An essential element of adaptive immunity is the selective binding of peptide antigens by major histocompatibility complex (MHC) class I proteins and their presentation to cytotoxic T lymphocytes on the cell surface. Using native mass spectrometry, we here analyze the binding of peptides to an empty disulfide-stabilized HLA-A*02:01 molecule. This novel approach allows us to examine the binding properties of diverse peptides. The unique stability of our MHC class I even enables us to determine the binding affinity of complexes, which are suboptimally loaded with truncated or charge-reduced peptides. Notably, a unique erucamide adduct decouples affinity analysis from peptide identity alleviating issues usually attributed to clustering. We discovered that two anchor positions at the binding surface between MHC and peptide can be stabilized independently and further analyze the contribution of other peptidic amino acids on the binding. We propose this as an alternative, likely universally applicable method to artificial prediction tools to estimate the binding strength of peptides to MHC class I complexes quickly and efficiently. This newly described MHC class I-peptide binding affinity quantitation represents a much needed orthogonal, confirmatory approach to existing computational affinity predictions and has the potential to eliminate binding affinity biases and thus accelerate drug discovery in infectious diseases autoimmunity, vaccine design, and cancer immunotherapy.
NetMHCpan-4.0: Improved Peptide–MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data
