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## How to use the data sets |
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### Use the already preprocessed data |
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The file `data/all.parquet` contains the preprocessed data. Load the dataset using |
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``` |
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from datasets import load_dataset |
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dataset = load_dataset("jglaser/binding_affinity") |
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``` |
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### Pre-process yourself |
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To manually perform the preprocessing, fownload the data sets from |
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1. BindingDB |
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In `bindingdb`, download the database as tab separated values |
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[https://bindingdb.org] > Download > BindingDB_All_2021m4.tsv.zip |
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and extract the zip archive into `bindingdb/data` |
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Run the steps in `bindingdb.ipynb` |
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2. PDBBind-cn |
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Register for an account at [https://www.pdbbind.org.cn/], confirm the validation |
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email, then login and download |
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- the Index files (1) |
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- the general protein-ligand complexes (2) |
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- the refined protein-ligand complexes (3) |
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Extract those files in `pdbbind/data` |
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Run the script `pdbbind.py` in a compute job on an MPI-enabled cluster |
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(e.g., `mpirun -n 64 pdbbind.py`). |
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Perform the steps in the notebook `pdbbind.ipynb` |
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3. BindingMOAD |
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Go to [https://bindingmoad.org] and download the files `every.csv` |
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(All of Binding MOAD, Binding Data) and the non-redundant biounits |
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(`nr_bind.zip`). Place and extract those files into `binding_moad`. |
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Run the script `moad.py` in a compute job on an MPI-enabled cluster |
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(e.g., `mpirun -n 64 moad.py). |
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Perform the steps in the notebook `moad.ipynb` |
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4. BioLIP |
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Download from [https://zhanglab.ccmb.med.umich.edu/BioLiP/] the files |
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- receptor_nr1.tar.bz2 (Receptor1, Non-redudant set) |
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- ligand_nr.tar.bz2 (Ligands) |
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- BioLiP_nr.tar.bz2 (Annotations) |
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and extract them in `biolip/data`. |
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Run the script `biolip.py` in a compute job on an MPI-enabled cluster |
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(e.g., `mpirun -n 64 biolip.py). |
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Perform sthe steps in the notebook `biolip.ipynb` |
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5. Final concatenation and filtering |
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Run the steps in the notebook `combine_dbs.ipynb` |
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