AqSolDB, a curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds
AqSolDB, a curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds
复制标题
DOI：
10.1038/s41597-019-0151-1
复制
发表时间：
2019-08-08
期刊：
影响因子：
9.8
通讯作者：
Er, Suleyman
中科院分区：
文献类型：
--
作者：
Sorkun, Murat Cihan;Khetan, Abhishek;Er, Suleyman
水是化学和生活中普遍存在的溶剂。因此，化合物的水溶性在各个领域（包括但不限于药物发现、油漆、涂料和电池材料设计）中发挥关键作用也就不足为奇了。水溶性的测量和预测是化学中一个复杂且普遍的挑战。对于后者，最近开发了不同的数据驱动预测模型来增强基于物理的建模方法。为了构建准确的数据驱动估计模型，这些模型使用的基础实验校准数据必须具有高保真度和高质量。现有的溶解度数据集显示了所涵盖化合物的化学空间、测量方法、实验条件以及数据的非标准表示、大小和可访问性方面的差异。为了解决这个问题，我们生成了一个新的化合物数据库 AqSolDB，方法是合并总共九个不同的水溶性数据集，整理合并的数据，标准化和验证化合物表示格式，用可靠性标签进行标记，并提供化合物的 2D 描述符作为补充资源。
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.