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An In Silico Approach for Identification of Inhibitors as a Potential Therapeutics Targeting SARS-Cov-2 Protease
SARS-CoV-2 caused COVID-19 which is pandemic and is a global health emergency. Protease is the drug target for corona viruses and this enzyme processes the production of polyproteins from the viral RNA. Objective of this study is to find the inhibitors against SARS-Cov-2 protease. AutoDock 4.2 was used for docking calculations. To check different molecules, test ligands like lopinavir, ritonavir (retroviral drugs) and hydroxychloroquine (anti-malarial drug) were docked against our target enzyme protease retrieved from Protein Data Bank. With respect to docking free binding energy, it is revealed that, Hydroxychloroquine has the lowest binding energy followed by Ritonavir and Lopinavir binds significantly to target enzyme protease. The results of this study provide a solid base for the use of Hydroxychloroquine against COVID-19 treatment. The interactions from structural models at the protease active site of virus can offer a valuable guide for more strategies for structure-based medications and the development of more operative inhibitors of SARS-CoV-2 protease.
Keywords
COVID-19, Hydroxychloroquine, In Silico, Lopinavir, Ritonavir, SARS-Cov-2i Protease.
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