{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T10:52:02Z","timestamp":1781088722711,"version":"3.54.1"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1011435","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2023,9,13]],"date-time":"2023-09-13T00:00:00Z","timestamp":1694563200000}}],"reference-count":63,"publisher":"Public Library of Science (PLoS)","issue":"8","license":[{"start":{"date-parts":[[2023,8,31]],"date-time":"2023-08-31T00:00:00Z","timestamp":1693440000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"publisher","award":["R35GM138146"],"award-info":[{"award-number":["R35GM138146"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["DBI2208679"],"award-info":[{"award-number":["DBI2208679"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Artificial intelligence-powered protein structure prediction methods have led to a paradigm-shift in computational structural biology, yet contemporary approaches for predicting the interfacial residues (i.e., sites) of protein-protein interaction (PPI) still rely on experimental structures. Recent studies have demonstrated benefits of employing graph convolution for PPI site prediction, but ignore symmetries naturally occurring in 3-dimensional space and act only on experimental coordinates. Here we present EquiPPIS, an E(3) equivariant graph neural network approach for PPI site prediction. EquiPPIS employs symmetry-aware graph convolutions that transform equivariantly with translation, rotation, and reflection in 3D space, providing richer representations for molecular data compared to invariant convolutions. EquiPPIS substantially outperforms state-of-the-art approaches based on the same experimental input, and exhibits remarkable robustness by attaining better accuracy with predicted structural models from AlphaFold2 than what existing methods can achieve even with experimental structures. Freely available at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/Bhattacharya-Lab\/EquiPPIS\" xlink:type=\"simple\">https:\/\/github.com\/Bhattacharya-Lab\/EquiPPIS<\/jats:ext-link>, EquiPPIS enables accurate PPI site prediction at scale.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1011435","type":"journal-article","created":{"date-parts":[[2023,8,31]],"date-time":"2023-08-31T17:41:32Z","timestamp":1693503692000},"page":"e1011435","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":34,"title":["E(3) equivariant graph neural networks for robust and accurate protein-protein interaction site prediction"],"prefix":"10.1371","volume":"19","author":[{"given":"Rahmatullah","family":"Roche","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bernard","family":"Moussad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Md Hossain","family":"Shuvo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9630-0141","authenticated-orcid":true,"given":"Debswapna","family":"Bhattacharya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2023,8,31]]},"reference":[{"issue":"1","key":"pcbi.1011435.ref001","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1073\/pnas.93.1.13","article-title":"Principles of protein-protein interactions","volume":"93","author":"S Jones","year":"1996","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"6","key":"pcbi.1011435.ref002","doi-asserted-by":"crossref","first-page":"1974","DOI":"10.1073\/pnas.0409522102","article-title":"Conserved patterns of protein interaction in multiple species","volume":"102","author":"R Sharan","year":"2005","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"3","key":"pcbi.1011435.ref003","doi-asserted-by":"crossref","first-page":"e42","DOI":"10.1371\/journal.pcbi.0030042","article-title":"Deciphering protein\u2013protein interactions","volume":"3","author":"BA Shoemaker","year":"2007","journal-title":"Part I. 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