Literature DB >> 11467952

Comparative binding energy analysis of the substrate specificity of haloalkane dehalogenase from Xanthobacter autotrophicus GJ10.

J Kmunícek1, S Luengo, F Gago, A R Ortiz, R C Wade, J Damborský.   

Abstract

Comparative binding energy (COMBINE) analysis was conducted for 18 substrates of the haloalkane dehalogenase from Xanthobacter autotrophicus GJ10 (DhlA): 1-chlorobutane, 1-chlorohexane, dichloromethane, 1,2-dichloroethane, 1,2-dichloropropane, 2-chloroethanol, epichlorohydrine, 2-chloroacetonitrile, 2-chloroacetamide, and their brominated analogues. The purpose of the COMBINE analysis was to identify the amino acid residues determining the substrate specificity of the haloalkane dehalogenase. This knowledge is essential for the tailoring of this enzyme for biotechnological applications. Complexes of the enzyme with these substrates were modeled and then refined by molecular mechanics energy minimization. The intermolecular enzyme-substrate energy was decomposed into residue-wise van der Waals and electrostatic contributions and complemented by surface area dependent and electrostatic desolvation terms. Partial least-squares projection to latent structures analysis was then used to establish relationships between the energy contributions and the experimental apparent dissociation constants. A model containing van der Waals and electrostatic intermolecular interaction energy contributions calculated using the AMBER force field explained 91% (73% cross-validated) of the quantitative variance in the apparent dissociation constants. A model based on van der Waals intermolecular contributions from AMBER and electrostatic interactions derived from the Poisson-Boltzmann equation explained 93% (74% cross-validated) of the quantitative variance. COMBINE models predicted correctly the change in apparent dissociation constants upon single-point mutation of DhlA for six enzyme-substrate complexes. The amino acid residues contributing most significantly to the substrate specificity of DhlA were identified; they include Asp124, Trp125, Phe164, Phe172, Trp175, Phe222, Pro223, and Leu263. These residues are suitable targets for modification by site-directed mutagenesis.

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Year:  2001        PMID: 11467952     DOI: 10.1021/bi010464p

Source DB:  PubMed          Journal:  Biochemistry        ISSN: 0006-2960            Impact factor:   3.162


  8 in total

1.  Reconstruction of mycobacterial dehalogenase Rv2579 by cumulative mutagenesis of haloalkane dehalogenase LinB.

Authors:  Yuji Nagata; Zbynek Prokop; Sona Marvanová; Jana Sýkorová; Marta Monincová; Masataka Tsuda; Jirí Damborský
Journal:  Appl Environ Microbiol       Date:  2003-04       Impact factor: 4.792

2.  A single mutation in a tunnel to the active site changes the mechanism and kinetics of product release in haloalkane dehalogenase LinB.

Authors:  Lada Biedermannová; Zbyněk Prokop; Artur Gora; Eva Chovancová; Mihály Kovács; Jiří Damborsky; Rebecca C Wade
Journal:  J Biol Chem       Date:  2012-06-28       Impact factor: 5.157

3.  Exploring the challenges of computational enzyme design by rebuilding the active site of a dehalogenase.

Authors:  Garima Jindal; Katerina Slanska; Veselin Kolev; Jiri Damborsky; Zbynek Prokop; Arieh Warshel
Journal:  Proc Natl Acad Sci U S A       Date:  2018-12-26       Impact factor: 11.205

4.  Functionally relevant motions of haloalkane dehalogenases occur in the specificity-modulating cap domains.

Authors:  Michal Otyepka; Jirí Damborský
Journal:  Protein Sci       Date:  2002-05       Impact factor: 6.725

5.  Comparative binding energy analysis of haloalkane dehalogenase substrates: modelling of enzyme-substrate complexes by molecular docking and quantum mechanical calculations.

Authors:  Jan Kmunícek; Michal Bohác; Santos Luengo; Federico Gago; Rebecca C Wade; Jirí Damborský
Journal:  J Comput Aided Mol Des       Date:  2003 May-Jun       Impact factor: 3.686

6.  A receptor dependent-4D QSAR approach to predict the activity of mutated enzymes.

Authors:  R Pravin Kumar; Naveen Kulkarni
Journal:  Sci Rep       Date:  2017-07-24       Impact factor: 4.379

7.  Prediction of Drug-Target Binding Kinetics by Comparative Binding Energy Analysis.

Authors:  Gaurav K Ganotra; Rebecca C Wade
Journal:  ACS Med Chem Lett       Date:  2018-10-04       Impact factor: 4.345

8.  Exploring the binding of BACE-1 inhibitors using comparative binding energy analysis (COMBINE).

Authors:  Shu Liu; Rao Fu; Xiao Cheng; Sheng-Ping Chen; Li-Hua Zhou
Journal:  BMC Struct Biol       Date:  2012-08-27
  8 in total

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