1. Abstract

There are codes, processed data and trained models for submission paper "Predicting Protein-Ligand Binding Affinity via Joint Global-Local Interaction Modeling" in ICDM 2022.

2. Processed data

Limited to the size of attachments, we only upload PDBbind 2016 core dataset and CSAR-HiQ dataset to test the trained models.

• PDBbind v2016 core set: ./data/2016_core_data
• CSAR-HiQ (including set1, set2): ./data/CSAR_HiQ_data

3. Code

• The code for our GLI model in ./models/global_local_interaction_model.py.
• The code for related baselines models in ./models/baseline_models.py
• The code for evaluating and test in ./test_model.py

4. Environments

• cuda: 11.0
• GPU: V100
• Packages: The required python package are listed in requirements.txt

5. Trained models and test command

In our submission, we used 10 fold-cross validation to evaluate our GLI framework performance. We provide some trained models in ./trained_models which were trained in PDBbind v2016 refined dataset, and tested in PDBbind v2016 core dataset and CASR-HiQ dataset.

To indicate the GLI framework based on different models:

• GLI-0: Taking GAT+GCN as the model in chemical info embedding module.
• GLI-1: Taking GIN as the model in chemical info embedding module.
• GLI-2: Taking GCN2 as the model in chemical info embedding module.

To indicate the GLI framework with different modules:

• GLI-*-c: Including chemical info embedding module.
• GLI-*-cg: Including chemical info embedding module, global interaction module.
• GLI-*-cl: Including chemical info embedding module, local interaction module.
• GLI-*-cgl: Including chemical info embedding module, global interaction module, local interaction module.

5.1 test models GLI-0-c, GLI-1-c, GLI-2-c

Command:

python test_model.py GLI-0-c
python test_model.py GLI-1-c
python test_model.py GLI-2-c

5.2 test models GLI-0-cg, GLI-1-cg, GLI-2-cg

Command:

python test_model.py GLI-0-cg
python test_model.py GLI-1-cg
python test_model.py GLI-2-cg

5.3 test models GLI-0-cl, GLI-1-cl, GLI-2-cl

Command:

python test_model.py GLI-0-cl
python test_model.py GLI-1-cl
python test_model.py GLI-2-cl

5.4 test models GLI-0-cgl, GLI-1-cgl, GLI-2-cgl

Command:

python test_model.py GLI-0-cgl
python test_model.py GLI-1-cgl
python test_model.py GLI-2-cgl