Improved Monoisotopic Mass Estimation for Deeper Proteome Coverage

Accurate assignment of monoisotopic peaks is essential for the identification of peptides in bottom-up proteomics. Misassignment or inaccurate attribution of peptidic ions leads to lower sensitivity and fewer total peptide identifications. In the present work, we present a performant, open-source, cross-platform algorithm, Monocle, for the rapid reassignment of instrument-assigned precursor peaks to monoisotopic peptide assignments. We demonstrate that the present algorithm can be integrated into many common proteomic pipelines and provides rapid conversion from multiple data source types. Finally, we show that our monoisotopic peak assignment results in up to a twofold increase in total peptide identifications compared to analyses lacking monoisotopic correction and a 44% improvement over previous monoisotopic peak correction algorithms.

Automated summary

In this study, a performant, open-source algorithm Monocle was introduced for rapid reassignment of instrument-assigned precursor peaks to monoisotopic peptide assignments. Results showed that the algorithm led to a twofold increase in total peptide identifications compared to analyses lacking monoisotopic correction, and a 44% improvement over previous monoisotopic peak correction algorithms.