| --- |
| tags: |
| - chemistry |
| - smiles |
| - molecules |
| - cheminformatics |
| - classification |
| pretty_name: Cocrystal Classification |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # Cocrystal Classification |
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| Binary classification dataset for predicting cocrystal formation given two small molecules represented as SMILES. |
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| For single‑sequence encoder models (e.g., BERT‑style), we provide `smiles`, which concatenates `smiles_a` and `smiles_b` with a period separator: `smiles_a.smiles_b`. For Bi-encoder and Cross‑encoder models, use the provided `smiles_a` and `smiles_b` fields directly. |
|
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| ## Source |
| - [Original dataset page](https://sites.google.com/view/medardemswahili/publications-awards#h.kcrgyq3r642s) |
|
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| ## Data fields |
| - `smiles_a` (string): Active Pharmaceutical Ingredient (API) SMILES. Unmodified from the source. |
| - `smiles_b` (string): Coformer SMILES. Unmodified from the source. |
| - `smiles` (string): Concatenation of `smiles_a` and `smiles_b` with a period, for encoder models. |
| - `label` (int): Binary class, {0: None, 1: Cocrystal}. |
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|
| ## Citation |
| Mswahili, M.E.; Lee, M.-J.; Martin, G.L.; Kim, J.; Kim, P.; Choi, G.J.; Jeong, Y.-S. Cocrystal Prediction Using Machine Learning Models and Descriptors. Applied Sciences, 2021, 11, 1323. https://doi.org/10.3390/app11031323 |
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| Please cite the authors above if you use this dataset. |
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