Assessment and Comparison of Database Search Engines for Peptidomic Applications

Abstract

Protein database search engines are an integral component of mass spectrometry-based peptidomic analyses. Given the unique computational challenges of peptidomics, many factors must be taken into consideration when optimizing search engine selection, as each platform has different algorithms by which tandem mass spectra are scored for subsequent peptide identifications. In this study, four different database search engines, PEAKS, MS-GF+, OMSSA, and X! Tandem, were compared with Aplysia californica and Rattus norvegicus peptidomics data sets, and various metrics were assessed such as the number of unique peptide and neuropeptide identifications, and peptide length distributions. Given the tested conditions, PEAKS was found to have the highest number of peptide and neuropeptide identifications out of the four search engines in both data sets. Furthermore, principal component analysis and multivariate logistic regression were employed to determine whether specific spectral features contribute to false C-terminal amidation assignments by each search engine. From this analysis, it was found that the primary features influencing incorrect peptide assignments were the precursor and fragment ion m/z errors. Finally, an assessment employing a mixed species protein database was performed to evaluate search engine precision and sensitivity when searched against an enlarged search space containing human proteins.

EndoGenius: Optimized Neuropeptide Identification from Mass Spectrometry Datasets

“…As most software implemented in neuropeptide workflows are typically designed for proteomics-based inquiries, the subsequent search results often lack optimization, illustrated by few PSMs and unique identifications. PEAKS Studio is a program routinely used in neuropeptide investigations, with notably increased performance compared to alternative software, attributed primarily to its hybrid de novo sequencing and database searching approach, which helps parse through highly homologous neuropeptides . In particular, its de novo sequencing algorithm is exhaustive, searching all possible combinations of amino acids, enabling a more sensitive algorithm compared with more common spectral graph-based algorithms .…”

“…PEAKS Studio is a program routinely used in neuropeptide investigations, with notably increased performance compared to alternative software, attributed primarily to its hybrid de novo sequencing and database searching approach, which helps parse through highly homologous neuropeptides. 45 In particular, its de novo sequencing algorithm is exhaustive, searching all possible combinations of amino acids, enabling a more sensitive algorithm compared with more common spectral graph-based algorithms. 17 Our group has recently released two software packages designed to redirect PEAKS results through pre-and postprocessing strategies aimed to increase the frequency of neuropeptide identification.…”

WOMBAT-P: Benchmarking Label-Free Proteomics Data Analysis Workflows

“…This can not be merely attributed to applied match-between run options, given that the TPP workflow separates similarly. While it is well attested in the literature 39,40,41 that different search engines identify non-identical sets of peptides from the same data, downstream components, such as for PSM validation 42 or protein inference 43 may also be of considerable influence.…”

WOMBAT-P: Benchmarking Label-Free Proteomics Data Analysis Workflows

“…This cannot be merely attributed to the applied match-between-runs option, given that the TPP workflow separates similarly. While it is well attested in the literature − that different search engines identify nonidentical sets of peptides from the same data, downstream components, such as for PSM validation or protein inference, may also be of considerable influence.…”