Natural-like products as potential SARS-CoV-2 Mpro inhibitors: in-silico drug discovery. Issue 15 (2nd September 2021)

• Record Type: Journal Article
• Authors: Ibrahim, Mahmoud A. A.; Abdeljawaad, Khlood A. A.; Abdelrahman, Alaa H. M.; Hegazy, Mohamed-Elamir F.
• Is Part Of: Journal of biomolecular structure & dynamics. Volume 39:Issue 15(2021)
• Page Start: 5722
• Page End: 5734
• Publication Date: 2021-09-02
• Subjects: COVID-19 -- main protease -- natural-like product -- molecular docking -- molecular dynamics -- drug-likeness; Biomolecules -- Periodicals; Molecular structure -- Periodicals; Molecular Biology -- Periodicals; Biomechanics -- Periodicals; 572
• DOI: 10.1080/07391102.2020.1790037
• Languages: English
• ISSNs: 0739-1102

Abstract

Abstract: In December 2019, a COVID-19 epidemic was discovered in Wuhan, China, and since has disseminated around the world impacting human health for millions. Herein, in-silico drug discovery approaches have been utilized to identify potential natural products (NPs) as Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) main protease (M pro ) inhibitors. The MolPort database that contains over 100, 000 NPs was screened and filtered using molecular docking techniques. Based on calculated docking scores, the top 5, 000 NPs/natural-like products (NLPs) were selected and subjected to molecular dynamics (MD) simulations followed by molecular mechanics–generalized Born surface area (MM-GBSA) binding energy calculations. Combined 50 ns MD simulations and MM-GBSA calculations revealed nine potent NLPs with binding affinities (Δ Gbinding ) > −48.0 kcal/mol. Interestingly, among the identified NLPs, four bis([1, 3]dioxolo)pyran-5-carboxamide derivatives showed Δ Gbinding > −56.0 kcal/mol, forming essential short hydrogen bonds with HIS163 and GLY143 amino acids via dioxolane oxygen atoms. Structural and energetic analyses over 50 ns MD simulation demonstrated NLP-M pro complex stability. Drug-likeness predictions revealed the prospects of the identified NLPs as potential drug candidates. The findings are expected to provide a novel contribution to the field of COVID-19 drug discovery. Communicated by Ramaswamy H. Sarma Abstract : UF0001