Computer simulation in the development of vaccines against covid-19 based on the hla-system antigens

The genetic variability of population may explain different individual immune responses to the SARS-CoV-2 virus. The use of genome- and peptidome-based technologies makes it possible to develop vaccines by optimizing the target antigens. The computer modeling methodology provides the scientific comm...

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Auteurs principaux: Dmitry A. Vologzhanin, Aleksandr S. Golota, Tatyana A. Kamilova, Olga V. Shneider, Sergey G. Sсherbak
Format: article
Langue:RU
Publié: Eco-vector 2021
Sujets:
hla
R
Accès en ligne:https://doaj.org/article/4e3125fa4c5b41438ac2e30ea82b78f4
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Résumé:The genetic variability of population may explain different individual immune responses to the SARS-CoV-2 virus. The use of genome- and peptidome-based technologies makes it possible to develop vaccines by optimizing the target antigens. The computer modeling methodology provides the scientific community with a more complete list of immunogenic peptides, including a number of new and cross-reactive candidates. Studies conducted independently of each other with different approaches provide a high degree of confidence in the reproducibility of results. Most of the effort in developing vaccines and drugs against SARS-CoV-2 is directed towards the thorn glycoprotein (protein S), a major inducer of neutralizing antibodies. Several vaccines have been shown to be effective in the preclinical studies and have been tested in the clinical trials to combat the COVID-19 infection. This review presents the profile of in silico predicted immunogenic peptides of the SARS-CoV-2 virus for the subsequent functional validation and vaccine development, and highlights the current advances in the development of subunit vaccines to combat COVID-19, taking into account the experience that has been previously achieved with SARS-CoV and MERS-CoV. The immunoinformatics techniques reduce the time and cost of developing vaccines that together can stop this new viral infection.