کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1362617 981492 2006 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Classification of dopamine antagonists using functional feature hypothesis and topological descriptors
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آلی
پیش نمایش صفحه اول مقاله
Classification of dopamine antagonists using functional feature hypothesis and topological descriptors
چکیده انگلیسی

The designing of selective dopamine antagonists for their own subreceptors can be useful in individual therapy of various neuropsychiatric disorders. Three-dimensional pharmacophore hypothesis and two-dimensional topological descriptors were used to investigate and compare different classes of dopamine antagonists. The structurally diverse D3 and D4 antagonists above preclinical trials were selected to map common structural features of highly selective and efficacious antagonists. The generated pharmacophore hypotheses were successfully employed as discriminative probe for database screening. To filter out the false positive from screening hits, the classification models by two-dimensional topological descriptors were built. Molconn-Z and BCUT topological descriptors were employed to develop a classification model for 1328 dopamine antagonists from MDDR database. The soft independent modeling of class analogy and artificial neural network, two supervised classification techniques, successfully classified D1, D3, and D4 antagonists at the average of 80% rates into their own active classes. The mean classification rates for D2 antagonists were obtained to 60% due to insufficient selective D2 antagonists. In this paper, we report the validity of our models generated using functional feature hypotheses and topological descriptors. The combining both of classification using functional feature hypotheses and topological descriptors would be a useful tool to predict selective antagonists.

Two-dimensional topological descriptors and three-dimensional pharmacophore hypothesis were used to investigate and compare different classes of dopamine antagonists. Molconn-Z and BCUT topological descriptors were employed to develop a classification model for 1475 dopamine antagonists from MDDR database. The combining both of classification using topological descriptors and functional feature hypotheses could be a useful tool to predict selective antagonists.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Bioorganic & Medicinal Chemistry - Volume 14, Issue 5, 1 March 2006, Pages 1454–1461
نویسندگان
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