کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1397704 1501188 2010 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Prediction of air to liver partition coefficient for volatile organic compounds using QSAR approaches
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آلی
پیش نمایش صفحه اول مقاله
Prediction of air to liver partition coefficient for volatile organic compounds using QSAR approaches
چکیده انگلیسی

In this work a quantitative structure-activity relationship (QSAR) technique was developed to investigate the air to liver partition coefficient (log Kliver) for volatile organic compounds (VOCs). Suitable set of molecular descriptors was calculated and the important descriptors were selected by GA-PLS methods. These variables were served as inputs to generate neural networks. After optimization and training of the networks, they were used for the calculation of log Kliver for the validation set. The root mean square errors for the neural network calculated log Kliver of training, test, and validation sets are 0.100, 0.091, and 0.112, respectively. Results obtained reveal the reliability and good predictivity of neural network for the prediction of air to liver partition coefficient for volatile organic compounds.

Plot of calculated air to liver partition coefficient against experimental values.Figure optionsDownload as PowerPoint slide

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Medicinal Chemistry - Volume 45, Issue 6, June 2010, Pages 2182–2190
نویسندگان
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