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http://dx.doi.org/10.5808/GI.2020.18.4.e43

Druggability for COVID-19: in silico discovery of potential drug compounds against nucleocapsid (N) protein of SARS-CoV-2  

Ray, Manisha (All India Institute of Medical Sciences)
Sarkar, Saurav (All India Institute of Medical Sciences)
Rath, Surya Narayan (Department of Bioinformatics, Odisha University of Agriculture and Technology)
Abstract
The coronavirus disease 2019 is a contagious disease and had caused havoc throughout the world by creating widespread mortality and morbidity. The unavailability of vaccines and proper antiviral drugs encourages the researchers to identify potential antiviral drugs to be used against the virus. The presence of RNA binding domain in the nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could be a potential drug target, which serves multiple critical functions during the viral life cycle, especially the viral replication. Since vaccine development might take some time, the identification of a drug compound targeting viral replication might offer a solution for treatment. The study analyzed the phylogenetic relationship of N protein sequence divergence with other 49 coronavirus species and also identified the conserved regions according to protein families through conserved domain search. Good structural binding affinities of a few natural and/or synthetic phytocompounds or drugs against N protein were determined using the molecular docking approaches. The analyzed compounds presented the higher numbers of hydrogen bonds of selected chemicals supporting the drug-ability of these compounds. Among them, the established antiviral drug glycyrrhizic acid and the phytochemical theaflavin can be considered as possible drug compounds against target N protein of SARS-CoV-2 as they showed lower binding affinities. The findings of this study might lead to the development of a drug for the SARS-CoV-2 mediated disease and offer solution to treatment of SARS-CoV-2 infection.
Keywords
COVID-19; molecular docking; molecular modeling; nucleocapsid protein; SARS-CoV-2;
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