A comparative and ablation study exploring different models for protein-ligand binding affinity prediction. The model categories studied in this project include traditional machine learning, graph neural networks, and structural deep learning models.
machine-learning bioinformatics cheminformatics protein-data-bank rdkit transfer-learning uniprot bindingdb 3d-cnn protein-ligand-binding-affinity multimodal-learning graph-attention-networks graph-neural-networks pytorch-geometric molecular-graphs plip computational-drug-discovery rcsb-pdb pdbbind structural-deep-learning
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Updated
Jul 18, 2026 - Jupyter Notebook