Optimization strategy for reversed-phase liquid chromatography of peptides

Optimization of gradient reversed phase chromatographic peak capacity for low molecular weight solutes

A general protocol for optimizing peak capacity for the separation of low molecular weight molecules under gradient elution conditions has not yet been developed. By studying the effects of gradient time, flow rate, temperature, final eluent composition, and column length on peak capacity, a protocol has been developed for the optimization of a separation of small molecules such as those seen in metabolomic studies. The strategy developed employs the Linear-Solvent-Strength Theory (LSS Theory) to predict retention, building on an approach for the optimization of the peak capacity of large molecules (peptides) in fixed column format separations.

Optimization methods in chromatography and capillary electrophoresis

Many methods have been developed in order to optimize the parameters of interest in either chromatography or capillary electrophoresis. In chemometric approaches experimental measurements are performed in such a way that all factors vary together. An objective function is utilized in which the analyst introduces the desired criteria (selectivity, resolution, time of analysis). Simplex methods and overlapping resolution maps are declining. Factorial designs and central composite designs are more and more popular in electrodriven capillary separations since the number of parameters to master is much larger than in either GC or LC. The use of artificial neural networks is increasing. The advantage of chemometrics tools is that no explicit models are required, conversely the number of experiments to perform may be high and boundaries of the domain are not straightforward to draw and the approach does more than is required. When models are available optimization is easier to perform by regression methods. Computer assisted methods in RPLC are readily available and work well but are still in infancy in CE. Linear solvation energy relationships seem a very valuable tool but estimates of coefficients still require many experiments.

Reversed-phase liquid chromatographic separation of complex samples by optimizing temperature and gradient time III. Improving the accuracy of computer simulation

Previous studies have shown that four experimental runs, where both temperature T and gradient time tG are varied, can be used for the reliable prediction of separation as a function of these two variables (two-dimensional optimization). Computer simulation (e.g., DryLab) can then be used to predict "optimized" conditions for maximum sample resolution using either isocratic or gradient elution. Samples that contain a large number of components (e.g., n>15-20) present a greater challenge. Resolution for these more complex samples is often quite sensitive to small changes in T or tG in turn requiring greater accuracy in predictions that result from computer simulation. In the present study of several samples, we have examined computer simulation errors that can arise from inexact expressions for retention time as a function of T, tG or isocratic %B. Resulting conclusions are applicable to both complex and simpler samples, in either one- or two-dimensional optimization. Means to anticipate and minimize the impact of these predictive errors are examined.

A desalting approach for MALDI-MS using on-probe hydrophobic self-assembled monolayers

One of the problems encountered in preparing samples for matrix-assisted laser desorption/ionization (MALDI) analysis is the presence of nonvolatile salts in the sample. This difficulty is often exacerbated by the necessity to prepare the sample in the appropriate sample-to-matrix ratio. This paper reports a probe surface derivatization method that greatly simplifies this sample preparation process. By constructing self-assembled monolayers of octadecyl mercaptan (C18) on the MALDI probe surface, we were able to generate a surface capable of reversibly binding polypeptides via hydrophobic interactions, which in turn, permits the analyte to be easily concentrated and desalted directly on the probe tip.

Selectivity due to conformational differences between helical and non-helical peptides in reversed-phase chromatography

The reversed-phase retention behaviour of two series of peptides, one non-helical and the other alpha-helical, was studied under various linear AB gradients in order to determine the effect of peptide conformation on selectivity of the separation. The non-helical series, designated X1, with the sequence Ac-XLGAKGAGVG-amide, exhibited negligible alpha-helical content in a hydrophobic medium; whereas, the amphipathic alpha-helical series, designated AX9, with the sequence Ac-EAEKAAKEXEKAAKEAEK-amide, exhibited high alpha-helical content in a hydrophobic medium. We have shown that plots of log k vs. phi (where k is the median capacity factor and phi is the median volume fraction of organic solvent) are very similar for any one peptide conformation, i.e., peptides from either the non-helical or amphipathic alpha-helical series exhibit similar S (solute parameter) values and the b (gradient steepness parameter) values are also similar for 17 different amino acid substitutions within each series of peptides. If mixtures of peptides from the two different series are separated using either increasing or decreasing gradient rates, large increases in resolution occur due to selectivity, which may be attributed to the difference in the log k vs. phi plots for each series of peptides. In addition, by using a polymer of an X1 peptide, which is 20 residues in length, it has been shown that the molecular mass difference between the X1 and the AX9 series of peptides is not sufficient to account for the selectivity difference. The S value of a non-amphipathic alpha-helical peptide further suggested that the difference in selectivity between the two series of peptides was due to differences in conformation. We believe that the peptide mixtures presented here provide a good model for studying selectivity effects due to conformational differences between peptides, an important concern when attempting to develop rational approaches to the prediction and optimization of peptide separation protocols from primary sequence information alone.