[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126637-en":3,"doc-seo-126637-105":30,"detail-sidebar-cat-0-en-105":95},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},126637,549768064622,"Anda","https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8",8,"Research & Report","Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes - Research summary","CD4+ T cells recognize peptides displayed on class II major histocompatibility complex (MHC-II) molecules, yet epitope prediction remains limited by the extreme polymorphism of MHC-II genes. The work curates a mass-spectrometry dataset containing 627,013 unique MHC-II ligands and uses it to define high-resolution binding motifs for 88 MHC-II alleles across multiple species. Motif analysis, supported by X-ray crystallography, uncovers a widespread reverse-binding mode for HLA-DP ligands. A machine-learning framework is then developed to predict binding specificities and ligands for any MHC-II allele, improving CD4+ T cell epitope predictions and enabling discovery of viral and bacterial epitopes.","Article  \nMachine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes  \nGraphical abstract  \nHighlights  \nd Analysis of MHC-II peptidomics data identifies >600,000 MHC-II ligands  \nAuthors  \nJulien Racle, Philippe Guillaume,  \nJulien Schmidt, ...,  \nMichal Bassani-Sternberg, Alexandre Harari, David Gfeller  \nCorrespondence  \n[julien.racle@unil.ch](julien.racle@unil.ch) (J.R.),  \n[david.gfeller@unil.ch](david.gfeller@unil.ch) (D.G.)  \nIn brief  \nCD4+ T cells recognize peptides displayed on MHC-II molecules. Racleet al. curate >600,000 MHC-II ligands and derive high-resolution motifs for 88 MHC-II alleles. These motifs reveal a widespread reverse-binding mode for HLA-DP ligands and improve predictions of CD4+ T cell epitopes with MixMHC2pred.  \nd Motif deconvolution determines high-resolution binding motifs for 88 MHC-II alleles  \nd Structural analysis uncovers alternative binding modes of MHC-II ligands  \nd MixMHC2pred improves predictions of CD4+ T cell epitopes  \nRacle et al., 2023, Immunity 56, 1359–1375  \nJune 13, 2023 ª 2023 The Authors. Published by Elsevier Inc.  \n[https://doi.org/10.1016/j.immuni.2023.03.009](https://doi.org/10.1016/j.immuni.2023.03.009)  \nll  \nll  \nOPEN ACCESS  \nArticle  \nMachine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes  \nJulien Racle,1,2,3,4,* Philippe Guillaume,1,4,5 Julien Schmidt,1,4,5 Justine Michaux,1,3,4,5,6 Am´ed´e Larabi,7 Kelvin Lau,7 Marta A.S. Perez,1,2,4 Giancarlo Croce,1,2,3,4 Rapha€el Genolet,1,4,5 George Coukos,1,3,4,5 Vincent Zoete,1,2,4 Florence Pojer,7 Michal Bassani-Sternberg,1,3,4,5,6 Alexandre Harari,1,3,4,5 and David Gfeller1,2,3,4,8,*  \n1Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland  \n2Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland  \n3Agora Cancer Research Centre, Lausanne, Switzerland  \n4Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland  \n5Department of Oncology UNIL CHUV, Ludwig Institute for Cancer Research, University Hospital of Lausanne, Lausanne, Switzerland  \n6Center of Experimental Therapeutics, Department of Oncology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland  \n7School of Life Sciences, Ecole Polytechnique F´ed´erale de Lausanne, Lausanne, Switzerland  \n8Lead contact  \n*Correspondence: [julien.racle@unil.ch](julien.racle@unil.ch) (J.R.), [david.gfeller@unil.ch](david.gfeller@unil.ch) (D.G.) [https://doi.org/10.1016/j.immuni.2023.03.009](https://doi.org/10.1016/j.immuni.2023.03.009)  \nSUMMARY  \nCD4+ T cells orchestratethe adaptive immune response against pathogens and cancer by recognizing epitopes presented on class II major histocompatibility complex (MHC-II) molecules. The high polymorphism of MHC-II genes represents an important hurdle toward accurate prediction and identification of CD4+ T cell epitopes. Here we collected and curated a dataset of 627,013 unique MHC-II ligands identified by mass spectrometry. This enabled us to precisely determine the binding motifs of 88 MHC-II alleles across humans, mice, cattle, and chickens. Analysis of these binding specificities combined with X-ray crystallography refined our understanding of the molecular determinants of MHC-II motifs and revealed a widespread reverse-binding mode in HLA-DP ligands. We then developed a machine-learning framework to accurately predict binding specificities and ligands of any MHC-II allele. This tool improves and expands predictions of CD4+ T cell epitopesand enables us to discover viral and bacterial epitopes following the aforementioned reverse-binding mode.  \nINTRODUCTION  \nCD4+ T cells are key components of the adaptive immune system. They are implicated in priming and modulating the immune response to pathogens and cancer. CD4+ T cells also play an essential role in cancer immunotherapy,1 ,2 as demonstrated by CD4+ T cell responses following neoantigen-based cancer vaccines3–","cbCaikH2tzFHQCcS","https://ap.wps.com/l/cbCaikH2tzFHQCcS","pdf",8459816,1,31,"English","en",105,"# Highlights\n## Curated MHC-II ligand dataset\n## Binding motifs for 88 alleles\n## Reverse-binding mode in HLA-DP\n## MixMHC2pred improves epitope prediction\n# Summary\n## Immunological context of CD4+ T cells and MHC-II polymorphism\n## Dataset size and cross-species coverage\n## Structural refinement and binding-mode discovery\n## Machine-learning framework for allele-agnostic prediction\n# Introduction\n## Role of CD4+ T cells in infection and cancer immunotherapy\n## MHC-II antigen presentation pathway and peptide loading\n## Canonical binding mode and known exceptions","[{\"question\":\"What dataset is curated to study MHC-II specificities?\",\"answer\":\"A curated collection of 627,013 unique MHC-II ligands identified by mass spectrometry.\"},{\"question\":\"How many MHC-II alleles and what output are derived from the analysis?\",\"answer\":\"High-resolution binding motifs are derived for 88 MHC-II alleles across humans, mice, cattle, and chickens.\"},{\"question\":\"What is the key binding-mode finding for HLA-DP ligands?\",\"answer\":\"Structural and motif analyses reveal a widespread reverse-binding mode for HLA-DP ligands.\"},{\"question\":\"How does MixMHC2pred support CD4+ T cell epitope prediction?\",\"answer\":\"It is a machine-learning framework that predicts binding specificities and ligands for any MHC-II allele, improving and expanding CD4+ T cell epitope predictions, including viral and bacterial epitopes.\"}]","Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes - Research summary | PDF",1785933965,78,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":90,"head_meta":92,"extra_data":94,"updated_unix":28},"machine-learning-predictions-of-mhc-ii-specificities-reveal-alternative-binding-mode-of-class-ii-epitopes-research-summary","",{"@graph":36,"@context":89},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-predictions-of-mhc-ii-specificities-reveal-alternative-binding-mode-of-class-ii-epitopes-research-summary/126637/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81,85],{"name":72,"@type":73,"acceptedAnswer":74},"What dataset is curated to study MHC-II specificities?","Question",{"text":75,"@type":76},"A curated collection of 627,013 unique MHC-II ligands identified by mass spectrometry.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How many MHC-II alleles and what output are derived from the analysis?",{"text":80,"@type":76},"High-resolution binding motifs are derived for 88 MHC-II alleles across humans, mice, cattle, and chickens.",{"name":82,"@type":73,"acceptedAnswer":83},"What is the key binding-mode finding for HLA-DP ligands?",{"text":84,"@type":76},"Structural and motif analyses reveal a widespread reverse-binding mode for HLA-DP ligands.",{"name":86,"@type":73,"acceptedAnswer":87},"How does MixMHC2pred support CD4+ T cell epitope prediction?",{"text":88,"@type":76},"It is a machine-learning framework that predicts binding specificities and ligands for any MHC-II allele, improving and expanding CD4+ T cell epitope predictions, including viral and bacterial epitopes.","https://schema.org",{"og:url":52,"og:type":91,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":93,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":96},[97,101,105,109,114,119,124,127,132,135,139],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},"Exam",70,"exam",{"id":110,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},5,"Comic",60,"comic",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},6,"Technology",50,"technology",{"id":120,"doc_module":4,"doc_module_name":46,"category_name":121,"show_sort_weight":122,"slug":123},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":125,"slug":126},30,"research-report",{"id":128,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":130,"slug":131},9,"Religion & Spirituality",20,"religion-spirituality",{"id":130,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":130,"slug":134},"World Cup","world-cup",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":136,"slug":138},10,"Lifestyle","lifestyle",{"id":140,"doc_module":4,"doc_module_name":46,"category_name":141,"show_sort_weight":110,"slug":142},19,"General","general"]