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Rational Enzyme Engineering Through Biophysical and Biochemical Modeling

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10.1021/acscatal.6b00028
 
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hdl:2117/84341

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Acebes, Sandra
Fernández-Fueyo, Elena
Monza, Emanuele
Lucas, Fatima
Almendral, David
Ruiz-Dueñas, Fracisco J.
Lund, Henrik
Martínez, Ángel T.
Guallar, Víctor
Document typeArticle
Defense date2016-02-03
PublisherACS Publications
Rights accessOpen Access
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
ProjectINDOX - Optimized oxidoreductases for medium and large scale industrial biotransformations (EC-FP7-613549)
DISENYO COMPUTACIONAL RACIONAL DE OXIDOREDUCTASAS PARA APLICACIONES INDUSTRIALES Y TECNOLOGICAS (MINECO-CTQ2013-48287-R)
NUEVAS ENZIMAS OXIDATIVAS PARA UNA INDUSTRIA SOSTENIBLE (MINECO-BIO2014-56388-R)
Abstract
Due to its importance in the pharmaceutical industry, ligand dynamic simulations have experienced a great expansion. Using all-atom models and cutting edge hardware, one can perform non-biased ligand migration, active site search and binding studies. In this letter we demonstrate (and validate by PCR mutagenesis) how these techniques, when combined with quantum mechanics, open new possibilities in enzyme engineering. We provide a complete analysis where: 1) biophysical simulations produce ligand diffusion and, 2) biochemical modeling samples the chemical event. Using such broad analysis we engineer a highly stable peroxidase activating the enzyme for new substrate oxidation after rational mutation of two non-conserved surface residues. In particular, we create a new surface-binding site, quantitatively predicting the in vitro change in oxidation rate obtained by mutagenic PCR and achieving a comparable specificity constant to active peroxidases.
CitationAcebes, Sandra [et al.]. Rational Enzyme Engineering Through Biophysical and Biochemical Modeling. "ACS Catalysis", 03 Febrer 2016, vol. 6, núm. 3, p. 1624-1629. 
URIhttp://hdl.handle.net/2117/84341
DOI10.1021/acscatal.6b00028
ISSN2155-5435
Publisher versionhttp://pubs.acs.org/doi/abs/10.1021/acscatal.6b00028
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