ReviewProtein science : a publication of the Protein Society2023
Dissecting the structural heterogeneity of proteins by native mass spectrometry.
Review in Protein science : a publication of the Protein Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 25 citations in OpenAlex.
- Article
- Proton Transfer Charge Reduction Enables Isobaric Labeling-Based Proteoform Quantification of Overlapping Signals in Top-Down Mass Spectrometry.Journal of the American Society for Mass Spectrometry · 2026Article
- Heterogeneity within phycobilisomes is highly orchestrated.Photosynthesis research · 2026Article
- State-of-the-Art and Future Directions in Structural Proteomics.Molecular & cellular proteomics : MCP · 2025Review
- Glycosylation-Dependent Stability of Human Pentraxin-2 Revealed by Surface-Induced Dissociation and Ion Mobility Mass Spectrometry.Angewandte Chemie (International ed. in English) · 2025Article
- Stabilization of Protein Interactions through Electrospray Additives in Negative Ion Mode Native Mass Spectrometry.Analytical chemistry · 2025Article
- Optimization of Capillary Vibrating Sharp-Edge Spray Ionization for Native Mass Spectrometry of Triplex DNA.ACS omega · 2025Article
- How Can Proteomics Help to Elucidate the Pathophysiological Crosstalk in Muscular Dystrophy and Associated Multi-System Dysfunction?Proteomes · 2024Article
- Mass Spectrometry-Based Proteomic Technology and Its Application to Study Skeletal Muscle Cell Biology.Cells · 2023Review
- Dissecting the structural heterogeneity of proteins by native mass spectrometry.Protein science : a publication of the Protein Society · 2023Review
- Protein glycosylation in lung cancer from a mass spectrometry perspective.Mass spectrometry reviewsReview
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A single gene yields many forms of proteins via combinations of posttranscriptional/posttranslational modifications. Proteins also fold into higher-order structures and interact with other molecules. The combined molecular diversity leads to the heterogeneity of proteins that manifests as distinct phenotypes. Structural biology has generated vast amounts of data, effectively enabling accurate structural prediction by computational methods. However, structures are often obtained heterologously under homogeneous states in vitro. The lack of native heterogeneity under cellular context creates challenges in precisely connecting the structural data to phenotypes. Mass spectrometry (MS) based proteomics methods can profile proteome composition of complex biological samples. Most MS methods follow the "bottom-up" approach, which denatures and digests proteins into short peptide fragments for ease of detection. Coupled with chemical biology approaches, higher-order structures can be probed via incorporation of covalent labels on native proteins that are maintained at the peptide level. Alternatively, native MS follows the "top-down" approach and directly analyzes intact proteins under nondenaturing conditions. Various tandem MS activation methods can dissect the intact proteins for in-depth structural elucidation. Herein, we review recent native MS applications for characterizing heterogeneous samples, including proteins binding to mixtures of ligands, homo/hetero-complexes with varying stoichiometry, intrinsically disordered proteins with dynamic conformations, glycoprotein complexes with mixed modification states, and active membrane protein complexes in near-native membrane environments. We summarize the benefits, challenges, and ongoing developments in native MS, with the hope to demonstrate an emerging technology that complements other tools by filling the knowledge gaps in understanding the molecular heterogeneity of proteins.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.