Some tools of QSAR/QSPR and drug development: Wiener and Terminal Wiener indices

Meryam Zeryouh, M. El Marraki, M. Essalih
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引用次数: 1

Abstract

Result of the increases in the size of molecular databases, big-data becomes a very important field of research in the discovery of a new drug. To predict chemical and biological properties of novel molecules based on their structural representations, the QSAR/QSPR models have been build. The Qualitative Structure Activity (resp. property) Relationships are based on the search for a relationship between a set of real numbers, molecular descriptors, and the property or activity that we want to predict. In this paper we recall the principle of QSAR/QSPR models, we discus a kind of molecular descriptors called topological indices, that is calculated from a graph representing a molecule. Then we give some results concerning the calculation of the Terminal Wiener index of some molecular graphs, and in the end we give an application for calculating the Terminal Wiener index of dendrimer graph.
QSAR/QSPR和药物开发的一些工具:Wiener和终端Wiener指数
由于分子数据库规模的增加,大数据成为新药发现的一个非常重要的研究领域。为了根据新分子的结构表征来预测其化学和生物学特性,我们建立了QSAR/QSPR模型。定性结构活动(参见。关系是基于对一组实数、分子描述符和我们想要预测的性质或活动之间的关系的搜索。本文回顾了QSAR/QSPR模型的基本原理,讨论了一种分子描述符——拓扑指标,它是由表示分子的图计算得到的。然后给出了一些分子图的终端维纳指数的计算结果,最后给出了计算树突图终端维纳指数的一个应用。
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