Supervised screening of Tecovirimat-like compounds as potential inhibitors for the monkeypox virus E8L protein.
Aamir MehmoodSadia NawabGuihua JiaAman Chandra KaushikDong-Qing WeiPublished in: Journal of biomolecular structure & dynamics (2023)
Monkeypox virus (MPXV) is a budding public health threat worldwide, and there lacks a personalized drug availability to treat MPXV infections. Tecovirimat, an antiviral drug against pox viruses, is recently confirmed to be effective against the MPXV in vitro using nanomolar concentrations. Therefore, the current study considers Tecovirimat as a reference compound for a machine learning-based guided screening to scan bioactive compounds from the DrugBank with similar chemical features or moieties as the Tecovirimat to inhibit the MPXV E8L surface binding protein. We used AlphaFold2 to model the E8L's 3D structure, followed by the conformational activity investigation of shortlisted drugs through computational structural biology approaches, including molecular docking and molecular dynamics simulations. As a result, we have shortlisted five drugs named ABX-1431, Alflutinib, Avacopan, Caspitant, and Darapalib that effectively engage the MPXV surface binding protein. Furthermore, the affinity of the proposed drugs is relatively higher than the Tecovirimat by having higher docking scores, establishing more hydrogen and hydrophobic bonds, engaging key residues in the target's structure, and exhibiting stable molecular dynamics.Communicated by Ramaswamy H. Sarma.
Keyphrases
- molecular dynamics simulations
- molecular docking
- molecular dynamics
- binding protein
- machine learning
- public health
- density functional theory
- drug induced
- artificial intelligence
- deep learning
- risk assessment
- big data
- adverse drug
- amino acid
- mass spectrometry
- genetic diversity
- global health
- human health
- aqueous solution