有机化合物的分子图和分子超图:比较分析

M. Skvortsova
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引用次数: 0

摘要

计算机化学是一门出现在化学、数学和信息学交叉领域的科学。为了解决这一领域的任何问题,都需要一些化学结构的数学表示。最广泛使用的描述分子结构的方法是将其表示为图G,其顶点和边对应于分子的原子和键。然而,可能还有其他描述分子结构的方法。本文提出了几种将有机化合物(碳氢化合物)分子结构表示为特殊类型超图Hk (k=1,2,…)的方法。并给出了图图分子模型与超图分子模型比较的一些结果。Hk的构造由图G中与分子(k=1,2,…)碳骨架对应的所有顶点的k阶邻域定义。此外,得到了表示Hk的邻接矩阵和对应图G的邻接矩阵的解析公式(k=1,2,…)。用确定的定量参数对传统图模型G和建议的超图模型Hk (k=1,2,…)进行了比较,表征了它们在计算机化学某些任务中的应用效率。这些研究使用了4套不同的碳氢化合物结构式和30种不同的定量参数。结果表明,在所有考虑的120例中,H1模型优于G模型的占97%,在其他情况下,这些模型是等效的。但当k≥2时,模型Hk较G和H1差。具体的例子也表明,在某些情况下,h1模型可能有助于构建结构-属性相关性,因为它们的使用使我们能够获得比g模型更精确的相关性(在75%的考虑情况下)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Molecular Graphs and Molecular Hypergraphs of Organic Compounds: Comparative Analysis
Computer chemistry is a field of science appearing at the intersection of chemistry, mathematics and informatics. For the solution of any task in this field some mathematical representation of chemical structures is need. The most widely used approach to description of molecular structure is based on its representation as a graph G with vertices and edges corresponding to atoms and bonds of molecule. However, there may be other ways of describing the molecular structure. In this paper a number of methods to present the molecular structures of organic compounds (hydrocarbons) as hypergraphs Hk (k=1,2,…) of special type is suggested. Some results of comparison of graph and hypergraph molecular models are also given. Construction of Hk is defined by neighborhoods of k-th order for all vertices in a graph G corresponding to the carbon skeleton of molecule (k=1,2,…). Besides, analytical formulae, expressing the adjacency matrices of Hk throw adjacency matrix of corresponding graph G are obtained (k=1,2,…). The comparison of traditional graph model G and suggested hypergraph models Hk (k=1,2,…) is made by definite quantitative parameters, characterizing the efficiency of their applications in some tasks of computer chemistry. Some 4 different sets of structural formulae of hydrocarbons and 30 different quantitative parameters are used for these investigations. It is shown, that in 97% of all considered 120 cases the model H1 is superior to the model G, and in other cases these models are equivalent. However, the models Hk for k ≥ 2 are worse than G and H1. It is also shown on concrete examples, that in some cases, H1-models may be useful in constructing the structure-property correlations, since their use allows us to obtain more precise correlations than for G-models (in 75% of considered cases).
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