RosettaCommons/SAbDab
ML Application Curated SAbDab Quickstart Usage Install HuggingFace Datasets package Each subset can be loaded into python using the Huggingface datasets library. First, from the command line install the datasets library $ pip install datasets Optionally set the cache directory, e.g. $ HF_HOME=${HOME}/.cache/huggingface/ $ export HF_HOME then, from within python load the datasets library >>> import datasets Load model datasets To… See the full description on the dataset page: https://huggingface.co/datasets/RosettaCommons/SAbDab.
ML Application Curated SAbDab
Quickstart Usage
Install HuggingFace Datasets package
Each subset can be loaded into python using the Huggingface datasets library. First, from the command line install the datasets library
$ pip install datasets
Optionally set the cache directory, e.g.
$ HFHOME=${HOME}/.cache/huggingface/ $ export HFHOME
then, from within python load the datasets library
>> import datasets
Load model datasets
To load structures from the entire SAbDab dataset, use datasets.load_dataset(...):
>> SAbDab= datasets.load_dataset("RosettaCommons/SAbDab")
Downloading readme: 7.87kB [00:00, 2.73MB/s] Downloading data: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████| 15.7M/15.7M [00:01<00:00, 8.22MB/s] Generating train split: 100%|████████████████████████████████████████████████████████████████████████████████| 20700/20700 [00:00<00:00, 80378.32 examples/s]
and the dataset is loaded as a datasets.arrow_dataset.Dataset
>> SAbDab
DatasetDict({ train: Dataset({ features: ['pdb', 'Hchain', 'Lchain', 'model', 'antigenchain', 'antigentype', 'antigenhetname', 'antigenname', 'shortheader', 'date', 'compound', 'organism', 'heavyspecies', 'lightspecies', 'antigenspecies', 'authors', 'resolution', 'method', 'rfree', 'rfactor', 'scfv', 'engineered', 'heavysubclass', 'lightsubclass', 'lightctype', 'affinity', 'deltag', 'affinitymethod', 'temperature', 'pmid', 'abangle', 'annotationH', 'annotationL', 'imgtH', 'imgtL', 'sequenceraw', 'sequenceH', 'sequenceL', 'structure', 'structurechothia', 'innrset', 'curatedqualitydataset', 'split'], num_rows: 20700 }) })
which is a column oriented format that can be accessed directly, converted in to a pandas.DataFrame, or parquet format, e.g.
>> SAbDab.data.column('pdb') >> SAbDab.topandas() >> SAbDab.toparquet("dataset.parquet")
Dataset Details
Dataset Description
This dataset contains curated data from the SAbDab as of Mar 4, 2026. The SAbDab is a database of antibody structures including experimental details, antibody nomenclature, affinity data and sequence annotations. Additional datasets include a ‘innrset’ that was assembled by querying SAbDab with Max. sequence identity 90% and ‘curatedqualitydataset’ that was assembled by querying SAbDab with Max. sequence identity 90%, bound structures, resolution below 4.0 Å. We also performed multivariate stratification on "antigentype", "heavyspecies", "method", "scfv", "engineered", "lightctype", "innrset", "curatedquality_dataset" to achieve an 80/10/10 train/test/validation split
- Acknowledgements: We kindly acknowledge the SAbDab team, RosettaCommons, and the following institutions: University of California, Los Angeles; University of Maryland; University of Oregon; University of Michigan; University of Pennsylvania; and the Wistar Institute.
- License: CC-BY 4.0
Dataset Sources
- Paper: Dunbar, J., Krawczyk, K. et al (2014). Nucleic Acids Res. 42. D1140-D1146
Uses
Screening of antibody-antigen interactions, querying structural features of antibodies, and more
Citation
@article{10.1093/nar/gkt1043, author = {Dunbar, James and Krawczyk, Konrad and Leem, Jinwoo and Baker, Terry and Fuchs, Angelika and Georges, Guy and Shi, Jiye and Deane, Charlotte M.}, title = {SAbDab: the structural antibody database}, journal = {Nucleic Acids Research}, volume = {42}, number = {D1}, pages = {D1140-D1146}, year = {2013}, month = {11}, abstract = {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.}, issn = {0305-1048}, doi = {10.1093/nar/gkt1043}, url = {https://doi.org/10.1093/nar/gkt1043}, eprint = {https://academic.oup.com/nar/article-pdf/42/D1/D1140/3538157/gkt1043.pdf} }
Dataset Card Authors
Miranda Simpson (miranda13nicoles@gmail.com), Becca Lee (beccalee5@g.ucla.edu), Nathaniel Felbinger (nfelbing@umd.edu), Pratyush Dhal (pdhal@umich.edu), Colby Agostino (colby.agostino@pennmedicine.upenn.edu)
