Prediction model based on decision tree analysis for laccase mediators.

Fabiola Medina, Sergio Aguila, Maria Camilla Baratto, Andrea Martorana, Riccardo Basosi, Joel B Alderete, Rafael Vazquez-Duhalt

Departamento de Química Orgánica, Grupo de Química Biológica y Computacional, Universidad de Concepción, Edmundo Larenas 129, Concepción, Chile.

Enzyme and microbial technology 2013 Jan 10

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A Structure Activity Relationship (SAR) study for laccase mediator systems was performed in order to correctly classify different natural phenolic mediators. Decision tree (DT) classification models with a set of five quantum-chemical calculated molecular descriptors were used. These descriptors included redox potential (ɛ°), ionization energy (E(i)), pK(a), enthalpy of formation of radical (Δ(f)H), and OH bond dissociation energy (D(O-H)). The rationale for selecting these descriptors is derived from the laccase-mediator mechanism. To validate the DT predictions, the kinetic constants of different compounds as laccase substrates, their ability for pesticide transformation as laccase-mediators, and radical stability were experimentally determined using Coriolopsis gallica laccase and the pesticide dichlorophen. The prediction capability of the DT model based on three proposed descriptors showed a complete agreement with the obtained experimental results. Copyright © 2012 Elsevier Inc. All rights reserved.

Citation

Fabiola Medina, Sergio Aguila, Maria Camilla Baratto, Andrea Martorana, Riccardo Basosi, Joel B Alderete, Rafael Vazquez-Duhalt. Prediction model based on decision tree analysis for laccase mediators. Enzyme and microbial technology. 2013 Jan 10;52(1):68-76