Literature DB >> 33692656

An Algorithm to Improve the Speed of Semi and Non-Specific Enzyme Searches in Proteomics.

Zach Rolfs1, Robert J Millikin1, Lloyd M Smith1.   

Abstract

BACKGROUND: The identification of non-specifically cleaved peptides in proteomics and peptidomics poses a significant computational challenge. Current strategies for the identification of such peptides are typically time consuming and hinder routine data analysis.
OBJECTIVE: We aimed to design an algorithm that would improve the speed of semi- and non-specific enzyme searches and could be applicable to existing search programs.
METHOD: We developed a novel search algorithm that leverages fragment-ion redundancy to simultaneously search multiple non-specifically cleaved peptides at once. Briefly, a theoretical peptide tandem mass spectrum is generated using only the fragment-ion series from a single terminus. This spectrum serves as a proxy for several shorter theoretical peptides sharing the same terminus. After database searching, amino acids are removed from the opposing terminus until the observed and theoretical precursor masses match within a given mass tolerance.
RESULTS: The algorithm was implemented in the search program MetaMorpheus and found to perform an order of magnitude faster than the traditional MetaMorpheus search and produce superior results.
CONCLUSION: We report a speedy non-specific enzyme search algorithm which is open-source and enables search programs to utilize fragment-ion redundancy to achieve a notable increase in search speed.

Entities:  

Keywords:  Algorithm; No-enzyme; Non-specific; Nonspecific; Open-Source; Peptidomics; Proteomics; Semi-specific

Year:  2020        PMID: 33692656      PMCID: PMC7943061          DOI: 10.2174/1574893615999200429123334

Source DB:  PubMed          Journal:  Curr Bioinform        ISSN: 1574-8936            Impact factor:   3.543


  23 in total

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  1 in total

1.  Binary Classifier for Computing Posterior Error Probabilities in MetaMorpheus.

Authors:  Michael R Shortreed; Robert J Millikin; Lei Liu; Zach Rolfs; Rachel M Miller; Leah V Schaffer; Brian L Frey; Lloyd M Smith
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  1 in total

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