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Dubey P, Pathak DP, Ali F, Chauhan G, Kalaiselvan V. In-vitro Evaluation of Triazine Scaffold for Anticancer Drug Development: A Review. Curr Drug Discov Technol 2024; 21:e170723218813. [PMID: 37461340 DOI: 10.2174/1570163820666230717161610] [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: 09/16/2022] [Revised: 03/27/2023] [Accepted: 05/12/2023] [Indexed: 07/21/2023]
Abstract
INTRODUCTION The widespread importance of the synthesis and modification of anticancer agents has given rise to many numbers of medicinal chemistry programs. In this regard, triazine derivatives have attracted attention due to their remarkable activity against a wide range of cancer cells. This evaluation covers work reports to define the anticancer activity, the most active synthesized compound for the target, the SAR and, when described, the probable MOA besides similarly considered to deliver complete and target-pointed data for the development of types of anti-tumour medicines of triazine derivatives. Triazine scaffold for the development of anticancer analogues. Triazine can also relate to numerous beneficial targets, and their analogues have auspicious in-vitro and in-vivo anti-tumour activity. Fused molecules can improve efficacy, and drug resistance and diminish side effects, and numerous hybrid molecules are beneath diverse stages of clinical trials, so hybrid derivatives of triazine may offer valuable therapeutic involvement for the dealing of tumours. OBJECTIVE The objective of the recent review was to summarize the recent reports on triazine as well as its analogues with respect to its anticancer therapeutic potential. CONCLUSION The content of the review would be helpful to update the researchers working towards the synthesis and designing of new molecules for the treatment of various types of cancer disease with the recent molecules that have been produced from the triazine scaffold. Triazine scaffolds based on 1,3,5-triazine considerably boost molecular diversity levels and enable covering chemical space in key medicinal chemistry fields.
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Affiliation(s)
- Pragya Dubey
- Department of Pharmaceutical Chemistry, Delhi Institute of Pharmaceutical Sciences and Research, Mehrauli- Badarpur Road, Sector 3, Pushp Vihar, New Delhi, 110017, India
| | - Dharam Pal Pathak
- Department of Pharmaceutical Chemistry, Delhi Institute of Pharmaceutical Sciences and Research, Mehrauli- Badarpur Road, Sector 3, Pushp Vihar, New Delhi, 110017, India
| | - Faraat Ali
- Department of Analytical Chemistry, Faculty of Pharmacy in Hradec Králové, Charles University, Akademika Heyrovského 1203, Hradec Králové 500 05, Czech Republic
- Department of Licensing and Enforcement, Laboratory Services, Botswana Medicines Regulatory Authority, Gaborone, Botswana
| | - Garima Chauhan
- Department of Pharmaceutical Chemistry, Delhi Institute of Pharmaceutical Sciences and Research, Mehrauli- Badarpur Road, Sector 3, Pushp Vihar, New Delhi, 110017, India
| | - Vivekanandan Kalaiselvan
- Indian Pharmacopoeia Commission, Ministry of Health and Family Welfare, Government of India, Sector-23, Raj Nagar, Ghaziabad 201002, India
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Haq KU, Sa'adah NL, Siswanto I, Suwito H. Bioactivity of dihydropyrimidinone derivatives as inhibitors of cyclooxygenase-2 (COX-2): an in silico approach. RSC Adv 2023; 13:34348-34357. [PMID: 38024961 PMCID: PMC10665647 DOI: 10.1039/d3ra05942a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 10/29/2023] [Indexed: 12/01/2023] Open
Abstract
Cyclooxygenase-2 (COX-2) is an enzyme involved in inflammation. The overexpression of COX-2 causes chronic inflammation, which can be prevented by COX-2 inhibitors. Generally, COX-2 inhibitors possess a carboxyl group and an aromatic ring in their molecular structure. These moieties are involved in the interaction with the active site of COX-2, thus playing a pivotal role in the inhibitory activity. Regarding the requisite molecular structure of COX-2 inhibitors, derivatives of dihydropyrimidinone (DHPM) are ideal candidates to be explored as COX-2 inhibitors, due to the ease of synthesis and their versatility to be transformed chemically. In this study, we prepared a novel small library consisting of 288 designed DHPM derivatives by varying the constituent components. The selection criteria of potential candidates for the COX-2 inhibitor of the data bank involve in silico studies via molecular docking investigations, prediction of ADMET and druglikeness, as well as molecular dynamics (MD) simulations. Molecular docking served as the initial step of selection, based on the comparison of grid score, docking pose, and interactions with those of lumiracoxib (LUR) as the original ligand of COX-2. The next criteria of selection were scores obtained from the ADMET and druglikeness by comparing the designed candidates with COX-2 inhibitors that were already marketed. Compound RDUE2 and SDT29 were the most potential candidates, which were further analyzed using the MD simulation. The results of the MD simulation indicated that RDUE2 and SDT29 interacted stably with amino acid residues on the active site of COX-2. The estimation of binding free energy indicated that SDT29 exhibited an inhibitory activity comparable to that of LUR, whereas RDUE2 showed a lower inhibitory activity than that of SDT29 and LUR.
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Affiliation(s)
- Kautsar Ul Haq
- Bioinformatic Division, University CoE-Research Center for Bio-Molecule Engineering (BIOME), Airlangga University Surabaya 60115 Indonesia
- Department of Chemistry, Faculty of Science and Technology, Airlangga University Surabaya 60115 Indonesia
| | - Nur Lailatus Sa'adah
- Department of Chemistry, Faculty of Science and Technology, Airlangga University Surabaya 60115 Indonesia
| | - Imam Siswanto
- Bioinformatic Division, University CoE-Research Center for Bio-Molecule Engineering (BIOME), Airlangga University Surabaya 60115 Indonesia
- Department of Chemistry, Faculty of Science and Technology, Airlangga University Surabaya 60115 Indonesia
| | - Hery Suwito
- Department of Chemistry, Faculty of Science and Technology, Airlangga University Surabaya 60115 Indonesia
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Bassani D, Moro S. Past, Present, and Future Perspectives on Computer-Aided Drug Design Methodologies. Molecules 2023; 28:molecules28093906. [PMID: 37175316 PMCID: PMC10180087 DOI: 10.3390/molecules28093906] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 04/28/2023] [Accepted: 05/02/2023] [Indexed: 05/15/2023] Open
Abstract
The application of computational approaches in drug discovery has been consolidated in the last decades. These families of techniques are usually grouped under the common name of "computer-aided drug design" (CADD), and they now constitute one of the pillars in the pharmaceutical discovery pipelines in many academic and industrial environments. Their implementation has been demonstrated to tremendously improve the speed of the early discovery steps, allowing for the proficient and rational choice of proper compounds for a desired therapeutic need among the extreme vastness of the drug-like chemical space. Moreover, the application of CADD approaches allows the rationalization of biochemical and interactive processes of pharmaceutical interest at the molecular level. Because of this, computational tools are now extensively used also in the field of rational 3D design and optimization of chemical entities starting from the structural information of the targets, which can be experimentally resolved or can also be obtained with other computer-based techniques. In this work, we revised the state-of-the-art computer-aided drug design methods, focusing on their application in different scenarios of pharmaceutical and biological interest, not only highlighting their great potential and their benefits, but also discussing their actual limitations and eventual weaknesses. This work can be considered a brief overview of computational methods for drug discovery.
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Affiliation(s)
- Davide Bassani
- Pharmaceutical Research & Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., 4070 Basel, Switzerland
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Via Marzolo 5, 35131 Padova, Italy
| | - Stefano Moro
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Via Marzolo 5, 35131 Padova, Italy
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Comparative Assessment of Docking Programs for Docking and Virtual Screening of Ribosomal Oxazolidinone Antibacterial Agents. Antibiotics (Basel) 2023; 12:antibiotics12030463. [PMID: 36978331 PMCID: PMC10044086 DOI: 10.3390/antibiotics12030463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 02/21/2023] [Accepted: 02/23/2023] [Indexed: 03/03/2023] Open
Abstract
Oxazolidinones are a broad-spectrum class of synthetic antibiotics that bind to the 50S ribosomal subunit of Gram-positive and Gram-negative bacteria. Many crystal structures of the ribosomes with oxazolidinone ligands have been reported in the literature, facilitating structure-based design using methods such as molecular docking. It would be of great interest to know in advance how well docking methods can reproduce the correct ligand binding modes and rank these correctly. We examined the performance of five molecular docking programs (AutoDock 4, AutoDock Vina, DOCK 6, rDock, and RLDock) for their ability to model ribosomal–ligand interactions with oxazolidinones. Eleven ribosomal crystal structures with oxazolidinones as the ligands were docked. The accuracy was evaluated by calculating the docked complexes’ root-mean-square deviation (RMSD) and the program’s internal scoring function. The rankings for each program based on the median RMSD between the native and predicted were DOCK 6 > AD4 > Vina > RDOCK >> RLDOCK. Results demonstrate that the top-performing program, DOCK 6, could accurately replicate the ligand binding in only four of the eleven ribosomes due to the poor electron density of said ribosomal structures. In this study, we have further benchmarked the performance of the DOCK 6 docking algorithm and scoring in improving virtual screening (VS) enrichment using the dataset of 285 oxazolidinone derivatives against oxazolidinone binding sites in the S. aureus ribosome. However, there was no clear trend between the structure and activity of the oxazolidinones in VS. Overall, the docking performance indicates that the RNA pocket’s high flexibility does not allow for accurate docking prediction, highlighting the need to validate VS. protocols for ligand-RNA before future use. Later, we developed a re-scoring method incorporating absolute docking scores and molecular descriptors, and the results indicate that the descriptors greatly improve the correlation of docking scores and pMIC values. Morgan fingerprint analysis was also used, suggesting that DOCK 6 underpredicted molecules with tail modifications with acetamide, n-methylacetamide, or n-ethylacetamide and over-predicted molecule derivatives with methylamino bits. Alternatively, a ligand-based approach similar to a field template was taken, indicating that each derivative’s tail groups have strong positive and negative electrostatic potential contributing to microbial activity. These results indicate that one should perform VS. campaigns of ribosomal antibiotics with care and that more comprehensive strategies, including molecular dynamics simulations and relative free energy calculations, might be necessary in conjunction with VS. and docking.
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Lessons Learnt from COVID-19: Computational Strategies for Facing Present and Future Pandemics. Int J Mol Sci 2023; 24:ijms24054401. [PMID: 36901832 PMCID: PMC10003049 DOI: 10.3390/ijms24054401] [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: 01/27/2023] [Revised: 02/19/2023] [Accepted: 02/21/2023] [Indexed: 02/25/2023] Open
Abstract
Since its outbreak in December 2019, the COVID-19 pandemic has caused the death of more than 6.5 million people around the world. The high transmissibility of its causative agent, the SARS-CoV-2 virus, coupled with its potentially lethal outcome, provoked a profound global economic and social crisis. The urgency of finding suitable pharmacological tools to tame the pandemic shed light on the ever-increasing importance of computer simulations in rationalizing and speeding up the design of new drugs, further stressing the need for developing quick and reliable methods to identify novel active molecules and characterize their mechanism of action. In the present work, we aim at providing the reader with a general overview of the COVID-19 pandemic, discussing the hallmarks in its management, from the initial attempts at drug repurposing to the commercialization of Paxlovid, the first orally available COVID-19 drug. Furthermore, we analyze and discuss the role of computer-aided drug discovery (CADD) techniques, especially those that fall in the structure-based drug design (SBDD) category, in facing present and future pandemics, by showcasing several successful examples of drug discovery campaigns where commonly used methods such as docking and molecular dynamics have been employed in the rational design of effective therapeutic entities against COVID-19.
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Pavan M, Menin S, Bassani D, Sturlese M, Moro S. Implementing a Scoring Function Based on Interaction Fingerprint for Autogrow4: Protein Kinase CK1δ as a Case Study. Front Mol Biosci 2022; 9:909499. [PMID: 35874609 PMCID: PMC9301033 DOI: 10.3389/fmolb.2022.909499] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 05/25/2022] [Indexed: 01/23/2023] Open
Abstract
In the last 20 years, fragment-based drug discovery (FBDD) has become a popular and consolidated approach within the drug discovery pipeline, due to its ability to bring several drug candidates to clinical trials, some of them even being approved and introduced to the market. A class of targets that have proven to be particularly suitable for this method is represented by kinases, as demonstrated by the approval of BRAF inhibitor vemurafenib. Within this wide and diverse set of proteins, protein kinase CK1δ is a particularly interesting target for the treatment of several widespread neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis. Computational methodologies, such as molecular docking, are already routinely and successfully applied in FBDD campaigns alongside experimental techniques, both in the hit-discovery and in the hit-optimization stage. Concerning this, the open-source software Autogrow, developed by the Durrant lab, is a semi-automated computational protocol that exploits a combination between a genetic algorithm and a molecular docking software for de novo drug design and lead optimization. In the current work, we present and discuss a modified version of the Autogrow code that implements a custom scoring function based on the similarity between the interaction fingerprint of investigated compounds and a crystal reference. To validate its performance, we performed both a de novo and a lead-optimization run (as described in the original publication), evaluating the ability of our fingerprint-based protocol to generate compounds similar to known CK1δ inhibitors based on both the predicted binding mode and the electrostatic and shape similarity in comparison with the standard Autogrow protocol.
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Unoh Y, Uehara S, Nakahara K, Nobori H, Yamatsu Y, Yamamoto S, Maruyama Y, Taoda Y, Kasamatsu K, Suto T, Kouki K, Nakahashi A, Kawashima S, Sanaki T, Toba S, Uemura K, Mizutare T, Ando S, Sasaki M, Orba Y, Sawa H, Sato A, Sato T, Kato T, Tachibana Y. Discovery of S-217622, a Noncovalent Oral SARS-CoV-2 3CL Protease Inhibitor Clinical Candidate for Treating COVID-19. J Med Chem 2022; 65:6499-6512. [PMID: 35352927 PMCID: PMC8982737 DOI: 10.1021/acs.jmedchem.2c00117] [Citation(s) in RCA: 219] [Impact Index Per Article: 109.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Indexed: 12/17/2022]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in millions of deaths and threatens public health and safety. Despite the rapid global spread of COVID-19 vaccines, effective oral antiviral drugs are urgently needed. Here, we describe the discovery of S-217622, the first oral noncovalent, nonpeptidic SARS-CoV-2 3CL protease inhibitor clinical candidate. S-217622 was discovered via virtual screening followed by biological screening of an in-house compound library, and optimization of the hit compound using a structure-based drug design strategy. S-217622 exhibited antiviral activity in vitro against current outbreaking SARS-CoV-2 variants and showed favorable pharmacokinetic profiles in vivo for once-daily oral dosing. Furthermore, S-217622 dose-dependently inhibited intrapulmonary replication of SARS-CoV-2 in mice, indicating that this novel noncovalent inhibitor could be a potential oral agent for treating COVID-19.
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Affiliation(s)
- Yuto Unoh
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Shota Uehara
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Kenji Nakahara
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Haruaki Nobori
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Yukiko Yamatsu
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Shiho Yamamoto
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Yuki Maruyama
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
- International
Institute for Zoonosis Control, Hokkaido
University, Sapporo 001-0020, Japan
| | - Yoshiyuki Taoda
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Koji Kasamatsu
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Takahiro Suto
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Kensuke Kouki
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Atsufumi Nakahashi
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Sho Kawashima
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Takao Sanaki
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Shinsuke Toba
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
- International
Institute for Zoonosis Control, Hokkaido
University, Sapporo 001-0020, Japan
| | - Kentaro Uemura
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
- International
Institute for Zoonosis Control, Hokkaido
University, Sapporo 001-0020, Japan
| | - Tohru Mizutare
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Shigeru Ando
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Michihito Sasaki
- International
Institute for Zoonosis Control, Hokkaido
University, Sapporo 001-0020, Japan
| | - Yasuko Orba
- International
Institute for Zoonosis Control, Hokkaido
University, Sapporo 001-0020, Japan
| | - Hirofumi Sawa
- International
Institute for Zoonosis Control, Hokkaido
University, Sapporo 001-0020, Japan
| | - Akihiko Sato
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
- International
Institute for Zoonosis Control, Hokkaido
University, Sapporo 001-0020, Japan
| | - Takafumi Sato
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Teruhisa Kato
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
| | - Yuki Tachibana
- Shionogi
Pharmaceutical Research Center, 3-1-1 Futaba-cho, Toyonaka, Osaka 561-0825, Japan
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Ghemrawi R, Khair M, Hasan S, Aldulaymi R, AlNeyadi SS, Atatreh N, Ghattas MA. The Discovery of Potent SHP2 Inhibitors with Anti-Proliferative Activity in Breast Cancer Cell Lines. Int J Mol Sci 2022; 23:ijms23084468. [PMID: 35457286 PMCID: PMC9030381 DOI: 10.3390/ijms23084468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 04/14/2022] [Accepted: 04/17/2022] [Indexed: 02/04/2023] Open
Abstract
Despite available treatments, breast cancer is the leading cause of cancer-related death. Knowing that the tyrosine phosphatase SHP2 is a regulator in tumorigenesis, developing inhibitors of SHP2 in breast cells is crucial. Our study investigated the effects of new compounds, purchased from NSC, on the phosphatase activity of SHP2 and the modulation of breast cancer cell lines’ proliferation and viability. A combined ligand-based and structure-based virtual screening protocol was validated, then performed, against SHP2 active site. Top ranked compounds were tested via SHP2 enzymatic assay, followed by measuring IC50 values. Subsequently, hits were tested for their anti-breast cancer viability and proliferative activity. Our experiments identified three compounds 13030, 24198, and 57774 as SHP2 inhibitors, with IC50 values in micromolar levels and considerable selectivity over the analogous enzyme SHP1. Long MD simulations of 500 ns showed a very promising binding mode in the SHP2 catalytic pocket. Furthermore, these compounds significantly reduced MCF-7 breast cancer cells’ proliferation and viability. Interestingly, two of our hits can have acridine or phenoxazine cyclic system known to intercalate in ds DNA. Therefore, our novel approach led to the discovery of SHP2 inhibitors, which could act as a starting point in the future for clinically useful anticancer agents.
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Affiliation(s)
- Rose Ghemrawi
- College of Pharmacy, Al Ain University, Abu Dhabi 112612, United Arab Emirates; (R.G.); (S.H.)
- AAU Health and Biomedical Research Center, Al Ain University, Abu Dhabi 112612, United Arab Emirates;
| | - Mostafa Khair
- Core Technology Platforms, New York University Abu Dhabi, Abu Dhabi 129188, United Arab Emirates;
| | - Shaima Hasan
- College of Pharmacy, Al Ain University, Abu Dhabi 112612, United Arab Emirates; (R.G.); (S.H.)
| | - Raghad Aldulaymi
- AAU Health and Biomedical Research Center, Al Ain University, Abu Dhabi 112612, United Arab Emirates;
| | - Shaikha S. AlNeyadi
- Department of Chemistry, College of Science, UAE University Al-Ain, Abu Dhabi 15551, United Arab Emirates;
| | - Noor Atatreh
- College of Pharmacy, Al Ain University, Abu Dhabi 112612, United Arab Emirates; (R.G.); (S.H.)
- AAU Health and Biomedical Research Center, Al Ain University, Abu Dhabi 112612, United Arab Emirates;
- Correspondence: (N.A.); (M.A.G.)
| | - Mohammad A. Ghattas
- College of Pharmacy, Al Ain University, Abu Dhabi 112612, United Arab Emirates; (R.G.); (S.H.)
- AAU Health and Biomedical Research Center, Al Ain University, Abu Dhabi 112612, United Arab Emirates;
- Correspondence: (N.A.); (M.A.G.)
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Pavan M, Bassani D, Bolcato G, Bissaro M, Sturles M, Moro S. Computational strategies to identify new drug candidates against neuroinflammation. Curr Med Chem 2022; 29:4756-4775. [PMID: 35135446 DOI: 10.2174/0929867329666220208095122] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 12/09/2021] [Accepted: 12/13/2021] [Indexed: 11/22/2022]
Abstract
The even more increasing application of computational approaches in these last decades has deeply modified the process of discovery and commercialization of new therapeutic entities. This is especially true in the field of neuroinflammation, in which both the peculiar anatomical localization and the presence of the blood-brain barrier makeit mandatory to finely tune the candidates' physicochemical properties from the early stages of the discovery pipeline. The aim of this review is therefore to provide a general overview to the readers about the topic of neuroinflammation, together with the most common computational strategies that can be exploited to discover and design small molecules controlling neuroinflammation, especially those based on the knowledge of the three-dimensional structure of the biological targets of therapeutic interest. The techniques used to describe the molecular recognition mechanisms, such as molecular docking and molecular dynamics, will therefore be eviscerated, highlighting their advantages and their limitations. Finally, we report several case studies in which computational methods have been applied in drug discovery on neuroinflammation, focusing on the last decade's research.
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Affiliation(s)
- Matteo Pavan
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences University of Padova, via Marzolo 5, 35131 Padova, Italy
| | - Davide Bassani
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences University of Padova, via Marzolo 5, 35131 Padova, Italy
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences University of Padova, via Marzolo 5, 35131 Padova, Italy
| | - Giovanni Bolcato
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences University of Padova, via Marzolo 5, 35131 Padova, Italy
| | - Maicol Bissaro
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences University of Padova, via Marzolo 5, 35131 Padova, Italy
| | - Mattia Sturles
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences University of Padova, via Marzolo 5, 35131 Padova, Italy
| | - Stefano Moro
- Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences University of Padova, via Marzolo 5, 35131 Padova, Italy
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Chang CC, Pan SF, Wu MH, Cheng CT, Su YR, Jiang SJ, Hsu HJ. Combinatorial Virtual Screening Revealed a Novel Scaffold for TNKS Inhibition to Combat Colorectal Cancer. Biomedicines 2022; 10:143. [PMID: 35052822 PMCID: PMC8773749 DOI: 10.3390/biomedicines10010143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 12/30/2021] [Accepted: 01/06/2022] [Indexed: 02/04/2023] Open
Abstract
The abnormal Wnt signaling pathway leads to a high expression of β-catenin, which causes several types of cancer, particularly colorectal cancer (CRC). The inhibition of tankyrase (TNKS) activity can reduce cancer cell growth, invasion, and resistance to treatment by blocking the Wnt signaling pathway. A pharmacophore search and pharmacophore docking were performed to identify potential TNKS inhibitors in the training databases. The weighted MM/PBSA binding free energy of the docking model was calculated to rank the databases. The reranked results indicated that 26.98% of TNKS inhibitors that were present in the top 5% of compounds in the database and near an ideal value ranked 28.57%. The National Cancer Institute database was selected for formal virtual screening, and 11 potential TNKS inhibitors were identified. An enzyme-based experiment was performed to demonstrate that of the 11 potential TNKS inhibitors, NSC295092 and NSC319963 had the most potential. Finally, Wnt pathway analysis was performed through a cell-based assay, which indicated that NSC319963 is the most likely TNKS inhibitor (pIC50 = 5.59). The antiproliferation assay demonstrated that NSC319963 can decrease colorectal cancer cell growth; therefore, the proposed method successfully identified a novel TNKS inhibitor that can alleviate CRC.
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Affiliation(s)
- Chun-Chun Chang
- Department of Laboratory Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 97004, Taiwan;
- Department of Laboratory Medicine and Biotechnology, College of Medicine, Tzu Chi University, Hualien 97004, Taiwan; (M.-H.W.); (Y.-R.S.)
| | - Sheng-Feng Pan
- Department of Biochemistry, School of Medicine, Tzu Chi University, Hualien 97004, Taiwan;
| | - Min-Huang Wu
- Department of Laboratory Medicine and Biotechnology, College of Medicine, Tzu Chi University, Hualien 97004, Taiwan; (M.-H.W.); (Y.-R.S.)
| | - Chun-Tse Cheng
- Department of Life Sciences, College of Medicine, Tzu Chi University, Hualien 97004, Taiwan;
| | - Yan-Rui Su
- Department of Laboratory Medicine and Biotechnology, College of Medicine, Tzu Chi University, Hualien 97004, Taiwan; (M.-H.W.); (Y.-R.S.)
| | - Shinn-Jong Jiang
- Department of Biochemistry, School of Medicine, Tzu Chi University, Hualien 97004, Taiwan;
| | - Hao-Jen Hsu
- Department of Biochemistry, School of Medicine, Tzu Chi University, Hualien 97004, Taiwan;
- Department of Life Sciences, College of Medicine, Tzu Chi University, Hualien 97004, Taiwan;
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MUHAMMED MT, AKI-YALCIN E. Pharmacophore Modeling in Drug Discovery: Methodology and Current Status. JOURNAL OF THE TURKISH CHEMICAL SOCIETY, SECTION A: CHEMISTRY 2021. [DOI: 10.18596/jotcsa.927426] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
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12
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Varela‐Rial A, Majewski M, De Fabritiis G. Structure based virtual screening: Fast and slow. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1544] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Alejandro Varela‐Rial
- Acellera Labs Barcelona Spain
- Computational Science Laboratory Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB) Barcelona Spain
| | - Maciej Majewski
- Computational Science Laboratory Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB) Barcelona Spain
| | - Gianni De Fabritiis
- Computational Science Laboratory Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB) Barcelona Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA) Barcelona Spain
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Identify potent SARS-CoV-2 main protease inhibitors via accelerated free energy perturbation-based virtual screening of existing drugs. Proc Natl Acad Sci U S A 2020; 117:27381-27387. [PMID: 33051297 PMCID: PMC7959488 DOI: 10.1073/pnas.2010470117] [Citation(s) in RCA: 147] [Impact Index Per Article: 36.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Drug repurposing effort for treatment of a new disease, such as COVID-19, usually starts from a virtual screening of existing drugs, followed by experimental validation, but the actual hit rate is generally rather low with traditional computational methods. It has been demonstrated that a new virtual screening approach with accelerated free energy perturbation-based absolute binding free energy (FEP-ABFE) predictions can reach an unprecedentedly high hit rate, leading to successful identification of 15 potent inhibitors of SARS-CoV-2 main protease (Mpro) from 25 computationally selected drugs under a threshold of Ki = 4 μM. The outcomes of this study are valuable for not only drug repurposing to treat COVID-19 but also demonstrating the promising potential of the FEP-ABFE prediction-based virtual screening approach. The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global crisis. There is no therapeutic treatment specific for COVID-19. It is highly desirable to identify potential antiviral agents against SARS-CoV-2 from existing drugs available for other diseases and thus repurpose them for treatment of COVID-19. In general, a drug repurposing effort for treatment of a new disease, such as COVID-19, usually starts from a virtual screening of existing drugs, followed by experimental validation, but the actual hit rate is generally rather low with traditional computational methods. Here we report a virtual screening approach with accelerated free energy perturbation-based absolute binding free energy (FEP-ABFE) predictions and its use in identifying drugs targeting SARS-CoV-2 main protease (Mpro). The accurate FEP-ABFE predictions were based on the use of a restraint energy distribution (RED) function, making the practical FEP-ABFE−based virtual screening of the existing drug library possible. As a result, out of 25 drugs predicted, 15 were confirmed as potent inhibitors of SARS-CoV-2 Mpro. The most potent one is dipyridamole (inhibitory constant Ki = 0.04 µM) which has shown promising therapeutic effects in subsequently conducted clinical studies for treatment of patients with COVID-19. Additionally, hydroxychloroquine (Ki = 0.36 µM) and chloroquine (Ki = 0.56 µM) were also found to potently inhibit SARS-CoV-2 Mpro. We anticipate that the FEP-ABFE prediction-based virtual screening approach will be useful in many other drug repurposing or discovery efforts.
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Yadav DK, Kumar S, Choi EH, Chaudhary S, Kim MH. Computational Modeling on Aquaporin-3 as Skin Cancer Target: A Virtual Screening Study. Front Chem 2020; 8:250. [PMID: 32351935 PMCID: PMC7175779 DOI: 10.3389/fchem.2020.00250] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Accepted: 03/17/2020] [Indexed: 12/25/2022] Open
Abstract
Aquaporin-3 (AQP3) is one of the aquaglyceroporins, which is expressed in the basolateral layer of the skin membrane. Studies have reported that human skin squamous cell carcinoma overexpresses AQP3 and inhibition of its function may alleviate skin tumorigenesis. In the present study, we have applied a virtual screening method that encompasses filters for physicochemical properties and molecular docking to select potential hit compounds that bind to the Aquaporin-3 protein. Based on molecular docking results, the top 20 hit compounds were analyzed for stability in the binding pocket using unconstrained molecular dynamics simulations and further evaluated for binding free energy. Furthermore, examined the ligand-unbinding pathway of the inhibitor from its bound form to explore possible routes for inhibitor approach to the ligand-binding site. With a good docking score, stability in the binding pocket, and free energy of binding, these hit compounds can be developed as Aquaporin-3 inhibitors in the near future.
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Affiliation(s)
- Dharmendra Kumar Yadav
- Gachon Institute of Pharmaceutical Science & Department of Pharmacy, College of Pharmacy, Gachon University, Incheon, South Korea
| | - Surendra Kumar
- Gachon Institute of Pharmaceutical Science & Department of Pharmacy, College of Pharmacy, Gachon University, Incheon, South Korea
| | - Eun-Ha Choi
- Plasma Bioscience Research Center/PDP Research Center, Kwangwoon University, Nowon-Gu, South Korea
| | - Sandeep Chaudhary
- Laboratory of Organic & Medicinal Chemistry, Department of Chemistry, Malaviya National Institute of Technology, Jaipur, India
| | - Mi-Hyun Kim
- Gachon Institute of Pharmaceutical Science & Department of Pharmacy, College of Pharmacy, Gachon University, Incheon, South Korea
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15
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Fratev F, Gutierrez DA, Aguilera RJ, Tyagi A, Damodaran C, Sirimulla S. Discovery of new AKT1 inhibitors by combination of in silico structure based virtual screening approaches and biological evaluations. J Biomol Struct Dyn 2020; 39:368-377. [DOI: 10.1080/07391102.2020.1715835] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
- Filip Fratev
- Department of Pharmaceutical Sciences, School of Pharmacy, The University of Texas at El Paso, El Paso, TX, USA
- Micar Innovation (Micar 21) Ltd, Sofia, Bulgaria
| | - Denisse A. Gutierrez
- Department of Biological Sciences, The University of Texas at El Paso, El Paso, TX, USA
| | - Renato J. Aguilera
- Department of Biological Sciences, The University of Texas at El Paso, El Paso, TX, USA
| | - Ashish Tyagi
- Department of Urology, University of Louisville, Louisville, KY, USA
| | - Chendil Damodaran
- Department of Urology, University of Louisville, Louisville, KY, USA
| | - Suman Sirimulla
- Department of Pharmaceutical Sciences, School of Pharmacy, The University of Texas at El Paso, El Paso, TX, USA
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Zidan AM, Saad EA, Ibrahim NE, Mahmoud A, Hashem MH, Hemeida AA. PHARMIP: An insilico method to predict genetics that underpin adverse drug reactions. MethodsX 2019; 7:100775. [PMID: 32123669 PMCID: PMC7036477 DOI: 10.1016/j.mex.2019.100775] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Accepted: 12/16/2019] [Indexed: 01/08/2023] Open
Abstract
Pharmacovigilance is the pharmacological science that focuses on the safe and appropriate use of drugs.Variability in response to drug therapy in both terms of safety and efficacy is highly related to patient's personal genomics. Hence, pharmacovigilance considers pharmacogenomics methodologies in the evaluation of medicinal products. The aim of this work is to introduce the pharmacovigilance/ pharmacogenomics insilico pipeline (PHARMIP) that uses the drug (or drug candidate) digital structure and the advances in bioinformatics tools and databases to figure-out the genetic factors underlying the drug reported adverse reactions (ADRs).PHARMIP uses user-friendly freely available bioinformatics resources to help pharmacovigilance and pharmacogenomics scientists with minimal bioinformatics experience to retrieve helpful information for their daily basis activities. Also, PHARMIP could help the advances in precision medicine in a drug-centric approach as it can be used to reveal genetic risk factors for certain drug ADRs. Domperidone was used as an example to the application of PHARMIP as the pipeline was initially developed during the insilico exploration of domperidone cardiotoxic ADRs. Method is composed of 3 main steps: Preparing the drug off-label targets (OLT) list. Retrieving the related diseases/ adverse reactions (DA) list. Analysis of DA list to get answers.
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Affiliation(s)
- Ahmad M Zidan
- Department of Bioinformatics, Genetic Engineering & Biotechnology Research Institute, University of Sadat City, Egypt
| | - Eman A Saad
- Department of Bioinformatics, Genetic Engineering & Biotechnology Research Institute, University of Sadat City, Egypt
| | - Nasser E Ibrahim
- Department of Bioinformatics, Genetic Engineering & Biotechnology Research Institute, University of Sadat City, Egypt
| | - Amal Mahmoud
- Department of Biology, College of Science, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, 31441, Dammam, Saudi Arabia
| | - Medhat H Hashem
- Department of Animal Biotechnology, Genetic Engineering & Biotechnology Research Institute, University of Sadat City, Egypt
| | - Alaa A Hemeida
- Department of Bioinformatics, Genetic Engineering & Biotechnology Research Institute, University of Sadat City, Egypt
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Fratev F, Miranda-Arango M, Lopez AB, Padilla E, Sirimulla S. Discovery of GlyT2 Inhibitors Using Structure-Based Pharmacophore Screening and Selectivity Studies by FEP+ Calculations. ACS Med Chem Lett 2019; 10:904-910. [PMID: 31223446 PMCID: PMC6580377 DOI: 10.1021/acsmedchemlett.9b00003] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Accepted: 05/21/2019] [Indexed: 12/23/2022] Open
Abstract
In recent years, mammalian Glycine transporter 2 (GlyT2) has emerged as a promising target for the development of compounds against chronic pain states. In our current work, we discovered a new set of promising hits that inhibit the glycine transporter at nano- and micromolar activity and have excellent selectivity over GlyT1 (as shown by in vitro studies) using a newly designed virtual screening (VS) protocol that combines a structure-based pharmacophore and docking screens with a success rate of 75%. Furthermore, the free energy perturbation calculations and molecular dynamics (MD) studies revealed the GlyT2 amino acid residues critical for the binding and selectivity of both Glycine and our Hit1 compound. The FEP+ results well-matched with the available literature mutational data proving the quality of the generated GlyT2 structure. On the basis of these results, we propose that our hit compounds may lead to new chronic pain agents to address unmet and challenging clinical needs.
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Affiliation(s)
- Filip Fratev
- Department
of Pharmaceutical Sciences, School of Pharmacy, The University of Texas at El Paso, El Paso, Texas 79968, United States
- Micar21 Ltd., Persenk 34B, 1407 Sofia, Bulgaria
| | - Manuel Miranda-Arango
- Department
of Biological Sciences, The University of
Texas at El Paso, 500 West University Avenue, El Paso, Texas 79902, United States
| | - Ashley Bryan Lopez
- Department
of Biological Sciences, The University of
Texas at El Paso, 500 West University Avenue, El Paso, Texas 79902, United States
| | - Elvia Padilla
- Department
of Biological Sciences, The University of
Texas at El Paso, 500 West University Avenue, El Paso, Texas 79902, United States
| | - Suman Sirimulla
- Department
of Pharmaceutical Sciences, School of Pharmacy, The University of Texas at El Paso, El Paso, Texas 79968, United States
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18
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NMR-Fragment Based Virtual Screening: A Brief Overview. Molecules 2018; 23:molecules23020233. [PMID: 29370102 PMCID: PMC6017141 DOI: 10.3390/molecules23020233] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Revised: 12/12/2017] [Accepted: 12/12/2017] [Indexed: 01/23/2023] Open
Abstract
Fragment-based drug discovery (FBDD) using NMR has become a central approach over the last twenty years for development of small molecule inhibitors against biological macromolecules, to control a variety of cellular processes. Yet, several considerations should be taken into account for obtaining a therapeutically relevant agent. In this review, we aim to list the considerations that make NMR fragment screening a successful process for yielding potent inhibitors. Factors that may govern the competence of NMR in fragment based drug discovery are discussed, as well as later steps that involve optimization of hits obtained by NMR-FBDD.
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Target identification, lead optimization and antitumor evaluation of some new 1,2,4-triazines as c-Met kinase inhibitors. Bioorg Chem 2017; 73:154-169. [DOI: 10.1016/j.bioorg.2017.06.009] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2017] [Revised: 06/22/2017] [Accepted: 06/23/2017] [Indexed: 11/19/2022]
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20
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Ban F, Dalal K, Li H, LeBlanc E, Rennie PS, Cherkasov A. Best Practices of Computer-Aided Drug Discovery: Lessons Learned from the Development of a Preclinical Candidate for Prostate Cancer with a New Mechanism of Action. J Chem Inf Model 2017; 57:1018-1028. [PMID: 28441481 DOI: 10.1021/acs.jcim.7b00137] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Small-molecule drug design is a complex and iterative decision-making process relying on pre-existing knowledge and driven by experimental data. Low-molecular-weight chemicals represent an attractive therapeutic option, as they are readily accessible to organic synthesis and can easily be characterized.1 Their potency as well as pharmacokinetic and pharmacodynamic properties can be systematically and rationally investigated and ultimately optimized via expert science behind medicinal chemistry and methods of computer-aided drug design (CADD). In recent years, significant advances in molecular modeling techniques have afforded a variety of tools to effectively identify potential binding pockets on prospective targets, to map key interactions between ligands and their binding sites, to construct and assess energetics of the resulting complexes, to predict ADMET properties of candidate compounds, and to systematically analyze experimental and computational data to derive meaningful structure-activity relationships leading to the creation of a drug candidate. This Perspective describes a real case of a drug discovery campaign accomplished in a relatively short time with limited resources. The study integrated an arsenal of available molecular modeling techniques with an array of experimental tools to successfully develop a novel class of potent and selective androgen receptor inhibitors with a novel mode of action. It resulted in the largest academic licensing deal in Canadian history, totaling $142M. This project exemplifies the importance of team science, an integrative approach to drug discovery, and the use of best practices in CADD. We posit that the lessons learned and best practices for executing an effective CADD project can be applied, with similar success, to many drug discovery projects in both academia and industry.
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Affiliation(s)
- Fuqiang Ban
- Vancouver Prostate Centre, Department of Urologic Sciences, Faculty of Medicine, The University of British Columbia , 2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6
| | - Kush Dalal
- Vancouver Prostate Centre, Department of Urologic Sciences, Faculty of Medicine, The University of British Columbia , 2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6
| | - Huifang Li
- Vancouver Prostate Centre, Department of Urologic Sciences, Faculty of Medicine, The University of British Columbia , 2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6
| | - Eric LeBlanc
- Vancouver Prostate Centre, Department of Urologic Sciences, Faculty of Medicine, The University of British Columbia , 2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6
| | - Paul S Rennie
- Vancouver Prostate Centre, Department of Urologic Sciences, Faculty of Medicine, The University of British Columbia , 2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6
| | - Artem Cherkasov
- Vancouver Prostate Centre, Department of Urologic Sciences, Faculty of Medicine, The University of British Columbia , 2660 Oak Street, Vancouver, British Columbia, Canada V6H 3Z6
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Liu F, Ma R, Riordan SM, Grimm MC, Liu L, Wang Y, Zhang L. Azathioprine, Mercaptopurine, and 5-Aminosalicylic Acid Affect the Growth of IBD-Associated Campylobacter Species and Other Enteric Microbes. Front Microbiol 2017; 8:527. [PMID: 28424670 PMCID: PMC5372805 DOI: 10.3389/fmicb.2017.00527] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Accepted: 03/14/2017] [Indexed: 12/28/2022] Open
Abstract
Campylobacter concisus is a bacterium that is associated with inflammatory bowel disease (IBD). Immunosuppressive drugs including azathioprine (AZA) and mercaptopurine (MP), and anti-inflammatory drug such as 5-aminosalicylic acid (5-ASA) are commonly used to treat patients with IBD. This study aimed to examine the effects of AZA, MP, and 5-ASA on the growth of IBD-associated bacterial species and to identify bacterial enzymes involved in immunosuppressive drug metabolism. A total of 15 bacterial strains of five species including 11 C. concisus strains, Bacteroides fragilis, Bacteroides vulgatus, Enterococcus faecalis, and Escherichia coli were examined. The impact of AZA, MP, and 5-ASA on the growth of these bacterial species was examined quantitatively using a plate counting method. The presence of enzymes involved in AZA and MP metabolism in these bacterial species was identified using bioinformatics tools. AZA and MP significantly inhibited the growth of all 11 C. concisus strains. C. concisus strains were more sensitive to AZA than MP. 5-ASA showed inhibitory effects to some C. concisus strains, while it promoted the growth of other C. concisus strains. AZA and MP also significantly inhibited the growth of B. fragilis and B. vulgatus. The growth of E. coli was significantly inhibited by 200 μg/ml of AZA as well as 100 and 200 μg/ml of 5-ASA. Bacterial enzymes related to AZA and MP metabolism were found, which varied in different bacterial species. In conclusion, AZA and MP have inhibitory effects to IBD-associated C. concisus and other enteric microbes, suggesting an additional therapeutic mechanism of these drugs in the treatment of IBD. The strain dependent differential impact of 5-ASA on the growth of C. concisus may also have clinical implication given that in some cases 5-ASA medications were found to cause exacerbations of colitis.
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Affiliation(s)
- Fang Liu
- School of Biotechnology and Biomolecular Sciences, University of New South WalesSydney, NSW, Australia
| | - Rena Ma
- School of Biotechnology and Biomolecular Sciences, University of New South WalesSydney, NSW, Australia
| | - Stephen M Riordan
- Gastrointestinal and Liver Unit, Prince of Wales Hospital, University of New South WalesSydney, NSW, Australia
| | - Michael C Grimm
- St George and Sutherland Clinical School, University of New South WalesSydney, NSW, Australia
| | - Lu Liu
- School of Medical Sciences, University of New South WalesSydney, NSW, Australia
| | - Yiming Wang
- School of Biotechnology and Biomolecular Sciences, University of New South WalesSydney, NSW, Australia
| | - Li Zhang
- School of Biotechnology and Biomolecular Sciences, University of New South WalesSydney, NSW, Australia
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22
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Identification of novel fluorescent probes preventing PrP Sc replication in prion diseases. Eur J Med Chem 2017; 127:859-873. [DOI: 10.1016/j.ejmech.2016.10.064] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2016] [Revised: 10/12/2016] [Accepted: 10/31/2016] [Indexed: 12/11/2022]
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Wieder M, Garon A, Perricone U, Boresch S, Seidel T, Almerico AM, Langer T. Common Hits Approach: Combining Pharmacophore Modeling and Molecular Dynamics Simulations. J Chem Inf Model 2017; 57:365-385. [PMID: 28072524 DOI: 10.1021/acs.jcim.6b00674] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
We present a new approach that incorporates flexibility based on extensive MD simulations of protein-ligand complexes into structure-based pharmacophore modeling and virtual screening. The approach uses the multiple coordinate sets saved during the MD simulations and generates for each frame a pharmacophore model. Pharmacophore models with the same pharmacophore features are pooled. In this way the high number of pharmacophore models that results from the MD simulation is reduced to only a few hundred representative pharmacophore models. Virtual screening runs are performed with every representative pharmacophore model; the screening results are combined and rescored to generate a single hit-list. The score for a particular molecule is calculated based on the number of representative pharmacophore models which classified it as active. Hence, the method is called common hits approach (CHA). The steps between the MD simulation and the final hit-list are performed automatically and without user interaction. We test the performance of CHA for virtual screening using screening databases with active and inactive compounds for 40 protein-ligand systems. The results of the CHA are compared to the (i) median screening performance of all representative pharmacophore models of protein-ligand systems, as well as to the virtual screening performance of (ii) a random classifier, (iii) the pharmacophore model derived from the experimental structure in the PDB, and (iv) the representative pharmacophore model appearing most frequently during the MD simulation. For the 34 (out of 40) protein-ligand complexes, for which at least one of the approaches was able to perform better than a random classifier, the highest enrichment was achieved using CHA in 68% of the cases, compared to 12% for the PDB pharmacophore model and 20% for the representative pharmacophore model appearing most frequently. The availabilithy of diverse sets of different pharmacophore models is utilized to analyze some additional questions of interest in 3D pharmacophore-based virtual screening.
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Affiliation(s)
- Marcus Wieder
- Faculty of Life Sciences, Department of Pharmaceutical Chemistry, University of Vienna , Althanstraße 14, 1090 Vienna, Austria.,Faculty of Chemistry, Department of Computational Biological Chemistry, University of Vienna , Währingerstraße 17, 1090 Vienna, Austria
| | - Arthur Garon
- Faculty of Life Sciences, Department of Pharmaceutical Chemistry, University of Vienna , Althanstraße 14, 1090 Vienna, Austria
| | - Ugo Perricone
- Faculty of Life Sciences, Department of Pharmaceutical Chemistry, University of Vienna , Althanstraße 14, 1090 Vienna, Austria.,Department of Biological, Chemical and Pharmaceutical Sciences and Technologies (STEBICEF), University of Palermo , Via Archirafi 32, Palermo, Italy
| | - Stefan Boresch
- Faculty of Chemistry, Department of Computational Biological Chemistry, University of Vienna , Währingerstraße 17, 1090 Vienna, Austria
| | - Thomas Seidel
- Faculty of Life Sciences, Department of Pharmaceutical Chemistry, University of Vienna , Althanstraße 14, 1090 Vienna, Austria
| | - Anna Maria Almerico
- Department of Biological, Chemical and Pharmaceutical Sciences and Technologies (STEBICEF), University of Palermo , Via Archirafi 32, Palermo, Italy
| | - Thierry Langer
- Faculty of Life Sciences, Department of Pharmaceutical Chemistry, University of Vienna , Althanstraße 14, 1090 Vienna, Austria
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Li GB, Yang LL, Yuan Y, Zou J, Cao Y, Yang SY, Xiang R, Xiang M. Virtual screening in small molecule discovery for epigenetic targets. Methods 2015; 71:158-66. [DOI: 10.1016/j.ymeth.2014.11.010] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2014] [Revised: 10/27/2014] [Accepted: 11/14/2014] [Indexed: 12/31/2022] Open
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Aparna V, Dineshkumar K, Mohanalakshmi N, Velmurugan D, Hopper W. Identification of natural compound inhibitors for multidrug efflux pumps of Escherichia coli and Pseudomonas aeruginosa using in silico high-throughput virtual screening and in vitro validation. PLoS One 2014; 9:e101840. [PMID: 25025665 PMCID: PMC4099075 DOI: 10.1371/journal.pone.0101840] [Citation(s) in RCA: 75] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2014] [Accepted: 06/12/2014] [Indexed: 11/18/2022] Open
Abstract
Pseudomonas aeruginosa and Escherichia coli are resistant to wide range of antibiotics rendering the treatment of infections very difficult. A main mechanism attributed to the resistance is the function of efflux pumps. MexAB-OprM and AcrAB-TolC are the tripartite efflux pump assemblies, responsible for multidrug resistance in P. aeruginosa and E. coli respectively. Substrates that are more susceptible for efflux are predicted to have a common pharmacophore feature map. In this study, a new criterion of excluding compounds with efflux substrate-like features was used, thereby refining the selection process and enriching the inhibitor identification process. An in-house database of phytochemicals was created and screened using high-throughput virtual screening against AcrB and MexB proteins and filtered by matching with the common pharmacophore models (AADHR, ADHNR, AAHNR, AADHN, AADNR, AAADN, AAADR, AAANR, AAAHN, AAADD and AAADH) generated using known efflux substrates. Phytochemical hits that matched with any one or more of the efflux substrate models were excluded from the study. Hits that do not have features similar to the efflux substrate models were docked using XP docking against the AcrB and MexB proteins. The best hits of the XP docking were validated by checkerboard synergy assay and ethidium bromide accumulation assay for their efflux inhibition potency. Lanatoside C and diadzein were filtered based on the synergistic potential and validated for their efflux inhibition potency using ethidium bromide accumulation study. These compounds exhibited the ability to increase the accumulation of ethidium bromide inside the bacterial cell as evidenced by these increase in fluorescence in the presence of the compounds. With this good correlation between in silico screening and positive efflux inhibitory activity in vitro, the two compounds, lanatoside C and diadzein could be promising efflux pump inhibitors and effective to use in combination therapy against drug resistant strains of P. aeruginosa and E. coli.
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Affiliation(s)
- Vasudevan Aparna
- Department of Bioinformatics, School of Bioengineering, Faculty of Engineering & Technology, SRM University, Kattankulathur, Tamilnadu, India
| | - Kesavan Dineshkumar
- Department of Bioinformatics, School of Bioengineering, Faculty of Engineering & Technology, SRM University, Kattankulathur, Tamilnadu, India
| | - Narasumani Mohanalakshmi
- Department of Bioinformatics, School of Bioengineering, Faculty of Engineering & Technology, SRM University, Kattankulathur, Tamilnadu, India
| | - Devadasan Velmurugan
- Centre of Advanced Study in Crystallography and Biophysics, University of Madras, Guindy Campus, Chennai, Tamilnadu, India
| | - Waheeta Hopper
- Department of Bioinformatics, School of Bioengineering, Faculty of Engineering & Technology, SRM University, Kattankulathur, Tamilnadu, India
- * E-mail:
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Larif S, Salem CB, Hmouda H, Bouraoui K. In silico screening and study of novel ERK2 inhibitors using 3D QSAR, docking and molecular dynamics. J Mol Graph Model 2014; 53:1-12. [PMID: 25064438 DOI: 10.1016/j.jmgm.2014.07.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2014] [Revised: 06/18/2014] [Accepted: 07/02/2014] [Indexed: 11/25/2022]
Abstract
ERK2 is a dual specificity protein kinase, part of the Ras/Raf/MEK/ERK signal transduction cascade. It forms an interesting target for inhibition based on its relationship with cell proliferation and oncogenesis. A 3D QSAR pharmacophore model (Hypo1) with high correlation (r=0.938) was developed for ERK2 ATP site on the basis of experimentally known inhibitors. The model included three hydrogen bonds, and one hydrophobic site. Assessment of Hypo1 through Fisher randomization, cost analysis, leave one out method and decoy test suggested that the model can reliably detect ERK2 inhibitors. Hypo1 has been used for virtual screening of potential inhibitors from ZINC, Drug Bank, NCI, Maybridge and Chembank databases. Using Hypo1 as a query, databases have been interrogated for compounds who meet the pharmacophore features. The resulting hit compounds were subject to docking and analysis. Docking and molecular dynamics analysis showed that in order to achieve a higher potency compounds have to interact with catalytic site, glycine rich loop, Hinge region, Gatekeeper region and ATP site entrance residues. We also identified catalytic site and Glycine rich loop as important regions to bind by molecules for better potency and selectivity.
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Affiliation(s)
- Sofiene Larif
- Metabolic Biophysics and Applied Pharmacology Laboratory, Department of Biophysics, Faculty of Medicine of Sousse, 4002 Sousse, Tunisia.
| | - Chaker Ben Salem
- Department of Clinical Pharmacology, Faculty of Medicine of Sousse, 4002 Sousse, Tunisia
| | - Houssem Hmouda
- Department of Clinical Pharmacology, Faculty of Medicine of Sousse, 4002 Sousse, Tunisia
| | - Kamel Bouraoui
- Department of Clinical Pharmacology, Faculty of Medicine of Sousse, 4002 Sousse, Tunisia
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27
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An integrated approach to knowledge-driven structure-based virtual screening. J Comput Aided Mol Des 2014; 28:927-39. [PMID: 24993405 DOI: 10.1007/s10822-014-9769-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2014] [Accepted: 06/23/2014] [Indexed: 12/18/2022]
Abstract
In many practical applications of structure-based virtual screening (VS) ligands are already known. This circumstance requires that the obtained hits need to satisfy initial made expectations i.e., they have to fulfill a predefined binding pattern and/or lie within a predefined physico-chemical property range. Based on the RApid Index-based Screening Engine (RAISE) approach, we introduce CRAISE-a user-controllable structure-based VS method. It efficiently realizes pharmacophore-guided protein-ligand docking to assess the library content but thereby concentrates only on molecules that have a chance to fulfill the given binding pattern. In order to focus only on hits satisfying given molecular properties, library profiles can be utilized to simultaneously filter compounds. CRAISE was evaluated on a range of strict to rather relaxed hypotheses with respect to its capability to guide binding-mode predictions and VS runs. The results reveal insights into a guided VS process. If a pharmacophore model is chosen appropriately, a binding mode below 2 Å is successfully reproduced for 85% of well-prepared structures, enrichment is increased up to median AUC of 73%, and the selectivity of the screening process is significantly enhanced leading up to seven times accelerated runtimes. In general, CRAISE supports a versatile structure-based VS approach allowing to assess hypotheses about putative ligands on a large scale.
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28
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Sanders MPA, Barbosa AJM, Zarzycka B, Nicolaes GA, Klomp JP, de Vlieg J, Del Rio A. Comparative Analysis of Pharmacophore Screening Tools. J Chem Inf Model 2012; 52:1607-20. [DOI: 10.1021/ci2005274] [Citation(s) in RCA: 78] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- Marijn P. A. Sanders
- Computational Drug Discovery
Group, CMBI, Radboud University Nijmegen, Geert Grooteplein Zuid 26-28,
6525 GA, Nijmegen, The Netherlands
| | - Arménio J. M. Barbosa
- Department of Experimental Pathology,
Alma Mater Studiorum, University of Bologna, Via S. Giacomo 14, 40126
Bologna, Italy
| | - Barbara Zarzycka
- Department
of Biochemistry, Cardiovascular
Research Institute Maastricht, Maastricht University, Universiteitssingel
50, 6229 ER, The Netherlands
| | - Gerry A.F. Nicolaes
- Department
of Biochemistry, Cardiovascular
Research Institute Maastricht, Maastricht University, Universiteitssingel
50, 6229 ER, The Netherlands
| | - Jan P.G. Klomp
- Lead Pharma Medicine, Kapittelweg
29, 6525 EN, Nijmegen, The Netherlands
| | - Jacob de Vlieg
- Computational Drug Discovery
Group, CMBI, Radboud University Nijmegen, Geert Grooteplein Zuid 26-28,
6525 GA, Nijmegen, The Netherlands
- Netherlands eScience Center,
Science Park 140, 1098XG, Amsterdam, The Netherlands
| | - Alberto Del Rio
- Department of Experimental Pathology,
Alma Mater Studiorum, University of Bologna, Via S. Giacomo 14, 40126
Bologna, Italy
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29
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Scior T, Bender A, Tresadern G, Medina-Franco JL, Martínez-Mayorga K, Langer T, Cuanalo-Contreras K, Agrafiotis DK. Recognizing Pitfalls in Virtual Screening: A Critical Review. J Chem Inf Model 2012; 52:867-81. [DOI: 10.1021/ci200528d] [Citation(s) in RCA: 294] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Thomas Scior
- Pharmacy Department, Facultad de Ciencias Químicas, Universidad Autónoma de Puebla, Puebla, Pue, México
| | - Andreas Bender
- Unilever Centre for Molecular
Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K
| | - Gary Tresadern
- Research Informatics & Integrative Genomics, Janssen Research & Development, Calle Jarama 75, Poligono Industrial, Toledo 45007, Spain
| | - José L. Medina-Franco
- Torrey Pines Institute for Molecular Studies, 11350 SW Village Parkway, Port
St. Lucie, Florida 34987, United States
| | - Karina Martínez-Mayorga
- Torrey Pines Institute for Molecular Studies, 11350 SW Village Parkway, Port
St. Lucie, Florida 34987, United States
| | - Thierry Langer
- Prestwick Chemical, Blvd Gonthier dʼAndernach, F-67400 Illkirch, France
| | - Karina Cuanalo-Contreras
- Pharmacy Department, Facultad de Ciencias Químicas, Universidad Autónoma de Puebla, Puebla, Pue, México
| | - Dimitris K. Agrafiotis
- Johnson & Johnson Pharmaceutical Research & Development, LLC, Welsh & McKean Roads, Spring House, Pennsylvania 19477, United States
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30
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Identification of novel potential HIF-prolyl hydroxylase inhibitors by in silico screening. Mol Divers 2011; 16:193-202. [DOI: 10.1007/s11030-011-9338-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2011] [Accepted: 10/07/2011] [Indexed: 10/16/2022]
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31
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Abstract
Computer-aided drug design plays a vital role in drug discovery and development and has become an indispensable tool in the pharmaceutical industry. Computational medicinal chemists can take advantage of all kinds of software and resources in the computer-aided drug design field for the purposes of discovering and optimizing biologically active compounds. This article reviews software and other resources related to computer-aided drug design approaches, putting particular emphasis on structure-based drug design, ligand-based drug design, chemical databases and chemoinformatics tools.
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32
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Reviewing ligand-based rational drug design: the search for an ATP synthase inhibitor. Int J Mol Sci 2011; 12:5304-18. [PMID: 21954360 PMCID: PMC3179167 DOI: 10.3390/ijms12085304] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2011] [Revised: 08/04/2011] [Accepted: 08/11/2011] [Indexed: 12/14/2022] Open
Abstract
Following major advances in the field of medicinal chemistry, novel drugs can now be designed systematically, instead of relying on old trial and error approaches. Current drug design strategies can be classified as being either ligand- or structure-based depending on the design process. In this paper, by describing the search for an ATP synthase inhibitor, we review two frequently used approaches in ligand-based drug design: The pharmacophore model and the quantitative structure-activity relationship (QSAR) method. Moreover, since ATP synthase ligands are potentially useful drugs in cancer therapy, pharmacophore models were constructed to pave the way for novel inhibitor designs.
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33
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Recent trends and observations in the design of high-quality screening collections. Future Med Chem 2011; 3:751-66. [DOI: 10.4155/fmc.11.15] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The design of a high-quality screening collection is of utmost importance for the early drug-discovery process and provides, in combination with high-quality assay systems, the foundation of future discoveries. Herein, we review recent trends and observations to successfully expand the access to bioactive chemical space, including the feedback from hit assessment interviews of high-throughput screening campaigns; recent successes with chemogenomics target family approaches, the identification of new relevant target/domain families, diversity-oriented synthesis and new emerging compound classes, and non-classical approaches, such as fragment-based screening and DNA-encoded chemical libraries. The role of in silico library design approaches are emphasized.
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34
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Löwer M, Geppert T, Schneider P, Hoy B, Wessler S, Schneider G. Inhibitors of Helicobacter pylori protease HtrA found by 'virtual ligand' screening combat bacterial invasion of epithelia. PLoS One 2011; 6:e17986. [PMID: 21483848 PMCID: PMC3069028 DOI: 10.1371/journal.pone.0017986] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2010] [Accepted: 02/17/2011] [Indexed: 02/03/2023] Open
Abstract
Background The human pathogen Helicobacter pylori (H. pylori) is a main cause for gastric inflammation and cancer. Increasing bacterial resistance against antibiotics demands for innovative strategies for therapeutic intervention. Methodology/Principal Findings We present a method for structure-based virtual screening that is based on the comprehensive prediction of ligand binding sites on a protein model and automated construction of a ligand-receptor interaction map. Pharmacophoric features of the map are clustered and transformed in a correlation vector (‘virtual ligand’) for rapid virtual screening of compound databases. This computer-based technique was validated for 18 different targets of pharmaceutical interest in a retrospective screening experiment. Prospective screening for inhibitory agents was performed for the protease HtrA from the human pathogen H. pylori using a homology model of the target protein. Among 22 tested compounds six block E-cadherin cleavage by HtrA in vitro and result in reduced scattering and wound healing of gastric epithelial cells, thereby preventing bacterial infiltration of the epithelium. Conclusions/Significance This study demonstrates that receptor-based virtual screening with a permissive (‘fuzzy’) pharmacophore model can help identify small bioactive agents for combating bacterial infection.
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Affiliation(s)
- Martin Löwer
- Institute of Organic Chemistry and Chemical Biology, Goethe-University, Frankfurt, Germany
| | - Tim Geppert
- Department of Chemistry and Applied Biosciences, Swiss Federal Institute of Technology (ETH), Zürich, Switzerland
| | - Petra Schneider
- Department of Chemistry and Applied Biosciences, Swiss Federal Institute of Technology (ETH), Zürich, Switzerland
| | - Benjamin Hoy
- Division of Microbiology, University of Salzburg, Salzburg, Austria
| | - Silja Wessler
- Division of Microbiology, University of Salzburg, Salzburg, Austria
| | - Gisbert Schneider
- Department of Chemistry and Applied Biosciences, Swiss Federal Institute of Technology (ETH), Zürich, Switzerland
- * E-mail:
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35
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Planesas JM, Claramunt RM, Teixidó J, Borrell JI, Pérez-Nueno VI. Improving VEGFR-2 Docking-Based Screening by Pharmacophore Postfiltering and Similarity Search Postprocessing. J Chem Inf Model 2011; 51:777-87. [DOI: 10.1021/ci1002763] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Affiliation(s)
- Jesús M. Planesas
- Departamento de Química Orgánica y Bio-Orgánica, Facultad de Ciencias, UNED, Senda del Rey 9, E-28040 Madrid, Spain
| | - Rosa M. Claramunt
- Departamento de Química Orgánica y Bio-Orgánica, Facultad de Ciencias, UNED, Senda del Rey 9, E-28040 Madrid, Spain
| | - Jordi Teixidó
- Grup d'Enginyeria Molecular, Institut Químic de Sarriá (IQS), Universitat Ramon Llull, Barcelona, Spain
| | - José I. Borrell
- Grup d'Enginyeria Molecular, Institut Químic de Sarriá (IQS), Universitat Ramon Llull, Barcelona, Spain
| | - Violeta I. Pérez-Nueno
- Grup d'Enginyeria Molecular, Institut Químic de Sarriá (IQS), Universitat Ramon Llull, Barcelona, Spain
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36
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Yuriev E, Agostino M, Ramsland PA. Challenges and advances in computational docking: 2009 in review. J Mol Recognit 2010; 24:149-64. [DOI: 10.1002/jmr.1077] [Citation(s) in RCA: 223] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2010] [Revised: 07/20/2010] [Accepted: 07/21/2010] [Indexed: 12/12/2022]
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37
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Ma XH, Wang R, Tan CY, Jiang YY, Lu T, Rao HB, Li XY, Go ML, Low BC, Chen YZ. Virtual screening of selective multitarget kinase inhibitors by combinatorial support vector machines. Mol Pharm 2010; 7:1545-60. [PMID: 20712327 DOI: 10.1021/mp100179t] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Multitarget agents have been increasingly explored for enhancing efficacy and reducing countertarget activities and toxicities. Efficient virtual screening (VS) tools for searching selective multitarget agents are desired. Combinatorial support vector machines (C-SVM) were tested as VS tools for searching dual-inhibitors of 11 combinations of 9 anticancer kinase targets (EGFR, VEGFR, PDGFR, Src, FGFR, Lck, CDK1, CDK2, GSK3). C-SVM trained on 233-1,316 non-dual-inhibitors correctly identified 26.8%-57.3% (majority >36%) of the 56-230 intra-kinase-group dual-inhibitors (equivalent to the 50-70% yields of two independent individual target VS tools), and 12.2% of the 41 inter-kinase-group dual-inhibitors. C-SVM were fairly selective in misidentifying as dual-inhibitors 3.7%-48.1% (majority <20%) of the 233-1,316 non-dual-inhibitors of the same kinase pairs and 0.98%-4.77% of the 3,971-5,180 inhibitors of other kinases. C-SVM produced low false-hit rates in misidentifying as dual-inhibitors 1,746-4,817 (0.013%-0.036%) of the 13.56 M PubChem compounds, 12-175 (0.007%-0.104%) of the 168 K MDDR compounds, and 0-84 (0.0%-2.9%) of the 19,495-38,483 MDDR compounds similar to the known dual-inhibitors. C-SVM was compared to other VS methods Surflex-Dock, DOCK Blaster, kNN and PNN against the same sets of kinase inhibitors and the full set or subset of the 1.02 M Zinc clean-leads data set. C-SVM produced comparable dual-inhibitor yields, slightly better false-hit rates for kinase inhibitors, and significantly lower false-hit rates for the Zinc clean-leads data set. Combinatorial SVM showed promising potential for searching selective multitarget agents against intra-kinase-group kinases without explicit knowledge of multitarget agents.
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Affiliation(s)
- X H Ma
- Bioinformatics and Drug Design Group, Department of Pharmacy, Centre for Computational Science and Engineering, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543
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38
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Del Rio A, Barbosa AJM, Caporuscio F, Mangiatordi GF. CoCoCo: a free suite of multiconformational chemical databases for high-throughput virtual screening purposes. MOLECULAR BIOSYSTEMS 2010; 6:2122-8. [DOI: 10.1039/c0mb00039f] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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