Automated reduction and interpretation of multidimensional mass spectra for analysis of complex peptide mixtures

Abstract

Here we develop a fully automated procedure for the analysis of liquid chromatography–mass spectrometry (LC–MS) datasets collected during the analysis of complex peptide mixtures. We present the underlying algorithm and outcomes of several experiments justifying its applicability. The novelty of our approach is to exploit the multidimensional character of the datasets. It is common knowledge that highly complex peptide mixtures can be analyzed by liquid chromatography coupled with mass spectrometry, but we are not aware of any existing automated MS spectra interpretation procedure designed to take into account the multidimensional character of the data. Our work fills this gap by providing an effective algorithm for this task, allowing for automated conversion of raw data to the list of masses of peptides.