In Silico Design of Novel Sulfonamide Derivatives as Hepatitis B Virus Polymerase Inhibitors Using Molecular Docking, 3D-QSAR, and ADMET Analysis

Hepatitis B virus (HBV) infection remains a major global health burden, underscoring the urgent need for new and effective antiviral agents. HBV polymerase is a key therapeutic target because it is essential for viral replication. In this study, 40 sulfonamide derivatives were investigated as potential inhibitors of HBV polymerase using an integrated in silico drug design approach combining molecular docking, 3D-QSAR modeling, and ADMET prediction. Molecular docking studies were performed to evaluate the binding affinity and interaction modes of compounds within the active site of HBV polymerase. The results demonstrated favorable binding modes, characterized by strong hydrogen bonds and hydrophobic interactions with key residues involved in enzymatic function. The developed 3D-QSAR model showed high statistical reliability, with a coefficient of determination (R²) of 0.92 for the training set and a cross-validated coefficient (Q²) of 0.63, along with good external predictive ability for the test set (Q² = 0.80), indicating robust predictive performance. Analysis of the contour maps identified critical steric and electrostatic features governing biological activity, providing valuable insights for rational molecular optimization. Based on these findings, ten new compounds were proposed. These results highlight the effectiveness of integrating 3D-QSAR modeling with molecular docking to identify, design, and optimize potent HBV polymerase inhibitors.