{"doi":"10.1016/j.jsb.2025.108166","title":"RosettaHDX: Predicting antibody-antigen interaction from hydrogen-deuterium exchange mass spectrometry data","abstract":"• A Rosetta method incorporating HDX-MS data to model Ab-Ag complexes is introduced • HDX-MS-guided sampling generated more near-native models for all benchmark complexes. • Docking performance is improved with as little as one HDX interacting peptide. • Results from docking with HDX can uncover allosteric peptides. High-throughput characterization of antibody-antigen complexes at the atomic level is critical for understanding antibody function enabling therapeutic development. Hydrogen-deuterium exchange mass spectrometry (HDX-MS) enables rapid epitope mapping, but its data are too sparse for independent structure determination. In this study, we introduce RosettaHDX, a hybrid method that combines computational docking with differential HDX-MS data to enhance the accuracy of antibody-antigen complex models beyond what either method can achieve individually. By incorporating HDX data as both distance restraints and a scoring term in the RosettaDock algorithm, RosettaHDX successfully generated near-native models (interface root-mean square deviation ≤ 4 Å) for all 9 benchmark complexes examined, averaging 3.6 times more near-native models than Rosetta alone. Near-native models among the top 10 scoring were identified in 3/9 cases, compared to 1/9 with Rosetta alone. Additionally, we developed a predictive metric based on docking results with HDX restraints to identify allosteric peptides in HDX datasets.","journal":"Journal of Structural Biology","year":2025,"id":520267,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":5,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9547,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":655135,"name":"Cristina E. Martina","orcid":"0000-0001-6526-9180","position":1,"is_corresponding":false},{"id":36760,"name":"Rocco Moretti","orcid":"0000-0003-2162-1116","position":2,"is_corresponding":false},{"id":679475,"name":"Marcus Nagel","orcid":null,"position":3,"is_corresponding":false},{"id":390309,"name":"Kevin L. Schey","orcid":"0000-0002-3959-1712","position":4,"is_corresponding":false},{"id":36757,"name":"Jens Meiler","orcid":"0000-0001-8945-193X","position":5,"is_corresponding":false},{"id":678300,"name":"Minh H. Tran","orcid":"0000-0002-3093-3659","position":0,"is_corresponding":true}],"reference_count":83,"raw_metadata":null,"created_at":"2026-07-19T02:49:28.470782Z","pmid":"39765317","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}