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Applied and Environmental Microbiology, February 2009, p. 823-836, Vol. 75, No. 3
0099-2240/09/$08.00+0 doi:10.1128/AEM.01951-08
Copyright © 2009, American Society for Microbiology. All Rights Reserved.
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Valeria Cafaro,1,
Giuseppe Bozza,1 and
Alberto Di Donato1,3
Dipartimento di Biologia Strutturale e Funzionale, Università di Napoli Federico II, Complesso Universitario di Monte S. Angelo, Via Cinthia 4, 80126 Naples, Italy,1 Facoltà di Scienze Biotecnologiche, Università di Napoli Federico II,2 CEINGE-Biotecnologie Avanzate S.c.ar.l., Naples, Italy3
Received 21 August 2008/ Accepted 28 November 2008
Bacterial multicomponent monooxygenases (BMMs) are a heterogeneous family of di-iron monooxygenases which share the very interesting ability to hydroxylate aliphatic and/or aromatic hydrocarbons. Each BMM possesses defined substrate specificity and regioselectivity which match the metabolic requirements of the strain from which it has been isolated. Pseudomonas sp. strain OX1, a strain able to metabolize o-, m-, and p-cresols, produces the BMM toluene/o-xylene monooxygenase (ToMO), which converts toluene to a mixture of o-, m-, and p-cresol isomers. In order to investigate the molecular determinants of ToMO regioselectivity, we prepared and characterized 15 single-mutant and 3 double-mutant forms of the ToMO active site pocket. Using the Monte Carlo approach, we prepared models of ToMO-substrate and ToMO-reaction intermediate complexes which allowed us to provide a molecular explanation for the regioselectivities of wild-type and mutant ToMO enzymes. Furthermore, using binding energy values calculated by energy analyses of the complexes and a simple mathematical model of the hydroxylation reaction, we were able to predict quantitatively the regioselectivities of the majority of the variant proteins with good accuracy. The results show not only that the fine-tuning of ToMO regioselectivity can be achieved through a careful alteration of the shape of the active site but also that the effects of the mutations on regioselectivity can be quantitatively predicted a priori.
Published ahead of print on 12 December 2008.
Supplemental material for this article may be found at http://aem.asm.org/.
Valeria Cafaro and Eugenio Notomista contributed equally to the paper.
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