In Silico Identification of Potent SARS-CoV-2 RdRp Inhibitors: DFT and Molecular Docking Analysis of Acylated Glucopyranoside Derivatives

Abstract

Severe acute respiratory syndrome (SARS) is a global health threat caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), highlighting the urgent need for the development of new therapeutic agents. This study involves a computational investigation of the design and assessment of several methyl α-D-glucopyranoside (MDG) derivatives as potential inhibitors of the SARS-CoV-2 RdRp chain. MDG derivatives 2-5 were optimized through quantum mechanical methods, and their therapeutic potential properties against SARS-CoV-2 was evaluated through a comprehensive in silico approach. Thermodynamic properties and frontier molecular orbital (FMO) studies were utilized to characterize the chemical stability and reactivity. Molecular electrostatic potential (MEP) and natural bond orbital (NBO) charge analyses revealed the reactive electrophilic and nucleophilic sites within the derivatives. Molecular docking was employed to predict the binding affinities and interaction profiles of the SARS-CoV-2 RdRp chain targets (PDB ID: 6M71). Molecular docking simulations indicated that compound 2, with its long aliphatic chains, exhibited the highest binding affinity, with a docking score of -7.1. The strong hydrogen bonding interactions with LYS47 and HIS133 and one hydrophobic contact with ALA130 (5.20 A), a key residue involved in active site accessibility, contributed to the high binding affinity of compound 2. Additionally, LYS47 formed strong hydrogen bonds with the derivative. ADMET predictions suggested that the derivatives generally possess a favorable safety profile, with low genotoxicity and neurotoxicity. Overall, these results demonstrate the promise of modified MDG derivatives as lead compounds and justify further in vitro and in vivo studies to validate their antiviral activity against SARS-CoV-2.

The Chittagong Univ. J. Sci. 46(1): 137-163, 2025