Use POINTNET files to generate point cloud data for proteins and ligands.All data must be in PDB format. All data should remove solvents, metals and ions. And use openbabel to add polar hydrogen (--AddPolarH)
./POINTNET {protein_path} {ligand_path} {out_path}
./POINTNET-2048 {protein_path} {ligand_path} {out_path}
./POINTNET-atomchannel {protein_path} {ligand_path} {out_path}
- Installation dependent environment
conda create -n point_cloud_envs
conda activate point_cloud_envs
conda install python=3.7
conda install pytorch torchvision torchaudio cudatoolkit=11.1 -c pytorch -c conda-forge- Prediction
python pred.py --file ./example/5c2h_11.09 --model PointTransformer
Other model parameters can be downloaded here
The machine learning script, as well as the training and test data, are available via the URL below.
Feature and script here
model for extract feature here
Download the PDBBind all data and Bigdata point cloud data using the URL below.
PDBBind all data here