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Cited by 313

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

To bind zinc or not to bind zinc: An examination of innovative approaches to improved metalloproteinase inhibition

Open access
Jacobsen, Jennifer A., Major Jourden, Jody L., Miller, Melissa T., Cohen, Seth M.·2010·Biochimica et Biophysica Acta (BBA) - Molecular Cell Research

Abstract

This short review highlights some recent advances in matrix metalloproteinase inhibitor (MMPi) design and development. Three distinct approaches to improved MMP inhibition are discussed: (1) the identification and investigation of novel zinc-binding groups (ZBGs), (2) the study of non-zinc-binding MMPi, and (3) mechanism-based MMPi that form covalent adducts with the protein. Each of these strategies is discussed and their respective advantages and remaining challenges are highlighted. The studies discussed here bode well for the development of ever more selective, potent, and well-tolerated MMPi for treating several important disease pathologies.

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Crossref · 10.1016/j.bbamcr.2009.08.006

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Metadata

Authors
Jacobsen, J. A., Major Jourden, J. L., Miller, M. T., & Cohen, S. M.
Venue
Biochimica et Biophysica Acta (BBA) - Molecular Cell Research
Publisher
Elsevier BV
Published
2010-01
Volume
1803
Issue
1
Pages
72-94
ISSN
0167-4889 (ISSN-L)
OpenAlex
W1998954104
Cited by
313
References
1
FWCI
4.08
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: To bind zinc or not to bind zinc: An examination of innovative approaches to improved metalloproteinase inhibition. https://app.cochat.ai/papers/10.1016/j.bbamcr.2009.08.006
The paper
Jacobsen, J. A., Major Jourden, J. L., Miller, M. T., & Cohen, S. M. (2010). To bind zinc or not to bind zinc: An examination of innovative approaches to improved metalloproteinase inhibition. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. https://doi.org/10.1016/j.bbamcr.2009.08.006

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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.