COMPUTATIONAL STUDIES OF THE NUCLEOCAPSID PROTEIN OF HUMAN IMMUNODEFICIENCY VIRUS-1 TO FIND A POTENT INHIBITOR

Objective: Viruses are obligate intracellular parasites of the host cellular mechanism. Their life cycle is dependent on the host. Human immunodeficiencyvirus (HIV) is a retrovirus which is considered a threat to humanity and a potential bioweapon. These studies have been conducted to make a potentinhibitor of this virus, but the rate of success is a very low as the virus is prone to mutations. The objective of this study is to find a potent inhibitormolecule for the protein nucleocapsid (NC) of HIV.Methods: Computational studies like docking play a major role in finding the protein-ligand interactions. In this study, the crystal structure of theprotein NC was subjected to high-throughput screening (HTS) against ZINC database to find potential inhibitors of the protein. The selected ligandswere then screened for toxicity using OSIRIS property calculator and Molinspiration. Docking was performed using AutoDock Vina.Results: HTS analysis provided top 200 hits from the clean fragment subset of ZINC database, out of which best 10 were chosen. These molecules werethen screened for toxicity and violations of Lipinski's rule of 5. A total of five molecules had no toxic effects and best drug scores. These five compoundswere the selected for docking analysis and it was found that the ligand benzene-1, 2-disulfonamide†had the best binding affinity and interacted withcrucial residues of the active site.Conclusion: From the AutoDock Vina studies, the best pose was obtained with least energy value from which it can be hypothesized that the compoundbenzene-1, 2-disulfonamide†can be considered as a potential inhibitor of the protein NC. Furthermore, wet lab studies have to be performed to findits efficiency and off-target activity.Keywords: Human immunodeficiency virus-1, Nucleocapsid protein, Psi region, Stem-loop 3, High-throughput screening

Applying synthetic biology and computational biology to advance biologics expression platforms

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