Characterization of binding affinity changes of SARS-CoV-2 omicron variant peptides to population-specific HLA
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| Publicado en: | Journal of Biomedical Science vol. 32 (2025), p. 1 |
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| Otros Autores: | , , , , , |
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Springer Nature B.V.
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| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
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| 022 | |a 1021-7770 | ||
| 022 | |a 1423-0127 | ||
| 024 | 7 | |a 10.1186/s12929-025-01139-5 |2 doi | |
| 035 | |a 3201879259 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 113325 |2 nlm | ||
| 100 | 1 | |a Che-Mai, Chang | |
| 245 | 1 | |a Characterization of binding affinity changes of SARS-CoV-2 omicron variant peptides to population-specific HLA | |
| 260 | |b Springer Nature B.V. |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a BackgroundThe evolution of SARS-CoV-2, particularly through new variants, presents significant global health challenges due to their potential for immune evasion and reduced vaccine effectiveness. This study aims to investigate the impact of mutations in the Spike protein of Omicron EG.5 and XBB.1.16 variants on the binding affinities of viral peptides to common human leukocyte antigen (HLA) class I and II alleles across Taiwanese, British, and Russian populations. Understanding these interactions is crucial for elucidating differences in immune responses and disease severity among diverse populations.MethodsWe updated the T-CoV portal to incorporate and analyze EG.5 and XBB.1.16 variants. Binding affinities between mutated Spike protein peptides and HLA class I and II alleles were predicted and compared across the three populations. Statistical analyses, including chi-squared tests, were conducted to assess the significance of binding affinity differences across the three populations and between HLA classes.ResultsOur findings revealed that mutations in the Spike protein had a more pronounced effect on HLA class II binding affinities than on HLA class I. While binding affinity profiles for HLA class I were largely consistent across populations, significant population-specific variations were observed for HLA class II alleles. Specifically, the British population exhibited lower proportions of tightly binding mutated peptides compared to the Taiwanese and Russian populations. Furthermore, substantial differences were identified in the binding affinity changes of mutated Spike peptides for HLA class II across Taiwanese, British, and Russian populations, as well as between the Omicron EG.5 and XBB.1.16 variants. Subsequent analyses revealed significant differences in the conservation and evolutionary trajectories of binding affinities between mutated Spike peptides and common HLA class II alleles, both between the EG.5 and XBB.1.16 variants and across the three populations for the XBB.1.16 variant.ConclusionsIn summary, Spike protein mutations in SARS-CoV-2 variants significantly influence immune responses by altering HLA-peptide interactions, with pronounced population-specific effects on HLA class II alleles. These findings underscore the critical role of HLA class II diversity in shaping immune responses and susceptibility to COVID-19. Integrating population-specific HLA profiles into vaccine development and public health strategies is essential for improving interventions against evolving SARS-CoV-2 variants. | |
| 653 | |a Public health | ||
| 653 | |a Evolution | ||
| 653 | |a Vaccines | ||
| 653 | |a Binding | ||
| 653 | |a Severe acute respiratory syndrome coronavirus 2 | ||
| 653 | |a Mutation | ||
| 653 | |a Peptides | ||
| 653 | |a Alleles | ||
| 653 | |a Genomes | ||
| 653 | |a COVID-19 | ||
| 653 | |a Viral diseases | ||
| 653 | |a Statistical analysis | ||
| 653 | |a Chi-square test | ||
| 653 | |a Proteins | ||
| 653 | |a Immune response | ||
| 653 | |a Vaccine development | ||
| 653 | |a Vaccine efficacy | ||
| 653 | |a Antigen presentation | ||
| 653 | |a Population genetics | ||
| 653 | |a Affinity | ||
| 653 | |a Populations | ||
| 653 | |a Pandemics | ||
| 653 | |a Histocompatibility antigen HLA | ||
| 653 | |a Spike protein | ||
| 653 | |a Global health | ||
| 653 | |a Social | ||
| 700 | 1 | |a Chang-Jiun Wu | |
| 700 | 1 | |a Shkurnikov, Maxim | |
| 700 | 1 | |a Chin-Lin, Guo | |
| 700 | 1 | |a Wan-Chen, Huang | |
| 700 | 1 | |a Tonevitsky, Alexander | |
| 700 | 1 | |a Wei-Chiao, Chang | |
| 773 | 0 | |t Journal of Biomedical Science |g vol. 32 (2025), p. 1 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3201879259/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3201879259/fulltext/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3201879259/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch |