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Protein Design: Toward Functional Metalloenzymes
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ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTProtein Design: Toward Functional MetalloenzymesFangting Yu†, Virginia M. Cangelosi†, Melissa L. Zastrow†, Matteo Tegoni‡, Jefferson S. Plegaria†, Alison G. Tebo†, Catherine S. Mocny†, Leela Ruckthong†, Hira Qayyum†, and Vincent L. Pecoraro*†View Author Information† University of Michigan, Ann Arbor, Michigan 48109, United States‡ University of Parma, I-43100 Parma, Italy*E-mail: [email protected]Cite this: Chem. Rev. 2014, 114, 7, 3495–3578Publication Date (Web):March 24, 2014Publication History Received20 August 2013Published online24 March 2014Published inissue 9 April 2014https://pubs.acs.org/doi/10.1021/cr400458xhttps://doi.org/10.1021/cr400458xreview-articleACS PublicationsCopyright © 2014 American Chemical SocietyRequest reuse permissionsArticle Views11583Altmetric-Citations370LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Copper,Metals,Monomers,Peptides and proteins,Redox reactions Get e-Alerts
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Metal3D: a general deep learning framework for accurate metal ion location prediction in proteins
Dürr, S. L., Levy, A., & Rothlisberger, U. (2023) · Nature Communications · doi:10.1038/s41467-023-37870-6 · Cited by 88
To what extent do structural changes in catalytic metal sites affect enzyme function?
Valasatava, Y., Rosato, A., Furnham, N., Thornton, J. M., & Andreini, C. (2018) · Journal of Inorganic Biochemistry · doi:10.1016/j.jinorgbio.2017.11.002 · Cited by 77
De Novo Design and Characterization of Copper Metallopeptides Inspired by Native Cupredoxins
Plegaria, J. S., Duca, M., Tard, C., Friedlander, T. J., Deb, A., Penner-Hahn, J. E., & Pecoraro, V. L. (2015) · Inorganic Chemistry · doi:10.1021/acs.inorgchem.5b01330 · Cited by 33
Self-citationRecent advances in automated protein design and its future challenges
Setiawan, D., Brender, J., & Zhang, Y. (2018) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2018.1465922 · Cited by 26
Metadata
- Authors
- Yu, F., Cangelosi, V. M., Zastrow, M. L., Tegoni, M., Plegaria, J. S., Tebo, A. G., Mocny, C. S., Ruckthong, L., Qayyum, H., & Pecoraro, V. L.
- Venue
- Chemical Reviews
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-03-24
- Volume
- 114
- Issue
- 7
- Pages
- 3495-3578
- ISSN
- 0009-2665 (ISSN-L)
- 1520-6890
- OpenAlex
- W2008279485
- Cited by
- 441
- References
- 716
- FWCI
- 3.90
- Type
- journal article
- Language
- en
- Open access
- green
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- Yu, F., Cangelosi, V. M., Zastrow, M. L., Tegoni, M., Plegaria, J. S., Tebo, A. G., Mocny, C. S., Ruckthong, L., Qayyum, H., & Pecoraro, V. L. (2014). Protein Design: Toward Functional Metalloenzymes. Chemical Reviews. https://doi.org/10.1021/cr400458x
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