In silico modeling for quick prediction of inhibitory activity against 3CL^pro enzyme in SARS CoV diseases

Abstract

As of 2 September 2020, the 2019 novel coronavirus or SARS CoV-2 has been responsible for more than 2,56,02,665 infections and 8,52,768 deaths worldwide. There has been an urgent need of newer drug discovery to tackle the situation. Severe acute respiratory syndrome-associated coronavirus 3C-like protease (or 3CL^pro) is a potential target as anti-SARS agents as it plays a vital role in the viral life cycle. This study aims at developing a quantitative structure–activity relationship (QSAR) model against a group of 3CL^pro inhibitors to study their structural requirements for their inhibitory activity. Further, molecular docking studies were carried out which helped in the justification of the QSAR findings. Moreover, molecular dynamics simulation study was performed for selected compounds to check the stability of interactions as suggested by the docking analysis. The current QSAR model was further used in the prediction and screening of large databases within a short time.

Communicated by Ramaswamy H. Sarma

Keywords:

• SARS CoV-2
• Covid-19
• coronavirus
• in silico
• QSAR

Disclosure statement

No potential conflict of interest was reported by the authors.

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Additional information

Funding

PD thanks Indian Council of Medical Research, New Delhi, for awarding with a Senior Research Fellowship, Financial assistance from the Indian Council of Medical Research (ICMR), New Delhi in the form of a senior research fellowship (File No: 5/3/8/27/ITR-F/2018-ITR; dated: 18.05.2018) to VK is thankfully acknowledged, KR thanks SERB, Govt. of India for financial assistance under the MATRICS scheme (MTR/2019/000008). SB likes to acknowledge financial support from the Science and Engineering Research Board (SERB), India, under grant EMR/2016/002141.