Immunoinformatics mapping of potential epitopes in SARS-CoV-2 structural proteins

Author:

Devi Yengkhom Damayanti,Goswami Himanshu Ballav,Konwar Sushmita,Doley Chandrima,Dolley Anutee,Devi Arpita,Chongtham Chen,Dowerah Dikshita,Biswa Vashkar,Jamir Latonglila,Kumar AdityaORCID,Satapathy Siddhartha Shankar,Ray Suvendra Kumar,Deka Ramesh Chandra,Doley Robin,Mandal Manabendra,Das Sandeep,Singh Chongtham Shyamsunder,Borah Partha Pratim,Nath Pabitra,Namsa Nima D.ORCID

Abstract

All approved coronavirus disease 2019 (COVID-19) vaccines in current use are safe, effective, and reduce the risk of severe illness. Although data on the immunological presentation of patients with COVID-19 is limited, increasing experimental evidence supports the significant contribution of B and T cells towards the resolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Despite the availability of several COVID-19 vaccines with high efficacy, more effective vaccines are still needed to protect against the new variants of SARS-CoV-2. Employing a comprehensive immunoinformatic prediction algorithm and leveraging the genetic closeness with SARS-CoV, we have predicted potential immune epitopes in the structural proteins of SARS-CoV-2. The S and N proteins of SARS-CoV-2 and SARS-CoVs are main targets of antibody detection and have motivated us to design four multi-epitope vaccines which were based on our predicted B- and T-cell epitopes of SARS-CoV-2 structural proteins. The cardinal epitopes selected for the vaccine constructs are predicted to possess antigenic, non-allergenic, and cytokine-inducing properties. Additionally, some of the predicted epitopes have been experimentally validated in published papers. Furthermore, we used the C-ImmSim server to predict effective immune responses induced by the epitope-based vaccines. Taken together, the immune epitopes predicted in this study provide a platform for future experimental validations which may facilitate the development of effective vaccine candidates and epitope-based serological diagnostic assays.

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

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