Hybrid quantum mechanical-molecular mechanical (QM/MM) simulations are widely used in studies of enzymatic catalysis. Up until now , it has usually been cost prohibitive to determine the convergence of these calculations with respect to the size of the QM region. Recent advances in reformulating electronic structure algorithms for stream processors such as graphical processing units have made QM/MM calculations of optimized reaction paths with QM regions comprising up to O(10^3) atoms feasible. Here, we leverage these GPU-accelerated quantum chemistry methods to investigate catalytic properties in catechol O-methyltransferase  . Using QM regions ranging in size from the reactant only (63 atoms) up to nearly one-third of the entire protein (940 atoms), we show that convergence of properties such as the activation energy of the catalyzed reaction can be quite slow. Convergence to within chemical accuracy for this case requires a quantum mechanical region with approximately 500 atoms . These results call for a more careful determination of QM region sizes in future QM/MM studies of enzymes.
Hybrid quantum mechanical-molecular mechanical (QM/MM) simulations are widely used in studies of enzymatic catalysis. Until recently , it has been cost prohibitive to determine the asymptotic limit of key energetic and structural properties with respect to increasingly large QM regions. Leveraging recent advances in electronic structure efficiency and accuracy, we investigate catalytic properties in catechol O-methyltransferase , a representative example of a methyltransferase critical to human health . Using QM regions ranging in size from reactants-only (64 atoms) to nearly one-third of the entire protein (940 atoms), we show that properties such as the activation energy approach within chemical accuracy of the large-QM asymptotic limits rather slowly, requiring approximately 500-600 atoms if the QM residues are chosen simply by distance from the substrate. This slow approach to asymptotic limit is due to charge transfer from protein residues to the reacting substrates. Our large QM/MM calculations enable identification of charge separation for fragments in the transition state as a key component of enzymatic methyl transfer rate enhancement. We introduce charge shift analysis that reveals the minimum number of protein residues (ca. 11-16 residues or 200-300 atoms for COMT) needed for quantitative agreement with large-QM simulations. The identified residues are not those that would be typically selected using criteria such as chemical intuition or proximity. These results provide a recipe for a more careful determination of QM region sizes in future QM/MM studies of enzymes.
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Up until now
Until recently
D
usually
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convergence of these calculations
asymptotic limit of key energetic and structural properties
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the size of the QM region. Recent advances in reformulating electronic structure algorithms for stream processors such as graphical processing units have made QM/MM calculations of optimized reaction paths with QM regions comprising up to O(10^3) atoms feasible. Here, we leverage these GPU-accelerated quantum chemistry methods to
increasingly large QM regions. Leveraging recent advances in electronic structure efficiency and accuracy, we
A
, a representative example of a methyltransferase critical to human health
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the reactant only (63 atoms) up
reactants-only (64 atoms)
D
convergence of
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of the catalyzed reaction can be quite slow. Convergence to within chemical accuracy for this case requires a quantum mechanical region with approximately 500 atoms . These results call
approach within chemical accuracy of the large-QM asymptotic limits rather slowly, requiring approximately 500-600 atoms if the QM residues are chosen simply by distance from the substrate. This slow approach to asymptotic limit is due to charge transfer from protein residues to the reacting substrates. Our large QM/MM calculations enable identification of charge separation for fragments in the transition state as a key component of enzymatic methyl transfer rate enhancement. We introduce charge shift analysis that reveals the minimum number of protein residues (ca. 11-16 residues or 200-300 atoms for COMT) needed for quantitative agreement with large-QM simulations. The identified residues are not those that would be typically selected using criteria such as chemical intuition or proximity. These results provide a recipe