AqSolDB, a curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds

Murat Sorkun, Abhishek Khetan, S. Er (Corresponding author)

Research output: Contribution to journalArticleAcademicpeer-review

9 Citations (Scopus)

Abstract

Water is a ubiquitous solvent in chemistry and life. It is therefore no surprise that the aqueous solubility of compounds has a key role in various domains, including but not limited to drug discovery, paint, coating, and battery materials design. Measurement and prediction of aqueous solubility is a complex and prevailing challenge in chemistry. For the latter, different data-driven prediction models have recently been developed to augment the physics-based modeling approaches. To construct accurate data-driven estimation models, it is essential that the underlying experimental calibration data used by these models is of high fidelity and quality. Existing solubility datasets show variance in the chemical space of compounds covered, measurement methods, experimental conditions, but also in the non-standard representations, size, and accessibility of data. To address this problem, we generated a new database of compounds, AqSolDB, by merging a total of nine different aqueous solubility datasets, curating the merged data, standardizing and validating the compound representation formats, marking with reliability labels, and providing 2D descriptors of compounds as a Supplementary Resource.
Original languageEnglish
Article number143
Number of pages8
JournalScientific Data
Volume6
Issue number1
DOIs
Publication statusPublished - 8 Aug 2019

Keywords

  • aqueous solubility
  • molecular dataset
  • data curation

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