Computational characterization of peptide binding stability to HLA-C allotypes and its association with HIV-1 infection progression and HIV-1 related neurocognitive impairment

Background: HLA-C molecules play a critical role in the immune response, particularly in antigen presentation and immune modulation. Methods: To investigate the effect of the most common HLA-C allotypes on the stability of the HLA-C-β-2 microglobulin-peptide complex, we used the NetMHCpan-4.2 bioinformatic tool that predicts peptide binding to MHC class I molecules. This allowed us to predict the probability of a broad set of peptides to be naturally processed, presented on each HLA-C allotype, and ultimately recognised by the immune system, measured by EL-score. By plotting the EL-score against the percentile of the peptide's stability rank position, curves were drawn to illustrate the relative stability of the binding interaction of each HLA-C allotype tested, and the area under the curve was calculated to determine a stability score for each HLA-C variant. Results: This approach permits us to greatly improve the classification of HLA-C allotypes according to their stability, overcoming the previous coarse stable and unstable binary classification. Analysis of two well-characterised HIV-1 patient cohorts, one focused on disease progression and the other on neurocognitive impairment, demonstrated a significant association between unstable HLA-C alleles, faster disease progression, and worse HIV-associated neurocognitive outcomes. Conclusions: These findings underscore the role of HLA-C stability in AIDS progression, suggesting that profiling HLA-C stability may serve as a predictive tool for HIV-1 disease management and assessing neurocognitive risk, with potential implications in personalised medicine.