{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T14:17:12Z","timestamp":1789395432816,"version":"build-2803163510"},"reference-count":63,"publisher":"American Chemical Society (ACS)","issue":"17","license":[{"start":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T00:00:00Z","timestamp":1787443200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T00:00:00Z","timestamp":1787443200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T00:00:00Z","timestamp":1787443200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-045"}],"funder":[{"DOI":"10.13039\/na","name":"Science and Technology Plan Project of Liaoning Province","doi-asserted-by":"publisher","award":["2025-MSLH-351"],"award-info":[{"award-number":["2025-MSLH-351"]}],"id":[{"id":"10.13039\/na","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/na","name":"Fundamental Research Funds for the Liaoning Universities","doi-asserted-by":"publisher","award":["LJ212410146026"],"award-info":[{"award-number":["LJ212410146026"]}],"id":[{"id":"10.13039\/na","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,9,14]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Mutation-induced changes in binding free energy (\u0394\u0394G) at antibody\u2013antigen interfaces are important for antibody optimization, mutational scanning, and viral immune escape assessment. However, computational prediction remains challenging because antibodies and antigens have distinct sequence backgrounds, mutation effects are often localized at interfaces, and related complexes may remain across training and evaluation partitions. We present AbAgMut-GNN as a task-oriented paired graph framework that coordinates established sequence and geometric learning components around explicit comparison of wild-type (WT) and mutant (MUT) antibody\u2013antigen complexes. AntiBERTy and ESM2 provide frozen residue-level embeddings for antibody and antigen chains, respectively, while mutation-centered, interface-aware, paired-residue, and contact-delta representations capture local perturbations and interaction remodeling. We evaluate AbAgMut-GNN under four complementary internal settings, including the PDB-based split, the complex-cluster split, the antibody-family preserving validation split, and the antigen-cluster-preserving validation split. Under the complex-cluster split, AbAgMut-GNN achieves Pearson correlation coefficients of 0.5841 on AB-Bind and 0.5480 on SKEMPI v2.0. External validation on SARS-CoV-2 and influenza antibody\u2013antigen systems further shows useful mutation-effect correlation trends, although absolute-error performance varies across target systems. Contact-masking and residue-class enrichment analyses indicate that model-derived importance patterns are associated with biologically relevant interface interactions. Overall, AbAgMut-GNN is best viewed as a task-oriented computational tool for trend-level mutation ranking and pre-experimental candidate prioritization rather than as a high-precision substitute for quantitative biophysical measurement.<\/jats:p>","DOI":"10.1021\/acs.jcim.6c01919","type":"journal-article","created":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T15:53:33Z","timestamp":1787932413000},"page":"11503-11526","source":"Crossref","is-referenced-by-count":0,"title":["Predicting Antibody\u2013Antigen\nMutation \u0394\u0394\n                    <i>G<\/i>\n                    via Side-Specific Protein\nLanguage Models and Paired Geometric\nGraph Learning"],"prefix":"10.1021","volume":"66","author":[{"given":"Wenchi","family":"Ge","sequence":"first","affiliation":[{"name":"University of Science and Technology Liaoning , , ,","place":["Anshan, China, 114051"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qijia","family":"Yu","sequence":"additional","affiliation":[{"name":"University of Science and Technology Liaoning , , ,","place":["Anshan, China, 114051"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jincen","family":"Shuai","sequence":"additional","affiliation":[{"name":"University of California , , ,","place":["Santa Cruz, United States, 95054"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9713-1864","authenticated-orcid":true,"given":"Qi","family":"Zhao","sequence":"additional","affiliation":[{"name":"University of Science and Technology Liaoning , , ,","place":["Anshan, China, 114051"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,8,23]]},"reference":[{"issue":"4","key":"2026091409084409100_cit1","doi-asserted-by":"publisher","first-page":"1225","DOI":"10.1021\/cr040409x","article-title":"Principles of protein-protein\ninteractions: what are the preferred ways for proteins to interact?","volume":"108","author":"Keskin","year":"2008","journal-title":"Chem. Rev."},{"key":"2026091409084409100_cit2","doi-asserted-by":"publisher","first-page":"302","DOI":"10.3389\/fimmu.2013.00302","article-title":"The structural\nbasis of antibody-antigen\nrecognition","volume":"4","author":"Sela-Culang","year":"2013","journal-title":"Front. Immunol."},{"issue":"1","key":"2026091409084409100_cit3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1006\/jmbi.1998.1843","article-title":"Anatomy of hot spots\nin protein interfaces","volume":"280","author":"Bogan","year":"1998","journal-title":"J. Mol. Biol."},{"issue":"5","key":"2026091409084409100_cit4","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1038\/nri1837","article-title":"Potent\nantibody therapeutics by design","volume":"6","author":"Carter","year":"2006","journal-title":"Nat. Rev. Immunol."},{"key":"2026091409084409100_cit5","doi-asserted-by":"publisher","first-page":"429","DOI":"10.1146\/annurev-immunol-020711-075032","article-title":"Germinal\ncenters","volume":"30","author":"Victora","year":"2012","journal-title":"Annu. Rev.\nImmunol."},{"issue":"2","key":"2026091409084409100_cit6","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1016\/S0022-2836(02)00264-4","article-title":"Comprehensive functional\nmaps of the antigen-binding site of an anti-ErbB2 antibody obtained\nwith shotgun scanning mutagenesis","volume":"320","author":"Vajdos","year":"2002","journal-title":"J. Mol. Biol."},{"key":"2026091409084409100_cit7","doi-asserted-by":"publisher","DOI":"10.1038\/s42004-023-01037-7","article-title":"Enhancing antibody affinity\nthrough experimental sampling of non-deleterious CDR mutations predicted\nby machine learning","volume":"6","author":"Clark","year":"2023","journal-title":"Commun. Chem."},{"issue":"6","key":"2026091409084409100_cit8","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbae488","article-title":"Development and experimental\nvalidation of computational methods for human antibody affinity enhancement","volume":"25","author":"Li","year":"2024","journal-title":"Briefings Bioinf."},{"issue":"6","key":"2026091409084409100_cit9","doi-asserted-by":"publisher","first-page":"478","DOI":"10.1002\/jmr.808","article-title":"Survey of the year 2005 commercial optical biosensor\nliterature","volume":"19","author":"Rich","year":"2006","journal-title":"J. Mol. 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