{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T17:07:11Z","timestamp":1772989631411,"version":"3.50.1"},"reference-count":49,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T00:00:00Z","timestamp":1772928000000},"content-version":"vor","delay-in-days":7,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Fundamental Research Funds for the Central Universities, China","award":["buctrc202337"],"award-info":[{"award-number":["buctrc202337"]}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["62173204"],"award-info":[{"award-number":["62173204"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Protein\u2013protein interactions (PPIs) are central to cellular signaling and regulation, and their dysregulation underlies many diseases. Predicting the impact of mutations on PPI stability, quantified as \u0394\u0394G, is essential for understanding disease mechanisms and guiding protein engineering. Here, we first present MutPPI, a graph-based deep-learning model that encodes full-residue structural features of protein\u2013protein complexes and employs a shared GIN-GAT feature extractor for wild-type and mutant complexes. MutPPI outperforms 12 existing methods on an antibody\u2013antigen single-point mutation dataset (S645). By integrating evolutionary information from protein language models, we further develop MutPPI-plus, achieving enhanced predictive performance. Second, we proposed a mutation-path-based data augmentation strategy, which enriches input modalities and improves generalization of both MutPPI and MutPPI-plus. After data augmentation, MutPPI-plus demonstrates state-of-the-art performance on S645 and three additional multi-point mutation datasets (SM_ZEMu, SM595, SM1124), substantially surpassing DDMut-PPI. Our analyses highlight the benefits of the multimodal framework and the physically informed data augmentation method. Together, these results provide a versatile computational tool for accurate \u0394\u0394G prediction, advancing rational protein design.<\/jats:p>","DOI":"10.1093\/bib\/bbag105","type":"journal-article","created":{"date-parts":[[2026,2,22]],"date-time":"2026-02-22T12:29:50Z","timestamp":1771763390000},"source":"Crossref","is-referenced-by-count":0,"title":["MutPPI+: a multimodal framework for predicting mutation effects on protein\u2013protein interactions via mutation-path-based data augmentation"],"prefix":"10.1093","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1780-8984","authenticated-orcid":false,"given":"Juntao","family":"Deng","sequence":"first","affiliation":[{"name":"Department of Automation, Tsinghua University , Shuangqing Road 30, Haidian District, Beijing, 100084 ,","place":["China"]}]},{"given":"Miao","family":"Gu","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University , Shuangqing Road 30, Haidian District, Beijing, 100084 ,","place":["China"]}]},{"given":"Pengyan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University , Shuangqing Road 30, Haidian District, Beijing, 100084 ,","place":["China"]}]},{"given":"Tao","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University , Shuangqing Road 30, Haidian District, Beijing, 100084 ,","place":["China"]}]},{"given":"Guansong","family":"Hu","sequence":"additional","affiliation":[{"name":"Institute for Healthcare Artificial Intelligence Application, Guangdong Second Provincial General Hospital , Xingang Middle Road 466, Haizhu District, Guangzhou, 510317 ,","place":["China"]},{"name":"Department of Nuclear Medicine, Jinan University , Huangpu Avenue West 601, Tianhe District, Guangzhou, 510632 ,","place":["China"]}]},{"given":"Mingyu","family":"Dong","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University , Shuangqing Road 30, Haidian District, Beijing, 100084 ,","place":["China"]}]},{"given":"Yabin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University , Shuangqing Road 30, Haidian District, Beijing, 100084 ,","place":["China"]}]},{"given":"Yizhen","family":"Song","sequence":"additional","affiliation":[{"name":"College of Information Science & Technology, Beijing University of Chemical Technology , Beisanhuan East Road 15, Chaoyang District, Beijing, 100029 ,","place":["China"]}]},{"given":"Yunfan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University , Shuangqing Road 30, Haidian District, Beijing, 100084 ,","place":["China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7273-0518","authenticated-orcid":false,"given":"Min","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University , Shuangqing Road 30, Haidian District, Beijing, 100084 ,","place":["China"]},{"name":"Institute for Healthcare Artificial Intelligence Application, Guangdong Second Provincial General Hospital , Xingang Middle Road 466, Haizhu District, Guangzhou, 510317 ,","place":["China"]}]},{"given":"Junzhang","family":"Tian","sequence":"additional","affiliation":[{"name":"Institute for Healthcare Artificial Intelligence Application, Guangdong Second Provincial General Hospital , Xingang Middle Road 466, Haizhu District, Guangzhou, 510317 ,","place":["China"]},{"name":"Department of Nuclear Medicine, Jinan University , Huangpu Avenue West 601, Tianhe District, Guangzhou, 510632 ,","place":["China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9845-6676","authenticated-orcid":false,"given":"Weibin","family":"Cheng","sequence":"additional","affiliation":[{"name":"Institute for Healthcare Artificial Intelligence Application, Guangdong Second Provincial General Hospital , Xingang Middle Road 466, Haizhu District, Guangzhou, 510317 ,","place":["China"]},{"name":"Department of Nuclear Medicine, Jinan University , Huangpu Avenue West 601, Tianhe District, Guangzhou, 510632 ,","place":["China"]}]}],"member":"286","published-online":{"date-parts":[[2026,3,8]]},"reference":[{"key":"2026030808003221600_ref1","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1038\/s41392-024-02036-3","article-title":"New insights into protein-protein interaction modulators in drug discovery and therapeutic advance","volume":"9","author":"Nada","year":"2024","journal-title":"Signal Transduct Target Ther"},{"key":"2026030808003221600_ref2","doi-asserted-by":"publisher","first-page":"eadr8063","DOI":"10.1126\/science.adr8063","article-title":"Design of intrinsically disordered region binding proteins","volume":"389","author":"Wu","year":"2025","journal-title":"Science"},{"key":"2026030808003221600_ref3","doi-asserted-by":"publisher","first-page":"539","DOI":"10.1016\/j.tibs.2023.01.008","article-title":"Fragment-based drug 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