College of Pharmacy, University of Arizona, 1703 E. Mabel St., Tucson, Arizona 85721.
College of Pharmacy, University of Arizona, 1703 E. Mabel St., Tucson, Arizona 85721.
J Pharm Sci. 2018 Jan;107(1):297-306. doi: 10.1016/j.xphs.2017.10.018. Epub 2017 Oct 23.
The UPPER model (Unified Physicochemical Property Estimation Relationships) has been used to predict 9 essential physicochemical properties of pure compounds. It was developed almost 25 years ago and has been validated by the Yalkowsky group for almost 2000 aliphatic, aromatic, and polyhalogenated hydrocarbons. UPPER is based on a group of additive and nonadditive descriptors along with a series of well-accepted thermodynamic relationships. In this model, the 2-dimensional chemical structure is the only input needed. This work extends the applicability of UPPER to hydrogen bonding and non-hydrogen bonding aromatic compounds with several functional groups such as alcohol, aldehyde, ketone, carboxylic acid, carbonate, carbamate, amine, amide, nitrile as well as aceto, and nitro compounds. The total data set includes almost 3000 compounds. Aside from the enthalpies and entropies of melting and boiling, no training set is used for the calculation of the properties. The results show that UPPER enables a reasonable estimation of all the considered properties.
UPPER 模型(统一物理化学性质估算关系)已被用于预测 9 种纯化合物的基本物理化学性质。它是在 25 年前开发的,已经由 Yalkowsky 小组验证了近 2000 种脂肪族、芳香族和多卤代烃。UPPER 基于一组加性和非加性描述符以及一系列公认的热力学关系。在这个模型中,二维化学结构是唯一需要的输入。这项工作将 UPPER 的适用性扩展到具有几个官能团的氢键和非氢键芳香族化合物,如醇、醛、酮、羧酸、碳酸盐、氨基甲酸酯、胺、酰胺、腈以及乙酰和硝基化合物。总数据集包括近 3000 种化合物。除了熔融和沸腾焓和熵之外,没有使用训练集来计算这些性质。结果表明,UPPER 能够合理估计所有考虑的性质。