In silico design of potential HCV NS5B inhibitors: a comprehensive approach combining combinatorial library generation, ensemble docking, MM-GBSA calculations, QSAR model development, and molecular dynamics

Abstract

HCV is a blood-borne RNA virus that causes acute and chronic hepatitis, cirrhosis, liver failure, and hepatocellular carcinoma. In the present work, a large in silico combinatorial library was generated using the privileged substructures of existing inhibitors of the HCV NS5B protein. Next, we performed a multistep virtual screening process to identify novel HCV NS5B inhibitors. Additionally, we assessed the hit compounds' pharmacokinetic characteristics to evaluate their potential as drugs. Hit molecules with drug-like properties were classified with fingerprint-based chemical similarity clustering. Molecular dynamics simulations confirmed the stability of complexes and provided a comprehensive understanding of the molecular interactions between the novel molecule classes and HCV NS5B polymerase. The results of this study set the stage for developing new scaffolds as allosteric inhibitors of HCV NS5B protein for drug designing objectives and highlight the promising prospects of using privileged substructures for screening library construction in pharmaceutical research.

Keywords

• NS5B
• Docking
• MM-GBSA
• QSAR
• ADME
• Molecular Dynamics

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