Publication Type : Conference Paper
Publisher : Springer
Source : Emerging Technologies in Data Mining and Information Security, 2022
Url : https://link.springer.com/chapter/10.1007/978-981-19-4676-9_56
Campus : Amritapuri
School : School of Computing
Year : 2022
Abstract : The greatest threat the world currently faces is due to the COVID-19 pandemic and its adverse effects. This in turn has obtained greater support in research and study on this field with the aim of a better tomorrow. Due to the large-scale spread of COVID-19 which in turn caused high possibility of mutations in this virus prompted us to conduct a study on the spike glycoprotein sequence of this highly debated organism. This study is conducted on two aspects: first on the spike glycoprotein sequences of coronaviruses infecting animals based on association with humans and the second on variants of SARS-CoV-2 based on geographic location of the sequences collected. Coronavirus is considered to be originated in bats and reached humans through unknown sources. We extend this possibility by conducting studies on the spike glycoprotein of coronaviruses that infect animals having some association with humans directly or indirectly as well as to provide better insights into the different mutations that had occurred to the SARS-CoV-2 as it spread through countries. The most similar organisms sharing a significant motif “KRSFIEDLLFNKV” of spike glycoprotein in our study are coronaviruses found in bats and cat. From the current study of mutations in the surface glycoprotein domain of SARS-CoV-2 observed in samples collected from 15 different countries, the amino acid present at 613th position was found to have the most stable mutation. The computational study detailed here provides better insights to the possible origins and transmission of SARS-CoV-2 viruses.
Cite this Research Publication : A Sha, M Nair, "Study of Spike Glycoprotein Motifs in Coronavirus Infecting Animals and Variants of SARS-CoV-2 Observed in Humans Across Countries", Emerging Technologies in Data Mining and Information Security, 2022