Machine learning reveals a non‐canonical mode of peptide binding to MHC class II molecules

Abstract

MHC class II molecules play a fundamental role in the cellular immune system: they load short peptide fragments derived from extracellular proteins and present them on the cell surface. It is currently thought that the peptide binds lying more or less flat in the MHC groove, with a fixed distance of nine amino acids between the first and last residue in contact with the MHCII. While confirming that the great majority of peptides bind to the MHC using this canonical mode, we report evidence for an alternative, less common mode of interaction. A fraction of observed ligands were shown to have an unconventional spacing of the anchor residues that directly interact with the MHC, which could only be accommodated to the canonical MHC motif either by imposing a more stretched out peptide backbone (an 8mer core) or by the peptide bulging out of the MHC groove (a 10mer core). We estimated that on average 2% of peptides bind with a core deletion, and 0·45% with a core insertion, but the frequency of such non-canonical cores was as high as 10% for certain MHCII molecules. A mutational analysis and experimental validation of a number of these anomalous ligands demonstrated that they could only fit to their MHC binding motif with a non-canonical binding core of length different from nine. This previously undescribed mode of peptide binding to MHCII molecules gives a more complete picture of peptide presentation by MHCII and allows us to model more accurately this event.

Predicting Antigen Presentation—What Could We Learn From a Million Peptides?

“…Considering the increasingly higher quality and throughput of class II HLA peptidomics data ( 15 , 21 , 86 , 138 , 139 ), we anticipate that analysis of HLA-II peptidomes will further enable researchers to investigate new properties of HLA-II molecules. For instance, it will be interesting to see whether the presence of bulging class II ligands, as recently reported from an analysis of in vitro binding data ( 163 ), can be confirmed in large-scale unbiased MS data.…”

Footprints of antigen processing boost MHC class II natural ligand predictions

“…This attribute facilitates peptide protrusion out of the groove, thereby allowing longer peptides (and potentially whole proteins) to be loaded onto MHC-II molecules [ 2 , 3 ]. Peptide binding to MHC-II is mainly determined by interactions within the peptide binding groove, which most commonly encompass a peptide with a consecutive stretch of nine amino acids [ 4 ]. Ligand residues protruding from either side of the MHC binding groove are commonly known as peptide flanking regions (PFRs).…”

New tools for MHC research from machine learning and predictive algorithms to the tumour immunopeptidome

“…The authors define a terminology for these hotspots and conduct a systematic analysis of in silico predicted hotspots and those derived from mass spectrometry, reiterating that hotspots defined from mass spectrometry data Although any such predictions start from the notion of defined anchor residues binding to defined MHC pockets, some peptides show unconventional spacing of anchor residues to enable interaction with MHC. 8 A recent study by Andreatta et al 8 argues that such examples involve either stretching of the peptide backbone, or bulging out of the peptide from the MHC groove (a 10mer core). This is an important caveat: the frequency of these noncanonical binding cores can reach 10% for some MHC class II alleles.…”

“…Although any such predictions start from the notion of defined anchor residues binding to defined MHC pockets, some peptides show unconventional spacing of anchor residues to enable interaction with MHC . A recent study by Andreatta et al . argues that such examples involve either stretching of the peptide backbone, or bulging out of the peptide from the MHC groove (a 10mer core).…”