{"doi":"10.1093/nar/gkae840","title":"TCR3d 2.0: expanding the T cell receptor structure database with new structures, tools and interactions","abstract":"Recognition of antigens by T cell receptors (TCRs) is a key component of adaptive immunity. Understanding the structures of these TCR interactions provides major insights into immune protection and diseases, and enables design of therapeutics, vaccines and predictive modeling algorithms. Previously, we released TCR3d, a database and resource for structures of TCRs and their recognition. Due to the growth of available structures and categories of complexes, the content of TCR3d has expanded substantially in the past 5 years. This expansion includes new tables dedicated to TCR mimic antibody complex structures, TCR-CD3 complexes and annotated Class I and II peptide-MHC complexes. Additionally, tools are available for users to calculate docking geometries for input TCR and TCR mimic complex structures. The core tables of TCR-peptide-MHC complexes have grown by 50%, and include binding affinity data for experimentally determined structures. These major content and feature updates enhance TCR3d as a resource for immunology, therapeutics and structural biology research, and enable advanced approaches for predictive TCR modeling and design. TCR3d is available at: https://tcr3d.ibbr.umd.edu.","journal":"Nucleic Acids Research","year":2024,"id":422693,"datarank":0.6643163229590641,"base_score":3.295836866004329,"endowment":3.295836866004329,"self_citation_contribution":0.4943755299006494,"citation_network_contribution":0.1699407930584147,"self_endowment_contribution":0.4943755299006494,"citer_contribution":0.1699407930584147,"corpus_percentile":69.90794461205229,"corpus_rank":3891,"citation_count":26,"citer_count":22,"citers_with_citation_signal":10,"citers_with_endowment":10,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.9214,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":52.0833,"fair_percentile":67.4411494955671,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1019777,"name":"Melyssa Cheung","orcid":"0000-0002-3232-2034","position":1,"is_corresponding":false},{"id":274871,"name":"Ragul Gowthaman","orcid":"0000-0002-0008-6401","position":2,"is_corresponding":false},{"id":1217662,"name":"M A Eisenberg","orcid":null,"position":3,"is_corresponding":false},{"id":299086,"name":"Brian M. Baker","orcid":"0000-0002-0864-0964","position":4,"is_corresponding":false},{"id":281772,"name":"Brian G. Pierce","orcid":"0000-0003-4821-0368","position":5,"is_corresponding":false},{"id":1019776,"name":"Valerie C. L. Lin","orcid":"0000-0002-7997-2771","position":0,"is_corresponding":true}],"reference_count":43,"raw_metadata":null,"created_at":"2026-07-19T01:57:51.642883Z","pmid":"39329260","pmcid":"PMC11701517","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":50.0,"fair_a":75.0,"fair_i":20.0,"fair_r":45.8333,"fair_zscore":0.698,"fair_rationale":{"fair_score":52.08,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":50.0,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"TCR3d is freely available at: https://tcr3d.ibbr.umd.edu","grounded":true,"rationale":"The dataset is identified by a URL, not a persistent identifier scheme.","anchors":["RDA-F1-01D — FAIR Data Maturity Model: 'Data is identified by a persistent identifier' (priorit","RDA-F1-02D — FAIR Data Maturity Model: 'Data is identified by a globally unique identifier'","FsF-F1-02D — F-UJI/FAIRsFAIR: 'Data is assigned a persistent identifier'"],"scored":true,"signal":null},{"key":"f_repository_named","label":"Named repository","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"TCR3d is freely available at: https://tcr3d.ibbr.umd.edu","grounded":true,"rationale":"The host is an institutional website, not a curated repository from the list.","anchors":["RDA-F4-01M — FAIR Data Maturity Model: metadata is offered so it can be harvested and indexed (","NIH DMS Policy Element 4 (NOT-OD-21-014) — name the repository where data will be archived","NSTC Desirable Characteristics of Data Repositories (2022) — 'Long-Term Sustainability', 'Reten"],"scored":true,"signal":null},{"key":"f_data_availability_statement","label":"Data-availability statement","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"TCR3d is freely available at: https://tcr3d.ibbr.umd.edu","grounded":true,"rationale":"The statement points to a URL, not a repository record with an accession. 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[majority verdict 'no' (4/5 passes agreed)]","gain":0.0,"priority":"useful","scored":false}],"suggestions":["Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For proteomics data, deposit in PRIDE (PXD accession) or ProteomeXchange.","Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. For proteomics data, deposit in PRIDE (PXD accession) or ProteomeXchange.","Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable. Prefer open proteomics formats such as mzML or mzIdentML.","Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the proteomics repository accession (e.g. from PRIDE (PXD accession) or ProteomeXchange) in the reference list."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v8","fulltext_source":"epmc_xml"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v8","fair_fulltext_source":"epmc_xml","fair_has_llm":true,"fair_computed_at":"2026-07-20T11:42:05.837252Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}