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Journal of Proteome Research
Article . 2021 . Peer-reviewed
License: STM Policy #29
Data sources: Crossref
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Collision Cross Sections for Native Proteomics: Challenges and Opportunities

Authors: Brandon T. Ruotolo;

Collision Cross Sections for Native Proteomics: Challenges and Opportunities

Abstract

Recent advancements place a comprehensive catalog of protein structure, oligomeric state, sequence, and modification status tentatively within reach, thus providing an unprecedented roadmap to therapies for many human diseases. To achieve this goal, revolutionary technologies capable of bridging key gaps in our ability to simultaneously measure protein composition and structure must be developed. Much of the current progress in this area has been catalyzed by mass spectrometry (MS) tools, which have become an indispensable resource for interrogating the structural proteome. For example, methods associated with native proteomics seek to comprehensively capture and quantify the endogenous assembly states for all proteins within an organism. Such technologies have often been partnered with ion mobility (IM) separation, from which collision cross section (CCS) information can be rapidly extracted to provide protein size information. IM technologies are also being developed that utilize CCS values to enhance the confidence of protein identification workflows derived from liquid chromatography-IM-MS analyses of enzymatically produced peptide mixtures. Such parallel advancements in technology beg the question: can CCS values prove similarly useful for the identification of intact proteins and their complexes in native proteomics? In this perspective, I examine current evidence and technology trends to explore the promise and limitations of such CCS information for the comprehensive analysis of multiprotein complexes from cellular mixtures.

Keywords

Proteomics, Proteome, Humans, Peptides, Mass Spectrometry

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    15
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Top 10%
Average
Top 10%
bronze