Molecular mechanics (MM) simulations have the potential to provide detailed insights into the mechanisms of enzymes that utilize nucleotides as cofactors. In most cases, the activities of these enzymes also require the binding of divalent cations to catalytic sites. However, modeling divalent cations in MM simulations has been challenging. The inclusion of explicit polarization was considered promising, but despite improvements over non-polarizable force fields and despite the inclusion of ‘Nonbonded-fix’ corrections, errors in interaction energies of divalent cations with proteins remain large. Importantly, the application of these models fails to reproduce experimental structural data on Mg²⁺-Protein-ATP complexes. Focusing on these complexes, here we provide a systematic assessment of the polarizable AMOEBA model and recommend critical changes that substantially improve its predictive performance. We first show that our recent revision of the AMOEBA protein model, AMOEBA-HFC, which contains high field corrections (HFC) to induced dipoles, dramatically improves Mg²⁺-protein interaction energies, reducing mean absolute errors from 17 to 10 kcal/mol. This further supports the general applicability of AMOEBA-HFC. The inclusion of many-body NB-fix corrections further reduce MAE to 6 kcal/mol, which amounts to less than 2% error. The errors are estimated with respect to vdW-inclusive density functional theory that we benchmark against CCSD(T) calculations and experiments. We also present a new model of ATP with revised polarization parameters to better capture its high field response, as well as new vdW and dihedral parameters. The ATP model accurately predicts experimental Mg²⁺-ATP binding free energy in the aqueous phase and provides new insights into how Mg²⁺associates with ATP. Finally, we show that molecular dynamics (MD) simulations of Mg²⁺-Kinase-ATP complexes carried out with these improvements lead to a better agreement in global and local catalytic site structures between MD and X-ray crystallography.

Julian Delgado

University of South Florida

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