Quantitative Structure-retention Relationship Study Research Articles

Quantitative structure-retention relationship study of the gas chromatographic retention indices of saturated esters on different stationary phases using novel topological indices

The gas chromatographic retention data of 90 saturated esters obtained isothermally at 150 °C on seven stationary phases (SE-30, OV-7, DC-710, OV-25, XE-60, OV-225 and Silar-5CP) are well-correlated with recently introduced Lu index and novel distance-based atom-type DAI topological indices using multiple linear regression (MLR) method. For the retention indices (RI) based on each stationary phase, the correlation coefficient r of the final models is larger than 0.994, and particularly, the decrease in the standard error is within the range of 53.0–64.8% as compared with the simple linear models with Lu index alone. The results indicate the efficiency of these indices in the structure–retention index correlations of complex compounds. The role of each of the molecular size and individual groups in the molecules is illustrated by analyzing the relative or fraction contributions of individual indices. The results also indicate that the molecular size makes a dominant contribution to retention behaviors, while some atomic type or groups have smaller influence dependent on the polarity of the column. The leave-one-out cross-validation demonstrates the final models to be statistically significant and reliable.

Quantitative Structure-Retention Relationships Applied to Reversed-Phase High-Perfromance Liquid Chromatography

A quantitative structure-retention relationships (QSRR) approach, as one of the all-important areas in modern chemical science, gives knowledge that is practical and necessary for drug design, combinatorial, and medicinal chemistries. A QSRR derived by means of various statistical procedures are reviewed from the viewpoint of identifying retention affecting various factors and understanding the mechanism of chromatographic separations. A brief summary of the theoretical background of QSRR is followed by presentation of reversed-phase high performance liquid chromatographic (RP-HPLC) separation theories of applications to the reported QSRR. Structural and physicochemical descriptors derived by RP-HPLC are discussed in relation to retention factors with special accent on properties of reversed-phase materials. Reported QSRR models are critically reviewed, bearing in mind their statistical predictability physical meaning. Information on retention mechanisms is briefly analyzed also. It is concluded that QSRR employing molecular descriptors expected to model fundamental intermolecular interactions. A QSRR studies are already demonstrated their great potential in most essential areas of contemporary chemistry. A quantity of scientific publications steadily grows from year to year, this implyies that the QSRR enormous advantage and potential in chemistry, biology, and pharmacology.

Comparison of Ridge Regression, Partial Least-Squares, Pairwise Correlation, Forward- and Best Subset Selection Methods for Prediction of Retention Indices for Aliphatic Alcohols

A quantitative structure-retention relationship (QSRR) study based on multiple linear regression (MLR) was performed for the description and prediction of Kováts retention indices (RI) of alcohol compounds. Alcohols were of saturated, linear or branched types and contained a hydroxyl group on the primary, secondary or tertiary carbon atoms. Constitutive and weighted holistic invariant molecular (WHIM) descriptors were used to represent the structure of alcohols in the MLR models. Before the model building, five variable selection methods were applied to select the most relevant variables from a large set of descriptors, respectively. The selected molecular properties were included into the MLR models. The efficiency of the variable selection methods was also compared. The selection methods were as follows: ridge regression (RR), partial least-squares method (PLS), pair-correlation method (PCM), forward selection (FS) and best subset selection (BSS). The stability and the validity of the MLR models were tested by a cross-validation technique using a leave-n-out technique. Neither RR nor PLS selected variables were able to describe the Kováts retention index properly, and PCM gave reliable results in the description but not for prediction. We built models with good predicting ability using FS and BSS as a selection method. The most relevant variables in the description and prediction of RIs were the mean electrotopological state index, the molecular mass, and WHIM indices characterizing size and shape.

Effect of ionization and the nature of the mobile phase in quantitative structure-retention relationship studies

The octanol-water distribution constant, commonly called partition coefficient, Po/w, is a parameter often retained as a measure of the hydrophobicity of a molecule. log Po/w, for a given molecule, can be conveniently evaluated constructing correlation lines between standard retention factor logarithms (log k) in reversed-phase liquid chromatography (RPLC) and standard log Po/w values. Many compounds of pharmaceutical interest can be quite hydrophobic and have, simultaneously, basic nitrogen atoms or acidic sulfur containing groups in their structure. This renders them ionizable. The hydrophobicity of the molecular drug form (Po/w value) is completely different from its ionic form (log Po/w(+ or -) value). The actual hydrophobicity of such ionizable molecule depends on the pH. It can be represented by an apparent Papp value that takes into account the amount of compound in its molecular and ionic state combining the Po/w and Po/w(+ or -) values. In this work, log k in RPLC for ionizable as well as non-ionizable pharmaceutical compounds with different therapeutic properties (10 beta-blockers, seven tricyclic antidepressants (TA), eight steroids and 12 sulfonamides) were correlated with log Po/w. Similar correlations were done between log k and the corrected log Papp values at pH 3. Aqueous-organic mobile phases containing acetonitrile (conventional RPLC) and micellar-organic mobile phases (micellar liquid chromatography, MLC), prepared with the anionic surfactant sodium dodecyl sulfate and the organic solvents acetonitrile, propanol or pentanol, were also used to elute the compounds. All mobile phases were buffered at pH 3. Using conventional retention RPLC data, the correlation of log k with log Po/w, was satisfactory for steroids because they cannot ionize. For ionizable beta-blockers and TAs, the use of log Papp values improved the quality of the correlations, but yielded similar results for sulfonamides. In MLC, since an electrostatic interaction is added to hydrophobic forces, poorer correlations were obtained in all cases. The retention data obtained in RPLC also seems to correlate better with the biological activity of the drugs.

Multivariate adaptive regression splines (MARS) in chromatographic quantitative structure–retention relationship studies

The multivariate adaptive regression splines (MARS) methodology was applied to build quantitative structure–retention relationships (QSRRs). The response (dependent variable) in the MARS models consisted of the logarithms of the extrapolated retention factors (log k w) of 83 structurally diverse drugs on a Unisphere PBD column, using isocratic elutions at pH 11.7. A set of 266 molecular descriptors was used as predictor (independent) variables in the MARS model building. The optimal MARS model uses 34 basis functions to describe the retention and has acceptable predictive properties for new objects. The molecular descriptors included in the model describe hydrophobicity, molecular size, complexity, shape and polarisability. Some additional MARS models were created using alternative strategies. These include models with log P as the single predictor and models obtained with only the three most important molecular descriptors. The use of classification and regression trees (CART) as feature selection technique for predictor variables used in the MARS model was also investigated. Further, it is also studied whether allowing quadratic terms instead of interaction terms might lead to better MARS models.

Quantitative Structure‐Retention Relationships (QSRR) of Some CNS Agents Studied on DB‐5 and DB‐17 Phases in Gas Chromatography

AbstractA QSRR study was performed to develop a predictive model correlating molecular structures with their RIs in gas chromatography. CNS agents included some benzodiazepines, barbiturates and phenytoin, which had been studied, previously, on two DB stationary phases with different phenyl percentages. At first, a high quality model (R=0.988, F=253.89 for DB‐5 and R=0.983, F=164.721 for DB‐17 column) was generated for two columns separately, using only calculated descriptors and multiple linear regression techniques. Then a combined model, added a polarity term of stationary phase (M), was also developed for these columns, and the result was satisfactory (R=0.989, F=232.354). The results of leave‐one‐out cross and external validation techniques showed good predictive ability of the models (R$\rm{ {_{cv}^{2}}}$=0.967, R$\rm{ {_{Prediction\ set}^{2}}}$=0.954). The results of the study indicated that a six‐parameter equation can be utilized for prediction of retention indices of compounds on DB‐5 and DB‐17 stationary phases simultaneously, for which there are no empirical RI values.

Quantitative structure–retention relationship study of α-, β 1-, and β 2-agonists using multiple linear regression and partial least-squares procedures

A quantitative structure–retention relationship (QSRR) study has been performed for the correlation of the gas chromatographic-mass spectrometry (GC-MS) relative retention times (RRT) of α-, β 1-, and β 2-agonists with their molecular characteristics in order to create models for the prediction of RRT values of unanalyzed molecules. The data structure was investigated by principal component analysis (PCA). Modeling of the RRT of α-, β 1-, and β 2-agonists, as a function of many diverse descriptors, was established by means of the multiple linear regression (MLR) and partial least-squares projections to latent structures (PLS) methods.

Correlation of Retention of Anilides and Some Molecular Descriptors. Application of Topological Indexes for Prediction of log k Values

A quantitative structure-retention relationships study, proceed by RP-18 HPLC, was used to investigate physicochemical parameters related to RP retention of para substituted anilides of 2,2-dimethylpropanoic, benzoic and α-phenylacetic acid, using a methanol-water mobile phase. Multiple linear regression analysis was used to correlate chromatographic retention constants of the compounds, dipole moments (μ mph ) and permittivities (ɛ mph ) of mobile phases and some molecular descriptors of the investigated compounds. The following molecular descriptors were applied: different topological indexes (M, 0 χ, 1 χ, 2 χ, 0 χ ν , 1 χ ν , 2 χ ν and M ν ), log P Rekker , log S, hydrogen-bond acceptor indicator (HA) and molecular weight. For the prediction of chromatographic retention of the compounds studied multiparametric equations are proposed. The reasonable predictive power of the proposed equations is obtained.

Classification and regression tree analysis for molecular descriptor selection and retention prediction in chromatographic quantitative structure–retention relationship studies

The use of the classification and regression tree (CART) methodology was studied in a quantitative structure–retention relationship (QSRR) context on a data set consisting of the retentions of 83 structurally diverse drugs on a Unisphere PBD column, using isocratic elutions at pH 11.7. The response (dependent variable) in the tree models consisted of the predicted retention factor (log k w) of the solutes, while a set of 266 molecular descriptors was used as explanatory variables in the tree building. Molecular descriptors related to the hydrophobicity (log P and Hy) and the size (TPC) of the molecules were selected out of these 266 descriptors in order to describe and predict retention. Besides the above mentioned, CART was also able to select hydrogen-bonding and molecular complexity descriptors. Since these variables are expected from QSRR knowledge, it demonstrates the potential of CART as a methodology to understand retention in chromatographic systems. The potential of CART to predict retention and thus occasionally to select an appropriate system for a given mixture was also evaluated. Reasonably good prediction, i.e. only 9% serious misclassification, was observed. Moreover, some of the misclassifications probably are inherent to the data set applied.

Stereoselective binding of 2,3-substituted 3-hydroxypropionic acids on an immobilised human serum albumin chiral stationary phase: stereochemical characterisation and quantitative structure–retention relationship study

The binding characteristics of a series of 2,3-substituted 3-hydroxypropionic acids, with anti-inflammatory properties, bearing two chiral centres, were studied by HPLC upon HSA (human serum albumin)-based stationary phase. The compounds were analysed in their stereoisomeric erythro and threo forms and the chromatographic conditions for enantioseparation of the erythro and threo forms were studied on human serum albumin stationary phase. The enantiomer elution order was determined by injection of the enriched samples or by carrying out the CD spectra of each enantiomeric fraction. The absolute configuration of the single enantiomers was assigned on the basis of their CD spectra. A QSRR study was performed by subjecting the chromatographic data of the compounds to multiparameter regression analysis against various molecular descriptors to have insight into the chiral recognition mechanism. The lipophilicity appeared to be the most important parameter in determining the affinity to the protein, the compounds’ capacity factors being linearly correlated to the experimental RP-HPLC partition coefficients (log k′ w). The enantioselectivity factors ( α) related to the enantiomers of the erythro and threo forms were studied taking into consideration both the physico-chemical parameters and the conformational behaviour of the compounds.

Application of multivariate mathematical-statistical methods to compare reversed-phase thin-layer and liquid chromatographic behaviour of tetrazolium salts in Quantitative Structure-Retention Relationships (QSRR) studies

The retention parameters of seven mono- and nine ditetrazolium salts were investigated by reversed-phase liquid chro- matography (RP-LC) using polyethylene-coated alumina support with various concentration of eluent-mixtures and by reversed- phase thin-layer chromatography (RP-TLC) using the same support and eluent-mixtures. Principal component analysis (PCA) fol- lowed by non-linear mapping (NLM) and varimax rotation was used for the determination of molecular substructures and physicochemical parameters accounting for the separation in the different methods and circumstances. Calculations proved that t he steric and electronic parameters have the highest influence on the retention of tetrazolium salts. This investigation uncovered that the thin-layer chromatography is strictly independent from liquid chromatography. It has been established that multivariate mathema ti- cal-statistical methods are the most appropriate ways for evaluation of large data matrices in various chromatographic departures.

Use of a Modified Nonlinear Mapping Method in Quantitative Structure Retention Relationship Study

The interaction of 20 nonsteroidal anti-inflammatory drugs with a model protein was studied by reversed-phase high-performance liquid chromatography and the relationship between the strength of interaction and the physicochemical parameters of drugs was elucidated by principal component analysis followed by modified nonlinear mapping and cluster analysis. It was established that the polarity and and sterical parameters of drugs exert the highest influence on the interaction. Cluster analysis and nonlinear mapping using the absolute values of principal component loadings explain more precisely the interaction than the traditional nonlinear mapping and cluster analysis do.

Comparison of partial least-square method and canonical correlation analysis in a quantitative structure–retention relationship study

The retention of 7 monotetrazolium and 9 ditetrazolium salts was determined on alumina and reversed-phase (RP) alumina layers using n-hexane-1-propanol and water-1-propanol mixtures as eluents. The retention capacity and the specific surface area of solutes in contact with the stationary phases were calculated. The relationship between retention characteristics and physicochemical parameters of solutes was elucidated by canonical correlation analysis and partial least-square regression analysis. Both methods found significant relationships between the chromatographic and physicochemical parameters, however, the results were different according to the method applied. Calculations suggested that the retention on both alumina and RP alumina layers is of mixed character, hydrophobic, electronic and steric parameters are equally involved in the retention.

Quantitative structure–retention relationship studies for predicting the gas chromatography retention indices of polycyclic aromatic hydrocarbons: Quasi-length of carbon chain and pseudo-conjugated system surface

A new method of quantitative structure–retention relationship studies is reported for predicting capillary gas chromatography (GC) retention indices of polycyclic aromatic hydrocarbons (PAHs) by using two physicochemical parameters: pseudo-conjugated π-system surface ( S π) and quasi-length of carbon chain ( N′), which represent the effect of the molecular π electronic conjugated surface and the molecular polarizability effect of PAHs on their corresponding gas chromatographic retention indices, respectively. Regression analysis is performed with regression coefficient being 0.9968 by using the above two parameters for capillary GC indices of 100 PAHs on SE-52 capillary columns. The results demonstrates a good linear relationship between the gas chromatographic retention index of PAHs and both their parameters N′ and S π. The method developed is successfully used for estimating and predicting the capillary GC retention index of PAHs.

Quantitative structure-retention relationship study of tetrazolium salts on alumina support.

The retention of 7 monotetrazolium and 9 ditetrazolium salts was determined on alumina and reversed-phase (RP) alumina layers using n-hexane-2-propanol and water-2-propanol mixtures as eluents. The retention capacity and the specific surface area of solutes in contact with the stationary phases were calculated. Quantitative structure-retention relationship calculations indicated that the retention capacity of solutes on RP alumina layers depended not only on the molecular hydrophobicity but also on the hydrogen-donor and acceptor properties. Specific surface areas were related to the electronic and steric parameters of the solutes. Calculations suggested that the retention on both alumina and RP alumina layers is of mixed character, hydrophobic, electronic and steric parameters are equally involved in the retention.

Use of cluster and principal component analysis in quantitative structure-retention relationship study

The retention time of 42 barbituric acid derivatives was determined on a porous graphitized carbon (PGC) column using water-acetonitrile mixtures as eluents. Linear correlations were calculated between the logarithm of the capacity factor and the acetonitrile concentration in the eluent. To find the relationship between the retention parameters and physicochemical parameters of barbiturates, principal component analysis followed by two-dimensional nonlinear mapping and cluster analysis was used. Calculations were carried out on both the correlation and the correlation matrices. The retention of barbituric acid derivatives on PGC column does not depend significantly on the hydrophobicity parameters of solutes suggesting that the selectivity of PGC column is different from that of traditional reversed-phase columns, although the eluents are typical reversed-phase eluents. The comparison of the various methods of calculation (using correlation or covariance matrix) indicated that they exert considerable effect on the results and therefore their simultaneous application is highly recommended.

Quantitative structure-retention relationships in doping control.

Regression equation modelling was used for the correlation of gas chromatographic relative retention times tRR of anabolic steroids, stimulants and narcotics with their molecular characteristics in order to create a model for the prediction of tRR values of unanalyzed molecules. Predicting chromatographic retention parameters is one of the main goals of the quantitative structure-retention relationships (QSRR) methodology. To be performed, QSRR studies require two tools; a methodology for the extraction of the structural characteristics and a statistical program for the correlation of these characteristics with the chromatographic data.

Structure-retention relationships of steroid hormones in reversed-phase liquid chromatography and micellar electrokinetic capillary chromatography

Quantitative structure-retention relationship (QSRR) studies are useful prediction, finding the relevant structural descriptors for analytes and estimating the relative biological activities of a series of analytes. Most of the studies have been conducted by RP-HPLC and a few by micellar electrokinetic capillary chromatography (MECC). The aim of this work was to find structural parameters and characteristics related to the RP retention and electrophoretic migration of steroids in order to predict the retention/migration of steroid hormones on the basis of their molecular structure. Retention data were obtained with an ODS column using as mobile phases aqueous methanol-acetonitrile (mobile phase A) and methanol-tetrahydrofuran (mobile phase B). MECC was conducted with a sodium dodecyl sulfate (SDS)-borate system and with a mixed micellar solution of SDS and sodium cholate. Several topological indices, such as the connectivity indices, X, were used as structural parameters. Steric factors seem to have a great effect on the retention of steroid hormones, especially with the MeCN-containing mobile phase. Retention in mobile phase B could be predicted more accurately. Topological indices can be used in the modelling and prediction of the retention/migration of steroid hormones when the solutes form a congeneric series and stereochemical properties do not govern the separation process.

Prediction of gas chromatographic retention data for hydrocarbons from naphthas

Regression equations that model the gas chromatographic retention behavior of hydrocarbons found in complex petrochemical mixtures were developed for two different stationary phases, SE-30 and Carbowax 20M. The models had relative standard errors in the range 1--2%. This quantitative structure-retention relationship (QSRR) study focused on a relatively heterogeneous data set and resulted in the generation of several statistical models that related Kovats' retention index with descriptors that encode molecular structure. Also investigated was the addition of boiling point as a physicochemical descriptor. These models bore a significant improvement over the models containing only structural descriptors, with R values of 0.996. 27 refs., 4 figs., 8 tabs.

Quantitative structure-retention relationship studies of sulfur vesicants

Quantitative structure-retention relationship (QSRR) methods were followed to relate the observed Kovats retention indices of sulfur vesicants with their molecular structure. Topological, electronic, and geometrical descriptors were calculated to represent the molecular structures. Then multiple linear regression techniques were used to generate regression equations to model the retention behavior on three stationary phases