BigSolDB 2.0, dataset of solubility values for organic compounds in different solvents at various temperatures
Abstract Solubility is one of the key properties of organic compounds that determines their applications in chemistry, materials science and pharmaceuticals. However, predicting solubility values in any solvent except water from a molecular structure still remains a challenging task in modern chemin...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05559-8 |
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| Summary: | Abstract Solubility is one of the key properties of organic compounds that determines their applications in chemistry, materials science and pharmaceuticals. However, predicting solubility values in any solvent except water from a molecular structure still remains a challenging task in modern cheminformatics, not least due to the lack of large and diverse datasets. In this study, we present a dataset containing 103944 experimental solubility values within a temperature range from 243 to 425 K for 1448 organic compounds measured in 213 individual solvents extracted from 1595 peer-reviewed articles. The molecular structures of solutes and solvents as well as solubility data are standardized and provided in a machine-readable format, allowing straightforward data-driven analysis. We have also developed a web-tool for interactive visualization and search within the dataset. This dataset can serve as a comprehensive benchmark for developing machine learning for predicting solubility. |
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| ISSN: | 2052-4463 |