Individual genetic variation may help to explain different immune responses to a coronavirus SARS-CoV-2 across a population. The in silico computer simulation methodology provides the experimental community with a more complete list of SARS-CoV-2 immunogenic peptides presented by the antigens of the HLA system. This review considers an array of computationally predicted immunogenic peptides from SARS-CoV-2 for in vitro functional validation and potential vaccine developments. Several independent studies conducted with different approaches showed a high degree of confidence and reproducibility of the results. Computer-assisted prediction is instrumental for a quick and cost-effective solution to prevent the spread and ultimately eliminate the infection. Most efforts to develop vaccines and drugs against SARS-CoV-2 target the spike glycoprotein (protein S), the major inducer of neutralizing antibodies. Several candidates have been shown to be effective in in vitro studies and have progressed to randomized trials in animals or humans against COVID-19 infection. This article highlights current advances in the development of subunit vaccines to combat COVID-19 that are reducing the time and costs of vaccine development.
|Translated title of the contribution|| ИММУНОИНФОРМАТИКА СИСТЕМЫ HLA И РАЗРАБОТКА НОВЫХ ВАКЦИН ПРОТИВ SARS-COV-2|
|Journal||Cellular Therapy and Transplantation|
|State||Published - 2021|
- IMMUNOGENIC PEPTIDES
- COMPUTATIONAL PREDICTION
- COMPUTER SIMULATION IN SILICO