QSRR study of psychiatric drugs using Classification and Regression Trees combined with adaptive Neuro-Fuzzy Inference System

被引:5
|
作者
Jalali-Heravi, Mehdi [1 ]
Shahbazikhah, Parvis [1 ]
Ghadiri-Bidhendi, Atieh [1 ]
机构
[1] Sharif Univ Technol, Dept Chem, Tehran, Iran
来源
QSAR & COMBINATORIAL SCIENCE | 2008年 / 27卷 / 06期
关键词
adaptive neuro-fuzzy inference system; classification and regression tree; gas chromatography; psychiatric drugs; quantitative structure-retention relationship;
D O I
10.1002/qsar.200710111
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
A new Quantitative Structure-Retention Relationship (QSRR) approach was carried out for prediction of gas-liquid retention times of 124 psychiatric drugs in whole blood on fused-silica capillary column coated with crosslinked methylsilicone with nitrogen-phosphorus detection. After screening the descriptors, a total of 699 topological, geometric, and electronic descriptors (zero- to three-dimensional) representing various structural characteristics were calculated for each molecule in the dataset. Combined method of Classification and Regression Tree (CART) as a feature selection method for the extraction of four relevant descriptors and Adaptive Neuro-Fuzzy Inference System (ANFIS) as a modeling technique was used for the prediction of retention times of diverse set of psychiatric drugs. The Root Mean Square Errors (RMSEs) for the calibration and prediction sets are 0.457 and 0.514, respectively.
引用
收藏
页码:729 / 739
页数:11
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