| --- |
| tags: |
| - molecules |
| - chemistry |
| - SMILES |
| --- |
| |
| ## How to use the data sets |
|
|
| This dataset contains more than 16,000 unique pairs of protein sequences and ligand SMILES, and the coordinates |
| of their complexes. |
|
|
| SMILES are assumed to be tokenized by the regex from P. Schwaller |
|
|
| Every (x,y,z) ligand coordinate maps onto a SMILES token, and is *nan* if the token does not represent an atom |
|
|
| Every receptor coordinate maps onto the Calpha coordinate of that residue. |
|
|
| The dataset can be used to fine-tune a language model, all data comes from PDBind-cn. |
|
|
| ### Use the already preprocessed data |
|
|
| Load a test/train split using |
|
|
| ``` |
| from datasets import load_dataset |
| train = load_dataset("jglaser/pdbbind_complexes",split='train[:90%]') |
| validation = load_dataset("jglaser/pdbbind_complexes",split='train[90%:]') |
| ``` |
|
|
| ### Pre-process yourself |
|
|
| To manually perform the preprocessing, download the data sets from P.DBBind-cn |
|
|
| Register for an account at <https://www.pdbbind.org.cn/>, confirm the validation |
| email, then login and download |
|
|
| - the Index files (1) |
| - the general protein-ligand complexes (2) |
| - the refined protein-ligand complexes (3) |
|
|
| Extract those files in `pdbbind/data` |
|
|
| Run the script `pdbbind.py` in a compute job on an MPI-enabled cluster |
| (e.g., `mpirun -n 64 pdbbind.py`). |
|
|
