2016
DOI: 10.12921/cmst.2016.22.01.004
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Computational Model for Chromatographic Relative Retention Time of Polychlorinated Biphenyls Using Sub-structural Molecular Fragments

Abstract: Quantitative structure-retention relationship (QSRR) analysis is a useful technique capable of relating chromatographic retention time to the chemical structure of a solute. Using the sub-structural molecular fragments (SMF) derived directly from the molecular structures, the gas chromatographic relative retention times (RRTs) of 209 polychlorinated biphenyls (PCBs) on the SE-54 stationary phase were calculated. An eight-variable regression equation with the correlation coefficient of 0.9945 and the root mean … Show more

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Cited by 2 publications
(3 citation statements)
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“…The obtained results in this study (RMSE = 0.016, R 2 = 0.992) were also compared to both the ones (RMSE = 0.0134, R 2 = 0.994) obtained using sub‐structural molecular fragments (SMF) derived directly from the molecular structures which is based on the splitting of a molecular graph on fragments as descriptors [18] and (RMSE = 0.0152, R 2 = 0.996) obtained using molecular electronegativity distance vector descriptors introduced by [19] for prediction of RRT of PCBs. As shown, the results are in a good agreement with each other, but the method introduced in this study is rapid and simple.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The obtained results in this study (RMSE = 0.016, R 2 = 0.992) were also compared to both the ones (RMSE = 0.0134, R 2 = 0.994) obtained using sub‐structural molecular fragments (SMF) derived directly from the molecular structures which is based on the splitting of a molecular graph on fragments as descriptors [18] and (RMSE = 0.0152, R 2 = 0.996) obtained using molecular electronegativity distance vector descriptors introduced by [19] for prediction of RRT of PCBs. As shown, the results are in a good agreement with each other, but the method introduced in this study is rapid and simple.…”
Section: Resultsmentioning
confidence: 99%
“…The present paper is focused on the application of 2D images, which are the proper structures of the compounds that can be drawn with aid of any appropriate program, as descriptors in QSRR. Thus, the MIA‐QSRR method was applied to PCB derivatives using PLS and PC‐RBFNNs as the linear and nonlinear modeling methods, to search for its predictive ability when compared to sub‐structural molecular fragments and molecular electronegativity distance vector descriptors results obtained from the literature [18,19]. Moreover, we are going to report the combination of multivariate image analysis and RBFNNs.…”
Section: Introductionmentioning
confidence: 99%
“…In our previous papers we reported on the application of QSPR techniques in developing a new, simplified approach to prediction of organic compounds properties using different models [27][28][29][30][31][32][33][34][35][36].…”
Section: Introductionmentioning
confidence: 99%