QSAR modeling based on structure-information for properties of interest in human health

被引:28
作者
Hall, LH [1 ]
Hall, LM
机构
[1] Eastern Nazarene Coll, Dept Chem, Quincy, MA 02170 USA
[2] Hall Associates Consulting, Quincy, MA 02170 USA
关键词
electrotopological state; molecular connectivity; structure-based; mechanism-based; QSAR; molecular topology;
D O I
10.1080/10629360412331319853
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The development of QSAR models based on topological structure description is presented for problems in human health. These models are based on the structure-information approach to quantitative biological modeling and prediction, in contrast to the mechanism-based approach. The structure-information approach is outlined, starting with basic structure information developed from the chemical graph ( connection table). Information explicit in the connection table ( element identity and skeletal connections) leads to significant ( implicit) structure information that is useful for establishing sound models of a wide range of properties of interest in drug design. Valence state definition leads to relationships for valence state electronegativity and atom/group molar volume. Based on these important aspects of molecules, together with skeletal branching patterns, both the electrotopological state (E-state) and molecular connectivity (chi indices) structure descriptors are developed and described. A summary of four QSAR models indicates the wide range of applicability of these structure descriptors and the predictive quality of QSAR models based on them: aqueous solubility ( 5535 chemically diverse compounds, 938 in external validation), percent oral absorption (% OA, 417 therapeutic drugs, 195 drugs in external validation testing), AMES mutagenicity (2963 compounds including 290 therapeutic drugs, 400 in external validation), fish toxicity ( 92 substituted phenols, anilines and substituted aromatics). These models are established independent of explicit three-dimensional (3-D) structure information and are directly interpretable in terms of the implicit structure information useful to the drug design process.
引用
收藏
页码:13 / 41
页数:29
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