SadNet/
│
└── convert.py #Convert Data Types if you need
└── extract aC.py #Generate seq.fasta, which will be used in parse data.py
└── get_name.py #Generate a training directory based on the PDBbind dataset, which is necessary for training.py
└── training.py #Execute training, the file will automatically call parse_data.py, GraphPairDataset.py, and finally generate the training model
└── parse_data.py #Process the data set and divide it into training set, validation set, and test set
└── GraphPairDataset.py #Build graph data for input intothe model
└── model_test.py #test your model
└── vision.py #Generate visualizations, as shown in the paper