{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T06:21:54Z","timestamp":1772173314792,"version":"3.50.1"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1012380","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T00:00:00Z","timestamp":1726185600000}}],"reference-count":56,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2024,9,3]],"date-time":"2024-09-03T00:00:00Z","timestamp":1725321600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["SFB 1310"],"award-info":[{"award-number":["SFB 1310"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000875","name":"Pew Charitable Trusts","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000875","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014276","name":"Pershing Square Sohn Cancer Research Alliance","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100014276","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Molecules of the Major Histocompatibility Complex (MHC) present short protein fragments on the cell surface, an important step in T cell immune recognition. MHC-I molecules process peptides from intracellular proteins; MHC-II molecules act in antigen-presenting cells and present peptides derived from extracellular proteins. Here we show that the sequence-dependent energy landscapes of MHC-peptide binding encode class-specific nonlinearities (epistasis). MHC-I has a smooth landscape with global epistasis; the binding energy is a simple deformation of an underlying linear trait. This form of epistasis enhances the discrimination between strong-binding peptides. In contrast, MHC-II has a rugged landscape with idiosyncratic epistasis: binding depends on detailed amino acid combinations at multiple positions of the peptide sequence. The form of epistasis affects the learning of energy landscapes from training data. For MHC-I, a low-complexity problem, we derive a simple matrix model of binding energies that outperforms current models trained by machine learning. For MHC-II, higher complexity prevents learning by simple regression methods. Epistasis also affects the energy and fitness effects of mutations in antigen-derived peptides (epitopes). In MHC-I, large-effect mutations occur predominantly in anchor positions of strong-binding epitopes. In MHC-II, large effects depend on the background epitope sequence but are broadly distributed over the epitope, generating a bigger target for escape mutations due to loss of presentation. Together, our analysis shows how an energy landscape of protein-protein binding constrains the target of escape mutations from T cell immunity, linking the complexity of the molecular interactions to the dynamics of adaptive immune response.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1012380","type":"journal-article","created":{"date-parts":[[2024,9,3]],"date-time":"2024-09-03T13:41:37Z","timestamp":1725370897000},"page":"e1012380","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":3,"title":["Energy landscapes of peptide-MHC binding"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3201-0479","authenticated-orcid":true,"given":"Laura","family":"Collesano","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marta","family":"\u0141uksza","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3575-6719","authenticated-orcid":true,"given":"Michael","family":"L\u00e4ssig","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2024,9,3]]},"reference":[{"issue":"44","key":"pcbi.1012380.ref001","doi-asserted-by":"crossref","first-page":"21969","DOI":"10.1073\/pnas.1916129116","article-title":"T cell antigen recognition: Evolution-driven affinities","volume":"116","author":"R Bosselut","year":"2019","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"4","key":"pcbi.1012380.ref002","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1002\/(SICI)1097-0282(1997)43:4<281::AID-BIP3>3.0.CO;2-R","article-title":"Peptide binding by class I and class II MHC molecules","volume":"43","author":"MA Batalia","year":"1997","journal-title":"Peptide Science"},{"issue":"12","key":"pcbi.1012380.ref003","doi-asserted-by":"crossref","first-page":"952","DOI":"10.1038\/nri1250","article-title":"Making sense of mass destruction: quantitating MHC class I antigen presentation","volume":"3","author":"JW Yewdell","year":"2003","journal-title":"Nature Reviews Immunology"},{"issue":"13","key":"pcbi.1012380.ref004","doi-asserted-by":"crossref","first-page":"2174","DOI":"10.1093\/bioinformatics\/btv123","article-title":"Automated benchmarking of peptide-MHC class I binding predictions","volume":"31","author":"T Trolle","year":"2015","journal-title":"Bioinformatics"},{"issue":"1","key":"pcbi.1012380.ref005","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1146\/annurev.immunol.17.1.51","article-title":"Immunodominance in major histocompatibility complex class I\u2013restricted T lymphocyte responses","volume":"17","author":"JW Yewdell","year":"1999","journal-title":"Annual review of immunology"},{"issue":"6382","key":"pcbi.1012380.ref006","doi-asserted-by":"crossref","first-page":"1355","DOI":"10.1126\/science.aar7112","article-title":"Personalized vaccines for cancer immunotherapy","volume":"359","author":"U Sahin","year":"2018","journal-title":"Science"},{"issue":"4","key":"pcbi.1012380.ref007","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1038\/s41571-020-00460-2","article-title":"Advances in the development of personalized neoantigen-based therapeutic cancer vaccines","volume":"18","author":"E Blass","year":"2021","journal-title":"Nature reviews Clinical oncology"},{"issue":"8","key":"pcbi.1012380.ref008","doi-asserted-by":"crossref","first-page":"911","DOI":"10.1038\/s43018-022-00418-6","article-title":"Cancer vaccines: the next immunotherapy frontier","volume":"3","author":"MJ Lin","year":"2022","journal-title":"Nature cancer"},{"issue":"1","key":"pcbi.1012380.ref009","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1146\/annurev.iy.13.040195.003103","article-title":"The three-dimensional structure of peptide-MHC complexes","volume":"13","author":"DR Madden","year":"1995","journal-title":"Annual review of immunology"},{"issue":"1","key":"pcbi.1012380.ref010","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1146\/annurev.immunol.16.1.323","article-title":"Mechanisms of MHC class I\u2013restricted antigen processing","volume":"16","author":"E Pamer","year":"1998","journal-title":"Annual review of immunology"},{"issue":"2","key":"pcbi.1012380.ref011","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/S0198-8859(97)00078-5","article-title":"Antigen presentation by MHC class II molecules: invariant chain function, protein trafficking, and the molecular basis of diverse determinant capture","volume":"54","author":"F Castellino","year":"1997","journal-title":"Human immunology"},{"issue":"6432","key":"pcbi.1012380.ref012","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1038\/364033a0","article-title":"Three-dimensional structure of the human class II histocompatibility antigen HLA-DR1","volume":"364","author":"JH Brown","year":"1993","journal-title":"Nature"},{"issue":"3","key":"pcbi.1012380.ref013","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1111\/imm.12889","article-title":"Improved methods for predicting peptide binding affinity to MHC class II molecules","volume":"154","author":"KK Jensen","year":"2018","journal-title":"Immunology"},{"issue":"5","key":"pcbi.1012380.ref014","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1016\/0092-8674(93)90472-3","article-title":"Prominent role of secondary anchor residues in peptide binding to HLA-A2. 1 molecules","volume":"74","author":"J Ruppert","year":"1993","journal-title":"Cell"},{"issue":"6324","key":"pcbi.1012380.ref015","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1038\/351290a0","article-title":"Allele-specific motifs revealed by sequencing of self-peptides eluted from MHC molecules","volume":"351","author":"K Falk","year":"1991","journal-title":"Nature"},{"issue":"6468","key":"pcbi.1012380.ref016","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1038\/368215a0","article-title":"Crystal structure of the human class II MHC protein HLA-DR1 complexed with an influenza virus peptide","volume":"368","author":"LJ Stern","year":"1994","journal-title":"Nature"},{"issue":"14","key":"pcbi.1012380.ref017","doi-asserted-by":"crossref","first-page":"1765","DOI":"10.1093\/bioinformatics\/btg247","article-title":"Examining the independent binding assumption for binding of peptide epitopes to MHC-I molecules","volume":"19","author":"B Peters","year":"2003","journal-title":"Bioinformatics"},{"issue":"3","key":"pcbi.1012380.ref018","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1111\/j.1365-2567.2010.03268.x","article-title":"MHC class II epitope predictive algorithms","volume":"130","author":"M Nielsen","year":"2010","journal-title":"Immunology"},{"issue":"3","key":"pcbi.1012380.ref019","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1021\/pr015513z","article-title":"Additive method for the prediction of protein- peptide binding affinity. Application to the MHC class I molecule HLA-A* 0201","volume":"1","author":"IA Doytchinova","year":"2002","journal-title":"Journal of proteome research"},{"issue":"3","key":"pcbi.1012380.ref020","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S1093-3263(03)00160-8","article-title":"Quantitative online prediction of peptide binding to the major histocompatibility complex","volume":"22","author":"CK Hattotuwagama","year":"2004","journal-title":"Journal of Molecular Graphics and Modelling"},{"issue":"4","key":"pcbi.1012380.ref021","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1093\/bioinformatics\/btv639","article-title":"Gapped sequence alignment using artificial neural networks: application to the MHC class I system","volume":"32","author":"M Andreatta","year":"2016","journal-title":"Bioinformatics"},{"issue":"1","key":"pcbi.1012380.ref022","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00251-008-0341-z","article-title":"NetMHCpan, a method for MHC class I binding prediction beyond humans","volume":"61","author":"I Hoof","year":"2009","journal-title":"Immunogenetics"},{"issue":"suppl_2","key":"pcbi.1012380.ref023","doi-asserted-by":"crossref","first-page":"W509","DOI":"10.1093\/nar\/gkn202","article-title":"NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8\u201311","volume":"36","author":"C Lundegaard","year":"2008","journal-title":"Nucleic acids research"},{"issue":"8","key":"pcbi.1012380.ref024","doi-asserted-by":"crossref","first-page":"e796","DOI":"10.1371\/journal.pone.0000796","article-title":"NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and-B locus protein of known sequence","volume":"2","author":"M Nielsen","year":"2007","journal-title":"PloS one"},{"issue":"1","key":"pcbi.1012380.ref025","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.cels.2018.05.014","article-title":"MHCflurry: open-source class I MHC binding affinity prediction","volume":"7","author":"TJ O\u2019Donnell","year":"2018","journal-title":"Cell systems"},{"issue":"1","key":"pcbi.1012380.ref026","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13073-016-0288-x","article-title":"NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasets","volume":"8","author":"M Nielsen","year":"2016","journal-title":"Genome medicine"},{"issue":"3","key":"pcbi.1012380.ref027","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1038\/s42256-022-00459-7","article-title":"A transformer-based model to predict peptide\u2013HLA class I binding and optimize mutated peptides for vaccine design","volume":"4","author":"Y Chu","year":"2022","journal-title":"Nature Machine Intelligence"},{"issue":"1","key":"pcbi.1012380.ref028","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1471-2105-10-296","article-title":"NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction","volume":"10","author":"M Nielsen","year":"2009","journal-title":"BMC bioinformatics"},{"issue":"7","key":"pcbi.1012380.ref029","doi-asserted-by":"crossref","first-page":"e1000107","DOI":"10.1371\/journal.pcbi.1000107","article-title":"Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan","volume":"4","author":"M Nielsen","year":"2008","journal-title":"PLoS computational biology"},{"issue":"1","key":"pcbi.1012380.ref030","doi-asserted-by":"crossref","first-page":"4414","DOI":"10.1038\/s41467-020-18204-2","article-title":"Repertoire-scale determination of class II MHC peptide binding via yeast display improves antigen prediction","volume":"11","author":"CG Rappazzo","year":"2020","journal-title":"Nature communications"},{"issue":"11","key":"pcbi.1012380.ref031","doi-asserted-by":"crossref","DOI":"10.21037\/atm.2018.05.32","article-title":"Opening the black box of neural networks: methods for interpreting neural network models in clinical applications","volume":"6","author":"Z Zhang","year":"2018","journal-title":"Annals of translational medicine"},{"issue":"6464","key":"pcbi.1012380.ref032","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1126\/science.aay4199","article-title":"Higher-fitness yeast genotypes are less robust to deleterious mutations","volume":"366","author":"MS Johnson","year":"2019","journal-title":"Science"},{"issue":"6034","key":"pcbi.1012380.ref033","doi-asserted-by":"crossref","first-page":"1190","DOI":"10.1126\/science.1203799","article-title":"Diminishing returns epistasis among beneficial mutations decelerates adaptation","volume":"332","author":"HH Chou","year":"2011","journal-title":"Science"},{"issue":"6","key":"pcbi.1012380.ref034","doi-asserted-by":"crossref","first-page":"684","DOI":"10.1016\/j.gde.2013.11.001","article-title":"Universality and predictability in molecular quantitative genetics","volume":"23","author":"A Nourmohammad","year":"2013","journal-title":"Current opinion in genetics & development"},{"issue":"4","key":"pcbi.1012380.ref035","doi-asserted-by":"crossref","first-page":"2013","DOI":"10.1534\/genetics.105.046078","article-title":"Epistasis for fitness-related quantitative traits in Arabidopsis thaliana grown in the field and in the greenhouse","volume":"171","author":"RL Malmberg","year":"2005","journal-title":"Genetics"},{"issue":"1","key":"pcbi.1012380.ref036","doi-asserted-by":"crossref","first-page":"7011","DOI":"10.1038\/s41467-022-34506-z","article-title":"Compensatory epistasis maintains ACE2 affinity in SARS-CoV-2 Omicron BA. 1","volume":"13","author":"A Moulana","year":"2022","journal-title":"Nature Communications"},{"key":"pcbi.1012380.ref037","doi-asserted-by":"crossref","first-page":"e83442","DOI":"10.7554\/eLife.83442","article-title":"The landscape of antibody binding affinity in SARS-CoV-2 Omicron BA. 1 evolution","volume":"12","author":"A Moulana","year":"2023","journal-title":"Elife"},{"issue":"1","key":"pcbi.1012380.ref038","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1186\/s12915-023-01585-3","article-title":"Epistasis and evolution: recent advances and an outlook for prediction","volume":"21","author":"MS Johnson","year":"2023","journal-title":"BMC biology"},{"issue":"12","key":"pcbi.1012380.ref039","doi-asserted-by":"crossref","first-page":"1685","DOI":"10.1038\/s41559-020-01286-y","article-title":"Idiosyncratic epistasis creates universals in mutational effects and evolutionary trajectories","volume":"4","author":"DM Lyons","year":"2020","journal-title":"Nature Ecology & Evolution"},{"key":"pcbi.1012380.ref040","doi-asserted-by":"crossref","first-page":"e64740","DOI":"10.7554\/eLife.64740","article-title":"Global epistasis emerges from a generic model of a complex trait","volume":"10","author":"G Reddy","year":"2021","journal-title":"Elife"},{"issue":"6593","key":"pcbi.1012380.ref041","doi-asserted-by":"crossref","first-page":"630","DOI":"10.1126\/science.abm4774","article-title":"Idiosyncratic epistasis leads to global fitness\u2013correlated trends","volume":"376","author":"CW Bakerlee","year":"2022","journal-title":"Science"},{"issue":"D1","key":"pcbi.1012380.ref042","doi-asserted-by":"crossref","first-page":"D339","DOI":"10.1093\/nar\/gky1006","article-title":"The immune epitope database (IEDB): 2018 update","volume":"47","author":"R Vita","year":"2019","journal-title":"Nucleic acids research"},{"issue":"1","key":"pcbi.1012380.ref043","first-page":"1","article-title":"Dataset size and composition impact the reliability of performance benchmarks for peptide-MHC binding predictions","volume":"15","author":"Y Kim","year":"2014","journal-title":"BMC bioinformatics"},{"issue":"12","key":"pcbi.1012380.ref044","doi-asserted-by":"crossref","first-page":"5586","DOI":"10.4049\/jimmunol.153.12.5586","article-title":"The relationship between class I binding affinity and immunogenicity of potential cytotoxic T cell epitopes","volume":"153","author":"A Sette","year":"1994","journal-title":"The Journal of Immunology"},{"issue":"11","key":"pcbi.1012380.ref045","doi-asserted-by":"crossref","first-page":"e1006457","DOI":"10.1371\/journal.pcbi.1006457","article-title":"Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes","volume":"14","author":"W Zhao","year":"2018","journal-title":"PLoS computational biology"},{"key":"pcbi.1012380.ref046","doi-asserted-by":"crossref","first-page":"1716","DOI":"10.3389\/fimmu.2018.01716","article-title":"Predicting antigen presentation\u2014what could we learn from a million peptides?","volume":"9","author":"D Gfeller","year":"2018","journal-title":"Frontiers in immunology"},{"issue":"34","key":"pcbi.1012380.ref047","doi-asserted-by":"crossref","first-page":"12376","DOI":"10.1073\/pnas.0805909105","article-title":"Energy-dependent fitness: a quantitative model for the evolution of yeast transcription factor binding sites","volume":"105","author":"V Mustonen","year":"2008","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"2","key":"pcbi.1012380.ref048","doi-asserted-by":"crossref","first-page":"739","DOI":"10.4049\/jimmunol.169.2.739","article-title":"The majority of immunogenic epitopes generate CD4+ T cells that are dependent on MHC class II-bound peptide-flanking residues","volume":"169","author":"PY Arnold","year":"2002","journal-title":"The Journal of Immunology"},{"key":"pcbi.1012380.ref049","doi-asserted-by":"crossref","first-page":"172","DOI":"10.3389\/fimmu.2013.00172","article-title":"Re-directing CD4+ T cell responses with the flanking residues of MHC class II-bound peptides: the core is not enough","volume":"4","author":"CJ Holland","year":"2013","journal-title":"Frontiers in immunology"},{"issue":"6","key":"pcbi.1012380.ref050","doi-asserted-by":"crossref","first-page":"1359","DOI":"10.1016\/j.immuni.2023.03.009","article-title":"Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes","volume":"56","author":"J Racle","year":"2023","journal-title":"Immunity"},{"issue":"7","key":"pcbi.1012380.ref051","doi-asserted-by":"crossref","first-page":"2272","DOI":"10.1093\/bioinformatics\/btz921","article-title":"Logomaker: beautiful sequence logos in Python","volume":"36","author":"A Tareen","year":"2020","journal-title":"Bioinformatics"},{"issue":"01","key":"pcbi.1012380.ref052","doi-asserted-by":"crossref","first-page":"P01012","DOI":"10.1088\/1742-5468\/2013\/01\/P01012","article-title":"Evolution of molecular phenotypes under stabilizing selection","volume":"2013","author":"A Nourmohammad","year":"2013","journal-title":"Journal of Statistical Mechanics: Theory and Experiment"},{"issue":"32","key":"pcbi.1012380.ref053","doi-asserted-by":"crossref","first-page":"E7550","DOI":"10.1073\/pnas.1804015115","article-title":"Inferring the shape of global epistasis","volume":"115","author":"J Otwinowski","year":"2018","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"7","key":"pcbi.1012380.ref054","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1016\/S0031-3203(96)00142-2","article-title":"The use of the area under the ROC curve in the evaluation of machine learning algorithms","volume":"30","author":"AP Bradley","year":"1997","journal-title":"Pattern recognition"},{"issue":"430","key":"pcbi.1012380.ref055","doi-asserted-by":"crossref","first-page":"773","DOI":"10.1080\/01621459.1995.10476572","article-title":"Bayes factors","volume":"90","author":"RE Kass","year":"1995","journal-title":"Journal of the american statistical association"},{"key":"pcbi.1012380.ref056","volume-title":"Deep learning","author":"I Goodfellow","year":"2016"}],"updated-by":[{"DOI":"10.1371\/journal.pcbi.1012380","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T00:00:00Z","timestamp":1726185600000}}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1012380","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T14:14:55Z","timestamp":1726236895000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1012380"}},"subtitle":[],"editor":[{"given":"Piero","family":"Fariselli","sequence":"first","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2024,9,3]]},"references-count":56,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2024,9,3]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1012380","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2024.03.19.585687","asserted-by":"object"}]},"ISSN":["1553-7358"],"issn-type":[{"value":"1553-7358","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,3]]}}}