Quantitative Structure Retention Research Articles

Quantitative structure—retention and retention—activity relationships of some 1,3-oxazolidine systems by RP-HPTLC and PCA

A quantitative structure–retention and retention–activity relationships investigations were performed on the lipophilicities of some 1,3-oxazolidine systems as estimated by RP-HPTLC retention parameters. The classical R Mo values were compared with the factors scores obtained by principal component analysis based also onto the TLC retention data. The lipophilicities ( R Mo and factor scores) were correlated with the theoretical molecular descriptors of 1,3-oxazolidine derivatives providing by the ALCHEMY 2000 software package. The reliability of the factor scores values as lipophilic indices are shown by their significant correlation with the classical R Mo values and other molecular descriptors. In addition, the “lipophilicity chart” described by the first two components, and/or the “lipophilicity space” described by the first three components have the effect of separating compounds from each other most effectively from the congeneric (similarity) aspect point of view. Finally, these findings support the idea that the chromatographic process of the investigated compounds in this paper and consequently their partitioning over a bio-membrane are controlled mainly by lipophilicity.

Immobilized artificial membrane chromatography: quantitative structure-retention relationships of structurally diverse drugs.

The chromatographic capacity factors (log k') for 32 structurally diverse drugs were determined by high performance liquid chromatography (HPLC) on a stationary phase composed of phospholipids, the so-called immobilized artificial membrane (IAM). In addition, quantitative structure-retention relationships (QSRR) were developed in order to explain the dependence of retention on the chemical structure of the neutral, acidic, and basic drugs considered in this study. The obtained retention data were modeled by means of multiple regression analysis (MLR) and partial least squares (PLS) techniques. The structures of the compounds under study were characterized by means of calculated physicochemical properties and several nonempirical descriptors. For the carboxylic compounds included in the analysis, the obtained results suggest that the IAM-retention is governed by hydrophobicity factors followed by electronic effects due to polarizability in second place. Further, from the analysis of the results obtained of two developed quantitative structure-permeability studies for 20 miscellaneous carboxylic compounds, it may be concluded that the balance between polarizability and hydrophobic effects is not the same toward IAM phases and biological membranes. These results suggest that the IAM phases could not be a suitable model in assessing the acid-membrane interactions. However, it is not possible to generalize this observation, and further work in this area needs to be done to obtain a full understanding of the partitioning of carboxylic compounds in biological membranes. For the non-carboxylic compounds included in the analysis, this work shows that the hydrophobic factors are of prime importance for the IAM-retention of these compounds, while the specific polar interactions, such as electron pair donor-acceptor interactions and electrostatic interactions, are also involved, but they are not dominant.

Prediction of Protein Retention Times in Anion‐Exchange Chromatography Systems Using Support Vector Regression.

Quantitative Structure-Retention Relationship (QSRR) models are developed for the prediction of protein retention times in anion-exchange chromatography systems. Topological, subdivided surface are...

Chemometric comparison of recent chromatographic and electrophoretic methods in a quantitative structure–retention and retention–activity relationship context

The retention characteristics of 21 basic pharmaceutical substances with a considerable difference in hydrophobicity (octanol–water partition coefficients, log P, between −0.026 and 6.45) are considered on an immobilized artificial membrane column, with a micellar liquid chromatography and a micellar electrokinetic capillary chromatography method. Utilising principal component analysis (PCA), it is seen that although the main retention principle is the same, the above methods as well as more classical RP-HPLC methods vary in secondary retention mechanisms. Combining the results of different methods a differentiation of the substances into their pharmacological families can be seen with PCA. The high correlations of the retention characteristics with log P and a biological parameter seem little affected by the method used.

Prediction of protein retention times in anion-exchange chromatography systems using support vector regression.

Quantitative Structure-Retention Relationship (QSRR) models are developed for the prediction of protein retention times in anion-exchange chromatography systems. Topological, subdivided surface area, and TAE (Transferable Atom Equivalent) electron-density-based descriptors are computed directly for a set of proteins using molecular connectivity patterns and crystal structure geometries. A novel algorithm based on Support Vector Machine (SVM) regression has been employed to obtain predictive QSRR models using a two-step computational strategy. In the first step, a sparse linear SVM was utilized as a feature selection procedure to remove irrelevant or redundant information. Subsequently, the selected features were used to produce an ensemble of nonlinear SVM regression models that were combined using bootstrap aggregation (bagging) techniques, where various combinations of training and validation data sets were selected from the pool of available data. A visualization scheme (star plots) was used to display the relative importance of each selected descriptor in the final set of "bagged" models. Once these predictive models have been validated, they can be used as an automated prediction tool for virtual high-throughput screening (VHTS).

Development of novel pesticides based on phytoalexins: Part 2. Quantitative structure-activity relationships of 2-heteroaryl-4-chromanone derivatives.

Phytoalexins are low-molecular-weight chemicals that immune systems of plants produce and accumulate in response to infections, especially those of fungal origin. Although their content is not high in plants, yet they have shown unique fungicidal activity and played an important role in the defence system of plants. In searching for novel environmentally benign fungicides with high activity, the structures of flavanone derivatives, one of the most important phytoalexins groups, have been modified via bioisosteric substitution and a series of 2-heteroaryl-4-chromanones were designed and synthesized. They showed good fungicidal activities against rice blast disease, Pyricularia grisea (Sacc). Their IC50 values were tested in vitro and the relationship between structure and fungicidal activity was analyzed quantitatively using a Hansch-Fujita approach. The results showed that hydrophobicity was very important for fungicidal activity and there is apparently an optimum hydrophobic property for the molecules at a log Pow value of about 2.7. In addition, the results indicated that electronic effects played an important role in binding with the receptor and that the C=O group was probably a electron-accepting site. The quantitative structure-retention correlative equation of the title compounds was also established.

Predictive quantitative structure retention relationship models for ion-exchange chromatography

A database of probe molecules and their reported ion-exchange chromatographic data was collected from the literature, after which an extensive set of both traditional and novel molecular property descriptors were computed for each probe molecule. A genetic algorithm/partial least squares (GA/PLS) approach was then used on the data to create a predictive Quantitative Structure-Retention Relationship (QSRR) model of retention where a subset of the original data was used for training and the remainder of the data as a test set. The utility of this model was demonstrated by using it to predict the chromatographic behavior of compounds not included in the training set. The results presented in this paper demonstrate the utility of modern QSRR modeling to predict chromatographic behavior in ion-exchange systems.

Study of the retention parameters of barbituric acid derivatives in reversed phase HPLC by using quantitative structure-retention relationships

Retention parameters of 45 different barbituric acid derivatives were determined on an amide embedded RP silica column (Discovery RP-AmideC16) using non-buffered methanol-water mixtures as eluents. Linear correlations were calculated between the logk values and the methanol concentration in the eluent. The intercept (logk 0) and slope (b) values of the line, the combined retention parameter (logk 0/b), asymmetry factor (AF 5) and theoretical plate (N) value of each barbituric acid derivative were correlated with different conventional and quantum chemical structural descriptors using Quantitative Structure-Retention Relationship (QSRR). The SRA (stepwise regression analysis) results indicated that the retention is mainly governed by the steric and the lipophilicity properties of the barbituric acid derivatives in water-methanol eluent mixtures.

Quantitative structure–enantioselective retention relationships for chromatographic separation of arylalkylcarbinols on Pirkle type chiral stationary phases

Quantitative structure–retention (QSRR, retention factors log k 1 and log k 2 for the first and second eluted enantiomer) as well as enantioselective retention relationships (QSERR, separation factor log α) for a series of 42 chiral arylalkylcarbinols on four brush-type chiral stationary phases are derived by multiple linear regression analyses and artificial neuronal network calculations using 2D and 3D molecular descriptors including those obtained by quantum chemical calculations. Separation factors are in addition modeled by the 3D-QSAR method of comparative molecular field analysis (CoMFA). For the retention factors the LUMO energy turns out to be the most important descriptor, whereas for log α it is the hydrophobicity of the analytes. With CoMFA both the steric and electrostatic field are found to be of almost comparable significance.

Quantitative structure–retention and retention–activity relationships of β-blocking agents by micellar liquid chromatography

Sixteen β-blocking agents (acebutolol, alprenolol, atenolol, bisoprolol, carteolol, celiprolol, esmolol, labetalol, metoprolol, nadolol, oxprenolol, pindolol, practolol, propranolol, sotalol and timolol) showing a large range of hydrophobicity (octanol–water partition coefficients, log P between −0.026 and 2.81) were subjected to micellar liquid chromatography with sodium dodecyl sulfate as micelle forming agent, and n-propanol as organic modifier. The correlation between log P and the retention factor extrapolated to a mobile phase free of micelles and organic modifier was investigated. The use of an interpolated retention factor or the retention factor for specific individual experimental mobile phases was however advantageous since the retention factors of all β-blocking agents were measurable in the selected mobile phases. Good correlations with log P and with in vitro biological parameters (cellular permeability coefficients in Caco-2 monolayers and apparent permeability coefficients in rat intestinal segments) were found.

Quantitative structure-retention relationships with model analytes as a means of an objective evaluation of chromatographic columns.

The performance of several previously designed model series of test analytes has been tested to characterize in an objective, quantitative manner modern stationary phases for reversed-phase high-performance liquid chromatography (RP-HPLC) using quantitative structure-retention relationships (QSRRs). Three QSRR approaches and three respective series of test analytes recommended for studies of the molecular mechanism of chromatographic retention are employed: the reduced linear solvation energy relationship (LSER)-based model of Abraham, a model employing structural descriptors from molecular modeling, and a model relating retention to the n-octanol-water partition coefficient log P. All of the models and test analytes proposed provide reliable QSRR equations. Those equations discriminate in quantitative terms individual columns and chromatographic systems and can be interpreted in straightforward rational chemical categories. In view of QSRRs, the differences in the intermolecular interactions between a given stationary phase and a structurally defined analyte rationalize the observed differences in retention. The QSRR models (previously derived retrospectively) are demonstrated to work well on new sets of RP-HPLC data. At the same time, it has been confirmed that the three test series of analytes have properly been designed and can be recommended for comparative studies of analytical columns. QSRRs once derived on a given column for model analytes can be used to predict the retention of other analytes of a defined structure. That in turn can facilitate the procedure of the rational optimization of chromatographic separations.

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.

Quantitative retention–structure and retention–activity relationships of barbiturates by micellar liquid chromatography

Studies on the structural requirements of chromatographic surfaces to emulate in vitro the partitioning process in biomembranes are of great interest. The use of micellar mobile phases in RPLC modifies the hydrophobicity of the stationary phase and provides hydrophobic and electrostatic sites of interaction as a consequence of the adsorption of surfactant monomers to the chromatographic surface. Modified stationary phases in MLC could be structurally similar to biomembranes, but thorough studies are necessary to confirm this. In this paper we focus our attention on barbiturates. The influence of the nature and concentration of the surfactant (Brij 35, SDS and CTAB) and the mobile phase pH on the retention of 13 barbiturates in modified C 18 stationary phases is studied. Quantitative structure–retention and structure–activity relationships for the barbiturates with different surfactants are proposed and compared with those obtained using hydro–organic mobile phases.

Study of Retention Behavior of Pesticides for Reversed Phase Liquid Chromatographic Separation by Quantitative Structure-Retention Relationships

Regression models that are useful for the explanation of the reversed phase liquid chromatographic retention behavior of the pesticides; triazines, phenoxyacetic esters and acetanilides were studied by quantitative structure - retention relationships (QSRRs). Descriptors were theoretically calculated by MM+ and AM1 method. The retention of triazines and phenoxyacetic esters in methanol-water was explained by solvation energy of specific site of solute, total solvation energy and polarizability which were chosen as nonspecific descriptors for acetonitrilewater. The retention of acetanilides was dependent not only on solvent-accessible surface area but on conformation of solute.

Application of Quantitative Structure-Retention Relationships for Reversed-Phase Liquid Chromatographic Separation of Pesticides.

Quantitative structure-retention relationships (QSRRs) models that predict the reversed-phase liquid chromatographic retention behavior of carboxamides and oxadiazoles are proposed. The intermolecular interaction, isomeric effect and substituent effect were explained by the descriptors determined from calculations with MM+ and AM1 methods. The retention of carboxamides was elucidated by using solvent-accessible surface area and x component of dipole moment. For oxadiazoles, 1-octanol/water partition coefficient (log P) and dipole moment were useful descriptors.

Identification of PCB Congeners by Gas Chromatography Electron Capture Detection Employing a Quantitative Structure-Retention Model

Quantitative structure-retention relationships based on high-resolution capillary dual column separation and employing dissimilar stationary phases have been developed for congener-specific identitication of polychlorinated biphenyls (PCBs) in complex environmental samples. Application of the prediction model, validated by gas chromatography/mass spectrometry, correctly assigned PCB congeners to 95% of a harbor sediment chromatographic profile. The standard Aroclor method of analysis resulted in 20% underestimation of total PCB concentration in the sediment sample compared to the congener-specific detection method.

Quantitative Structure‐Retention Relationships in Capillary Electrophoresis of Inorganic Cations and β‐Adrenolytic and Sulfonamides Compounds

AbstractQuantitative structure‐(electrophoretic) retention relationships (QSRR) were determined for metal cations using ionic radius, atomic mass and ionization energy as structural parameters. The QSRR show that atomic mass, Am, can be treated as a descriptor of differences of electrophoretic retardation of inorganic cations. Am is a measure of the effective surface area of the solutes. The ionic radius of metals, Ir, accounts for the effective charge of a solute. The ionization energy, Ei, provides a correction to Ir with regard to solute charge. High predictive potency of QSRR and direct access to the required descriptors allow for the application of the approach in identification of individual components of mixtures of metals. In case of the capillary electrophoretic parameters of organic solutes molecular mass is a most significant retention descriptor identified. It can be considered a first approximation of the electrophoretic retardation factor. Further progress in QSRR in capillary electrophoresis of drugs requires reliable descriptors of effective charge of organic solutes.

Quantitative structure-retention and structure-odor intensity relationships for a diverse group of odor-active compounds

Numerical representations of structure-based features are used to estimate both the retention indexes and sweetnesses of a diverse set of industrially important fragrance compounds. Retention indexes measured on nonpolar as well as polar stationary phases are modeled with accuracies of 3.6% and 5.6% at the mean of the respective retention ranges. Similar success was achieved when the developed equations were applied to predict the retention indexes of external data set compounds. Finally, the implications of using strictly 2-D structural information versus incorporating geometrical information are explored and discussed. The intensity of sweetness attributed to each compound is quantitatively predicted using identical multiple linear regression techniques. Difficulties encountered in this portion of the study warranted a critique of the procedures used to gain access to the odor data. As a consequence, the limited control exerted over several experimental variables is questioned.

QSRR in Liquid Chromatography Aided by Computational Chemistry

Abstract A quantitative structure-retention relation in reversed-phase liquid chromatography was studied with values calculated by computational chemistry. These values were Van der Waals volume and surface area, calculated by MOPAC-BlogP, total energy calculated by Molecular Mechanics (MM2), kinetic, potential and total energies calculated by Molecular Dynamics (MD), and total energy and dipole moment calculated by Extended Huckel theory (EH). The precision of predicted retention time of non-ionic compounds is improved by using these values instead of Van der Waals volume calculated by Bondi's method and derealization energy from literature.

Mechanism of retention of benzodiazepines in affinity, reversed-phase and adsorption high-performance liquid chromatography in view of quantitative structure retention relationships

Quantitative structure-retention relationships (QSRRS) were compared for a set of 1,4-benzodiazepine (BDZ) test solutes analyzed by high-performance liquid affinity chromatography (HPLAC), reversed-phase (RP) and adsorption (normal-phase, NP) high-performance liquid chromatography (HPLC). The HPLAC data reflected the enantioselective retention on a human serum albumin-based chiral stationary phase (HSA-CSP); RP-HPLC data were determined on a specially deactivated hydrocarbon-bonded silica material; NP-HPLC was performed on a graphitized carbon stationary phase. Molecular descriptors reflecting additive-constitutive properties of the solutes as well as their geometry and electron charge distribution were generated using molecular modelling software. The QSRR equations derived for each chromatographic mode involved different sets of molecular descriptors. Analysis of the physical meaning of the individual descriptors allowed for interpretation of separation mechanisms at molecular (submolecular) level and rationalization of the observed separation patterns. For HPLAC the contributions by hydrophobic, steric and electrostatic factors were quantified and accounted for the differential retention of enantiomers. Retention in RP-HPLC was demonstrated to be a net effect of both non-specific (dispersive) and directional (electrostatic) intermolecular interactions between solute and molecules of both stationary and mobile phases. QSRR equations derived for NP-HPLC proved the predominance of specific dipolar and charge-transfer attractive interactions. The QSRR-based models obtained appear a reliable and convincing proof for involvement of distinctive mechanisms in different HPLC systems.