SAbDab: the structural antibody database
Open accessAbstract
Structural antibody database (SAbDab; http://opig.stats.ox.ac.uk/webapps/sabdab) is an online resource containing all the publicly available antibody structures annotated and presented in a consistent fashion. The data are annotated with several properties including experimental information, gene details, correct heavy and light chain pairings, antigen details and, where available, antibody-antigen binding affinity. The user can select structures, according to these attributes as well as structural properties such as complementarity determining region loop conformation and variable domain orientation. Individual structures, datasets and the complete database can be downloaded.
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According to specific criteria, antibody structures from the PDB are listed in SAbDab, a database containing 12,367 Fv region structures as of June 2022, and abYsis.
“Similarly, according to specific criteria, antibody structures from the PDB are listed in the Structural Antibody Database (SAbDab) [13], a database containing 12 367 Fv region structures as of June 2022, and abYsis [14].”
From Computational and artificial intelligence-based methods for antibody development (2023) · cites this paper as [13]
According to SAbDab, of the approximately 150,000 structures deposited in the PDB to date as many as 3500 are identified as containing at least one antibody (or nanobody) chain.
“According to SAbDab, of the approximately 150 000 structures deposited in the PDB to date as many as 3500 are identified as containing at least one antibody (or nanobody) chain.”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [16]
The increasing number of structural, sequence and experimental data on antibodies being deposited in the public domain provides the necessary foundation for improving data-driven methods.
“The increasing number of structural [16], sequence [17] and experimental data [18–21] on antibodies being deposited in the public domain provides the necessary foundation for improving such data-driven methods.”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [16]
SAbDab specifically allows for a bulk download of its weekly updatable database, providing an up-to-date resource for applications such as antibody modelling or docking.
“SAbDab specifically allows for a bulk download of its weekly updatable database, providing an up-to-date resource for applications such as antibody modelling or docking.”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [16]
SabDab and Abysis allow retrieval of particular structures given a query antibody sequence (SAbDab) or by using more advanced features such as canonical classes of the CDRs (Abysis).
“SabDab and Abysis allow retrieval of particular structures given a query antibody sequence (SAbDab) or by using more advanced features such as canonical classes of the CDRs (Abysis).”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [16]
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- Authors
- Dunbar, J., Krawczyk, K., Leem, J., Baker, T., Fuchs, A., Georges, G., Shi, J., & Deane, C. M.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Deane, Charlotte M.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-11-08
- Volume
- 42
- Issue
- D1
- Pages
- D1140-D1146
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC3965125
- OpenAlex
- W2110505462
- Cited by
- 674
- References
- 38
- Citations by year
- 2026: 126 · 2025: 130 · 2024: 94 · 2023: 74 · 2022: 73 · 2021: 45 · 2020: 24 · 2019: 22 · 2018: 27 · 2017: 20 · 2016: 18 · 2015: 12 · 2014: 9
- FWCI
- 10.07
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nucleic Acids Research (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Oxford University Research Archive (ORA) (University of Oxford) (acceptedVersion, cc-by)
- Funders
- Engineering and Physical Sciences Research Council (EP/K032402/1, 1231608)
- 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
- antibody structure, antibody affinity, hypervariable region, protein structure annotation
- MeSH terms
- Antibodies, Antibody Affinity, Binding Sites, Antibody, Terminology as Topic, Protein Conformation, Internet, Complementarity Determining Regions, Databases, Protein
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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