Literature DB >> 26530855

Activity prediction of substrates in NADH-dependent carbonyl reductase by docking requires catalytic constraints and charge parameterization of catalytic zinc environment.

Gaurao V Dhoke1, Christoph Loderer2, Mehdi D Davari1, Marion Ansorge-Schumacher2, Ulrich Schwaneberg1,3, Marco Bocola4.   

Abstract

Molecular docking of substrates is more challenging compared to inhibitors as the reaction mechanism has to be considered. This becomes more pronounced for zinc-dependent enzymes since the coordination state of the catalytic zinc ion is of greater importance. In order to develop a predictive substrate docking protocol, we have performed molecular docking studies of diketone substrates using the catalytic state of carbonyl reductase 2 from Candida parapsilosis (CPCR2). Different docking protocols using two docking methods (AutoDock Vina and AutoDock4.2) with two different sets of atomic charges (AM1-BCC and HF-RESP) for catalytic zinc environment and substrates as well as two sets of vdW parameters for zinc ion were examined. We have selected the catalytic binding pose of each substrate by applying mechanism based distance criteria. To compare the performance of the docking protocols, the correlation plots for the binding energies of these catalytic poses were obtained against experimental Vmax values of the 11 diketone substrates for CPCR2. The best correlation of 0.73 was achieved with AutoDock4.2 while treating catalytic zinc ion in optimized non-bonded (NBopt) state with +1.01 charge on the zinc ion, compared to 0.36 in non-bonded (+2.00 charge on the zinc ion) state. These results indicate the importance of catalytic constraints and charge parameterization of catalytic zinc environment for the prediction of substrate activity in zinc-dependent enzymes by molecular docking. The developed predictive docking protocol described here is in principle generally applicable for the efficient in silico substrate spectra characterization of zinc-dependent ADH.

Entities:  

Keywords:  Alcohol dehydrogenase (ADH); Candida parapsilosis; Diketones; Molecular docking; Substrate prediction; Zinc-dependent enzyme

Mesh:

Substances:

Year:  2015        PMID: 26530855     DOI: 10.1007/s10822-015-9878-8

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  46 in total

1.  Increasing the precision of comparative models with YASARA NOVA--a self-parameterizing force field.

Authors:  Elmar Krieger; Günther Koraimann; Gert Vriend
Journal:  Proteins       Date:  2002-05-15

2.  Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation.

Authors:  Araz Jakalian; David B Jack; Christopher I Bayly
Journal:  J Comput Chem       Date:  2002-12       Impact factor: 3.376

3.  Development and testing of a general amber force field.

Authors:  Junmei Wang; Romain M Wolf; James W Caldwell; Peter A Kollman; David A Case
Journal:  J Comput Chem       Date:  2004-07-15       Impact factor: 3.376

4.  Who's who? Allocation of carbonyl reductase isoenzymes from Candida parapsilosis by combining bio- and computational chemistry.

Authors:  Andre Jakoblinnert; Marco Bocola; Monideepa Bhattacharjee; Sonja Steinsiek; Mara Bönitz-Dulat; Ulrich Schwaneberg; Marion B Ansorge-Schumacher
Journal:  Chembiochem       Date:  2012-02-29       Impact factor: 3.164

5.  Automatic atom type and bond type perception in molecular mechanical calculations.

Authors:  Junmei Wang; Wei Wang; Peter A Kollman; David A Case
Journal:  J Mol Graph Model       Date:  2006-02-03       Impact factor: 2.518

6.  Molecular docking for substrate identification: the short-chain dehydrogenases/reductases.

Authors:  Angelo D Favia; Irene Nobeli; Fabian Glaser; Janet M Thornton
Journal:  J Mol Biol       Date:  2007-11-01       Impact factor: 5.469

Review 7.  Matrix metalloproteinases (MMPs): chemical-biological functions and (Q)SARs.

Authors:  Rajeshwar P Verma; Corwin Hansch
Journal:  Bioorg Med Chem       Date:  2007-01-17       Impact factor: 3.641

8.  AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility.

Authors:  Garrett M Morris; Ruth Huey; William Lindstrom; Michel F Sanner; Richard K Belew; David S Goodsell; Arthur J Olson
Journal:  J Comput Chem       Date:  2009-12       Impact factor: 3.376

Review 9.  Practical chiral alcohol manufacture using ketoreductases.

Authors:  Gjalt W Huisman; Jack Liang; Anke Krebber
Journal:  Curr Opin Chem Biol       Date:  2010-01-12       Impact factor: 8.822

10.  AutoDock4(Zn): an improved AutoDock force field for small-molecule docking to zinc metalloproteins.

Authors:  Diogo Santos-Martins; Stefano Forli; Maria João Ramos; Arthur J Olson
Journal:  J Chem Inf Model       Date:  2014-07-18       Impact factor: 4.956

View more
  2 in total

1.  Advanced Insights into Catalytic and Structural Features of the Zinc-Dependent Alcohol Dehydrogenase from Thauera aromatica.

Authors:  Frances Stark; Christoph Loderer; Mark Petchey; Gideon Grogan; Marion B Ansorge-Schumacher
Journal:  Chembiochem       Date:  2022-06-14       Impact factor: 3.461

2.  Reversal of Regioselectivity in Zinc-Dependent Medium-Chain Alcohol Dehydrogenase from Rhodococcus erythropolis toward Octanone Derivatives.

Authors:  Gaurao V Dhoke; Yunus Ensari; Dinc Yasat Hacibaloglu; Anna Gärtner; Anna Joëlle Ruff; Marco Bocola; Mehdi D Davari
Journal:  Chembiochem       Date:  2020-06-30       Impact factor: 3.164

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.