Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis.

ABSTRACT: Due to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure-Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against the main protease (Mpro) of SARS-CoV-2. The QSAR analysis developed on multivariate GA-MLR (Genetic Algorithm-Multilinear Regression) model with acceptable statistical performance (R² = 0.898, Q²loo = 0.859, etc.). QSAR analysis attributed the good correlation with different types of atoms like non-ring Carbons and Nitrogens, amide Nitrogen, sp²-hybridized Carbons, etc. Thus, the QSAR model has a good balance of qualitative and quantitative requirements (balance

SUBMITTER: Zaki MEA 

PROVIDER: S-EPMC8070011 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature