new drug compounds [...].
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Affiliation(s)
- Lidia Ciccone
- Department of Pharmacy, University of Pisa, Via Bonanno 6, 56126 Pisa, Italy;
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