Optimization of MS/MS spectral library searching for higher-energy collisional dissociation (HCD) spectra of peptides

Abstract

Spectral library searching has gained more acceptance as an alternative to traditional sequence database searching in shotgun proteomics data analysis. In the past few years, due to the availability of data, most spectral libraries are compiled from low-resolution data from ion traps. More recently, however, newer mass spectrometers have been developed to acquire high-resolution tandem mass spectra at high scan rates, making it increasingly feasible to compile comprehensive spectral libraries of such data. To date, however, there is no systematic study to evaluate or optimize the performance of spectral library searching in such cases. In this study, we made use of a large publicly available HCD dataset acquired from 11 human cell lines to evaluate and optimize spectral library searching for high-resolution, high-mass accuracy MS/MS data. This dataset was obtained on two different LTQ-Orbitrap mass spectrometers. On the more advanced “high-field” instrument, two different resolution settings were used, which produced rather different fragmentation patterns. We optimized our spectral library searching algorithm for these two variants of HCD data in terms of the number of peaks retained and the bin width used to vectorize the spectra. We also proposed a rank transform procedure prior to dot product calculation to reduce the effect of variable peak intensities. Our results showed that spectral library searching after optimization still significantly outperformed the sequence database search engine OMSSA at equalized search space, and that spectral library searching can still be effective for high-resolution MS/MS spectra if the library and the query data were acquired under different experimental settings.

Date of Award	2013
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology