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![]() ![]() The Gibbs energy of a particular species comprises contributions from many geometric conformers and can thus be obtained by averaging over their respective Gibbs energies. First, it has to accurately account for the different minimal energy geometric conformations that coexist in the solution phase. Solution phase thermochemistry faces two major challenges. However, predicting standard Gibbs reaction energies of metabolic reactions is significantly more challenging since biochemical reactions occur in solution. Quantum chemistry has been successful at predicting the thermodynamics of gas phase chemical reactions with chemical accuracy 9, 10, 11. Finally, we outline future research directions that can deliver chemical accuracy to metabolic reaction thermochemistry by using quantum chemical approaches. In this work, we analyze the different contributions to the errors in predicting Gibbs reaction energies using quantum chemistry. Additionally, they can take advantage of an established hierarchy of increasingly accurate (and increasingly costly) quantum chemical methods. Using first-principles methods for predicting thermodynamic parameters offers several crucial advantages: Nonempirical methods are not limited by the available experimental data, thus reducing the risk of overfitting and providing a consistent approach throughout all of metabolism. Our objective is to develop a quantum-chemistry based computational framework for thermodynamics of metabolism that is competitive with GCMs. Here, we present the first nonempirical high-throughput computational method for estimating values of metabolic reactions from quantum chemistry. Modern GCMs account for pH and combine group contribution estimates with more accurate reactant contributions 7, 8. GCMs employ additive schemes with increments for functional groups obtained from fitting to experimental data. ![]() The group contribution methods (GCMs) are empirical computational approaches that are currently used for estimating values from standard Gibbs formation energies of reactants and products 4, 5, 6, 7. However, experimental values are available only for a small fraction of all known metabolic reactions 3. Accurate standard Gibbs reaction energies of biochemical reactions are crucial inputs for thermodynamics-based flux balance analysis, in which they are used to impose constraints on metabolite concentrations 1 and to determine the ratios of forward and backward fluxes 2. ![]() Thermodynamics is fundamental for understanding the design principles of natural metabolic processes and for engineering efficient new metabolic pathways. ![]()
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