Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12779/6232
Title: Prediction model based on decision tree analysis for laccase mediators
Authors: Medina, F.
Aguila, S.
Baratto, Maria Camilla 
Martorana, Andrea
Basosi, Riccardo 
Alderete, J. B.
Vazquez Duhalt, R.
Keywords: Laccase mediators; pesticide transformation; prediction model; quantum-chemistry; SAR; Electron Paramagnetic Resonance; radical intermediates
Issue Date: 2013
Project: None 
Journal: ENZYME AND MICROBIAL TECHNOLOGY
Abstract: 
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, ionization energy, pKa, enthalpy of formation of radical and O-H bond dissociation energy (DO-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 C. 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.
Description: 
56003
URI: http://hdl.handle.net/20.500.12779/6232
ISSN: 0141-0229
DOI: 10.1016/j.enzmictec.2012.10.009
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