کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1361152 | 981458 | 2008 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A genetic algorithm optimized fuzzy neural network analysis of the affinity of inhibitors for HIV-1 protease
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آلی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: A genetic algorithm optimized fuzzy neural network analysis of the affinity of inhibitors for HIV-1 protease A genetic algorithm optimized fuzzy neural network analysis of the affinity of inhibitors for HIV-1 protease](/preview/png/1361152.png)
چکیده انگلیسی
A fuzzy neural network (FNN) was trained on a dataset of 177 HIV-1 protease ligands with experimentally measured IC50 values. A set of descriptors was selected to build nonlinear quantitative structure-activity relationships. A genetic algorithm (GA) was implemented to optimize the architecture of the fuzzy neural network used to predict biological activity of HIV-1 protease inhibitors. Evolutionary methods were used to apply feature selection (FS) to this model. Results obtained on an external test set of 21 molecules, with and without feature selection, were compared. Applying feature selection to the GA-FNN resulted in a more accurate prediction of biological activity. Fuzzy IF/THEN rules were extracted from the optimized FNN. In the future the developed models are expected to be useful in the rational design of novel enzyme inhibitors for HIV-1 protease.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Bioorganic & Medicinal Chemistry - Volume 16, Issue 6, 15 March 2008, Pages 2903-2911
Journal: Bioorganic & Medicinal Chemistry - Volume 16, Issue 6, 15 March 2008, Pages 2903-2911
نویسندگان
Levente Fabry-Asztalos, RaËzvan Andonie, Catharine J. Collar, Sarah Abdul-Wahid, Nicholas Salim,