Retention prediction system conditions

In this contribution, we will describe the basic approach to construct the retention prediction system in reversed-phase LC for alkyl-benzenes, polycyclic airomatic hydrocau bons (PAHs) aind polau group substituted benzenes, baised on the use of sudi established relationships between retention and physicodiemlcal parameters of these compounds. The system has been constructed on a 16—bit microcomputer, and the application for optimization of sepairation conditions will be demonstrated. 

This equation means that, if X, the concentration of organic modifier in the mobile phase, and and P, descriptors ofa compound are given, the logarithm of the capacity factor, log k can be determined for any chromatographic conditions. This is the basic concept of the retention prediction system investigated in this study. 

According to the above mentioned procedures, the computer-assisted retention prediction system (RPS) for the CIS column wascon-structed on the 16-bit microcomputer. The flow-chart of thisfunction of RPS is shown in Figure 2. In the use of RPS as the system to predict retention times of solutes, the following data eure input with the interactive style after accessing the function on the CRT of the computer (1) the compound name or the chemical formula of interesting solutes, (2) experimental conditions (mobile phase (M), volume fraction of organic modifier in the mobile phase (X), flow rate of the mobile phase (F)). 

Finally, structure-based predictive software is commercially available (such as CHROMDREAM, CHROMSWORD or ELUEX) for mobile phase optimisation in RPC. This software incorporates some features of the expert system, as it predicts the retention on the basis of the molecular structures of all sample components (which should be known) and the known behaviour of model compounds on various HPLC columns. No initial experimental runs are necessary as the retention data are calculated from the additive contributions of the individual structural elements to the retention, contained in the software databa.se and consequently optimum composition of the mobile phase is suggested. Such predictions are necessarily only approximate, do not take into account stereochemical and intramolecular interaction effects, and predicted separation conditions can be used rather as the recommendation for the initial experimental run in the subsequent optimisation procedure. 

Computer programs enable the user to use well-established relationships between separation, retention, and chromatographic conditions to allow the prediction of results of different experiments and optimization of separation conditions, working mainly with a PC rather than with an HPLC system. In this case, a user enters some information such as run data and conditions, and works with the software interactively. 

Also in this case the calculated (predicted) retention values showed good agreement with the experimental results. It has been concluded that pH gradient elution may enhance the separation efficacy of RP-HPLC systems when one or more analyses contain dissociable molecular parts [81]. As numerous natural pigments and synthetic dyes contain ioniz-able groups, the calculations and theories presented in [80] and [81] and discussed above may facilitate the prediction of the effect of mobile phase pH on their retention, and consequently may promote the rapid selection of optimal chromatographic conditions for their separation. 

Natural extracts generally contain molecules with highly different retention characteristics which cannot be separated under isocratic conditions. The application of gradient elution is a necessity for these types of natural samples. However, the optimization of gradient elution on the base of isocratic data is cumbersome and the prediction of retention in gradient elution from isocratic data is difficult. Retention in an isocratic system can be described by a polynomial function ... 

The method has been proposed for the prediction of retention data in isocratic systems from data measured in gradient elution and vice versa [84], Similar calculation methods may be very important in the analysis of natural extracts containing pigments with highly different chemical structure and retention characteristics. The calculations make possible the rational design of optimal separation conditions with a minimal number of experimental runs. 

The pKa of the imidazole ring is near 6 (16) so histamine would only exist as an ion in the acidic (pH = 2-3) mobile phase. One would predict no retention on a bonded phase column under this condition however, it does occur. Figure 3 is the simplest way to account for this retention. Here, the mineral acid acts as the counter-ion, as well as the buffer. All of the histamine in the mobile phase is in the ionic form and is in equilibrium with the ion-pair which is only soluble in the stationary phase chemically bonded to silica. Histamine only elutes in the ionic form and is then derivatized for detection. A sharp peak in the chromatogram with good shape and no change in retention time with variation in sample concentration indicates a working system. However, if the paired ion has some solubility in the mobile phase, peak tailing occurs. 

Darvas et al. (1999) and Tarjanyi et al. 1998 presented an illustration of the predictions of MetabolExpert for the drug (-)-diprenyl. A metabolic tree was shown including 4 generations and 36 different metabolites. For 25 of these metabolites experimental retention times were reported. It is not clear whether all these 25 metabolites were observed in experimental metabolism studies. Most metabolic studies report relatively few metabolites minor ones may not be detected or identified and their observation may be dependent on the experimental conditions used in the analysis. An important predicted metabolite of deprenyl, benzyl methyl ketone, was reported to be observed only when an appropriate HPLC extraction system was used (Darvas et al., 1999). Bencze et al. (2000) have illustrated the use of the system in conjunction with the related HazardExpert system in a hazard assessment of ethylene oxide. 

Quantitative chromium solid-state speciation in chromite ore processing residue (COPR) has defined the mineral species and the processes controlling the retention and release of Cr(VI) from CO PR-contaminated sites (Hillier et al, 2003). Information that, used within a process-based modelling framework, has helped to predict the impact of changes in physicochemical conditions on the COPR, to test the extent to which the system may be considered at equilibrium and that, therefore, need to be considered within the context of informed remediation (Geelhoed et al, 2001). 

In order to be able to predict the retention behavior of peptides of different composition, of peptides of the same composition but different sequence (positional isomers), and of diastereoisomeric peptides, a knowledge of the incremental contribution of each amino acid to the overall contact area term is required not only for each well-defined stationary phase but also for each mobile-phase condition. Group retention coefficient summation approaches based on the assumption that selectivity differences can be ascribed predominantly to amino acid sequence differences, have been developed by Meek (46a, 52b) and Su et al. (45a). These treatments have subsequently been applied to a number of different elution systems (52c-52e). A comparative analysis of the different amino acid group contribution coefficients derived for phosphate, perchlorate, pyridine/acetate, trifluoroacetate, and bicarbonate buffer systems has been reported (52f). 

Different models of the retention in these complex systems do not allow for accurate prediction of the analyte retention, but they assist in the understanding of the processes governing analyte migration through the column and also help in the selection of starting conditions and intelligent optimization of a particular separation. 

In the past, several theoretical models were proposed for the description of the reversed-phase retention process. Some theories based on the detailed consideration of the analyte retention mechanism give a realistic physicochemical description of the chromatographic system, but are practically inapplicable for routine computer-assisted optimization or prediction due to then-complexity [9,10]. Others allow retention optimization and prediction within a narrow range of conditions and require extensive experimental data for the retention of model compounds at specified conditions [11]. 

The retention factor is also used to predict the position in time of a particular compound under the selected conditions of separation. For example, the k can be used to compare solute retention from one chromatographic system to another because—given the same mobile phase, stationary phase, and stationary phase particle size—it will not differ with flow rate or column diameter and length. 

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