A DEEP LEARNING BASED METHOD FOR ESTIMATING EFFECTIVE PROTEIN-LIGAND AFFINITY
prerequirment:
anaconda python 2.7 tensorflow keras scklearn numpy pandas
################## ################# For testing cases that have experimental value step 1: unzip the all_data/data.zip, by cd all_data; unzip data.zip
step 2: got the performance estimator(r value, rmse, etc) by: python deep_learn_rob_residual_zhpxxx_n_regression_load_drop50.py
step 3: list the vina score, the DeepBindRG prediction value, and the experimental value (all_energies.sort is the output file from vina docking) python perform_vina.py
check the output file out_list.csv
collumn 1-4 are : name,experiment value, DeepBindRG value, Vina value
############################ ############################ For application cases that have no experimental value:
python deep_learn_rob_residual_zhpxxx_n_regression_load_drop50_use.py
check the out_file.csv
Citation: DeepBindRG: a deep learning based method for estimating effective protein-ligand affinity
If there is any technique problem, please no hestitated to contact by email [email protected].