Datasets for: Group Contribution and Machine Learning Approaches to Predict Abraham Solute Parameters, Solvation Free Energy, and Solvation Enthalpy

The datasets and supplementary materials for the manuscript "Group Contribution and Machine Learning Approaches to Predict Abraham Solute Parameters, Solvation Free Energy, and Solvation Enthalpy". Citations should refer directly to the manuscript (refer to the DOI 10.1021/acs.jcim.1c01103). The preprint version of of the manuscript is also available at: 10.33774/chemrxiv-2021-djd3d-v2 Regarding "Solvation_data-1.0.0.zip": The datasets include the curated data for: (1) Abraham solute parameters, (2) solvation free energy, (3) solvation enthalpy, (4) gas-water partition coefficient (logKw), (5) water-1-octanol partition coefficient (logPow). The fitted Abraham and Mintz solvent parameters are also included. Detailed information can be found in the "README.txt" file of the zip file. Regarding "ML_model_files.zip": This contains the machine learning model files for SoluteML and DirectML. For the instruction on how to use it, please refer to the chemprop_solvation git repository (https://github.com/fhvermei/chemprop_solvation