Abstract

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.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call