AI-driven drug repurposing and binding pose meta dynamics identifies novel targets for monkeypox virus

Author:

Patel,Chiragkumar

Mall, Raghvendra

Bensmail, Halima
Author Address

Department 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., Department of Immunology, St. Jude Children 39;s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA; Biotechnology Research Center, Technology Innovation Institute, Abu Dhabi 9639, United Arab Emirates. Electronic address: raghvendra.mall@stjude.org., Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha 34110, Qatar. Electronic address: hbensmail@hbku.edu.qa.,

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. Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.

See More

Author Address