| --- |
| license: mit |
| language: |
| - en |
| tags: |
| - PyTorch |
| - PyTorch Geometric |
| pipeline_tag: graph-ml |
| --- |
| |
| # Multi-Head Graph Isomorphism Network (GINE) for Molecular Property Prediction |
|
|
| This is a Multi-Head Graph Isomorphism Network (GINE) model designed for predicting molecular properties such as lipophilicity, molecular weight, hydrogen bond donor count, and hydrogen bond acceptor count from SMILES strings. The model takes a SMILES string as input, converts it into a graph representation, and outputs the predicted properties. |
| Training data from ChemBL library |
|
|
| Full project file at https://github.com/teohyc/drug_agent |
| |
| |
| ## Usage |
| |
| ```python |
| from prop_gnn_infer import predict_mol |
| from prop_gnn_model import MoleculeGINE |
|
|
| #change to your test SMILES strings |
| print(predict_mol(test_smiles=["O=C1N=C2SCCN2C(=O)C1Cc1ccc(Cl)cc1", "C[C@@H]1C[C@H]2[C@@H]3CCC4=CC(=O)C=C[C@]4(C)[C@@]3(F)[C@@H](O)C[C@]2(C)[C@@]1(C)C(=O)CO"])) |
| ``` |
