Activatea Ion-ETD outperforms Ion trap collisional activation for large-scale peptide analysis

摘要

By normalizing peptide secondary structure to a relatively unfolded state during ETD ion-ion reaction (AI-ETD) using IR photons, more peptides can be identified by a wide margin as compared to ETD alone. Much of this gain is realized in the form of high m/z precursors, a subset of peptides which typically exhibit poor ETD fragmentation. The optimal energy of irradiation is a function of precursor peptide m/z, with smaller m/z precursors requiring less energy than their larger m/z counterparts. This is largely due to different magnitudes of gas phase secondary structure as higher m/z precursors tend to posses more folded structures. Thus, the optimal implementation of AI-ETD is to set the laser wattage in a data-dependent manner based upon precursor m/z. Moreover, using the modified LTQ-XL, we are able to indirectly measure the rate at which peptides of moderate charge and m/z refold, and find such rates to be on the order of approx300 (mu)s assuming first order refolding kinetics.