AbDb: antibody structure database-a database of PDB-derived antibody structures
Open accessAbstract
In order to analyse structures of proteins of a particular class, these need to be extracted from Protein Data Bank (PDB) files. In the case of antibodies, there are a number of special considerations: (i) identifying antibodies in the PDB is not trivial, (ii) they may be crystallized with or without antigen, (iii) for analysis purposes, one is normally only interested in the Fv region of the antibody, (iv) structural analysis of epitopes, in particular, requires individual antibody–antigen complexes from a PDB file which may contain multiple copies of the same, or different, antibodies and (v) standard numbering schemes should be applied. Consequently, there is a need for a specialist resource containing pre-numbered non-redundant antibody Fv structures with their cognate antigens. We have created an automatically updated resource, AbDb, which collects the Fv regions from antibody structures using information from our SACS database which summarizes antibody structures from the PDB. PDB files containing multiple structures are split and numbered and each antibody structure is associated with its antigen where available. Antibody structures with only light or heavy chains have also been processed and sequences of antibodies are compared to identify multiple structures of the same antibody. The data may be queried on the basis of PDB code, or the name or species of the antibody or antigen, and the complete datasets may be downloaded. Database URL: www.bioinf.org.uk/abs/abdb/
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Fv regions from antibodies have been updated in the Antibody Structure Database (AbDb) using information from the Summary of Antibody Crystal Structures (SACS) dataset.
“Fv regions from the antibody have been updated in the Antibody Structure Database (AbDb) using information from the Summary of Antibody Crystal Structures (SACS) dataset [12].”
From Computational and artificial intelligence-based methods for antibody development (2023) · cites this paper as [12]
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BackgroundComputational and artificial intelligence-based methods for antibody development
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“A detailed side-by-side evaluation of available databases (NAStructuralDB, SabDab (Dunbar et al. 2014), AbDb (Ferdous and Martin 2018), AACDB (Zhou et al. 2024), SAAINT-DB (Huang et al. 2025), IMGT/3Dstructure-DB (Ehrenmann, Kaas, and Lefranc 2010) and SNAC-DB (Gupta et al. 2025)).”
- Authors
- Ferdous, S., & Martin, A. C. R.
- Affiliations
- Institute of Structural and Molecular Biology (GB)
- Corresponding author
- Martin, Andrew C R
- Venue
- Database
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-01-01
- Volume
- 2018
- ISSN
- 1758-0463 (ISSN-L)
- PMC
- PMC5925428
- OpenAlex
- W2801127413
- Cited by
- 87
- References
- 24
- Citations by year
- 2026: 8 · 2025: 20 · 2024: 15 · 2023: 8 · 2022: 12 · 2021: 12 · 2020: 5 · 2019: 5 · 2018: 2
- FWCI
- 4.15
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Database (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Monoclonal and Polyclonal Antibodies Research
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Keywords
- immune complexes, Protein Data Bank
- MeSH terms
- Protein Domains, Animals, Antibodies, Humans, Databases, Protein
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