bgao95/SIU

1. Files

gnn_cnn_data.zip

The dataset used to train gnn and cnn-3d model.

split_60.zip

The dataset used to train Uni-Mol or ProFSA model for the SIU 0.6 version. It contains train.lmdb, valid.lmdb and test.lmdb.

split_90.zip

The dataset used to train Uni-Mol or ProFSA model for the SIU 0.9 version. It contains train.lmdb, valid.lmdb and test.lmdb.

pretrain_weights.zip

Pretrained weights for Uni-Mol and ProFSA.

profsa.pt: weights for pretrained ProFSA model

mol_pre_no_h_220816.pt: weights for pretrained Uni-Mol molecular Encoder

pocket_pre_220816.pt: weights for pretrained Uni-Mol pocketr Encoder

final_dic.pkl

Complete dataset file in pickle format

result_structures.zip

contains all structure files for protein and docked small molecules.

2. Dataset Format

final_dic.pkl

each key is an uniprot id

corresponding value is a list of dictionaries. Each dictionary is a data point and has following keys:

Key	Description
atoms	atom types in ligand
coordinates	list of different conformations of the ligand
pocket_atoms	atom types in pocket
pocket_coordinates	atom positions of the pocket
source_data	pdbid and uniprot id information
label	dictionary for different labels
ik	inchikey of ligand
smi	smiles of ligand

Other lmdb files

All data are in lmdb format, and have the same keys as shown above.

Note that for single task learning, the albel is a float value instead of a dictionary.