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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Lee SC, Chang YJ, Shin DM, Han J, Seo MH, Fazelinia H, Maranas CD, Kim HS (2009) Designing the substrate specificity of d-hydantoinase using a rational approach. Enzyme Microb Technol 44:170–175
Fazelinia H, Cirino PC, Maranas CD (2007) Extending iterative protein redesign and optimization (IPRO) in protein library design for ligand specificity. Biophys J 92:2120–2130
Senger RS, Papoutsakis ET (2008) Genome-scale model for Clostridium acetobutylicum: part I. Metabolic network resolution and analysis. Biotechnol Bioeng 101:1036–1052
Senger RS, Papoutsakis ET (2008) Genome-scale model for Clostridium acetobutylicum: part II. Development of specific proton flux states and numerically determined sub-systems. Biotechnol Bioeng 101:1053–1071
Lee J, Yun H, Feist AM, Palsson BO, Lee SY (2008) Genome-scale reconstruction and in silico analysis of the clostridium acetobutylicum ATCC 824 metabolic network. Appl Microbiol Biotechnol 80:849–862
Duarte NC, Becker SA, Jamshidi N, Thiele I, Mo ML, Vo TD, Srivas R, Palsson BO (2007) Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci USA 104:1777–1782
Thomas R, Paredes CJ, Mehrotra S, Hatzimanikatis V, Papoutsakis ET (2007) A model-based optimization framework for the inference of regulatory interactions using time-course DNA microarray expression data. BMC Bioinform 8:228–236
Fazelinia H, Cirino PC, Maranas CD (2009) OptGraft: a computational procedure for transferring a binding site onto an existing protein scaffold. Prot Sci 18:180–195
Becker SA, Feist AM, Mo ML, Hannum G, Palsson BO, Herrgard MJ (2007) Quantitative prediction of cellular metabolism with constraint-based models: the COBRA toolbox. Nat Protoc 2:727–738
Feist AM, Herrgard MJ, Thiele I, Reed JL, Palsson BO (2009) Reconstruction of biochemical networks in microorganisms. Nat Rev Microbiol 7:129–143
Hatzimanikatis V, Li CH, Ionita JA, Henry CS, Jankowski MD, Broadbelt LJ (2005) Exploring the diversity of complex metabolic networks. Bioinformatics 21:1603–1609
Henry CS, Jankowski MD, Broadbelt LJ, Hatzimanikatis V (2006) Genome-scale thermodynamic analysis of Escherichia coli metabolism. Biophys J 90:1453–1461
Finley SD, Broadbelt LJ, Hatzimanikatis V (2009) Thermodynamic analysis of biodegradation pathways. Biotechnol Bioeng 103:532–541
Broadbelt LJ, Stark SM, Klein MT (1994) Computer generated reaction networks: on-the-fly calculation of species properties using computational quantum chemistry. Chem Eng Sci 49:4991–5010
Broadbelt LJ, Stark SM, Klein MT (1994) Computer-generated pyrolysis modeling - on-the-fly generation of species, reactions, and rates. Ind Eng Chem Res 33:790–799
Broadbelt LJ, Stark SM, Klein MT (1995) Termination of computer-generated reaction-mechanisms—species rank-based convergence criterion. Ind Eng Chem Res 34:2566–2573
Gonzalez-Lergier J, Broadbelt LJ, Hatzimanikatis V (2005) Theoretical considerations and computational analysis of the complexity in polyketide synthesis pathways. J Chem Soc 127:9930–9938
Finley SD, Broadbelt LJ, Hatzimanikatis V (2009) Thermodynamic analysis of biodegradation pathways. Biotechnol Bioeng 104:1086–1097
Henry CS, Broadbelt LJ, Hatzimanikatis V (2010) Discovery and analysis of novel metabolic pathways for the biosynthesis of industrial chemicals: 3-hydroxypropanoate. Biotechnol Bioeng 106:462–473
Wiback SJ, Famili I, Greenberg HJ, Palsson BØ (2004) Monte Carlo sampling can be used to determine the size and shape of the steady-state flux space. J Theor Biol 228:437–447
Broadbelt LJ, Klein MT, Dean BD, Andrews SM (1995) Structure/reactivity relationships for high-performance polyamides—kinetics of the reactions of N,N′-dihexylphthalamides in the presence of added copper iodide and water. J Polym Sci A Polym Chem 33:533–545
Evans MG, Polanyi M (1938) Inertia and driving force of chemical reactions. Trans Faraday Soc 34:11–24
Osuna S, Houk KN (2009) 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. Chem Eur J 15:13219–13231
Assary RS, Broadbelt LA (2010) Computational screening of novel thiamine-catalyzed decarboxylation reaction of 2-keto acids. Bioprocess Biosyst Eng 34:375–388
Becke AD (1988) Density-functional exchange-energy approximation with correct asymptotic-behavior. Phys Rev Abstr 38:3098–3100
Becke AD (1993) Density-functional thermochemistry.3. The role of exact exchange. J Chem Phys 98:5648–5652
Lee CT, Yang WT, Parr RG (1988) Development of the colle-salvetti correlation-energy formula into a functional of the electron-density. Phys Rev B 37:785–789
Frisch MJ et al (2003) Gaussian03, revision E.01. Gaussian Inc, Wallingford
Takano Y, Houk KN (2005) Benchmarking the conductor-like polarizable continuum model (CPCM) for aqueous solvation free energies of neutral and ionic organic molecules. J Chem Theor Comput 1:70–77
Cossi M, Rega N, Scalmani G, Barone V (2003) Energies, structures, and electronic properties of molecules in solution with the C-PCM solvation model. J Comput Chem 24:669–681
Barone V, Cossi M (1998) Quantum calculation of molecular energies and energy gradients in solution by a conductor solvent model. J Phys Chem A 102:1995–2001
Wang J, Dong H, Li S, He H (2005) Theoretical study toward understanding the catalytic mechanism of pyruvate decarboxylase. J Phys Chem B 109:18664–18672
Siegbahn P, Himo F (2009) Recent developments of the quantum chemical cluster approach for modeling enzyme reactions. J Biol Inorg Chem 14:643–651
Acknowledgments
The authors are grateful for the financial support of the National Science Foundation (CBET-0835800). This material is based upon work supported as part of the Institute for Atom-efficient Chemical Transformations (IACT), an Energy Frontier Research Center funded by the US Department of Energy, Office of Science, and Office of Basic Energy Sciences. We gratefully acknowledge grants of computer time from the ANL Center for Nanoscale Materials.
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All gas phase energetics performed in this investigation are given in Tables S1 and S2.
Table S1
Calculated free energy of the reaction (ΔGreaction) and activation free energy barrier (ΔGTS ) for the C–C bond formation and cleavage with ThDP co-factor and various 2-keto acids at 298 K in gas phase using B3LYP/6-31 + G(d) level of theory. Values are reported in kcal/mol. (DOC 35 kb)
Table S2
Computed free energy of the reaction, calculated transition state barriers and predicted transition state barriers at the B3LYP/6-31 G(d) level of theory for the C–C bond formation and C–C bond breaking reactions in the gas phase (298 K). Chloro, amino, methoxy and hydroxy substituted pyruvic acid (pyr), 2-keto butanoic acid (but), 2-keto-isovaleric acid (iso), and 2-keto-valeric acid (val) were used for this study. All values are reported in kcal/mol. (DOC 42 kb)
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Assary, R.S., Broadbelt, L.J. & Curtiss, L.A. 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. J Mol Model 18, 145–150 (2012). https://doi.org/10.1007/s00894-011-1062-z
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DOI: https://doi.org/10.1007/s00894-011-1062-z