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Recognizing Significant Motifs of Corona Virus Spike Proteins using Computational Approaches

Publication Type : Conference Paper

Publisher : IEEE

Source : 2021 2nd Global Conference for Advancement in Technology, GCAT 2021

Url : https://ieeexplore.ieee.org/abstract/document/9587841

Campus : Amritapuri

School : School of Computing

Center : Computational Bioscience

Year : 2021

Abstract : The different mutated variants of Corona Virus (SARS-CoV-2), affected a large percentage of the world population so far. On this light, any study on understanding the virus’s immunity to vaccines and medicines has greater relevance. Studies on Angiotensin-converting enzyme 2 (ACE2), the main entry receptor for the SARS-COV-2 S protein is significantly important in understanding SARS-COV-2 infection in host cells. The functional implications of various motifs found in the spike glycoprotein and its conformational changes had been studied previously to better understand the pathogenesis. The computational study, described herein, have focused on the disease transmission mechanisms of the virus especially on the receptor recognition mechanisms during viral infection. This study used different computational techniques to identify significant motif of the SARS-CoV-2 S Glycoprotein. Different corona viral genomes were compared against the reference genome (Wuhan seafood market isolate) and the possible intermediate hosts of the virus has been proposed based on the similarity in the motifs which are critical for viral infections. Previous studies on S protein motifs of proteolytic cleavage site are revisited here using computational techniques to suggest the possible intermediate hosts of infection.

Cite this Research Publication : Nair, M., Anusree, P. R., & Babu, A. (2021). Recognizing significant motifs of corona virus spike proteins using computational approaches. Paper presented at the 2021 2nd Global Conference for Advancement in Technology, GCAT 2021, doi:10.1109/GCAT52182.2021.9587841

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