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SAbDab2 Machine Learning Dataset
Clean, curated antibody and antibody–antigen-complex structures from SAbDab2, specifically post-processed for ML applications, alongside standardised train/test-splits. The current releas
File Size848.1 MB
Data TypeDataset
Published2026
Licensecc-by-4.0
Total Views3,837
Total Downloads2,811
Clean, curated antibody and antibody–antigen-complex structures from SAbDab2, specifically post-processed for ML applications, alongside standardised train/test-splits.
The current release contains 15,810 structures from 8,796 PDB IDs, corresponding to 5,424 unique antibodies (SAbDab2 IDs), composed as follows:
| antibody type | with antigen | no antigen | total structures |
| paired-chain (FV-like) |
8230 (52.1%)
|
4137 (26.2%)
|
12367 (78.2%)
|
| single-domain heavy (VHH-like) |
2083 (13.2%)
|
1235 (8.0%)
|
3318 (21.0%)
|
| single-domain light (VL-like) |
37 (0.2%)
|
27 (0.2%)
|
64 (0.4%)
|
| VNAR | 45 (0.3%) | 16 (0.1%) | 61 (0.4%) |
| total structures |
10395 (65.7%)
|
5415 (34.3%) |
15810 (100.0%)
|
Each structure file contains a single paired-chain or single-chain antibody, cropped to the variable region, alongside any antigen chains. Around 7.9% of structures bind antigens consisting of multiple polymer chains.
We provide two distinct train/test splits of these structures, both based on sequence similarity.
- The ab-split (
ab_split.csv) accounts for similarity between antibody sequences. To avoid data leakage via the antigen, use this only for antigen-agnostic tasks like prediction of antibody structure in solution. - The ab-ag-split (
abag_split.csv) additionally considers similarity between any protein, peptide, DNA and RNA antigen sequences. Use this for antigen-aware tasks like antibody–antigen complex modelling.
These same splits are also available filtered down to just single-domain (VHH-like and VL-like) structures (
ab_split_sd.csv and abag_split_sd.csv).Unless otherwise noted, splits are backward-compatible, allowing models trained on previously published versions of this dataset to be benchmarked on the most recent test split.
More details in the
README.md accompanying this download.<
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Files are hosted on the source repository. Click download to access the full dataset.
Capel, Henriette L. (2026). SAbDab2 Machine Learning Dataset. https://doi.org/10.5281/zenodo.22019991