Molecular modeling of quantitative structure retention relationship studies: retention behavior of polychlorinated dibenzofurans on gas chromatographic stationary phases of varying polarity by a novel molecular distance edge vector

Chemical structures of polychlorinated dibenzodioxin (PCDD) congeners are described by a novel molecular distance edge vector (VMDE), developed in our laboratory, that consists of the modified molecular distance edge parameters based on the identical group as a pseudo-atom instead of a traditional atom. Quantitative structure retention relationships (QSRRs) between the new VMDE parameters and the gas chromatographic retention behavior of PCDDs are then generated by a multiple linear regression method for nonpolar, moderately polar, and polar stationary phases. All QSRR models with a high correlation (R > 0.99) are developed for nonpolar, moderately polar, and polar columns (DB-5, SP-2100, SE-54, and OV-1701). Cross validation with the leave-one-out procedure is performed, and satisfactory results are obtained with high correlation. The obtained results show that the new VMDE vector is adapted to characterize the chemical structure and model the retention behavior of PCDDs on various polar stationary phases.     

Predictions of Reversed-Phase Gradient Elution LC Separations Supported by QSRR

Previous studies demonstrated that quantitative structure-retention relationships (QSRR) combined with the linear solvent strength (LSS) model allow for prediction of gradient reversed-phase liquid chromatography retention time for any analyte of a known molecular structure under defined LC conditions. A QSRR model derived at the selected gradient time and at the same gradient time was tested. The aim the present study was to evaluate the accuracy of QSRR predictions used during the predictions of LC gradient retention times with variable gradient times. For this purpose, predictions of retention times at two gradient times were used to find the optimal, different gradient times. In the first step, experimental retention data for the model set of analytes were used to derive appropriate QSRR models at two gradient times. These QSRR models were further used to predict gradient retention times for another set of testing analytes at the two selected above gradient times. Then, applying linear solvent-strength (LSS) theory, the predicted retention times for test analytes were used to find other optimal gradient times for those analytes. Satisfactory predictions of gradient retention times for test analytes were obtained at gradient times different from those applied for model analytes.     

Comparison of theoretical and experimental models for characterizing solvent properties using reversed phase liquid chromatography

Theoretical and experimental quantitative structure–retention relationships (QSRR) models are useful for characterizing solvent properties and column selectivity in reversed phase liquid chromatography (RPLC). The chromatographic behavior of a model analyte, the herbicide atrazine, in a system derived from nine organic solvents and three chromatographic columns was used for developing QSRR models. Multiple linear regression (MLR) and partial least squares regression (PLSR) were used as statistical approaches. The similarities and differences between linear solvation energy relationships (LSER), and semi-empirical and theoretical molecular models were demonstrated. QSRR models show high predictive power, and can successfully predict retention factor (log k) for new solvents. The models are useful for solvent optimization and reducing time for method development in RPLC. The herbicide atrazine can be readily analyzed at a low level, and all three columns provided good resolution, high-performance and symmetrical peaks. The method is suitable for analysis of atrazine in water samples.     

苯乙酮衍生物气相色谱QSRR及其保留机理研究

以色谱热力学理论为基础,选取影响化合物色谱保留的分子结构和性质描述符号,采用MOPAC2000V1.3半经验分子轨道化学计算软件包PM3哈密顿函数算得的量化及物化参数,通过有进有出的逐步回归分析方法建立了苯乙酮衍生物在OV系列固定相上的气相色谱QSRR方程。所建立的多元回归方程相关系数均大于0.99。根据所建立的QSRR方程对苯乙酮衍生物的色谱保留机理进行了解释。     

烃类化合物在不同色谱柱上的定量结构-保留相关性研究

运用量子化学中的AMI方法计算烃类化合物的分子结构描述参数,借助逐步回归法建立了烃类化合物在不同极性色谱柱上的QSRR模型。结果表明：烷烃、烯烃、二烯烃类化合物在不同极性的色谱柱上的色谱保留与其分子结构描述参数之间具有较好的线性关系,烃类化合物在不同极性固定相上的保留主要与溶质分子的MR有关,即与溶质分子的色散力有关。随着溶质分子的不饱和度的增加,或固定相极性的增强,溶质分子与固定相之间的电荷传递作用随之增强。而且,烃类化合物在不同极性固定相上的色谱保留的QSRR模型均可用量化参数HOMO、LUMO、EICE以及MR参数来描述。所建立的在不同极性色谱柱上的烃类化合物的色谱保留QSRR模型预测烃类化合物的色谱保留值时具有较好的稳定性和准确性。     

Quantitative structure-retention relationships for ionic and non-ionic compounds in biopartitioning micellar chromatography

Quantitative structure-retention relationships, QSRRs, represent a powerful tool in chromatography. The objectives of QSRR studies are to predict the chromatographic retention behaviour of solutes based on their structural properties, to elucidate retention mechanisms, to optimize the separation of complex mixtures or to prepare experimental designs. In this paper, using the retention factors of 151 structurally unrelated solutes that cover a wide range of hydrophobicity, molecular size, hydrogen bonding properties and ionization degrees obtained in biopartitioning micellar chromatography (BMC) at different Brij35 micellar concentrations, several multivariate QSRR models are tested. It is demonstrated that the chromatographic retention of any molecule in BMC, independently of its family, can be adequately described by its hydrophobicity (expressed as log P) and its anionic and cationic total molar charge (expressed as alpha(A) and alpha(B)).