readme.txt

prerequirment:

anaconda python 2.7
tensorflow
keras
scklearn
numpy
pandas



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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

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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