Project description:GNPS GC/MS analysis of various compounds for library search 14
RIGHT_SSL_EI_sleep_5_3_min_60_15dg_min_290_as_Center_1mkl_spli50_40min
Project description:GNPS GC/MS analysis of various compounds for library search 15
RIGHT_SSL_EI_sleep_STER_4_min_40_15dg_min_210_5dg_min_280_as_Center_1mkl_split10
Project description:Tandem mass spectrometry (MS/MS) is the gold standard for intact glycopeptide identification, enabling peptide sequence elucidation and site-specific localization of glycan compositions. Beam-type collisional activation is generally sufficient for N-glycopeptides, while electron-driven dissociation is crucial for site localization in O-glycopeptides. Modern glycoproteomic methods often employ multiple dissociation techniques within a single LC-MS/MS analysis, but this approach frequently sacrifices sensitivity when analyzing multiple glycopeptide classes simultaneously. Here we explore the utility of intelligent data acquisition for glycoproteomics through real-time library searching (RTLS) to match oxonium ion patterns for on-the-fly selection of the appropriate dissociation method. By matching dissociation method with glycopeptide class, this autonomous dissociation-type selection (ADS) generates equivalent numbers of N-glycopeptide identifications relative to traditional beam-type collisional activation methods while also yielding comparable numbers of site-localized O-glycopeptide identifications relative to conventional electron transfer dissociation-based methods. The ADS approach represents a step forward in glycoproteomics throughput by enabling site-specific characterization of both N-and O-glycopeptides within the same LC-MS/MS acquisition.
Project description:Identifying mixture components is a well-known challenge in analytical chemistry. The Inverted Library Search Algorithm is a recently proposed method for identifying mixture components using in-source collision induced dissociation (is-CID) mass spectra of a query mixture and a reference library of pure compound is-CID mass spectra ( J. Am. Soc. Mass Spectrom. 2021, 32 (7), 1725-1734). This article presents several subtle but important advances to the algorithm, including updated compound matching strategies that improve result explainability and spectral filtering to better handle noisy mass spectra as is often observed with real-world samples such as seized drug evidence.