Literature DB >> 21523538

Brønsted-Evans-Polanyi relationships for C-C bond forming and C-C bond breaking reactions in thiamine-catalyzed decarboxylation of 2-keto acids using density functional theory.

Rajeev Surendran Assary1, Linda J Broadbelt, Larry A Curtiss.   

Abstract

The concept of generalized enzyme reactions suggests that a wide variety of substrates can undergo enzymatic transformations, including those whose biotransformation has not yet been realized. The use of quantum chemistry to evaluate kinetic feasibility is an attractive approach to identify enzymes for the proposed transformation. However, the sheer number of novel transformations that can be generated makes this impractical as a screening approach. Therefore, it is essential to develop structure/activity relationships based on quantities that are more efficient to calculate. In this work, we propose a structure/activity relationship based on the free energy of binding or reaction of non-native substrates to evaluate the catalysis relative to that of native substrates. While Brønsted-Evans-Polanyi (BEP) relationships such as that proposed here have found broad application in heterogeneous catalysis, their extension to enzymatic catalysis is limited. We report here on density functional theory (DFT) studies for C-C bond formation and C-C bond cleavage associated with the decarboxylation of six 2-keto acids by a thiamine-containing enzyme (EC 1.2.7.1) and demonstrate a linear relationship between the free energy of reaction and the activation barrier. We then applied this relationship to predict the activation barriers of 17 chemically similar novel reactions. These calculations reveal that there is a clear correlation between the free energy of formation of the transition state and the free energy of the reaction, suggesting that this method can be further extended to predict the kinetics of novel reactions through our computational framework for discovery of novel biochemical transformations.

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Year:  2011        PMID: 21523538     DOI: 10.1007/s00894-011-1062-z

Source DB:  PubMed          Journal:  J Mol Model        ISSN: 0948-5023            Impact factor:   1.810


  24 in total

1.  Monte Carlo sampling can be used to determine the size and shape of the steady-state flux space.

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2.  Theoretical study toward understanding the catalytic mechanism of pyruvate decarboxylase.

Authors:  Jianyi Wang; Hao Dong; Shuhua Li; Hongwu He
Journal:  J Phys Chem B       Date:  2005-10-06       Impact factor: 2.991

3.  Computational screening of novel thiamine-catalyzed decarboxylation reactions of 2-keto acids.

Authors:  Rajeev S Assary; Linda J Broadbelt
Journal:  Bioprocess Biosyst Eng       Date:  2011-03       Impact factor: 3.210

4.  Thermodynamic analysis of biodegradation pathways.

Authors:  Stacey D Finley; Linda J Broadbelt; Vassily Hatzimanikatis
Journal:  Biotechnol Bioeng       Date:  2009-06-15       Impact factor: 4.530

5.  Genome-scale model for Clostridium acetobutylicum: Part II. Development of specific proton flux states and numerically determined sub-systems.

Authors:  Ryan S Senger; Eleftherios T Papoutsakis
Journal:  Biotechnol Bioeng       Date:  2008-12-01       Impact factor: 4.530

6.  Discovery and analysis of novel metabolic pathways for the biosynthesis of industrial chemicals: 3-hydroxypropanoate.

Authors:  Christopher S Henry; Linda J Broadbelt; Vassily Hatzimanikatis
Journal:  Biotechnol Bioeng       Date:  2010-06-15       Impact factor: 4.530

7.  Cycloaddition reactions of butadiene and 1,3-dipoles to curved arenes, fullerenes, and nanotubes: theoretical evaluation of the role of distortion energies on activation barriers.

Authors:  Sílvia Osuna; Kendall N Houk
Journal:  Chemistry       Date:  2009-12-07       Impact factor: 5.236

8.  Computational framework for predictive biodegradation.

Authors:  Stacey D Finley; Linda J Broadbelt; Vassily Hatzimanikatis
Journal:  Biotechnol Bioeng       Date:  2009-12-15       Impact factor: 4.530

Review 9.  Reconstruction of biochemical networks in microorganisms.

Authors:  Adam M Feist; Markus J Herrgård; Ines Thiele; Jennie L Reed; Bernhard Ø Palsson
Journal:  Nat Rev Microbiol       Date:  2008-12-31       Impact factor: 60.633

10.  A model-based optimization framework for the inference of regulatory interactions using time-course DNA microarray expression data.

Authors:  Reuben Thomas; Carlos J Paredes; Sanjay Mehrotra; Vassily Hatzimanikatis; Eleftherios T Papoutsakis
Journal:  BMC Bioinformatics       Date:  2007-06-29       Impact factor: 3.169

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