{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,22]],"date-time":"2026-03-22T09:34:02Z","timestamp":1774172042557,"version":"3.50.1"},"reference-count":52,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2024,10,23]],"date-time":"2024-10-23T00:00:00Z","timestamp":1729641600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000024","name":"CIHR","doi-asserted-by":"publisher","award":["PJT-159750"],"award-info":[{"award-number":["PJT-159750"]}],"id":[{"id":"10.13039\/501100000024","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000024","name":"CIHR","doi-asserted-by":"publisher","award":["PJT-166008"],"award-info":[{"award-number":["PJT-166008"]}],"id":[{"id":"10.13039\/501100000024","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Protein\u2013protein interactions are essential for a variety of biological phenomena including mediating biochemical reactions, cell signaling, and the immune response. Proteins seek to form interfaces which reduce overall system energy. Although determination of single polypeptide chain protein structures has been revolutionized by deep learning techniques, complex prediction has still not been perfected. Additionally, experimentally determining structures is incredibly resource and time expensive. An alternative is the technique of computational docking, which takes the solved individual structures of proteins to produce candidate interfaces (decoys). Decoys are then scored using a mathematical function that assess the quality of the system, known as scoring functions. Beyond docking, scoring functions are a critical component of assessing structures produced by many protein generative models. Scoring models are also used as a final filtering in many generative deep learning models including those that generate antibody binders, and those which perform docking.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In this work, we present improved scoring functions for protein\u2013protein interactions which utilizes cutting-edge Euclidean graph neural network architectures, to assess protein\u2013protein interfaces. These Euclidean docking score models are known as EuDockScore, and EuDockScore-Ab with the latter being antibody\u2013antigen dock specific. Finally, we provided EuDockScore-AFM a model trained on antibody\u2013antigen outputs from AlphaFold-Multimer (AFM) which proves useful in reranking large numbers of AFM outputs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The code for these models is available at https:\/\/gitlab.com\/mcfeemat\/eudockscore.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae636","type":"journal-article","created":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T15:24:25Z","timestamp":1729524265000},"source":"Crossref","is-referenced-by-count":3,"title":["EuDockScore: Euclidean graph neural networks for scoring protein\u2013protein interfaces"],"prefix":"10.1093","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2112-1402","authenticated-orcid":false,"given":"Matthew","family":"McFee","sequence":"first","affiliation":[{"name":"Department of Molecular Genetics, The University of Toronto , Toronto, ON M5S 1A8,","place":["Canada"]},{"name":"Donnelly Centre for Cellular and Biomolecular Research, The University of Toronto , Toronto, ON M5S 3E1,","place":["Canada"]}]},{"given":"Jisun","family":"Kim","sequence":"additional","affiliation":[{"name":"Donnelly Centre for Cellular and Biomolecular Research, The University of Toronto , Toronto, ON M5S 3E1,","place":["Canada"]}]},{"given":"Philip M","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Molecular Genetics, The University of Toronto , Toronto, ON M5S 1A8,","place":["Canada"]},{"name":"Donnelly Centre for Cellular and Biomolecular Research, The University of Toronto , Toronto, ON M5S 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