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Adithya Acharya
School of Biotechnology and Bioinformatics, Maharashtra, India

A computational approach for the identification of potential drug  library molecule against SARS-CoV-2 (COVID-19) main protease 

The pandemic caused by novel coronavirus disease 2019 (COVID-19) infecting millions of  populations and after WHO has declared the COVID-19 a pandemic the need for finding a  potential drug candidate is the need of the hour. Since the protein ID for main protease is  available so our work is designing a potential drug library against the protease but till now no final candidate is available for the management and currently only symptomatic treatment is carried out for the disease. The crystal structure of SARS COVID-19 main protease with the  PDB ID 6WTT is available in protein data bank. We are trying to identify the binding site and  are planning to design a library of compounds with reference to the test set which are currently  used for the symptomatic treatment. The virtual library will be docked against the main protein  by software like Autodock Vina and IGem Dock to see the binding efficiency of the potential  candidates and to find the lead candidate. By designing a virtual library we are planning to  identify whether we can get a potential candidate which may block the binding site and become  effective against SARS-Cov-2 (COVID-19).