Reconstruction and Re-evaluation of SFCNN for PLA Scoring

This project reconstructs and re-evaluates the SFCNN (Scoring Function 3D Convolutional Neural Network) for protein-ligand binding affinity prediction. The implementation is available in the SFCNN_PLA_torch repository.

Work completed

• Constructed a PyTorch implementation of the model architecture, training procedure, and evaluation pipeline.
• Developed a benchmark that allows related models to infer directly from the 3D structure of protein-ligand complexes instead of using decoupled protein and ligand structures.