Accurately predicting solubility curves via a thermodynamic cycle, machine learning, and solvent ensembles

The datasets and supplementary materials for the manuscript "Accurately predicting solubility curves via a thermodynamic cycle, machine learning, and solvent ensembles" by Emad Al Ibrahim, Nathan Morgan, Simon Muller, Saikiran Motati, and William H. Green. The files include compiled data for solubility, logP, enthalpy of fusion, melting point, and activity coefficients. *Note that only the data approved for public release is shared here. Description:dHfus_DB.csv: Enthalpy of fusion data - used for training/validationTmp_DB.csv: Melting point temperature data - used for training/validationDrug_like_molecules: Folder containing the drug-like solutes added to gamma_QM_DBgamma_QM_DB: Activity coefficient data from COSMO-RS - used for training/validationlogP: Folder containing logP datasets used for testing (OPERA, SAMPL6, and SAMPL7)Solubility: Folder containing solubility datasets used for testing - all_solubility.csv is the data from 15 datasets, and BiggerSolDB is the combination shared both with and without Zwitterions本数据集及补充材料对应论文《基于热力学循环、机器学习与溶剂集合精准预测溶解度曲线》，作者为Emad Al Ibrahim、Nathan Morgan、Simon Muller、Saikiran Motati与William H. Green。 本数据集包含经整理的溶解度、正辛醇-水分配系数(logP)、熔融焓、熔点及活度系数数据。 *注意：此处仅共享经许可可公开发布的数据。 数据集说明： dHfus_DB.csv：熔融焓数据，用于模型训练与验证 Tmp_DB.csv：熔点数据，用于模型训练与验证 Drug_like_molecules文件夹：内含添加至gamma_QM_DB的类药物溶质数据 gamma_QM_DB：来自COSMO-RS的活度系数数据，用于模型训练与验证 logP文件夹：包含用于模型测试的logP数据集，涵盖OPERA、SAMPL6及SAMPL7三类数据集 Solubility文件夹：包含用于模型测试的溶解度数据集，其中all_solubility.csv整合了15个数据集的原始数据，BiggerSolDB则为包含与不包含两性离子(Zwitterions)样本的合并数据集