Datasets › MIPE
MIPE (Improving Paratope and Epitope Prediction by Multi-Modal Contrastive Learning and Interaction Informativeness Estimation)
Datasets. From the publicly accessible Structural Antibody Database (SAbDab), we collected a total of 7571 antibodyantigen complexes, with the sequence data in FASTA format and structural data in PDB format. Following previous studies [Pittala and Bailey-Kellogg, 2020], we used CD-HIT [Li and Godzik, 2006] to remove high-homology antibody and antigen sequences with the thresholds of 95% and 90% sequence identity, respectively. Subsequently, we excluded antibodies and antigens with any residue type rather than 20 naturally occurring types. Finally, we compiled a dataset consisting of 626 binding antibody-antigen pairs, including their sequences, structures, and corresponding interaction maps. Noteworthy, antibodies primarily bind to antigens through their CDR regions. Most researchers use Euclidean distance to define paratopes and epitopes, and we follow the usual way in our dataset: within the CDR regions/antigen, a residue is labeled as a paratope/epitope if the Euclidean distance between its backbone atom and any backbone atom on the other antigen/CDR regions is less than 4.5 ˚ A.
Benchmarks archive 2025-07-28
All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Antibody-antigen binding prediction | MIPE | ParaSurf AUC-PR 0.781 | ParaSurf: A Surface-Based Deep Learning Approach for... | aggelos-michael-papadopoulos/ParaSurf | 7 | Compare |
Papers archive 2025-07-28
7 shown of 7 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 7. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| ParaSurf: A Surface-Based Deep Learning Approach for Paratope-Antigen Interaction Prediction | 1 | 1 | 8 Feb 2025 | not harvested |
| Improving Paratope and Epitope Prediction by Multi-Modal Contrastive Learning and Interaction Informativeness Estimation | 1 | 1 | 31 May 2024 | not harvested |
| PeSTo: parameter-free geometric deep learning for accurate prediction of protein binding interfaces | 1 | 1 | 18 Apr 2023 | not harvested |
| Paragraph—antibody paratope prediction using graph neural networks with minimal feature vectors | 1 | 1 | 12 Oct 2022 | not harvested |
| Learning context-aware structural representations to predict antigen and antibody binding interfaces | 1 | 1 | 22 Apr 2020 | not harvested |
| Attentive cross-modal paratope prediction | 0 | 1 | 12 Jun 2018 | not harvested |
| Parapred: antibody paratope prediction using convolutional and recurrent neural networks | 1 | 1 | 16 Apr 2018 | not harvested |
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
MIT
Modalities archive 2025-07-28
Languages archive 2025-07-28
Variants archive 2025-07-28
- MIPE
1 variant name, as the archive lists them.
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