Immunoinformatic Evaluation of the Cross-presentation of Donor Major Histocompatibility Derived Epitopes by Recipient Major Histocompatibility Class I Molecules in Transplantation Rejection

Aim: The aim of this study was to analyze the cross-presentation of allopeptides derived from donor major histocompatibility (MHC) molecules by recipient class I MHC molecules in the context of transplantation rejection.Materials and Methods: The MHC molecules were selected based on frequency distribution in the Kerala (India) population using the "allelefrequency. net" database. The most frequent alleles were chosen as donor and recipient alleles. Different immunoinformatics servers such as Netcytotoxic T lymphocyte, NetMHCpan, and Immune Epitope Database MHC I were used for predicting potential T-cell epitopes, and MHC class I epitopes, respectively, from the chosen donor MHC molecule. Three peptides with strong binding affinities in all three predictions were selected for further analysis. The binding of these peptides to the second MHC class I molecule, the recipient one, and transporter associated with antigen processing protein was confirmed by molecular docking using the "AutoDockVina" tool. The binding interactions were visualized using the "Discovery Studio Visualizer" platform.Results: The ability of the selected class I MHC molecule, human leukocyte antigens (HLAs)-A* 11:01, considered the donor allele, to act as an exogenous antigen and to get processed into peptides and presented on the second class I MHC molecule, HLA-A*02:01, considered the recipient allele was confirmed. This immunoinformatics approach could help us to identify potential epitopes from an HLA class I molecule and to measure its ability to get cross-presented on a second HLA class I molecule to trigger the process of cell-mediated rejection.Conclusion: This immunoinformatics approach could help us to identify potential epitopes from an HLA class I molecule and to measure its ability to get cross-presented on a second HLA class I molecule to trigger the process of cell-mediated rejection. Our study provides an easy in silico method for predicting the chances of cell mediated rejection in organ transplantations involving an unrelated donor. We hope that this computational analysis will pave the way for simplifying the process involved in organ rejection prediction.