{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T09:29:30Z","timestamp":1785403770823,"version":"3.56.0"},"posted":{"date-parts":[[2026,7,20]]},"group-title":"Immunology","reference-count":87,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T00:00:00Z","timestamp":1784505600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100013352","name":"Tow Foundation","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100013352","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100019408","name":"Marcus Foundation","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100019408","id-type":"DOI","asserted-by":"crossref"}]},{"id":[{"id":"https:\/\/ror.org\/05r5zfp34","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014599","name":"The Mark Foundation for Cancer Research","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100014599","id-type":"DOI","asserted-by":"crossref"}]},{"id":[{"id":"https:\/\/ror.org\/040gcmg81","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,7,20]]},"abstract":"<jats:p>\n                  Adaptive immunity relies on T-cell receptor (TCR) recognition of peptides presented by the major histocompatibility complex (pMHC). Accurate prediction of TCR:pMHC binding pairs from sequence data remains a longstanding challenge in computational immunology, limiting the development of precision immunotherapies like cancer vaccines and adoptive cell therapies. Here, we present enFoldX (\n                  <jats:bold>en<\/jats:bold>\n                  semble of\n                  <jats:bold>Fold<\/jats:bold>\n                  ed comple\n                  <jats:bold>X<\/jats:bold>\n                  es), a structure-based approach leveraging biophysical characterization of AlphaFold3-generated ensembles to classify TCR:pMHC sequence pairs as cognate versus non-cognate. Unlike previous methods reliant on only sequence data or a single, static predicted structure, enFoldX extracts features from an entire generated ensemble with a custom focus on the biophysical binding interface. Our model distinguishes T cell reactivity between peptides differing by a single amino acid substitution, the resolution required for cancer neoantigens, and generalizes to unseen peptides, MHCs, and TCRs, a major objective for artificial intelligence (AI) in immunology. Our performance on these crucial tasks demonstrates that diverse, structural sampling of biophysical interactions over an ensemble is fundamental for accurate AI-driven binding predictions and offers lessons for efficient future data generation to improve models. Our findings therefore offer a scalable framework to accelerate therapeutic binder design, and we provide access to a publicly available code repository.\n                <\/jats:p>","DOI":"10.64898\/2026.07.14.738340","type":"posted-content","created":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T20:30:17Z","timestamp":1784579417000},"source":"Crossref","is-referenced-by-count":0,"title":["Ensembles of\n                  <i>in silico<\/i>\n                  structures enable T cell peptide-MHC binding prediction"],"prefix":"10.64898","author":[{"given":"O","family":"Lyudovyk","sequence":"first","affiliation":[{"name":"Tri-institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medicine, New York, NY USA"},{"name":"The Halvorsen Center for Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA"},{"name":"Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"JA","family":"Levine","sequence":"additional","affiliation":[{"name":"Tri-institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medicine, New York, NY USA"},{"name":"The Halvorsen Center for Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA"},{"name":"Laboratory of Lymphocyte Dynamics, The Rockefeller University, New York, NY USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M","family":"Pathil","sequence":"additional","affiliation":[{"name":"The Halvorsen Center for Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA"},{"name":"Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA"},{"name":"Physiology, Biophysics & Systems Biology, Weill Cornell Medicine, New York, NY USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1735-2347","authenticated-orcid":false,"given":"S","family":"Martis","sequence":"additional","affiliation":[{"name":"The Halvorsen Center for Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A","family":"Streltsov","sequence":"additional","affiliation":[{"name":"Johnson Graduate School of Management, Cornell University, Ithaca, NY USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Z","family":"Sethna","sequence":"additional","affiliation":[{"name":"The Halvorsen Center for Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA"},{"name":"Immuno-Oncology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA"},{"name":"The Olayan Center for Cancer Vaccines, Memorial Sloan Kettering Cancer Center, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Y","family":"Elhanati","sequence":"additional","affiliation":[{"name":"The Halvorsen Center for Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"VP","family":"Balachandran","sequence":"additional","affiliation":[{"name":"Immuno-Oncology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA"},{"name":"The Olayan Center for Cancer Vaccines, Memorial Sloan Kettering Cancer Center, New York, NY, USA"},{"name":"Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Q","family":"Morris","sequence":"additional","affiliation":[{"name":"Tri-institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medicine, New York, NY USA"},{"name":"Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA"},{"name":"Physiology, Biophysics & Systems Biology, Weill Cornell Medicine, New York, NY USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"BD","family":"Greenbaum","sequence":"additional","affiliation":[{"name":"The Halvorsen Center for Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA"},{"name":"Immuno-Oncology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA"},{"name":"The Olayan Center for Cancer Vaccines, Memorial Sloan Kettering Cancer Center, New York, NY, 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