Neural network-based QSAR and insecticide discovery: spinetoram

被引:107
作者
Sparks, Thomas C. [1 ]
Crouse, Gary D. [1 ]
Dripps, James E. [1 ]
Anzeveno, Peter [1 ]
Martynow, Jacek [1 ]
DeAmicis, Carl V. [1 ]
Gifford, James [1 ]
机构
[1] Dow AgroSci, Discovery Res, Indianapolis, IN 46268 USA
关键词
artificial neural networks; neural network based qsar; quantitative structure activity relationships; QSAR; spinetoram; spinosyns; virtual screening;
D O I
10.1007/s10822-008-9205-8
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Improvements in the efficacy and spectrum of the spinosyns, novel fermentation derived insecticide, has long been a goal within Dow AgroSciences. As large and complex fermentation products identifying specific modifications to the spinosyns likely to result in improved activity was a difficult process, since most modifications decreased the activity. A variety of approaches were investigated to identify new synthetic directions for the spinosyn chemistry including several explorations of the quantitative structure activity relationships (QSAR) of spinosyns, which initially were unsuccessful. However, application of artificial neural networks (ANN) to the spinosyn QSAR problem identified new directions for improved activity in the chemistry, which subsequent synthesis and testing confirmed. The ANN-based analogs coupled with other information on substitution effects resulting from spinosyn structure activity relationships lead to the discovery of spinetoram (XDE-175). Launched in late 2007, spinetoram provides both improved efficacy and an expanded spectrum while maintaining the exceptional environmental and toxicological profile already established for the spinosyn chemistry.
引用
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页码:393 / 401
页数:9
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