Editor-in-Chief Hatice Kübra Elçioğlu Vice Editors Levent Kabasakal Esra Tatar Online ISSN 2630-6344 Publisher Marmara University Frequency Bimonthly (Six issues / year) Abbreviation J.Res.Pharm. Former Name Marmara Pharmaceutical Journal
Journal of Research in Pharmacy 2023 , Vol 27 , Issue Supp.
DISCOVERY OF NOVEL HCV NS5B POLYMERASE INHIBITORS BY IN SILICO APPROACHES
Berin KARAMAN MAYACK1
1Department of Pharmacology, School of Medicine, University of California Davis, Davis, CA 95616, USA
2Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Istanbul University, Istanbul, Türkiye
DOI : 10.29228/jrp.456 Hepatitis C Virus (HCV) is a blood-borne RNA virus that causes inflammation of the liver that can lead to liver cirrhosis and hepatocellular carcinoma [1]. Non-structural protein 5B (NS5B) is an essential component of HCV for viral transcription and genome replication [2]. As there is no close mammalian analog for this enzyme, it has been the focus of many drug discovery projects [3]. In the present work, a combination of different computer-aided drug design approaches such as ensemble docking, binding free energy calculations, and quantitative structure-activity relationship (QSAR) model generation was applied to identify novel inhibitors of NS5B.

In the first step, all available protein structures in Protein Data Bank in a complex with thumb site 2 inhibitors were collected. Then, an automated KNIME [4] workflow was generated to select a few representative structures of the conformational changes in the binding pocket upon ligand binding. In total eight NS5B-inhibitor complexes were selected for further in silico work. Next, a virtual combinatorial library was obtained using the privileged substructures of known NS5B inhibitors. Different congeneric series of compounds including phenylalanine derivatives, thiophene-2-carboxylic acid derivatives, and anthranilic acid derivatives were used for the database formation. Upon ligand preparation, over 182.000 molecules were built. Consequently, known thumb site 2 inhibitors were docked with GLIDE-SP [5-7] and rescored with Prime MM-GBSA [8,9] protocol implemented in Schrödinger software to estimate the docking and binding free energy scores that will be used as a threshold for filtering the newly produced combinatorial library. In addition, categorical and numerical QSAR models were generated based on the known thumb site 2 inhibitors and used in the post-filtering step. Compounds that were predicted as actives will be visually analyzed and selected further for synthesis and biological evaluation. Keywords : HCV, NS5B, ensemble docking, MM-GBSA, QSAR

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