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

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.

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.

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.

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.

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.