Literature DB >> 28898788

Molecular modelling and quantum biochemistry computations of a naturally occurring bioremediation enzyme: Alkane hydroxylase from Pseudomonas putida P1.

B G de Sousa1, J I N Oliveira2, E L Albuquerque2, U L Fulco2, V E Amaro3, C A G Blaha4.   

Abstract

Many species of bacteria involved in degradation of n-alkanes have an important constitutional metabolic enzyme, the alkane hydroxylase called AlkB, specialized in the conversion of hydrocarbons molecules that can be used as carbon and/or energy source. This enzyme plays an important role in the microbial degradation of oil, chlorinated hydrocarbons, fuel additives, and many other compounds. A number of these enzymes has been biochemically characterized in detail because the potential of alkane hydroxylases to catalyse high added-value reactions is widely recognized. Nevertheless, the industrial and process bioremediation application of them is restricted, owing to their complex biochemistry, challenging process requirements, and the limited number of their three-dimensional structures. Furthermore, AlkB has great potential as biocatalysts for selective transformation of a wide range of chemically inert unreactive alkanes into reactive chemical precursors that can be used as tools for bioremediation and bioprocesses. Aiming to understand the possible ways the AlkB enzyme Pseudomonas putida P1 interacts with octane, octanol and 1-octyne, we consider its suitable biochemical structure taking into account a 3-D homology modelling. Besides, by using a quantum chemistry computational model based on the density functional theory (DFT), we determine possible protein-substrate interaction regions measured by means of its binding energy simulated throughout the Molecular Fractionation with Conjugated Caps (MFCC) approach.
Copyright © 2017 Elsevier Inc. All rights reserved.

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Keywords:  3-D homology modelling; Alkane hydroxylase; Binding energy; Pseudomonas putida P1; Quantum chemistry approach

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Year:  2017        PMID: 28898788     DOI: 10.1016/j.jmgm.2017.08.021

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN: 1093-3263            Impact factor:   2.518


  1 in total

1.  The electrostatic embedding contribution to DFT calculations of ligand-amino acid residues interaction.

Authors:  Tamires C da Silva Ribeiro; Marcelo L Lyra; Vinícius Manzoni
Journal:  J Mol Model       Date:  2018-07-19       Impact factor: 1.810

  1 in total

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