Computer-Assisted Drug Virtual Screening Based on the Natural Product Databases

Recent advances in medicinal chemistry strategies for the development of METTL3 inhibitors

N6-methyladenosine (m6A), the most abundant RNA modification in eukaryotic cells, exerts a critical influence on RNA function and gene expression. It has attracted considerable attention within the rapidly evolving field of epitranscriptomics. METTL3 is a key enzyme for m6A modification and is essential for maintaining normal m6A levels. High expression of METTL3 is closely associated with various cancers, including gastric cancer, liver cancer, and leukemia. Inhibiting METTL3 has shown potential in slowing cancer progression, thereby driving the development of METTL3 inhibitors. In this work, we summarize recent advancements in the development of METTL3 inhibitor, with a focus on medicinal chemistry strategies employed during discovery and optimization phases. We explore the application of structure-activity relationship (SAR) studies and protein-targeted degradation techniques, while addressing key challenges associated with their characterization and clinical translation. This review underscores the therapeutic potential of METTL3 inhibitors in modulating epitranscriptomic pathways and aims to offer perspectives for future research in this rapidly evolving field.

Expression of LASS2 Can be Regulated by Dihydroartemisinin to Regulate Cisplatin Chemosensitivity in Bladder Cancer Cells

INTRODUCTION

The aim of this study was to investigate the potential of dihydroartemisinin to augment the efficacy of cisplatin chemotherapy through the modulation of LASS2 expression.

METHODS

TCMSP, CTR-DB, TCGA-BLC, and other databases were used to analyze the possibility of LASS2 as the target gene of dihydroartemisinin. Cell experiments revealed the synergistic effect of DDP and DHA. Animal experiments showed that DHA inhibited the growth of DDP-treated mice. In addition, WB, real-time PCR, and immunohistochemical analysis showed that DHA enhanced LASS2 (CERS2) expression in bladder cancer cells and DDP-treated mice.

RESULTS

LASS2 is associated with cisplatin chemosensitivity.LASS2 expression levels are different between BLC tissues and normal tissues. COX analysis showed that patients with high LASS2 expression had a higher cumulative overall survival rate than those with low LASS2 expression. The Sankey plot showed that LASS2 expression is lower in BLC tissues with more advanced stage and distant metastasis. The docking score of DHA and LASS2 reached the maximum value of -5.5259, indicating that DHA had a strong binding affinity with LASS2 targets. CCK8 assay showed that the most effective concentration ratio of DHA to DDP was 2.5 μg/ml + 10μg/ml. In vivo experiments showed that DHA inhibited tumor growth in cisplatin-treated mice. In addition, WB, RT-qPCR, and immunohistochemical analysis showed that DHA was able to enhance LASS2 expression in BLC cells and DDP-treated mice.

CONCLUSION

The upregulation of LASS2 (CERS2) expression in bladder cancer cells by DHA has been found to enhance cisplatin chemosensitivity.

High-throughput screening identification of apigenin that reverses the colistin resistance of mcr-1-positive pathogens

The plasmid-mediated gene mcr-1 that makes bacteria resistant to the antibiotic colistin is spreading quickly, which means that colistin is no longer working well to treat Gram-negative bacterial infections. Herein, we utilized a computer-aided high-throughput screening drugs method to identify the natural product apigenin, a potential mcr-protein inhibitor, which effectively enhanced the antimicrobial activity of colistin. Several assays, including a checkerboard minimum inhibitory concentration assay, a time-kill assay, the combined disk test, molecular simulation dynamics, and animal infection models assay, were conducted to verify whether apigenin enhanced the ability of colistin to fight Gram-negative bacterial infections. The results showed that apigenin improved the antimicrobial activity of colistin against multidrug-resistant Enterobacteriaceae infection. Moreover, apigenin not only did not increase the toxic effect of colistin but also had the ability to effectively inhibit the frequency of bacterial resistance mutations to colistin. Studies clearly elucidated that apigenin could interfere with the thermal stability of the protein by binding to the mcr-1 protein. Additionally, the combination of apigenin and colistin could exert multiple effects, including disrupting bacterial membranes, the generation of bacterial nitric oxide and reactive oxygen species, as well as inhibiting bacterial adenosine triphosphate production. Furthermore, the addition of apigenin was able to significantly inhibit colistin-stimulated high expression levels of the bacterial mcr-1 gene. Finally, apigenin exhibited a characteristic anti-inflammatory effect while enhancing the antimicrobial activity of colistin against mcr-1-positive Escherichia coli (E. coli) infected animals. In conclusion, as a potential lead compound, apigenin is promising in combination with colistin in the future treatment of mcr-1-positive E. coli infections.IMPORTANCEThis study found that apigenin was able to inhibit the activity of the mcr-1 protein using a high-throughput virtual screening method. Apigenin effectively enhanced the antimicrobial activity of colistin against multidrug-resistant Enterobacteriaceae, including mcr-1-positive strains, in vitro and in vivo. This study will provide new options and strategies for the future treatment of multidrug-resistant pathogen infections.

Preparation of imidazolium ionic liquid functionalized paper membrane for selective extraction of caffeic acid and its structural and functional analogues from Taraxaci Herba

In the search for pharmaceutically active compounds from natural products, it is crucial and challenging to develop separation or purification methods that target not only structurally similar compounds but also those with specific pharmaceutical functions. The adsorption-based method is widely employed in this field and holds potential for this application, given the diverse range of functional monomers that can be chosen based on structural or functional selectivity. In this work, an imidazolium ionic liquid (IL) modified paper membrane was synthesized via microwave reaction. Caffeic acid (CA), with potential interactions with imidazolium IL and a representative component of phenolic acids in Taraxaci Herba, was chosen as a target compound. After optimization of synthesis and extraction parameters, the resulting extraction membrane could be used to quantitatively analyze CA at ng/ml level, and to extract CA's analogues from the sample matrix. Cheminformatics confirmed the presence of structural and functional similarity among these extracted compounds. This study offers a novel approach to preparing a readily synthesized extraction membrane capable of isolating compounds with structural and functional analogies, as well as developing a membrane solid-phase extraction-based analytical method for natural products.

Discovering potential WRN inhibitors from natural product database through computational methods

Microsatellite instability (MSI) is a relatively common feature associated with multiple cancers, and Werner syndrome (WRN) ATP-dependent helicase has been recognized as a novel target for treating MSI cancers, such as colorectal cancer. A small-molecule inhibitor targeting WRN would be a promising strategy for treating colorectal cancer with high MSI expression. In this study, we employed a computer-assisted drug discovery strategy to screen over 30,000 natural product molecules. By using a combination of docking, ligand efficiency, Molecular Mechanics/Generalized Born Surface Area (MM/GBSA), and thermodynamic integration (TI) calculations, we identified MOL008980, MOL010740, MOL011832, T4743, TN1166, and TNP-002173 as potential WRN inhibitors. Subsequent molecular dynamics simulation revealed that these screened natural products possessed better binding dynamic characteristics than ATP substrate and were capable of inhibiting the dynamic process of WRN, making them potential strong ATP competitive inhibitors. In conclusion, our computational approach revealed potential WRN inhibitors from a natural product database, providing a theoretical basis for future research.

Fungi-enabled pore channel regulation and defect engineering of a novel micro-reactor for treating complex effluents

Defect engineering has become a significant research area in recent years; however, little has been reported on the biological method for modulating the intrinsic carbon defects of the biochar framework. Herein, a fungi-enabled method for the fabrication of porous carbon/Fe₃O₄/Ag (PC/Fe₃O₄/Ag) composites was developed, and the mechanism underlying the hierarchical structure is elucidated for the first time. By regulating the cultivation process of fungi on water hyacinth biomass, a well-developed interconnected structure and carbon defects acting as potential catalytic active sites were formed. This new material with antibacterial, adsorption and photodegradation properties could be an excellent choice for treating the mixed dyestuff effluents with oils and bacteria, also guiding pore channel regulation and defect engineering in materials science. Numerical simulations were carried out to demonstrate the remarkable catalytic activity.

Novel Target Study to Cure Cardiovascular Disease regarding Proprotein Converse Subtilisin/Kexin Type 9

Objective

This study is aimed at screening the potential ideal lead compounds from natural drug library (ZINC database), which had potential inhibition effects against proprotein converse subtilisin/kexin type 9 (PCSK9), and contributing to enrich the practical basis of PCSK9 inhibitor screening.

Methods

A series of computer-aided virtual screening techniques were used to identify potential inhibitors of PCSK9. Structure-based virtual screening by LibDock was carried out to calculate the LibDock scores, followed by ADME (absorption, distribution, metabolism, and excretion) and toxicity predictions. Molecule docking was next employed to demonstrate the binding affinity and mechanism between the candidate ligands and PCSK9 macromolecule. Finally, molecular dynamics simulation was performed to evaluate the stability of ligand-PCSK9 complex under natural circumstance.

Results

Two novel natural compounds ZINC000004099069 and ZINC000014952116 from the ZINC database were found to bind with PCSK9 with a higher binging affinity together with more favorable interaction energy. Also, they were predicted to be non-CYP2D6 inhibitors, together with low rodent carcinogenicity and AMES mutagenicity as well as hepatotoxicity. Molecular dynamics simulation analysis demonstrated that these two complex ZINC000004099069- and ZINC000014952116-PCSK9 had more favorable potential energy compared to the reference ligand, which could exist stably whether in vivo or in vitro.

Conclusion

This study elucidated that ZINC000004099069 and ZINC000014952116 were finally screened as safe and potential drug candidates, which may have great significance in the development of PCSK9 inhibitor development.

Discovery of 7, 4'-dimethoxy-3-hydroxyflavone as a protease-activated receptor 4 antagonist with antithrombotic activity and less bleeding tendency in mice

There is growing evidence of the importance of protease-activated receptor 4 (PAR4), one of thrombin receptors, as a therapeutic target in thrombotic cardiovascular diseases. In the present study, we utilized ligand-based virtual screening, bioassay, and structure-activity relationship study to discover PAR4 antagonists with new chemical scaffolds from natural origin, and examined their application as antiplatelet agents. By using these approaches, we have identified a flavonoid, 7, 4'-dimethoxy-3-hydroxyflavone, that exhibits anti-PAR4 activity. 7, 4'-Dimethoxy-3-hydroxyflavone inhibited PAR4-mediated human platelet aggregation, GPIIb/IIIa activation, and P-selectin secretion. Also, it inhibited PAR4 downstream signaling pathways, including Ca2+/protein kinase C, Akt, and MAP kinases ERK and p38, in human platelets, and suppressed PAR4-mediated β-arrestin recruitment in CHO-K1 cells exogenously expressed human PAR4. In a microfluidic system, 7, 4'-dimethoxy-3-hydroxyflavone reduced thrombus formation on collagen-coated chambers at an arterial shear rate in recalcified whole blood. Furthermore, mice treated with 7, 4'-dimethoxy-3-hydroxyflavone were significantly protected from FeCl3-induced carotid arterial occlusions, without significantly affecting tail bleeding time. In conclusion, 7, 4'-dimethoxy-3-hydroxyflavone represents a new class of nature-based PAR4 antagonist, it shows effective in vivo antithrombotic properties with less bleeding tendency, and could be a potential candidate for developing new antiplatelet agents.

Artificial intelligence and machine-learning approaches in structure and ligand-based discovery of drugs affecting central nervous system

CNS disorders are indications with a very high unmet medical needs, relatively smaller number of available drugs, and a subpar satisfaction level among patients and caregiver. Discovery of CNS drugs is extremely expensive affair with its own unique challenges leading to extremely high attrition rates and low efficiency. With explosion of data in information age, there is hardly any aspect of life that has not been touched by data driven technologies such as artificial intelligence (AI) and machine learning (ML). Drug discovery is no exception, emergence of big data via genomic, proteomic, biological, and chemical technologies has driven pharmaceutical giants to collaborate with AI oriented companies to revolutionise drug discovery, with the goal of increasing the efficiency of the process. In recent years many examples of innovative applications of AI and ML techniques in CNS drug discovery has been reported. Research on therapeutics for diseases such as schizophrenia, Alzheimer's and Parkinsonism has been provided with a new direction and thrust from these developments. AI and ML has been applied to both ligand-based and structure-based drug discovery and design of CNS therapeutics. In this review, we have summarised the general aspects of AI and ML from the perspective of drug discovery followed by a comprehensive coverage of the recent developments in the applications of AI/ML techniques in CNS drug discovery.

Mechanism by which Eucommia ulmoides leaves Regulate Nonalcoholic fatty liver disease based on system pharmacology

ETHNOPHARMACOLOGICAL RELEVANCE

Eucommia ulmoides (E. ulmoides) leaves are included in the Chinese Pharmacopoeia, and are traditionally used to treat hypertension, obesity, diabetes, and other diseases. Numerous pharmacological studies have shown that E. ulmoides has a good effect on lowering blood lipids and can improve obesity and nonalcoholic fatty liver.

AIM

To study the mechanism of E. ulmoides leaves in regulating nonalcoholic fatty liver disease by combining prediction and validation.

METHODS

Using network pharmacology, and molecular docking to predict E. ulmoides in regulating the action mechanism and potential active ingredients of nonalcoholic fatty liver, large hole adsorption resin enrichment active sites, in vitro experiments were performed to verify its fat-lowering effect and mechanism.

RESULTS

The major components of E. ulmoides leaves exhibited good combination with lipid metabolism-regulating core proteins, particularly flavonoids. EUL 50 significantly reduced lipid accumulation, and increased PPARγ. Compared with the control group, the autophagy level increased after the administration of EUL 50. PPARγ decreased significantly after the addition of chloroquine (CQ, autophagy inhibitor).

CONCLUSION

The active ingredients in E. ulmoides leaves regulating nonalcoholic fatty liver disease are mainly flavonoids and phenolics. EUL 50 may play a role in lowering lipids by regulating PPARγ expression through inducing autophagy.

Plant Derived Bioactive Compounds, Their Anti-Cancer Effects and In Silico Approaches as an Alternative Target Treatment Strategy for Breast Cancer: An Updated Overview

Cancer is one of the most common malignant diseases that occur worldwide, among which breast cancer is the second leading cause of death in women. The subtypes are associated with differences in the outcome and were selected for treatments according to the estrogen receptor, progesterone receptor, and human epidermal growth factor receptor. Triple-negative breast cancer, one of the subtypes of breast cancer, is difficult to treat and can even lead to death. If breast cancer is not treated during the initial stages, it may spread to nearby organs, a process called metastasis, through the blood or lymph system. For in vitro studies, MCF-7, MDA-MB-231, MDA-MB-468, and T47B are the most commonly used breast cancer cell lines. Clinically, chemotherapy and radiotherapy are usually expensive and can also cause side effects. To overcome these issues, medicinal plants could be the best alternative for chemotherapeutic drugs with fewer side effects and cost-effectiveness. Furthermore, the genes involved in breast cancer can be regulated and synergized with signaling molecules to suppress the proliferation of breast cancer cells. In addition, nanoparticles encapsulating (nano-encapsulation) medicinal plant extracts showed a significant reduction in the apoptotic and cytotoxic activities of breast cancer cells. This present review mainly speculates an overview of the native medicinal plant derived anti-cancerous compounds with its efficiency, types and pathways involved in breast cancer along with its genes, the mechanism of breast cancer brain metastasis, chemoresistivity and its mechanism, bioinformatics approaches which could be an effective alternative for drug discovery.

Cheminformatics in Natural Product-based Drug Discovery

This review seeks to provide a timely survey of the scope and limitations of cheminformatics methods in natural product-based drug discovery. Following an overview of data resources of chemical, biological and structural information on natural products, we discuss, among other aspects, in silico methods for (i) data curation and natural products dereplication, (ii) analysis, visualization, navigation and comparison of the chemical space, (iii) quantification of natural product-likeness, (iv) prediction of the bioactivities (virtual screening, target prediction), ADME and safety profiles (toxicity) of natural products, (v) natural products-inspired de novo design and (vi) prediction of natural products prone to cause interference with biological assays. Among the many methods discussed are rule-based, similarity-based, shape-based, pharmacophore-based and network-based approaches, docking and machine learning methods.

Anticancer Plants: A Review of the Active Phytochemicals, Applications in Animal Models, and Regulatory Aspects

The rising burden of cancer worldwide calls for an alternative treatment solution. Herbal medicine provides a very feasible alternative to western medicine against cancer. This article reviews the selected plant species with active phytochemicals, the animal models used for these studies, and their regulatory aspects. This study is based on a meticulous literature review conducted through the search of relevant keywords in databases, Web of Science, Scopus, PubMed, and Google Scholar. Twenty plants were selected based on defined selection criteria for their potent anticancer compounds. The detailed analysis of the research studies revealed that plants play an indispensable role in fighting different cancers such as breast, stomach, oral, colon, lung, hepatic, cervical, and blood cancer cell lines. The in vitro studies showed cancer cell inhibition through DNA damage and activation of apoptosis-inducing enzymes by the secondary metabolites in the plant extracts. Studies that reported in vivo activities of these plants showed remarkable results in the inhibition of cancer in animal models. Further studies should be performed on exploring more plants, their active compounds, and the mechanism of anticancer actions for use as standard herbal medicine.