Abstract
Hydrogen/deuterium exchange-mass spectrometry (HDX-MS) is a powerful tool for studying protein structure and dynamics. As a bottom-up LC-MS technique, its success largely depends on peptide identifications made by peptide mapping prior to HDX measurements. We previously demonstrated that combining peptide mapping results from complementary single- and multipass cyclic ion mobility-mass spectrometry (cIM-MS) experiments, an approach we term "multi-sequence" cIM-MS, can enhance HDX-MS by increasing peptide identifications. However, this approach required labor-intensive, manual handling of the acquired data, including lengthy optimization of drift time (DT) versus DT full width half maximum (FWHM) trendlines during peak detection processing to combat cyclic wrap-around effects. Here, we present MultiPassMerger, an open-source software tool that automates the processing, merging, and filtering of single- and multipass cIM-MS peptide mapping data. MultiPassMerger was validated through re-analysis of several model proteins. Its automated capabilities enabled better optimization of DT versus DT FWHM trendlines on a protein-specific basis, enhancing peptide identification relative to manually optimized trendlines. Beyond automating our previous approach, MultiPassMerger also introduces a novel "multi-trendline" processing method, involving iterative processing using multiple trendlines and merging of results to better sample ions across the DT versus DT FWHM distribution. Using MultiPassMerger with both multi-sequence and multi-trendline strategies increased peptide identifications up to 392% relative to SYNAPT G2-Si with linear ion mobility and 102% relative to use of single-pass cIM-MS alone. Consequently, MultiPassMerger can enhance peptide mapping and makes this approach practical and more accessible to the wider HDX-MS community. MultiPassMerger is available as a downloadable Windows executable at https://politislab.uk/multipassmerger.