Shiny Pravallikan Karukutla and Krupanidhi Sreerama*

Department of Biotechnology, Vignan’s Foundation for Science, Technology and Research, India

*Corresponding Author: Krupanidhi Sreerama, Department of Biotechnology, Vignan’s Foundation for Science, Technology and Research, India.

Received: July 09, 2021; Published: July 29, 2021

Abstract

SARS-CoV-2 infection became pandemic and public concern due to the outbreak of COVID-19. Since its appearance in Wuhan, China in December 2019 the infection spread across continents. Substantial numbers of global population were disrupted both in their health and family structure. The spike protein is found to be the key protein of coronavirus as it anchors to human alveolar epithelial cells. Hence, the present study is focused on immune informatics analysis of spike glycoprotein (S-protein) of SARS-CoV-2 to explore MHC binding potential of its epitopes. Out of 5058 peptides, each with nine residues obtained through NetMHCpan version 4.1b, six peptides were predicted as epitopes with strong binding potential to HLA-A*02:01, whose distribution is ~33.8% among Indian Asians. Among these six peptides, the amino acid sequence starting from 417^th position namely KIADYNYKL was found to be highly probable antigen with a value of 1.6639 derived through VaxiJen V2.0. Peptides predicted in the receptor binding region also revealed that the aforementioned peptide ranked as the strong binder to HLA-A*02:01. The secondary structure prediction of RBD performed through Phyre2 revealed that these peptide residues spanned to stretch in beta strand followed by random coil and reported as immunodominant region using Immunome Browser tool. This study would pave the path to understand the prevalent Delta Plus variant of CoV2 (K417N) and facilitates to design a recombinant vaccine.

Keywords: HLA-A02:01; Spike Protein; SARS CoV2; Delta Plus Variant

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Citation

Citation: Shiny Pravallikan Karukutla and Krupanidhi Sreerama. “MHC Binding Potential of RBD Domain in Spike Protein of SARS CoV2”. Acta Scientific Computer Sciences 2.5 (2021): 22-25.

Copyright

Copyright: © 2021 Shiny Pravallikan Karukutla and Krupanidhi Sreerama. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.