Authors
Michael R Hoopmann, Jimmy K Eng, Conor P Herlihy, Devin K Schweppe
Published in
Journal of the American Society for Mass Spectrometry. Volume 37. Issue 11. Pages 2973-2977. Nov 04, 2026.
Abstract
Database search remains a cornerstone of data-dependent proteomics. Its adaptation to real-time search (RTS) enables intelligent, on-the-fly acquisition decisions such as triggering validation or quantitation scans only when warranted. Because RTS must keep pace with ever-faster mass spectrometers using limited local compute, search algorithms must be fast and memory-efficient. Here, we present Telescope, a lightweight, open-source database search algorithm and sandbox designed for developing and testing RTS methods. Telescope uses a fragment ion index strategy that stores each indexed fragment in four bytes, supporting billions of peptidoforms while keeping memory tractable, and reproduces Comet's Xcorr scoring through a modular, heavily annotated codebase intended as a functional search tool and foundation for building more elaborate RTS strategies. Using a data-streaming application to replicate mass spectrometer acquisition at multiple scan rates, we show that Telescope replicates Comet's identifications while achieving per-spectrum search times in the microsecond range. Telescope scales to whole-proteome tryptic and semitryptic searches with combinations of methionine oxidation and phosphorylation. At per-scan search speeds ranging from 5,000 to 20,000 Hz, Telescope keeps pace beyond current instrument acquisition speeds, leaving computational headroom for added RTS capabilities such as retention-time alignment, quantification, and precursor prioritization.
PMID:
42980296
Bibliographic data and abstract were imported from PubMed on 04 Nov 2026.
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