Comparison of monolithic and 1.8-μm RP-18 silica capillary columns using chromatographic data and mass spectrometric...

A goal in proteomics is the analysis of proteins by LC-MS. The proteins are enzymatically digested and the resulting peptides are chromatographically separated and introduced into a tandem MS. The obtained MS data are used for a search in sequence databases, providing identification scores for the proteins. A method to improve that score is to increase the chromatographic separation and peak capacity. In this study, the chromatographic conditions were optimized for a relatively large gradient time by varying the flow rate and gradient composition. The influence of the monolithic column length (15 and 64 cm) and particle diameter (1.8 μm; 15-cm length) on the sample peak capacity, productivity and identification score was studied. For comparison of gradient systems, a scaling factor was introduced to normalize the properties/performance of columns for material, diameter and length. As model proteins/digests, a simple (myoglobin) and a larger (BSA) protein were used. The smallest peak width, highest identification scores (54 and 89% for BSA and myoglobin, respectively) and productivity (5.0 and 4.0, respectively) were obtained for the 15-cm particulate column. The study also demonstrates that a further increase in the chromatographic performance is beneficial for BSA but hardly increases the identification score for the relatively small myoglobin.