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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
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 pa...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
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Molecular Diversity Preservation International (MDPI)
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2920560/ https://www.ncbi.nlm.nih.gov/pubmed/20717530 http://dx.doi.org/10.3390/ijms11072681 |
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author | Stasiak, Jolanta Koba, Marcin Bober, Leszek Bączek, Tomasz |
author_facet | Stasiak, Jolanta Koba, Marcin Bober, Leszek Bączek, Tomasz |
author_sort | Stasiak, Jolanta |
collection | PubMed |
description | 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). |
format | Text |
id | pubmed-2920560 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-29205602010-08-17 Principal Component Analysis of HPLC Retention Data and Molecular Modeling Structural Parameters of Cardiovascular System Drugs in View of Their Pharmacological Activity Stasiak, Jolanta Koba, Marcin Bober, Leszek Bączek, Tomasz Int J Mol Sci Article 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). Molecular Diversity Preservation International (MDPI) 2010-07-09 /pmc/articles/PMC2920560/ /pubmed/20717530 http://dx.doi.org/10.3390/ijms11072681 Text en © 2010 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. http://creativecommons.org/licenses/by/3.0 This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Stasiak, Jolanta Koba, Marcin Bober, Leszek Bączek, Tomasz Principal Component Analysis of HPLC Retention Data and Molecular Modeling Structural Parameters of Cardiovascular System Drugs in View of Their Pharmacological Activity |
title | Principal Component Analysis of HPLC Retention Data and Molecular Modeling Structural Parameters of Cardiovascular System Drugs in View of Their Pharmacological Activity |
title_full | Principal Component Analysis of HPLC Retention Data and Molecular Modeling Structural Parameters of Cardiovascular System Drugs in View of Their Pharmacological Activity |
title_fullStr | Principal Component Analysis of HPLC Retention Data and Molecular Modeling Structural Parameters of Cardiovascular System Drugs in View of Their Pharmacological Activity |
title_full_unstemmed | Principal Component Analysis of HPLC Retention Data and Molecular Modeling Structural Parameters of Cardiovascular System Drugs in View of Their Pharmacological Activity |
title_short | Principal Component Analysis of HPLC Retention Data and Molecular Modeling Structural Parameters of Cardiovascular System Drugs in View of Their Pharmacological Activity |
title_sort | principal component analysis of hplc retention data and molecular modeling structural parameters of cardiovascular system drugs in view of their pharmacological activity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2920560/ https://www.ncbi.nlm.nih.gov/pubmed/20717530 http://dx.doi.org/10.3390/ijms11072681 |
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