Istituto di Ricerche Farmacologiche Mario Negri, 20156, Via La Masa 19, Milano, Italy.
Chemosphere. 2013 Jan;90(2):877-80. doi: 10.1016/j.chemosphere.2012.07.035. Epub 2012 Aug 23.
Water solubility is an important characteristic of a chemical in many aspects. However experimental definition of the endpoint for all substances is impossible. In this study quantitative structure-property relationships (QSPRs) for negative logarithm of water solubility-logS (mol L(-1)) are built up for five random splits into the sub-training set (≈55%), the calibration set (≈25%), and the test set (≈20%). Simplified molecular input-line entry system (SMILES) is used as the representation of the molecular structure. Optimal SMILES-based descriptors are calculated by means of the Monte Carlo method using the CORAL software (http://www.insilico.eu/coral). These one-variable models for water solubility are characterized by the following average values of the statistical characteristics: n(sub_train)=725-763; n(calib)=312-343; n(test)=231-261; r(sub_train)(2)=0.9211±0.0028; r(calib)(2)=0.9555±0.0045; r(test)(2)=0.9365±0.0073; s(sub_train)=0.561±0.0086; s(calib)=0.453±0.0209; s(test)=0.520±0.0205. Thus, the reproducibility of statistical quality of suggested models for water solubility confirmed for five various splits.
水溶性是化学物质在许多方面的一个重要特性。然而，对于所有物质，实验性地定义终点是不可能的。在这项研究中，建立了五个随机分割的子训练集（约 55%）、校准集（约 25%）和测试集（约 20%）的负对数水溶解度-logS（mol L(-1)）的定量结构-性质关系（QSPR）。简化分子输入线进入系统（SMILES）被用作分子结构的表示。最优的基于 SMILES 的描述符通过使用 CORAL 软件（http://www.insilico.eu/coral）的蒙特卡罗方法计算。这些单变量的水溶性模型的特征在于以下统计特征的平均值：n(sub_train)=725-763;n(calib)=312-343;n(test)=231-261;r(sub_train)(2)=0.9211±0.0028;r(calib)(2)=0.9555±0.0045;r(test)(2)=0.9365±0.0073;s(sub_train)=0.561±0.0086;s(calib)=0.453±0.0209;s(test)=0.520±0.0205。因此，对于五个不同的分割，建议的水溶性模型的统计质量的可重复性得到了确认。
