solubility's Introduction

solubility

An implementation of Delaney's ESOL method using the RDKit

ESOL:  Estimating Aqueous Solubility Directly from Molecular Structure 
John S. Delaney, J. Chem. Inf. Comput. Sci., 2004, 44, 1000 - 1005
https://pubs.acs.org/doi/abs/10.1021/ci034243x

There are 4 scripts in this repo.

esol.py - has the routines to calculate ESOL and few associated utility functions. Depends on the RDKit, pandas and scikit learn, all of which are part of the RDKit distribution. See the RDKit site for installation instructions.
solubility_comparison.py - compares ESOL calculation with 3 models calculated by DeepChem (Random Forest, Weave, Graph Convolution). Requires a DeepChem installation. See the DeepChem site for installation instructions.
evaluate_results.py - compares results calculated in solubility_comparison.py and generates a couple of plots. Requires matplotlib and and scipy.

pip install matplotlib scipy

confidence_interval_vs_correlation.py - generates a plot showing the relationship between correlation, number of datapoints and confidence intervals. Same requirements as evaluate_results.py.

The repo also contains 2 datafiles.

delaney.csv - a csv file with data from the supporting material for https://pubs.acs.org/doi/abs/10.1021/ci034243x
dls_100_unique.csv - csv file with solubility data for 56 compounds not in the delaney.csv. Note that the original file from the University of St Andrews https://doi.org/10.17630/3a3a5abc-8458-4924-8e6c-b804347605e8 has 100 compounds, 44 of which are duplicated in delaney.csv.

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