The structural origin of chromatographic retention data

QSRR Models for Kováts' Retention Indices of a Variety of Volatile Organic Compounds on Polar and Apolar GC Stationary Phases Using Molecular Connectivity Indexes

Quantitative structure-retention relationship (QSRR) approaches, based on molecular connectivity indices are useful to predict the gas chromatography of Kováts relative retention indices (GC-RRIs) of 132 volatile organic compounds (VOCs) on different 12 (4 apolar and 8 polar) stationary phases (C₆₇, C₁₀₃, C₇₈, C_∞, POH, TTF, MTF, PCL, PBR, TMO, PSH and PCN) at 130 °C. Full geometry optimization based on Austin model 1 semi-empirical molecular orbital method was carried out. The sets of 30 molecular descriptors were derived directly from the topological structures of the compounds from DRAGON program. By means of the final variable selection method, which is elimination selection stepwise regression algorithms, three optimal descriptors were selected to develop a QSRR model to predict the RRI of organic compounds on each stationary phase with a correlation coefficient between 0.9378 and 0.9673 and a leave-one-out cross-validation correlation coefficient between 0.9325 and 0.9653. The root mean squares errors over different 12 phases were within the range of 0.0333–0.0458. Furthermore, the accuracy of all developed models was confirmed using procedures of Y-randomization, external validation through an odd–even number and division of the entire dataset into training and test sets. A successful interpretation of the complex relationship between GC RRIs of VOCs and the chemical structures was achieved by QSRR. The three connectivity indexes in the models are also rationally interpreted, which indicated that all organic compounds’ RRI was precisely represented by molecular connectivity indexes.

Methods for generating second dimension retention index data in comprehensive two-dimensional gas chromatography

Two methods of generating transportable second dimension retention data are outlined for comprehensive two-dimensional gas chromatography (GC x GC). They are both refinements of a previously outlined procedure, which adapted 'isovolatile' curves to retention prediction maps developed in our laboratory, extended to a more polar homologous series, the linear primary alcohols. The earlier work investigated maps based on alkanes and methyl ketones and methyl esters; here the method of data collection to generate the retention map has also changed, extending the retention base range. The resulting retention map permits a retention basis to be used for GC x GC data, however, a more polar retention set than alkanes is required. The calculation of 'retention indices' is aided by the generation of 'fractional reference compound' curves, by either direct manipulation of data local to the solute, or generation of a discrete curve coincident with the retention co-ordinates of the target compound.

A new descriptor for structure-property and structure-activity correlations

We consider an improvement of a multiple regression analysis (MRA) for the correlation of boiling points of alcohols using descriptors that involve a variable part. In the search for the best descriptors based on weighted paths we came upon a novel molecular descriptor, the use of which was apparently overlooked in the past. The novel descriptor counts paths of length three; however, only those associated with an oxygen atom are counted.

QSPR modeling: graph connectivity indices versus line graph connectivity indices

Five QSPR models of alkanes were reinvestigated. Properties considered were molecular surface-dependent properties (boiling points and gas chromatographic retention indices) and molecular volume-dependent properties (molar volumes and molar refractions). The vertex- and edge-connectivity indices were used as structural parameters. In each studied case we computed connectivity indices of alkane trees and alkane line graphs and searched for the optimum exponent. Models based on indices with an optimum exponent and on the standard value of the exponent were compared. Thus, for each property we generated six QSPR models (four for alkane trees and two for the corresponding line graphs). In all studied cases QSPR models based on connectivity indices with optimum exponents have better statistical characteristics than the models based on connectivity indices with the standard value of the exponent. The comparison between models based on vertex- and edge-connectivity indices gave in two cases (molar volumes and molar refractions) better models based on edge-connectivity indices and in three cases (boiling points for octanes and nonanes and gas chromatographic retention indices) better models based on vertex-connectivity indices. Thus, it appears that the edge-connectivity index is more appropriate to be used in the structure-molecular volume properties modeling and the vertex-connectivity index in the structure-molecular surface properties modeling. The use of line graphs did not improve the predictive power of the connectivity indices. Only in one case (boiling points of nonanes) a better model was obtained with the use of line graphs.

Modeling chromatographic parameters by a novel graph theoretical sub-structural approach

A novel approach to the study of quantitative relationships between chromatographic parameters and the chemical structure is introduced. It is based on the computation of the spectral moments of the topological bond matrix by using different weights as diagonal entries of this matrix. The main advantage of the present approach is that the quantitative contributions of the structural fragments of molecules to the chromatographic parameters studied can be obtained explicitly. By using this approach we study two data sets: one composed of 156 alkanes and the other of 81 oxygen-containing organic molecules. In both cases excellent quantitative structure-chromatographic retention relationships were obtained. The contributions of the different fragments to the chromatographic retention were generated obtaining tables of additive contributions to the properties studied. The physicochemical interpretation of the results on the basis of the retention mechanisms is also analyzed in light of this new approach.

Correlation of activity of 2-(X-benzyloxy)-4,6-dimethoxyacetophenones with topological indices and with the Hansch equation

The antispasmodic activities of the 2-(X-benzyloxy)-4,6-dimethoxyacetophenones (X = H, 4'-F, 4'-NO2, 4'-CH3, 4'-Cl, 3',4'-(CH3)2, 4'-OCH3, 4'-Br, 4'-C(CH3)3, 4'-OCH2C6H5) against acetylcholine-induced contraction of the guinea pig ileum were correlated with different topological indices. Good correlations were obtained through a simple regression equation with electrotopological state indices (Si) for the carbon atoms S(C1) and S(C6). Using multiple linear regression with two variables the best correlations were obtained with carbons in the 6- and 1-positions with sigma. Such results indicate that the corresponding carbon atoms play an important role in the biological activity. The equation of Hansch showed that the activity of these compounds increases when the ring substituent in the benzyloxy group are more highly electron-releasing and hydrophobic.

Calculation of retention indices by molecular topology: chlorinated alkanes

This study was undertaken to test the ability of the molecular connectivity model to predict retention indices using both statistical correlation coefficients and correctly predicted elution sequences as criteria of fit. The test was performed on three groups of chloroalkanes. Regression analyses show that the molecular connectivity model successfully predicts the retention indices of chlorinated alkanes on polar and non-polar stationary phases. However, first-order molecular connectivity indices alone are not sufficient, higher order indices are demonstrated to be necessary. The results also indicate that different structural features determine the retention index values of mono- and dichlorides. For monochlorides the major factor is the size of the alkyl chain, while for dichlorides the major factor is the topological relation between the two chlorine atoms. The comparison of the results obtained with the molecular connectivity model and the empirical additive scheme reveals several important advantages of the molecular connectivity approach.