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MOLECULAR MODELING AND VIRTUAL SCREENING FOR COMPUTER-AIDED DESIGN OF HCV NS5B POLYMERASE INHIBITORS

Jul 2026 · Universal Journal of Pharmaceutical Research · 0 citations · 52 references

TL;DR

The integration of molecular modeling and in silico screening successfully identified six potent candidate inhibitors of the HCV NS5B polymerase with favorable pharmacokinetic profiles, which represent high-affinity candidates for future therapeutic development.

Abstract

Aims and objectives: This study aims to design new inhibitors for the Hepatitis C Virus (HCV) Non-Structural Protein 5B (NS5B) polymerase, an enzyme essential for viral replication. The research addresses an urgent public health issue affecting 71 million people and causing approximately 242,000 deaths annually. Methodology: The research follows a computer-aided rational design approach. A Quantitative Structure-Activity Relationship (QSAR) model was developed using 24 quinazolinone derivatives (QDs) to correlate Gibbs free energy with experimental inhibition constants. The bound conformations of the ligands were used to construct a 3D-QSAR pharmacophore (PH4) model. A virtual library of 168,750 QDs was generated and filtered using ADME (Absorption, Distribution, Metabolism, and Excretion) criteria and PH4 screening. Conformational stability was evaluated through 200-ns molecular dynamics (MD) simulations. Binding free energy variations were quantified using the Molecular Mechanics - Generalized Born Surface Area (MM-GBSA) approach on MD trajectories, calculating molecular mechanics energy, solvation energy, and surface area contributions under the OPLS2005 force field. Results: The QSAR model showed high predictive power and the PH4 model achieved an R2 of 0.85. Screening identified 39 potent analogues. The lead candidate, 3-6-4-45, exhibited a predicted inhibitory concentration of 0.62 nM, approximately 96 times more active than the best reference ligand (60 nM). MD simulations confirmed stability with RMSD values between 1.5 and 3 Å. MM-GBSA binding energies converged with predicted complexation energies, validating the computational reliability. Conclusion: The integration of molecular modeling and in silico screening successfully identified six potent candidate inhibitors of the HCV NS5B polymerase with favorable pharmacokinetic profiles. These analogues represent high-affinity candidates for future therapeutic development.                         Peer Review History: Received 5 April 2026;   Reviewed 13 May 2026; Accepted  10 June; Available online 15 July 2026 Academic Editor: Dr. Iman Muhammad Higazy, National Research Center, Egypt, imane.higazy@hotmail.com Reviewers: Dr. Sarfaraz Ahmed, Global Institute of Pharmaceutical Education and Research, Kashipur, Uttarakhand, India, sarfarazahmed1@gmail.com  Prof. Amani S. Awaad, Prince Sattam Bin Abdulaziz University, Al-Kharj. KSA., amaniawaad@hotmail.com

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