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利用可优化的奇偶维纳多项式描述符生成的定量结构-性质关系。

Quantitative structure-property relationships generated with optimizable even/odd Wiener polynomial descriptors.

作者信息

Ivanciuc O, Ivanciuc T, Klein D J

机构信息

Department of Marine Sciences, Texas A & M University at Galveston, Fort Crockett Campus, 5007 Avenue U Galveston, TX 77551, USA.

出版信息

SAR QSAR Environ Res. 2001;12(1-2):1-16. doi: 10.1080/10629360108035368.

Abstract

Chemical structures of organic compounds are characterized numerically by a variety of structural descriptors, one of the earliest and most widely used being the Wiener index W, derived from the interatomic distances in a molecular graph. Extensive use of distance-based structural descriptors or topological indices has been made in QSPR and QSAR models, drug design, toxicology, virtual screening of combinatorial libraries, similarity and diversity assessment. Novel topological indices are introduced representing a partitioning of the Wiener polynomial based on counts of even and odd molecular graph distances. During the QSAR/QSPR modeling process the variables of the even and odd power functions are optimized in order to offer an improved mapping of the investigated property. These novel topological indices are tested in QSPR models for the boiling temperature, molar heat capacity, standard Gibbs energy of formation, vaporization enthalpy, refractive index, and density of alkanes. In many cases, the even/odd Wiener polynomial indices proposed here give notably improved correlations or suggest simpler QSPR models.

摘要

有机化合物的化学结构通过各种结构描述符进行数字表征,其中最早且应用最广泛的是维纳指数W,它源自分子图中的原子间距离。基于距离的结构描述符或拓扑指数在定量结构-性质关系(QSPR)和定量结构-活性关系(QSAR)模型、药物设计、毒理学、组合库虚拟筛选、相似性和多样性评估中得到了广泛应用。引入了新的拓扑指数,该指数基于分子图中偶数和奇数距离的计数来表示维纳多项式的划分。在QSAR/QSPR建模过程中,对偶数和奇数幂函数的变量进行优化,以便更好地映射所研究的性质。这些新的拓扑指数在QSPR模型中针对烷烃的沸点、摩尔热容、标准生成吉布斯自由能、汽化焓、折射率和密度进行了测试。在许多情况下,这里提出的偶数/奇数维纳多项式指数给出了显著改善的相关性,或者表明了更简单的QSPR模型。

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