LAUSR

The Orbitrap Astral mass spectrometer features outstanding speed, resolution, and sensitivity, making data-independent acquisition (DIA) the preferred method for deep profiling in shotgun proteomics. However, as for data generated by an Orbitrap Astral mass spectrometer, the current search engines cannot detect unexpected modifications, which are novel in biology and chemistry systems. Here we present OpenSpec, a computational workflow specifically designed for comprehensive identification of unexpected modifications from Astral-DIA data sets. The workflow incorporates a Transformer-based precursor-fragment grouping model to deconvolute DIA data to generate DDA-like pseudo-MS/MS spectra, achieving a DDA-based open search strategy on Astral-DIA data. We evaluated OpenSpec through a benchmarking study with synthetic peptides emulating diverse modification patterns and complemented by systematic comparison between DIA and DDA acquisition modes on identical samples. We investigated unexpected modifications of cysteine across various sample pretreatment conditions. OpenSpec is available for download from GitHub: https://github.com/BUAA-LiuLab/OpenSpec.git.