JUMPlib: Integrative\nSearch Tool Combining Fragment\nIon Indexing with Comprehensive TMT Spectral Libraries

The\nidentification of peptides is a cornerstone of mass\nspectrometry-based\nproteomics. Spectral library-based algorithms are well-established\nmethods to enhance the identification efficiency of peptides during\ndatabase searches in proteomics. However, these algorithms are not\nspecifically tailored for tandem mass tag (TMT)-based proteomics due\nto the lack of high-quality TMT spectral libraries. Here, we introduce\nJUMPlib, a computational tool for a TMT-based spectral library search.\nJUMPlib comprises components for generating spectral libraries, conducting\nlibrary searches, filtering peptide identifications, and quantifying\npeptides and proteins. Fragment ion indexing in the libraries increases\nthe search speed and utilizing the experimental retention time of\nprecursor ions improves peptide identification. We found that methionine\noxidation is a major factor contributing to large shifts in peptide\nretention time. To test the JUMPlib program, we curated two comprehensive\nhuman libraries for the labeling of TMT6/10/11 and TMT16/18 reagents,\nwith ∼286,000 precursor ions and ∼304,000 precursor\nions, respectively. Our analyses demonstrate that JUMPlib, employing\nthe fragment ion index strategy, enhances search speed and exhibits\nhigh sensitivity and specificity, achieving approximately a 25% increase\nin peptide-spectrum matches compared to other search tools. Overall,\nJUMPlib serves as a streamlined computational platform designed to\nenhance peptide identification in TMT-based proteomics. Both the JUMPlib\nsource code and libraries are publicly available.