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Determination of partitioning of drug molecules using immobilized liposome chromatography and chemometrics methods.

Abstract：

:The quantitative structure-property relationship (QSPR) of drug molecules against the immobilized liposome chromatography partitioning (log K(s)) was studied. The genetic algorithm (GA) was employed to select the variables that resulted in the best-fitted models. After the variables were selected, the linear multivariate regressions (e.g. partial least squares (PLS)) as well as the non-linear regressions (e.g. the kernel PLS (KPLS) and Levenberg-Marquardt artificial neural network (L-M ANN)) were utilized to construct the linear and non-linear QSPR models. The correlation coefficient cross validation (Q(2)) and relative error for calibration, prediction and test sets L-M ANN model are (0.987, 0.971, 0.952) and (3.14, 3.54, 6.61), respectively. The obtained results using L-M ANN were compared with those of GA-PLS and GA-KPLS, exhibiting that the L-M ANN model demonstrated a better performance than that of the other models. This is the first research on the QSPR of the drug molecules against the log K(s) using the GA-KPLS and L-M ANN.

journal_name

Drug Test Anal

journal_title

Drug testing and analysis

authors

Noorizadeh H,Farmany A

doi

10.1002/dta.262

subject

Has Abstract

pub_date

2012-02-01 00:00:00

pages

151-7

issue

2

eissn

1942-7603

issn

1942-7611

journal_volume

4

pub_type

杂志文章

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