AI-driven drug repurposing and binding pose meta dynamics identifies novel targets for monkeypox virus
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Updated: Aug 5, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Chirag N Patel1, Raghvendra Mall2, Halima Bensmail3
1Department of Botany, Bioinformatics and Climate Change Impacts Management, School of Science, Gujarat University, Ahmedabad 380009, India; Chemical Biology Laboratory, Center for Cancer Research, National Cancer Institute, National Institute of Health, Frederick, MD 21702, USA.
Abstract:
Monkeypox virus (MPXV) was confirmed in May 2022 and designated a global health emergency by WHO in July 2022. MPX virions are big, enclosed, brick-shaped, and contain a linear, double-stranded DNA genome as well as enzymes. MPXV particles bind to the host cell membrane via a variety of viral-host protein interactions. As a result, the wrapped structure is a potential therapeutic target. DeepRepurpose, an artificial intelligence-based compound-viral proteins interaction framework, was used via a transfer learning setting to prioritize a set of FDA approved and investigational drugs which can potentially inhibit MPXV viral proteins. To filter and narrow down the lead compounds from curated collections of pharmaceutical compounds, we used a rigorous computational framework that included homology modeling, molecular docking, dynamic simulations, binding free energy calculations, and binding pose metadynamics. We identified Elvitegravir as a potential inhibitor of MPXV virus using our comprehensive pipeline.
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