Computational discovery and evaluation of hepatitis C virus NS5B inhibitors: combining structure-based design, QSAR, molecular docking, and molecular dynamics

Abstract

Abstract Hepatitis C virus (HCV) infection is a global health burden affecting approximately 170 million people, necessitating the development of potent inhibitors for the NS5B RNA-dependent RNA polymerase. In this study, 20 newly synthesized bisamide derivatives were evaluated using a multi-stage computational workflow. Structural optimizations were performed using Density Functional Theory (DFT) at the B3LYP/6-31G* level. Quantitative Structure-Activity Relationship (QSAR) modeling via Genetic Function Approximation (GFA) yielded a statistically robust model (R2 = 0.9515, R2adj = 0.9273, Q2 = 0.8881, and R2test = 0.6872), with its reliability confirmed through applicability domain analysis. Molecular docking against the NS5B polymerase receptor (PDB ID: 3QFK) identified compound 3 as the most potent lead with a MolDock score of −174.522 kcal/mol. Pharmacokinetic assessment demonstrated that compound 3 adheres to Lipinski’s rules, exhibiting a favorable drug-likeness profile. Using compound 3 as a template, the novel derivative SAD3 was designed, showing enhanced binding efficiency compared to existing standard therapies. The dynamic stability of these complexes was validated through 100 ns Molecular Dynamics (MD) simulations, where compound 3 and SAD3 exhibited average RMSD values of 1.90 Å and 1.87 Å, respectively, demonstrating structural integrity comparable to Ribavirin (1.64 Å). Furthermore, RMSF analysis highlighted minimal fluctuations in key catalytic residues, confirming a stable binding interface. These findings identify compound 3 and its derivative SAD3 as highly promising candidates for future anti-HCV drug development.