Optimized Magnesium Force Field Parameters for Biomolecular Simulations with Accurate Solvation, Ion-Binding, and Water-Exchange Properties.

Kara K Grotz,Sergio Cruz-León,Nadine Schwierz

doi:10.1021/acs.jctc.0c01281

Kara K Grotz, Sergio Cruz-León + Show 1 more

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https://doi.org/10.1021/acs.jctc.0c01281

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Abstract

Magnesium ions play an essential role in many vital processes. To correctly describe their interactions in molecular dynamics simulations, an accurate parametrization is crucial. Despite the importance and considerable scientific effort, current force fields based on the commonly used 12–6 Lennard-Jones interaction potential fail to reproduce a variety of experimental solution properties. In particular, no parametrization exists so far that simultaneously reproduces the solvation free energy and the distance to the water oxygens in the first hydration shell. Moreover, current Mg2+ force fields significantly underestimate the rate of water exchange leading to unrealistically slow exchange kinetics. In order to make progress in the development of improved models, we systematically optimize the Mg2+ parameters in combination with the TIP3P water model in a much larger parameter space than previously done. The results show that a long-ranged interaction potential and modified Lorentz–Berthelot combination rules allow us to accurately reproduce multiple experimental properties including the solvation free energy, the distances to the oxygens of the first hydration shell, the hydration number, the activity coefficient derivative in MgCl2 solutions, the self-diffusion coefficient, and the binding affinity to the phosphate oxygen of RNA. Matching this broad range of thermodynamic properties, we present two sets of optimal parameters: MicroMg yields water exchange on the microsecond timescale in agreement with experiments. NanoMg yields water exchange on the nanosecond timescale facilitating the direct observation of ion-binding events. As shown for the example of the add A-riboswitch, the optimized parameters correctly reproduce the structure of specifically bound ions and permit the de novo prediction of Mg2+-binding sites in biomolecular simulations.

Highlights

Magnesium ions play a crucial role in a large variety of physiological processes such as ATP hydrolysis, cellular signaling, or the catalytic activity of enzymes and ribozymes.[1−4] In particular, in nucleic acid systems, Mg2+ ions are essential to stabilize the tertiary structure, to drive folding or to enable catalytic reactions.[3,5−11] Due to the biochemical importance of Mg2+, the modeling of these ions has received significant scientific attention.[12−21] providing a quantitative description of their interactions and resolving their role in the folding and function of biomolecules is challenging
In the most widely used force fields, Mg2+ ions are modeled as point charges and the electrostatic, dispersion, and excluded volume interactions are taken into account by a pairwise interaction potential
For Allneŕ −Villa and Li−Merz (12−6), an upper estimate is given based on transition state theory (TST) since the number of transitions is insufficient to calculate the rate from eq 5

Summary

Introduction

Magnesium ions play a crucial role in a large variety of physiological processes such as ATP hydrolysis, cellular signaling, or the catalytic activity of enzymes and ribozymes.[1−4] In particular, in nucleic acid systems, Mg2+ ions are essential to stabilize the tertiary structure, to drive folding or to enable catalytic reactions.[3,5−11] Due to the biochemical importance of Mg2+, the modeling of these ions has received significant scientific attention.[12−21] providing a quantitative description of their interactions and resolving their role in the folding and function of biomolecules is challenging. Classical all-atom simulations allow us to treat much larger and biologically relevant systems but require accurate empirical force fields. In order to provide accurate Mg2+ models, the two parameters of the LJ potential are typically adjusted to reproduce experimental solution properties such as the solvation free energy ΔGsolv,[17−20] the distance to the water oxygens in the first coordination number hydration n1.13,16−20 shell R1,13,14,16,18,19 and the In addition to thermodynamic and structural data, including kinetic properties in the parametrization is crucial to capture dynamical processes such as water exchange, ion-binding, or ion-pairing.[16,20,23]

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