Genetic Algorithm Based Design and Experimental Characterization of a Highly Thermostable Metalloprotein.
The development of thermostable and solvent-tolerant metalloproteins is a long-sought goal for many applications in synthetic biology and biotechnology. In this work, we were able to engineer a highly thermostable and organic solvent-stable metallo variant of the B1 domain of protein G (GB1) with a...
| Publicado en: | Journal of the American Chemical Society Vol. 140; no. 13; pp. 4517 - 4522 |
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| Autores principales: | , , , , |
| Formato: | Artículo |
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American Chemical Society
4/4/2018
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=128955137&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 128955137 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00027863 ACS jtl: Journal of the American Chemical Society issn: 00027863 maglogo: N pubinfo: dt: 4/4/2018 vid: 140 iid: 13 pid: 997 pub: American Chemical Society artinfo: ui: 128955137 10.1021/jacs.7b10660 ppf: 4517 ppct: 5 formats: tig: atl: Genetic Algorithm Based Design and Experimental Characterization of a Highly Thermostable Metalloprotein. aug: au: Bozkurt, Esra Perez, Marta A. S. Hovius, Ruud Browning, Nicholas J. Rothlisberger, Ursula affil: Laboratory of Computational Chemistry and Biochemistry, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland Laboratory of Protein Engineering, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland su: Structural optimization Genetic algorithms Synthetic biology Metalloproteins Molecular dynamics Mathematical models sug: subj: Structural optimization Genetic algorithms Synthetic biology Metalloproteins Molecular dynamics Mathematical models ab: The development of thermostable and solvent-tolerant metalloproteins is a long-sought goal for many applications in synthetic biology and biotechnology. In this work, we were able to engineer a highly thermostable and organic solvent-stable metallo variant of the B1 domain of protein G (GB1) with a tetrahedral zinc binding site reminiscent of the one of thermolysin. Promising candidates were designed computationally by applying a protocol based on classical and first-principles molecular dynamics simulations in combination with genetic algorithm optimization. The most promising of the computationally predicted mutants was expressed and structurally characterized and yielded a highly thermostable protein. The experimental results thus confirm the predictive power of the applied computational protein engineering approach for the de novo design of highly stable metalloproteins. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2018 holdings: @attributes: islocal: N |
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