MS Amanda 2.0: Advancements in the standalone implementation

Abstract

RATIONALE: Database search engines are the preferred method to identify peptides in mass spectrometry data. However, valuable software is in this context not only defined by a powerful algorithm to separate correct from false identifications but is also defined by constant maintenance and continuous improvements. METHODS: In 2014, we presented our peptide identification algorithm MS Amanda, showing its suitability for identifying peptides in high resolution tandem mass spectrometry data and its ability to outperform widely used tools to identify peptides. Since then, we have continuously worked on improvements to enhance its usability and to support new trends and developments in this fast growing field, while keeping the original scoring algorithm to assess the quality of a peptide spectrum match unchanged. RESULTS: In this manuscript, we present the outcome of these efforts, MS Amanda 2.0, a faster and more flexible standalone version with the original scoring algorithm. The new implementation has led to a 3x -5x speedup, is able to handle new ion types and supports standard data formats. We also show that MS Amanda 2.0 works best when using only the most common ion types in a particular search instead of all possible ion types. CONCLUSIONS:MS Amanda is available free of charge from https://ms.imp.ac.at/index.php?action=msamanda.

Wide Window Acquisition and AI-based data analysis to reach deep proteome coverage for a wide sample range, including single cell proteomic inputs

“…For peptide identification, RAW files were loaded into Proteome Discoverer (v.3.0.0.757, Thermo Scientific). All the created MS/MS spectra were searched either using MSAmanda v.2.0 14,15 or CHIMERYS TM (MSAID GmbH, Germany). For the processing step, the RAW files were searched against the mouse Uniprot reference database (2022-03-04; 21,962 sequences and 11,728,099 residues) and a in-house contaminant database (PD-Contaminants_IGGs_v17_tagsremoved; 344 sequences and 142,046 residues).…”

“…Even more pronounced was the improvement on the identification rate assigning 2.6 times as many PSMs to MS/MS spectra in comparison to MS Amanda 2.0. 14,15 Using a wider precursor isolation window of 4 m/z, which we relate to as wide window acquisition (WWA), we generated richer, more complex MS2 spectra, further favoring the advantage of CHIMERYS TM to decipher highly chimeric fragmentation spectra. This boosted the identification rate of CHIMERYS TM to around 125% meaning that on average there was more than one PSM per MS/MS spectrum identified, corresponding to a 4.6-fold boost over the classical search engine employed, while peptide IDs were boosted by 113% and protein IDs by 41%.…”

A Chloroplast Protein Atlas Reveals Novel Structures and Spatial Organization of Biosynthetic Pathways

“…Raw files were searched using MSAmanda 2.0 (Dorfer et al, 2021) and Sequest HT algorithms (Eng et al, 1994) within the Proteome Discoverer 2.5.0 suite (Thermo Scientific, USA). 10 ppm MS1 and 0.4 Da MS2 mass tolerances were specified.…”

“…Raw files were searched using MSAmanda 2.0 (Dorfer et al, 2021) and Sequest HT algorithms (Eng et al, 1994) % probability and contained at least 2 identified peptides. Protein probabilities were assigned by the Protein Prophet algorithm (Nesvizhskii et al, 2003).…”

Deep-Sea Anemones Are Prospective Source of New Antimicrobial and Cytotoxic Compounds

“…Peak lists obtained from MS/MS spectra were identified using Data Analysis Software ver. 4.4 (Bruker Daltonics, Bremen, Germany), OMSSA version 2.1.9 [78], Andromeda version 1.5.3.4 [79], MS Amanda version 2.0.0.17442 [80], MS-GF+ version release 22 March 2021 [81], and Comet version 2021.01 rev. 0 [82].…”