Kabra, R and Singh, S (2021) Evolutionary Artificial Intelligence Based Peptide Discoveries for Effective Covid-19 Therapeutics. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease, 1867 (1). p. 165978.

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Abstract

An epidemic caused by COVID-19 in China turned into pandemic within a short duration affecting countries worldwide. Researchers and companies around the world are working on all the possible strategies to develop a curative or preventive strategy for the same, which includes vaccine development, drug repurposing, plasma therapy, and drug discovery based on Artificial intelligence. Therapeutic approaches based on Computational biology and Machine-learning algorithms are specially considered, with a view that these could provide a fast and accurate outcome in the present scenario. As an effort towards developing possible therapeutics for COVID-19, we have used machine-learning algorithms for the generation of alignment kernels from diverse viral sequences of Covid-19 reported from India, China, Italy and USA. Using these diverse sequences we have identified the conserved motifs and subsequently a peptide library was designed against them. Of these, 4 peptides have shown strong binding affinity against the main protease of SARS-CoV-2 (Mpro) and also maintained their stability and specificity under physiological conditions as observed through MD Simulations. Our data suggest that these evolutionary peptides against COVID-19 if found effective may provide cross-protection against diverse Covid-19 variants.

Item Type:	Article
Subjects:	Bioinformatics and Proteomics
Depositing User:	Mr. Rameshwar Nema
Date Deposited:	07 Feb 2021 13:27
Last Modified:	07 Feb 2021 13:27
URI:	http://nccs.sciencecentral.in/id/eprint/898

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