Proteomics

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Quantitative fragmentomics to map affinities of interactomes


ABSTRACT: ~500,000 protein interactions have been identified in human but most binding affinities remain unknown, limiting quantitative investigation of interactome-function relationships. This gap can be filled by systematically measuring the affinities of minimal interacting protein fragments, the building blocks of interactomes. As a proof of principle, we experimentally measured 65,000 affinities involving 266 human PDZ domains (practically the complete "PDZome"), 424 human PDZ-Binding Motifs (~10% of the "PBMome") and 24 viral motifs. We determined binding constants for ~18,000 interactions that passed the detection threshold. Independent AP-MS experiments and database surveys demonstrated the strong agreement of quantitative fragmentomics with full-length protein interactomics. We evidence hot spots for viral interference, which allow a viral PBM, such as that of HPV-E6 oncoprotein, to impact the cell proteome way beyond its immediate binders. We propose to distinguish interactomes and complexomes, viewed as intrinsic and extrinsic properties linked by the law of mass action.

INSTRUMENT(S): LTQ Orbitrap Elite

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture

SUBMITTER: Luc Negroni  

LAB HEAD: Gergo Gogl

PROVIDER: PXD027743 | Pride | 2022-10-14

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
200512_GG_Ech01_rep1.msf Msf
200512_GG_Ech01_rep1.raw Raw
200512_GG_Ech01_rep2.msf Msf
200512_GG_Ech01_rep2.raw Raw
200512_GG_Ech01_rep3.msf Msf
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Publications


Human protein networks have been widely explored but most binding affinities remain unknown, hindering quantitative interactome-function studies. Yet interactomes rely on minimal interacting fragments displaying quantifiable affinities. Here, we measure the affinities of 65,000 interactions involving PDZ domains and their target PDZ-binding motifs (PBM) within a human interactome region particularly relevant for viral infection and cancer. We calculate interactomic distances, identify hot spots  ...[more]

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