Msc. Bioinformatics SBI - PYT project Based on Kandel, J., Tayara, H. & Chong, K.T. PUResNet: prediction of protein-ligand binding sites using deep residual neural network. J Cheminform 13, 65 (2021). https://doi.org/10.1186/s13321-021-00547-7
Núria Fàbrega - Marc Ciruela - 2023
In this repository you can find all the files needed to execute the binding site predictor. But there are more files included that explain the process followed to obtain the current model.
Folder BSPredictor contains Python scripts needed to run the binding site predictor, validation and to build a new model.
Folder scPDB clustering cotains the Jupyter notebooks used to build the training and validation set for the current model.
Folder Validation contains the scripts used to calculate metrics on our model.
All scripts and jupyter notebooks that are mentioned in the writen document are inside some of these directories.
Please consult the enclosed pdf document with tutorial and more information before runing any prediction. It is imporotant to have all dependencies installed before trying to run any of the scripts.