Chemical-informatics approach to COVID-19 drug discovery: Exploration of important fragments and data mining based prediction of some hits from natural origins as main protease (Mpro) inhibitors.

ABSTRACT: As the world struggles against current global pandemic of novel coronavirus disease (COVID-19), it is challenging to trigger drug discovery efforts to search broad-spectrum antiviral agents. Thus, there is a need of strong and sustainable global collaborative works especially in terms of new and existing data analysis and sharing which will join the dots of knowledge gap. Our present chemical-informatics based data analysis approach is an attempt of application of previous activity data of SARS-CoV main protease (Mpro) inhibitors to accelerate the search of present SARS-CoV-2 Mpro inhibitors. The study design was composed of three major aspects: (1) classification QSAR based data mining of diverse SARS-CoV Mpro inhibitors, (2) identification of favourable and/or unfavourable molecular feat

SUBMITTER: Ghosh K 

PROVIDER: S-EPMC7405777 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature