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Principal component analysis of HPLC retention data and molecular modeling structural parameters of cardiovascular system drugs in view of their pharmacological activity.

Abstract：

:Evaluation of relationships between molecular modeling structural parameters and high-performance liquid chromatography (HPLC) retention data of 11 cardiovascular system drugs by principal component analysis (PCA) in relation to their pharmacological activity was performed. The six retention data parameters were determined on three different HPLC columns (Nucleosil C18 AB with octadecylsilica stationary phase, IAM PC C10/C3 with chemically bounded phosphatidylcholine, and Nucleosil 100-5 OH with chemically bounded propanodiole), and using isocratically acetonitrile: Britton-Robinson buffer as the mobile phase. Additionally, molecular modeling studies were performed with the use of HyperChem software and MM+ molecular mechanics with the semi-empirical AM1 method deriving 20 structural descriptors. Factor analysis obtained with the use of various sets of parameters: structural parameters, HPLC retention data, and all 26 considered parameters, led to the extraction of two main factors. The first principal component (factor 1) accounted for 44-57% of the variance in the data. The second principal component (factor 2) explained 29-33% of data variance. Moreover, the total data variance explained by the first two factors was at the level of 73-90%. More importantly, the PCA analysis of the HPLC retention data and structural parameters allows the segregation of circulatory system drugs according to their pharmacological (cardiovascular) properties as shown by the distribution of the individual drugs on the plane determined by the two principal components (factors 1 and 2).

journal_name

Int J Mol Sci

journal_title

International journal of molecular sciences

authors

Stasiak J,Koba M,Bober L,Baczek T

doi

10.3390/ijms11072681

subject

Has Abstract

pub_date

2010-07-09 00:00:00

pages

2681-98

issue

7

issn

1422-0067

journal_volume

11

pub_type

杂志文章

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