Use of topological indices of polychlorinated biphenyls in structure–retention relationships

Krawczuk, Anna; Voelkel, Adam; Lulek, Janina; Urbaniak, R; Szyrwińska, Katarzyna

doi:10.1016/j.chroma.2003.08.037

Cited by 14 publications

(5 citation statements)

References 16 publications

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“…The interval of the distribution between the total amount of substituents and the RRTs of 209 PCBs and biphenyl is shown in Figure 2(a). The horizontal line represents the mean RRTs for each substituent number, and a significant linear correlation (R 2 of 0.998) was observed, similar to the results of Krawczuk et al [14]. To investigate this correlation further, we have considered the total amount of substituents in the ortho/meta/para positions and generated the lists of the different types of substituents in PCBs (Table SIII).…”

Section: The Correlation Between the Total Amount Of Substituents Andsupporting

confidence: 73%

“…Because of a large number of PCBs and physicochemical similarities, the separation of 209 congeners has remained a complex problem. Many authors have quantitative structureretention relationship (QSRR) methodology to predict the gaschromatographic relative retention times (RRTs) via topological indices [14], weighted holistic invariant molecular descriptors [15], molecular electronegativity distance vectors [16], molecular connectivity [17], or combinations of descriptors for various classes [18]. Unfortunately, the specific meanings of the referring descriptors were abstract and unhelpful for the optimization stage or the regulation of chromatographic separation.…”

Section: Introductionmentioning

confidence: 99%

“…Unlike the quantum chemical or topology descriptors, the substituent characteristics intuitively reflect the number or positional relationship of the chlorine atoms, which might provide specific regulation by explaining the differences in RRTs because the number and position of the chlorine atoms determine both the physical and the biological properties of each PCB [19]. In recent decades, Krawczuk et al [14] revealed that the best correlation occurs between RRTs and the number of chlorine atoms, and a similar conclusion was revealed by Gramatica et al [15]; Liu et al [16] reported that the non-ortho index, I no , had a positive effect on RRT of a PCB molecule. Meanwhile, studies have considered substituent descriptors to establish the QSRR for RRTs of PCBs but obtained only a general conclusion: "There is high dependency of retention time of PCBs and number and position of chlorine atoms in PCBs" [20].…”

Section: Introductionmentioning

confidence: 99%

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How do the substituents affect and regulate the relative retention times of polychlorinated biphenyls during gas chromatography?

Jiang

2015

Journal of Chemometrics

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The effects and regulatory actions of the polychlorinated biphenyls (PCBs) substituent characteristics on their relative retention times (RRTs) during gas chromatography were analyzed based on known experimental RRTs of 209 PCB congeners and biphenyl; the substituent characteristics used for this analysis included the total amount of substituents, the similarity between two phenyl rings in a single PCB congener, the substituents distribution in single phenyl ring, the main/second-order interactions effects at each position, and the combined effect of two phenyl rings. At last, the universality of regulation was validated on other experimental conditions. Among them, the full factorial experimental design included 10 factors correlated with each substituent position and two levels (0, 1) were initially applied to the domains of the substituent characteristics. The obtained results have revealed that increasing the total amount of substituents can increase the RRTs of PCBs linearly, but similarities between the two rings cannot control the RRTs effectively. Meanwhile, the more compact the substituent distributions on a single phenyl ring are, the bigger the RRTs of PCBs are. Based on a full factorial experimental design, the overall important trend for each position is as follows: para > meta > ortho and the main regulatory substituents for the second-order interaction effects are distributed in the same phenyl ring in the following sequence: N o > N m > N p . The congener with two perpendicular phenyl rings exhibits a milder combined effect on RRTs and smaller RRT relatively. The regulation has a good universality among different experimental conditions, revealing the dominant effect of substituent characteristics on RRTs of PCBs.

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Section: The Correlation Between the Total Amount Of Substituents Andsupporting

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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How do the substituents affect and regulate the relative retention times of polychlorinated biphenyls during gas chromatography?

Jiang

2015

Journal of Chemometrics

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“…Moreover, the combination of J with the first-order Randic connectivity index 1 χ improved the results obtained. Krawczuk et al [29]; used the J index and the electro-topological index for the prediction of retention data of polychlorinated biphenyls. J index has been used also as index of reference to test the performance of new TIs.…”

Section: Applications Of Molecular Informaticsmentioning

confidence: 99%

MIANN Models of Networks of Biochemical Reactions, Ecosystems, and U.S. Supreme Court with Balaban-Markov Indices

Duardo-Sánchez¹,

González-Dı́az²,

Porto-Pazos

2015

CBIO

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We can use Artificial Neural Networks (ANNs) and graph Topological Indices (TIs) to seek structureproperty relationship. Balabans' J index is one of the classic TIs for chemo-informatics studies. We used here Markov chains to generalize the J index and apply it to bioinformatics, systems biology, and social sciences. We seek new ANN models to show the discrimination power of the new indices at node level in three proofof-concept experiments. First, we calculated more than 1,000,000 values of the new Balaban-Markov centralities Jk(i) and other indices for all nodes in >100 complex networks. In the three experiments, we found new MIANN models with >80% of Specificity (Sp) and Sensitivity (Sn) in train and validation series for Metabolic Reactions of Networks (MRNs) for 42 organisms (bacteria, yeast, nematode and plants), 73 Biological Interaction Webs or Networks (BINs), and 43 sub-networks of U.S. Supreme court citations in different decades from 1791 to 2005. This work may open a new route for the application of TIs to unravel hidden structure-property relationships in complex bio-molecular, ecological, and social networks.

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“…6,7 Due to PCBs' complex composition the separation of PCBs has been a great challenge for analytical chemists and much research focused on identification of individual PCB congeners. [8][9][10][11][12][13][14][15][16] Some of the commonly used methods for the analysis of PCBs in environmental samples are gas chromatography (GC) techniques using capillary columns with different polarities coupled with appropriate detectors such as flame ionization detector, electron capture detector, and mass spectrometry (MS). [17][18][19] Despite the broad range of GC stationary phases available, none can separate all PCBs from each other.…”

mentioning

confidence: 99%

Radial basis function neural networks based on projection pursuit approach and solvatochromic descriptors: single and full column prediction of gas chromatography retention behavior of polychlorinated biphenyls

Hassanzadeh

Ebrahimi

Kompany‐Zareh

et al. 2016

Journal of Chemometrics

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The ultimate goal of projection methods is to search “interesting” projections in a low‐dimensional subspace that can uncover the natural structure of the data. The aim of this work is to compare the ability of projection pursuit (PP) and principal component analysis (PCA) in dimension reduction. For this purpose to be achieved, the scores of PP and PCA, by a different number of factors, were used as inputs of radial basis function (RBF) neural network. RBF neural network was used as a nonlinear regression method in a quantitative structure‐retention relationships study of 209 polychlorinated biphenyls (PCBs). The dependent variable was the high‐resolution gas chromatographic relative retention times of PCBs on 18 different stationary phases, and independent variables were solvatochromic solute descriptors. The results demonstrate that the dimension reduction ability of the PP is better than that of the PCA for both single and full column retention models.

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Use of topological indices of polychlorinated biphenyls in structure–retention relationships

Cited by 14 publications

References 16 publications

How do the substituents affect and regulate the relative retention times of polychlorinated biphenyls during gas chromatography?

How do the substituents affect and regulate the relative retention times of polychlorinated biphenyls during gas chromatography?

MIANN Models of Networks of Biochemical Reactions, Ecosystems, and U.S. Supreme Court with Balaban-Markov Indices

Radial basis function neural networks based on projection pursuit approach and solvatochromic descriptors: single and full column prediction of gas chromatography retention behavior of polychlorinated biphenyls

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