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Updated: Jun 6, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
ROC-guided virtual screening, molecular dynamics simulation, and bioactivity validation assessment Z195914464 as a
Xiongpiao Wei1, Min Li1, Yuanbiao Tu2
1Jiangxi Provincial Key Laboratory of Drug Design and Evaluation, School of Pharmacy, Jiangxi Science & Technology Normal University, Economic Development Zone, 330013 Nanchang City, Jiangxi Province, China.
Abstract:
Discovering novel class anti-SARS-CoV-2 compounds with novel backbones is essential for preventing and controlling SARS-CoV-2 transmission, which poses a substantial threat to the health and social sustainable development of the global population because of its high pathogenicity and high transmissibility. Although the potential mutation of SARS-CoV-2 might diminish the therapeutic efficacy of drugs, 3CL Mpro is the target highly conservative in contrast with other targets. It is an essential enzyme for coronavirus replication. Based on this, this study utilized the drug discovery strategy of Knime molecular filtering framework, ROC-guided virtual screening, clustering analysis, binding mode analysis, and activity evaluation approaches to identify compound Z195914464 (IC50: 7.19 μM) is a novel class inhibitor of anti-SARS-CoV-2 against the 3CL Mpro target. In addition, based on molecular dynamics simulations and MMPBSA analyses, discovered that compound Z195914464 can interact with more key residues and lower bonding energies, which explains why it exhibited more activity than the other three compounds. In summary, this study developed a method for the rapid and accurate discovery of active compounds and can also be applied in the discovery of active compounds in other targets.
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