The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Activity-based probes for the proteomic profiling of metalloproteases
Open accessAbstract
Metalloproteases (MPs) are a large and diverse class of enzymes implicated in numerous physiological and pathological processes, including tissue remodeling, peptide hormone processing, and cancer. MPs are tightly regulated by multiple posttranslational mechanisms in vivo , hindering their functional analysis by conventional genomic and proteomic methods. Here we describe a general strategy for creating activity-based proteomic probes for MPs by coupling a zinc-chelating hydroxamate to a benzophenone photocrosslinker, which promote selective binding and modification of MP active sites, respectively. These probes labeled active MPs but not their zymogen or inhibitor-bound counterparts and were used to identify members of this enzyme class up-regulated in invasive cancer cells and to evaluate the selectivity of MP inhibitors in whole proteomes. Interestingly, the matrix metalloproteinase inhibitor GM6001 (ilomastat), which is currently in clinical development, was found to also target the neprilysin, aminopeptidase, and dipeptidylpeptidase clans of MPs. These results demonstrate that MPs can display overlapping inhibitor sensitivities despite lacking sequence homology and stress the need to evaluate MP inhibitors broadly across this enzyme class to develop agents with suitable target selectivities in vivo . Activity-based profiling offers a powerful means for conducting such screens, as this approach can be carried out directly in whole proteomes, thereby facilitating the discovery of disease-associated MPs concurrently with inhibitors that selectively target these proteins.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Quantitative analysis of complex protein mixtures using isotope-coded affinity tags
Gygi, S. P., Rist, B., Gerber, S. A., Turecek, F., Gelb, M. H., & Aebersold, R. (1999) · Nature Biotechnology · doi:10.1038/13690 · Cited by 4,683
Strategies for MMP inhibition in cancer: innovations for the post-trial era
Overall, C. M., & López-Otín, C. (2002) · Nature Reviews Cancer · doi:10.1038/nrc884 · Cited by 1,349
Chemistry-Based Functional Proteomics Reveals Novel Members of the Deubiquitinating Enzyme Family
Borodovsky, A., Ovaa, H., Kolli, N., Gan-Erdene, T., Wilkinson, K. D., Ploegh, H. L., & Kessler, B. M. (2002) · Chemistry & Biology · doi:10.1016/s1074-5521(02)00248-x · Cited by 588
Cited by
In situ click chemistry generation of cyclooxygenase-2 inhibitors
Bhardwaj, A., Kaur, J., Wuest, M., & Wuest, F. (2017) · Nature Communications · doi:10.1038/s41467-016-0009-6 · Cited by 7,448
Activity-Based Protein Profiling: From Enzyme Chemistry to Proteomic Chemistry
Cravatt, B. F., Wright, A. T., & Kozarich, J. W. (2008) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.75.101304.124125 · Cited by 1,270
Self-citationMatrix Metalloproteinases As Novel Biomarker s and Potential Therapeutic Targets in Human Cancer
Roy, R., Yang, J., & Moses, M. A. (2009) · Journal of Clinical Oncology · doi:10.1200/jco.2009.23.5556 · Cited by 854
The MCL-1 BH3 helix is an exclusive MCL-1 inhibitor and apoptosis sensitizer
Stewart, M. L., Fire, E., Keating, A. E., & Walensky, L. D. (2010) · Nature Chemical Biology · doi:10.1038/nchembio.391 · Cited by 418
Diazirine based photoaffinity labeling
Dubinsky, L., Krom, B. P., & Meijler, M. M. (2012) · Bioorganic & Medicinal Chemistry · doi:10.1016/j.bmc.2011.06.066 · Cited by 396
Metadata
- Authors
- Saghatelian, A., Jessani, N., Joseph, A., Humphrey, M., & Cravatt, B. F.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2004-06-25
- Volume
- 101
- Issue
- 27
- Pages
- 10000-10005
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2079888227
- Cited by
- 456
- References
- 3
- FWCI
- 11.26
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Activity-based probes for the proteomic profiling of metalloproteases. https://app.cochat.ai/papers/10.1073/pnas.0402784101
- The paper
- Saghatelian, A., Jessani, N., Joseph, A., Humphrey, M., & Cravatt, B. F. (2004). Activity-based probes for the proteomic profiling of metalloproteases. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0402784101
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.