QSPR and QSAR models derived using large molecular descriptor spaces. A review of CODESSA applications

被引：69

作者：

Karelson, M

Maran, U

Wang, YL

Katritzky, AR

机构：

[1] Univ Tartu, Dept Chem, EE-51014 Tartu, Estonia

[2] Univ Florida, Dept Chem, Ctr Heterocycl Cpds, Gainesville, FL 32611 USA

来源：

COLLECTION OF CZECHOSLOVAK CHEMICAL COMMUNICATIONS | 1999年 / 64卷 / 10期

关键词：

molecular descriptors; QSPR; QSAR; property or activity prediction;

D O I：

10.1135/cccc19991551

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

An overview on the development of QSPR/QSAR equations using various descriptor-mining techniques and multilinear regression analysis in the framework of the CODESSA (Comprehensive Descriptors for Structural and Statistical Analysis) program is given. The description of the methodologies applied in CODESSA is followed by the presentation of the QSAR and QSPR models derived for eighteen molecular activities and properties. The properties cover single molecular species, interactions between different molecular species, properties of surfactants, complex properties and properties of polymers. A review with 54 references.

引用

收藏

页码：1551 / 1571

页数：21

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