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

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.