Prediction of Peptide Retention in RP-LC

The retention of small peptides can be predicted by summing the hydrophobic contribution to retention of each amino acid of peptides. But the retention time of peptides larger than 10–15 residues are less than that predicted by summing the retention coefficients of each constitutive residue. A new prediction model, considering the effects of the peptide length and contact area of each amino acid with the stationary phase for larger peptides was proposed. The model was validated by 136 peptides identified by nano-flow 2-D-LC-ESI-MS-MS platform and other retention data observed from literature. The high degree of correlation between the observed and predicted retention time by using the new model is not only good evidence for the accuracy of our predictive method, but supports the supposition that the peptide length and contact area of each amino acid with stationary phase are important factors affecting peptide retention time for larger peptide. In addition it is found that the range of peptide length is wider, the accuracy of prediction is better. The ratio coefficient of surface area of non-polar, polar and charged amino residues contacting with the stationary phase were all calculated to be less than one. Revised: 30 June and 11 August 2005     

Retention Characteristics of Peptides in RP-LC: Peptide Retention Prediction

A review of recent results of the use of chromatographic retention data in peptide identification and in the development of procedures for peptide retention prediction is presented. In recent years, reversed phase LC (RP-LC) has become an important tool in the separation of peptides in MS analysis. A challenging problem in a further expansion of RP-LC applications is the use of already available retention information for the identification purposes simultaneously with MS–MS identification. This overview focuses on the retention characteristics suggested in LC. We will discuss the application of the retention index concept in LC, which is widely used in GC to characterize retention of organic compounds. The use of retention indices as retention characteristics of analytes in LC was first suggested at the end of 1970s, however the application of retention indices is still somewhat rare today. There are several reasons for this. One is the relatively high sensitivity and variability of retention indices to the change of parameters of chromatographic systems. Another is the chemical restrictions in the search of the universal set of reference compounds suitable for retention scaling. Several methods were suggested for the prediction of the retention times of peptides. A frequently used approach is based on the additivity scheme and calculation of the elution time through the summation of retention coefficients of amino acids constituting the peptide. Such an approach allows fairly accurate predictions of the retention time of peptides made up of not more then 15–20 amino acid residues. Additional correction factors were suggested to improve predictions including corrections for the peptide length, peptide hydrophobicity, sequence of amino acids, etc. Suggested procedures are discussed in detail. Application of predicted retention times in the identification of peptides is considered. Current status of LC retention data collections is presented.     

含氧化合物气相色谱保留指数的预测

通过对部分含氧化合物(醇、酯、醛、酮)在不同固定相不同柱温下的849个样本的气相色谱保留指数值(RI)与其部分参数:拓扑指数(mQ)、定位基参数(Sox)、固定液极性值(CP)及柱温(T)建立定量结构-色谱保留相关(QSRR)模型。分别利用多元线性回归(MLR)、偏最小二乘回归(PLSR)、人工神经网络(ANN)建模,同时采用内部及外部双重验证的办法对所得模型稳定性能进行深入分析和检验,建模计算值、留一法(LOO)交互检验(CV)预测值和外部样本预测值的复相关系数Rcum、QLOO和Rext分别为0.9832、0.9829和0.9836(MLR);0.9832、0.9830和0.9836(PLSR);0.9910、0.9909和0.9900(ANN)。结果表明:所建定量结构保留关系(QSRR)模型具有良好的稳定性和预测能力,较好地揭示了含氧化合物(醇、酯、醛、酮)在不同色谱条件下气相色谱保留指数的变化规律。     

Application of the Solvatic Model for Prediction of Retention in RP-LC for Multi-Step Gradient Profiles

Application of the solvatic retention model of reversed-phase liquid chromatography was studied to predict retention of phenylisothiocyanate derivatives of amino acids from structural formulae and stationary and mobile phase properties. The gradient elution mode with methanol and acetonitrile aqueous mobile phases was used. It was shown that practically acceptable prediction or retention time values can be achieved after the first approximation step when experimental data of one run are used. The zero approximation level predictions—from structural formulae, column and mobile phase properties can be used as a “first guess” method from which further optimization can begin.

     

人工神经网络方法预测气相色谱保留值

本文运用一典型的人工神经网络模型－“反向传播“模型的改进形式，研究了诱导效应指数Ｉ，摩尔折射度Ｒｏ，疏水亲脂参数ＩｇＰ，以及分子联通性指数与气象色谱保留行为的关系，实现了对色谱保留植的预测。神经网络预测模型的最大相对误差不超过８．７％。结果表明，该方法性能良好，可望成为色谱保留值预测的有效手段。     

拓扑指数在预测氯代苯同分异构体的色谱保留值中的应用

采用三阶分子连接性指数计算分子有效表面积参数和有效体积参数，从而使ＵＮＩＦＡＣ基团贡献法能关联和预测氯代苯同分异构体的色谱保留值，实验值与预测值的相对误差小于１０％。     

不同极性固定相上醇色谱保留指数的预测

采用拓扑指数(mQ)、定位基参数(SOX)及固定液极性值(CP)与脂肪醇在6种固定相上的气相色谱保留指数值(RI)进行了相关分析,发现RI与上述参数间存在良好的相关性,其关系可表示为:RI=158·384 57·7220Q-12·0491Q 5·720SOX 5·756CP R=0·9913继以留一法(Leave-one-out,LOO)进行交互检验,相关系数RCV=0·9909。说明所建定量结构-保留关系(QSRR)模型具有良好的稳定性和预测能力,较好地揭示了脂肪醇类物质在不同固定相上气相色谱保留指数的变化规律。     

电拓扑状态预测有机磷酸酯类化合物的气相色谱保留指数

以原子类型电拓扑状态指数(ETSI)有效表征35个有机磷酸酯类化合物(OP)的分子结构, 应用基于预测的变量选择与模型化(VSMP)方法建立OP化合物在3种不同固定相上的气相色谱保留指数(RI)与分子结构(ETSI)的定量相关模型. 结果表明, 影响不同固定相上OP色谱保留的主要结构因素都是由7个ETSI描述子对应的子结构碎片, 即: ＝CH₂,≡C—, aaC—, ＝O, —O—, Cl和Br. 其中子结构aaC—, ＝O和—O与OP化合物母体骨架密切相关, 而＝CH₂,≡C—, —Cl和—Br反映支链或取代基的变化. 通过多元线性回归法建立OP化合物在三个固定相上的定量结构-保留相关模型(QSRR)发现, 各QSAR模型的估计相关系数均在0.99以上, LOO检验相关系数在0.98以上, 表明模型具有良好估计能力与稳定性. 应用28个OP训练集样本构建的QSRR模型预测外部7个检验集RI结果表明训练集模型具有良好预测能力.     

气相色谱保留指数定性方法研究进展

综述了程序升温气相色谱保留指数,I^T与Kovats恒温保留指数,之间的关系、I^T的标准化和重现性问题以及定量结构保留指数关系(QSRR)研究进展;对于应用特殊检测器和极性柱定性、对多环芳烃和多氯联苯类物质利用保留指数定性的情况,选择非正构烷烃类同系物作为参考标准时准确性大为提高,比较了由此得到的保留指数与Kovats保留指数的关系;展望了利用保留指数定性的前景。     

Chromatographic Identification of Cyclohexane Chlorination Products by an Additive Scheme for the Prediction of Retention Indices

Identification of the products of free-radical chlorination of cyclohexane seems to be a complex analytical problem due to the following principal reasons: (1) the available reference information (both standard mass spectra and gas chromatographic retention indices, RI) is strongly restricted to the data for only few simplest congeners, (2) mass spectra of isomeric chlorinated derivatives are practically indistinguishable, and (3) the number of isomers increases with the growing number of chlorine atoms in the molecule until six. To solve this problem, the modified additive scheme for precalculation of the RIs of chlorinated cyclohexanes on standard non-polar polydimethyl siloxane stationary phases was proposed and used. This approach is based on the data for congeners with fewer number of chlorine atoms in the molecule; the principal feature is its applicability to a diastereomers. The final set of both experimental and precalculated RI values permits us to identify unambiguously more than 20 products of cyclohexane chlorination in reaction mixtures. Different modes of the quality control of evaluated retention indices are discussed.     

Combined Effect of Temperature and Ternary Mobile Phase Composition on the Retention in Ternary Isocratic and Gradient Elution RP-LC under Isothermal Conditions. Application to the Retention Prediction of Four Macrolide Antibiotics

Retention models considering simultaneously ternary mobile phase organic contents and column temperature (T) were developed by a direct combination of equations expressing separately the dependence of the retention upon each of these factors. Thus, a combination of a linear dependence of the logarithm of the solute retention factor, ln k (T), against 1/T, i.e. ln k (T) = a + b/T, and of either a linear or a quadratic dependence of ln k upon the compositions of a binary mobile phase, gave two different expressions for the logarithm of the solute retention factor in terms of both temperature and organic contents in the ternary mobile phase. The effectiveness of the above models was tested in the prediction of isothermal retention of a mixture of four macrolide antibiotics under ternary isocratic and gradient elution conditions using mobile phases modified by methanol and acetonitrile. The limiting case of using ternary eluents with constant ratio of the concentrations of the two organic modifiers was also tested.     

Comparison of Retention Indices of Some Monosubstituted Benzenes Calculated by Different Mathematical Methods in RP-LC

In reversed phase liquid chromatography, the retention indices of benzene and nine mono substituted benzenes with different functionality based on the alkan-2-ones and alkyl aryl ketones retention index standards have been determined by the application of two new mathematical adaptation methods, viz. a multiparametric least-squares regression iterative method based on the determination of the adjusted retention times and a local cubic interpolation method directly using the total retention times. The two methods were applied to two types of columns. The first group includes four octadecyl-C₁₈ columns with different packing materials obtained from different manufacturers, while the second comprises an octyl-C₈ column. The retention indices have been extensively studied using either methanol–water or acetonitrile–water mobile phase systems. The influences of the concentration of the organic modifier in the mobile phase (methanol or acetonitrile), the column temperature, and the column packing material on retention indices of the set of the ten monoaromatics studied were also investigated. The calculated multiparametric retention indices values, those obtained by the local cubic interpolation and Kováts’ methods are compared. Good agreement was observed between the retention indices calculated by the three methods.     

电拓扑状态预测多氯二苯并噻吩及噻吩砜化合物的气相色谱保留指数

以原子类型电拓扑状态指数(ETSI)有效表征了135 个多氯二苯并噻吩(PCDT)和135 个多氯二苯并噻吩砜(PCDTO₂)的分子结构, 应用基于预测的变量选择与模型化(VSMP)方法建立PCDT 和PCDTO₂ 化合物在DB-5 气相色谱柱上的气相色谱保留指数(RI)与分子结构(ETSI)的定量相关模型, 模型的相关系数r² 分别为0.9939 和0.9729, LOO 交叉验证相关系数 q² 分别为0.9921 和0.9692. 为验证模型稳定性和预测能力, 应用17 个PCDT 和PCDTO₂ 训练集样本构建的QSRR 模型的r² 分别为0.9959 和0.9783, LOO 交叉验证相关系数 q² 分别为0.9921 和0.9740, 说明模型具有良好的稳定性. 以此模型预测外部8 个检验集及110 个预测集的RI 值, 8 个检验集样本的结果表明训练集模型具有良好预测能力.     

色谱保留值预测模型的研究进展

综述了国内外色谱保留值预测模型的研究进展,着重介绍了一种新兴的预测模型———CFD模型,比较了CFD模型和统计预测模型的优缺点,在此基础上对色谱保留值预测模型的发展前景进行了展望。引用文献59篇。