Abstract

LEAD DISCOVERY OF NEW ANTIVIRAL ENTITIES THROUGH THE GENERATION OF 3D-QSAR PHARMACOPHORE HYPOTHESIS VIRTUAL SCREENING AND MOLECULAR DOCKING STUDY

Rania Sobhi*, Nahla A. Farag and Haidy Khalid

ABSTRACT

Sofosbuvir (Sovaldi) is the most successful clinically used antiviral agent targeted for the treatment of Hepatitis C. The study is aiming to discover new lead entities acting as specific inhibitors of the NS5B RNA-dependent RNA polymerase that is essential for viral replication. The recent approach of computer-aided drug design is a challenge nowadays in drug discovery. We generate a 3D-QSAR pharmacophore model from a training set of 17 nucleoside analogue inhibitors including Sofosbuvir with congeneric structures and known (IC50) for each antiviral agent. A valid 3D- QSAR pharmacophore model has been successfully generated to identify the binding features responsible for the biological activity using Discovery Studio software version The generated hypothesis is used for virtual screening of 3D databases which reveals 73 nucleoside analogues as coded compounds of expected nucleoside inhibitor antiviral activity. Followed by Molecular Docking of the compounds of highest fit values to the prepared HCV RNA dependent RNA polymerase NS5B enzyme which is downloaded from the protein data bank (4WTG) with its natural inhibitor SOFOSBUVIR DIPHOSPHATE GS-607596 to estimate the binding affinity and the geometrical orientation of the proposed compound in the HCV RNA dependent RNA polymerase NS5B binding site.

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