IDENTIFICATION AND COMPARISON OF POSSIBLE EPITOPE – DESIGNED TARGETS USING IN-SILICO TECHNIQUES FOR CORONA VIRUS
Author(s):
M. Nithya, Dr. Horne Iona Averal
Keywords:
Coronavirus, COVID-19, SARS-CoV-2, Epitope based techniques, In- silico techniques, MHC prediction, Bioinformatics
Abstract
The SARS Coronavirus-2 (SARS-CoV-2) epidemic has become a global issue that has raised concerns for the scientific community to design and find a way to combat this deadly virus. To date, the epidemic has claimed hundreds of thousands of lives as a result of infection and spread. Growing evidence suggests that T cells may play a key role in the fight against acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Therefore, COVID-19 vaccines that can obtain a strong T cell response may be very important. The design, development and evaluation of vaccine trials help to understand the T cell epitopes of SARS-CoV-2, which is less well known. Because of the challenges of diagnosing epitopes by experimentation, many studies have suggested the use of in-silico methods. Here, we present of the in-silico methods used to predict SARS-CoV-2 T cell epitopes. These methods use a different set of technical methods, which often focus on machine learning. Functional comparisons are based on the diagnostic power of a specific set of immunogenic epitopes determined by experiments targeted T cells in recovering COVID-19 patients, highlighting the relative functional relevance of the various methods adopted by in - Silico studies. The investigation also prioritizes ideas for future research guidelines.
Article Details
Unique Paper ID: 153688

Publication Volume & Issue: Volume 8, Issue 8

Page(s): 280 - 289
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