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.

Medina, F., Aguila, S., Baratto, M.C., Martorana, A., Basosi, R., Alderete, J.B., et al. (2013). Prediction model based on decision tree analysis for laccase mediators. ENZYME AND MICROBIAL TECHNOLOGY, 52(1), 68-76 [10.1016/j.enzmictec.2012.10.009].

Prediction model based on decision tree analysis for laccase mediators

BARATTO, MARIA CAMILLA;MARTORANA, ANDREA;BASOSI, RICCARDO;
2013-01-01

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.
Medina, F., Aguila, S., Baratto, M.C., Martorana, A., Basosi, R., Alderete, J.B., et al. (2013). Prediction model based on decision tree analysis for laccase mediators. ENZYME AND MICROBIAL TECHNOLOGY, 52(1), 68-76 [10.1016/j.enzmictec.2012.10.009].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/41303
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