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Semi-Empirical Topological Method for Prediction of the Relative Retention Time of Polychlorinated Biphenyl Congeners on 18 Different HR GC Columns
High resolution gas chromatographic relative retention time (HRGC-RRT) models were developed to predict relative retention times of the 209 individual polychlorinated biphenyls (PCBs) congeners. To estimate and predict the HRGC-RRT values of all PCBs on 18 different stationary phases, a multiple lin...
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Formato: | Texto |
Lenguaje: | English |
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Vieweg Verlag
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2925070/ https://www.ncbi.nlm.nih.gov/pubmed/20835381 http://dx.doi.org/10.1365/s10337-010-1696-5 |
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author | Ghavami, Raouf Mohammad Sajadi, S. |
author_facet | Ghavami, Raouf Mohammad Sajadi, S. |
author_sort | Ghavami, Raouf |
collection | PubMed |
description | High resolution gas chromatographic relative retention time (HRGC-RRT) models were developed to predict relative retention times of the 209 individual polychlorinated biphenyls (PCBs) congeners. To estimate and predict the HRGC-RRT values of all PCBs on 18 different stationary phases, a multiple linear regression equation of the form RRT = a (o) + a (1) (no. o-Cl) + a (2) (no. m-Cl) + a (3) (no. p-Cl) + a (4) (V (M) or S (M)) was used. Molecular descriptors in the models included the number of ortho-, meta-, and para-chlorine substituents (no. o-Cl, m-Cl and p-Cl, respectively), the semi-empirically calculated molecular volume (V (M)), and the molecular surface area (S (M)). By means of the final variable selection method, four optimal semi-empirical descriptors were selected to develop a QSRR model for the prediction of RRT in PCBs with a correlation coefficient between 0.9272 and 0.9928 and a leave-one-out cross-validation correlation coefficient between 0.9230 and 0.9924 on each stationary phase. The root mean squares errors over different 18 stationary phases are within the range of 0.0108–0.0335. The accuracy of all the developed models were investigated using cross-validation leave-one-out (LOO), Y-randomization, external validation through an odd–even number and division of the entire data set into training and test sets. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1365/s10337-010-1696-5) contains supplementary material, which is available to authorized users. |
format | Text |
id | pubmed-2925070 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Vieweg Verlag |
record_format | MEDLINE/PubMed |
spelling | pubmed-29250702010-09-10 Semi-Empirical Topological Method for Prediction of the Relative Retention Time of Polychlorinated Biphenyl Congeners on 18 Different HR GC Columns Ghavami, Raouf Mohammad Sajadi, S. Chromatographia Original High resolution gas chromatographic relative retention time (HRGC-RRT) models were developed to predict relative retention times of the 209 individual polychlorinated biphenyls (PCBs) congeners. To estimate and predict the HRGC-RRT values of all PCBs on 18 different stationary phases, a multiple linear regression equation of the form RRT = a (o) + a (1) (no. o-Cl) + a (2) (no. m-Cl) + a (3) (no. p-Cl) + a (4) (V (M) or S (M)) was used. Molecular descriptors in the models included the number of ortho-, meta-, and para-chlorine substituents (no. o-Cl, m-Cl and p-Cl, respectively), the semi-empirically calculated molecular volume (V (M)), and the molecular surface area (S (M)). By means of the final variable selection method, four optimal semi-empirical descriptors were selected to develop a QSRR model for the prediction of RRT in PCBs with a correlation coefficient between 0.9272 and 0.9928 and a leave-one-out cross-validation correlation coefficient between 0.9230 and 0.9924 on each stationary phase. The root mean squares errors over different 18 stationary phases are within the range of 0.0108–0.0335. The accuracy of all the developed models were investigated using cross-validation leave-one-out (LOO), Y-randomization, external validation through an odd–even number and division of the entire data set into training and test sets. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1365/s10337-010-1696-5) contains supplementary material, which is available to authorized users. Vieweg Verlag 2010-08-10 2010 /pmc/articles/PMC2925070/ /pubmed/20835381 http://dx.doi.org/10.1365/s10337-010-1696-5 Text en © The Author(s) 2010 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. |
spellingShingle | Original Ghavami, Raouf Mohammad Sajadi, S. Semi-Empirical Topological Method for Prediction of the Relative Retention Time of Polychlorinated Biphenyl Congeners on 18 Different HR GC Columns |
title | Semi-Empirical Topological Method for Prediction of the Relative Retention Time of Polychlorinated Biphenyl Congeners on 18 Different HR GC Columns |
title_full | Semi-Empirical Topological Method for Prediction of the Relative Retention Time of Polychlorinated Biphenyl Congeners on 18 Different HR GC Columns |
title_fullStr | Semi-Empirical Topological Method for Prediction of the Relative Retention Time of Polychlorinated Biphenyl Congeners on 18 Different HR GC Columns |
title_full_unstemmed | Semi-Empirical Topological Method for Prediction of the Relative Retention Time of Polychlorinated Biphenyl Congeners on 18 Different HR GC Columns |
title_short | Semi-Empirical Topological Method for Prediction of the Relative Retention Time of Polychlorinated Biphenyl Congeners on 18 Different HR GC Columns |
title_sort | semi-empirical topological method for prediction of the relative retention time of polychlorinated biphenyl congeners on 18 different hr gc columns |
topic | Original |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2925070/ https://www.ncbi.nlm.nih.gov/pubmed/20835381 http://dx.doi.org/10.1365/s10337-010-1696-5 |
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