Computational discovery of novel human rhinovirus 3 C protease inhibitors: molecular docking, dynamic simulations, free energy landscape, MMPBSA and ADMET analysis.

Abstract

Human rhinoviruses (HRVs) are major causative agents of the common cold and are strongly associated with asthma exacerbation, highlighting the need for effective antivirals. Because the viral 3 C protease (3Cpro) is essential for polyprotein processing and is highly conserved among HRV species, it represents an attractive therapeutic target. In this study, we performed structure-based virtual screening of 49,437 compounds against HRV-C 3Cpro using AutoDock Vina, followed by ADMET-based prioritization of the top hits. Docking analysis identified two lead compounds that favorably occupied the catalytic pocket and formed stabilizing interactions with key residues, including His40, Glu71, and Cys147, in comparison with the reference inhibitor rupintrivir. In 200-ns molecular dynamics simulations, both compounds stabilized the protease relative to the apo form, with compound 1 showing the lowest protein RMSD (1.21 ± 0.22 Å) and compound 2 producing the lowest Cys147 RMSF (0.48 Å). Both ligands also displayed lower ligand RMSD values than rupintrivir (compound 1: 1.49 ± 0.78 Å; compound 2: 2.01 ± 0.39 Å; rupintrivir: 4.83 ± 0.89 Å), indicating more persistent binding within the active site. MM/PBSA analysis further supported stronger effective binding for compound 1 (-23.59 ± 6.87 kcal/mol) and compound 2 (-25.25 ± 5.75 kcal/mol) than for rupintrivir (-19.43 ± 4.46 kcal/mol). Taken together, these results identify compounds 1 and 2 as promising non-covalent HRV 3Cpro inhibitor candidates for further experimental validation.