ArticlePloS one2016
Discovery of Novel Hepatitis C Virus NS5B Polymerase Inhibitors by Combining Random Forest, Multiple e-Pharmacophore Modeling and Docking.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 56 citations in OpenAlex.
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- 1-Sulfonyl-3-amino-1ACS omega · 2023Article
- A Random Forest Model for Peptide Classification Based on Virtual Docking Data.International journal of molecular sciences · 2023Article
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- RdRp (RNA-dependent RNA polymerase): A key target providing anti-virals for the management of various viral diseases.Journal of molecular structure · 2022Review
- Artificial Intelligence-Based Ensemble Learning Model for Prediction of Hepatitis C Disease.Frontiers in public health · 2022Article
- In silico identification of novel SARS-COV-2 2'-O-methyltransferase (nsp16) inhibitors: structure-based virtual screening, molecular dynamics simulation and MM-PBSA approaches.Journal of enzyme inhibition and medicinal chemistry · 2021Article
- A Novel Small Molecule Inhibits Hepatitis C Virus Propagation in Cell Culture.Microbiology spectrum · 2021Article
- Development of Machine Learning Models and the Discovery of a New Antiviral Compound against Yellow Fever Virus.Journal of chemical information and modeling · 2021Article
- Immuno-Informatics Analysis of Pakistan-Based HCV Subtype-3a for Chimeric Polypeptide Vaccine Design.Vaccines · 2021Article
- Predicting New Anti-Norovirus Inhibitor With the Help of Machine Learning Algorithms and Molecular Dynamics Simulation-Based Model.Frontiers in chemistry · 2021Article
- Benzothiazoles as potential antiviral agents.The Journal of pharmacy and pharmacology · 2020Review
- Carbazole Derivatives as Antiviral Agents: An Overview.Molecules (Basel, Switzerland) · 2019Review
- Targeting HCV polymerase: a structural and dynamic perspective into the mechanism of selective covalent inhibition.RSC advances · 2018Article
- Distribution and Driving Factors of Forest Swamp Conversions in a Cold Temperate Region.International journal of environmental research and public health · 2018Article
- Quantitative Structure-Activity Relationship Model for HCVNS5B inhibitors based on an Antlion Optimizer-Adaptive Neuro-Fuzzy Inference System.Scientific reports · 2018Article
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Authors and funding
11 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The NS5B polymerase is one of the most attractive targets for developing new drugs to block Hepatitis C virus (HCV) infection. We describe the discovery of novel potent HCV NS5B polymerase inhibitors by employing a virtual screening (VS) approach, which is based on random forest (RB-VS), e-pharmacophore (PB-VS), and docking (DB-VS) methods. In the RB-VS stage, after feature selection, a model with 16 descriptors was used. In the PB-VS stage, six energy-based pharmacophore (e-pharmacophore) models from different crystal structures of the NS5B polymerase with ligands binding at the palm I, thumb I and thumb II regions were used. In the DB-VS stage, the Glide SP and XP docking protocols with default parameters were employed. In the virtual screening approach, the RB-VS, PB-VS and DB-VS methods were applied in increasing order of complexity to screen the InterBioScreen database. From the final hits, we selected 5 compounds for further anti-HCV activity and cellular cytotoxicity assay. All 5 compounds were found to inhibit NS5B polymerase with IC50 values of 2.01-23.84 μM and displayed anti-HCV activities with EC50 values ranging from 1.61 to 21.88 μM, and all compounds displayed no cellular cytotoxicity (CC50 > 100 μM) except compound N2, which displayed weak cytotoxicity with a CC50 value of 51.3 μM. The hit compound N2 had the best antiviral activity against HCV, with a selective index of 32.1. The 5 hit compounds with new scaffolds could potentially serve as NS5B polymerase inhibitors through further optimization and development.
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