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Cited by 366

The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.

Global Mapping of the Topography and Magnitude of Proteolytic Events in Apoptosis

Open access
Dix, Melissa M., Simon, Gabriel M., Cravatt, Benjamin F.·2008·Cell

Abstract

SUMMARY Proteolysis is a key regulatory process that promotes the (in)activation, translocation, and/or degradation of proteins. As such, there is considerable interest in methods to comprehensively characterize proteolytic pathways in biological systems. Here, we describe a robust and versatile proteomic platform that enables direct visualization of the topography and magnitude of proteolytic events on a global scale. We use this method to generate a proteome-wide map of proteolytic events induced by the intrinsic apoptotic pathway. This profile contained 91 characterized caspase substrates as well as 170 additional proteins not previously known to be cleaved during apoptosis. Surprisingly, the vast majority of proteolyzed proteins, regardless of the extent of cleavage, yielded persistent fragments that correspond to discrete protein domains, suggesting that the generation of active effector proteins may be a principal function of apoptotic proteolytic cascades.

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Crossref · 10.1016/j.cell.2008.06.038

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Metadata

Authors
Dix, M. M., Simon, G. M., & Cravatt, B. F.
Venue
Cell
Publisher
Elsevier BV
Published
2008-08
Volume
134
Issue
4
Pages
679-691
ISSN
0092-8674 (ISSN-L)
OpenAlex
W2060470491
Cited by
366
References
48
FWCI
15.62
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Global Mapping of the Topography and Magnitude of Proteolytic Events in Apoptosis. https://app.cochat.ai/papers/10.1016/j.cell.2008.06.038
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Dix, M. M., Simon, G. M., & Cravatt, B. F. (2008). Global Mapping of the Topography and Magnitude of Proteolytic Events in Apoptosis. Cell. https://doi.org/10.1016/j.cell.2008.06.038

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.