Chorismate mutase has been well studied both experimentally and computationally. However, there are still several unanswered questions about how the Claisen rearrangement from chorismate to prephenate is catalyzed, including the importance of conformational constraint of the flexible substrate, and how active site hydrogen bonding stabilizes the transition state. The Residue Interaction Network-based ResidUe Selector (RINRUS) software toolkit is used to examine the effect of conformational sampling and gain insight on the fluctuation of the active site by QM-cluster modeling. We propose several alternatives for generating conformational clustering from MD simulation to evaluate the catalytic reaction. Structural clustering is compared to novel topological clustering from Residue Interaction Network information. We then use a consistent model-building scheme in RINRUS to generate a statistical thermodynamics framework for QM-cluster modeling of enzymes with Density Functional Theory (DFT). The over 250 QM-cluster models sampled provide a ΔG<sup>‡</sup> of 10.32 ± 5.18 kcal/mol compared to the experimental value of 15.4 kcal/mol at 25 <sup>0</sup>C. While the difference between theory and experiment is consequential, our group can follow with reliable RINRUS-based calibration of DFT functionals, basis set, and implicit solvation implementations to improve the accuracy of QM-cluster models.

QM-cluster Modeling of chorismate mutase based on sampling MD simulation

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