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

Title:An Algorithm to Improve the Speed of Semi and Non-specific Enzyme Searches in Proteomics

Volume: 15 Issue: 9

Author(s): Zach Rolfs, Robert J. Millikin and Lloyd M. Smith*

Affiliation:

• Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706,United States

Keywords: Proteomics, algorithm, peptidomics, non-specific, nonspecific, no-enzyme, semi-specific, open-source.

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 nonspecific enzyme searches and could be applied to existing search programs.

Methods: 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 that is open-source and enables search programs to utilize fragment-ion redundancy to achieve a notable increase in search speed.

Cite this article as:

Rolfs Zach , Millikin J. Robert and Smith M. Lloyd *, An Algorithm to Improve the Speed of Semi and Non-specific Enzyme Searches in Proteomics, Current Bioinformatics 2020; 15 (9) . https://dx.doi.org/10.2174/1574893615999200429123334