کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1179795 | 962798 | 2011 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Virtual screening of a combinatorial library of enantioselective catalysts with chirality codes and counterpropagation neural networks
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موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Conformation-independent chirality codes, radial distribution function (RDF) codes, and indicator variables are implemented to represent 1914 catalysts in a combinatorial library which was tested by Riant and co-workers for the asymmetric-hydrogen transfer to acetophenone. The catalysts which combine a metallic center with a chiral ligand have been evaluated in terms of both enantiomeric excess and yield. A counterpropagation neural network (CPG NN) was trained with a small fraction of the library to predict the performance of catalysts, and applied to the virtual screening of the remaining library. Selection of <Â 20.8% of the virtual library with the highest predicted performance enables to identify up to 85.5% of the best catalysts. The approach illustrates a chemoinformatic method to assist the optimization of resources for the screening of enantioselective catalysts.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 109, Issue 2, 15 December 2011, Pages 113-119
Journal: Chemometrics and Intelligent Laboratory Systems - Volume 109, Issue 2, 15 December 2011, Pages 113-119
نویسندگان
Qing-You Zhang, Dan-Dan Zhang, Jing-Ya Li, Yan-Mei Zhou, Lu Xu,