Kinetic pathways of water exchange in the first hydration shell of magnesium: influence of water model and ionic force field

Water exchange between the first and second hydration shell is essential for the role of Mg2+ in biochemical processes. In order to provide microscopic insights into the exchange mechanism, we resolve the exchange pathways by all-atom molecular dynamics simulations and transition path sampling. Since the exchange kinetics relies on the choice of the water model and the ionic force field, we systematically investigate the influence of seven different polarizable and non-polarizable water and three different Mg2+ models. In all cases, water exchange can occur either via an indirect or direct mechanism (exchanging molecules occupy different/same position on the water octahedron). In addition, the results reveal a crossover from an interchange dissociative (Id) to an associative (Ia) reaction mechanism dependent on the range of the Mg2+-water interaction potential of the respective force field. Standard non-polarizable force fields follow the Id mechanism in agreement with experimental results. By contrast, polarizable and long-ranged non-polarizable force fields follow the Ia mechanism. Our results provide a comprehensive view on the influence of the water model and the ionic force field on the exchange dynamics and the foundation to assess the choice of the force field in biomolecular simulations

Artificial intelligence resolves kinetic pathways of magnesium binding to RNA

[Image: see text] Magnesium is an indispensable cofactor in countless vital processes. In order to understand its functional role, the characterization of the binding pathways to biomolecules such as RNA is crucial. Despite the importance, a molecular description is still lacking since the transition from the water-mediated outer-sphere to the direct inner-sphere coordination is on the millisecond time scale and therefore out of reach for conventional simulation techniques. To fill this gap, we use transition path sampling to resolve the binding pathways and to elucidate the role of the solvent in the binding process. The results reveal that the molecular void provoked by the leaving phosphate oxygen of the RNA is immediately filled by an entering water molecule. In addition, water molecules from the first and second hydration shell couple to the concerted exchange. To capture the intimate solute–solvent coupling, we perform a committor analysis as the basis for a machine learning algorithm that derives the optimal deep learning model from thousands of scanned architectures using hyperparameter tuning. The results reveal that the properly optimized deep network architecture recognizes the important solvent structures, extracts the relevant information, and predicts the commitment probability with high accuracy. Our results provide detailed insights into the solute–solvent coupling which is ubiquitous for kosmotropic ions and governs a large variety of biochemical reactions in aqueous solutions

Colloidal systems in three-dimensional microchannels: lattice control via channel width and external force

The structural behavior of hard spheres interacting with repulsive (screened Coulomb) interaction in narrow constrictions is investigated using Brownian dynamics simulations. The system of particles adapts to the confining potential and the interaction energies by a self-consistent arrangement of the particles. It results in the formation of planes throughout the three-dimensional channel. The presence of hard walls leads to structural deviations from the unbounded (infinite) crystal. The arrangement of the particles is perturbed by diffusion and an external driving force leading to a density gradient along the channel. The particles accommodate to the density gradient by reducing the number of planes if it is energetically favorable. This reduction in the number of planes is analogous to the reduction in the number of layers in two-dimensional systems. The influence of a self-organized order within the system is reflected in the velocity of the particles and their diffusive behavior

Hofmeister series for metal-cation–RNA interactions: the interplay of binding affinity and exchange kinetics

A large variety of physicochemical properties involving RNA depends on the type of metal cation present in solution. In order to gain microscopic insight into the origin of these ion specific effects, we apply molecular dynamics simulations to describe the interactions of metal cations and RNA. For the three most common ion binding sites on RNA, we calculate the binding affinities and exchange rates of eight different mono- and divalent metal cations. Our results reveal that binding sites involving phosphate groups preferentially bind metal cations with high charge density (such as Mg2+) in inner-sphere conformations while binding sites involving N7 or O6 atoms preferentially bind cations with low charge density (such as K+). The binding affinity therefore follows a direct Hofmeister series at the backbone but is reversed at the nucleobases leading to a high selectivity of ion binding sites on RNA. In addition, the exchange rates for cation binding cover almost 5 orders of magnitude, leading to a vastly different time scale for the lifetimes of contact pairs. Taken together, the site-specific binding affinities and the specific lifetime of contact pairs provide the microscopic explanation of ion specific effects observed in a wide variety of macroscopic RNA properties. Finally, combining the results from atomistic simulations with extended Poisson-Boltzmann theory allows us to predict the distribution of metal cations around double-stranded RNA at finite concentrations and to reproduce the results of ion counting experiments with good accuracy

Optimized magnesium force field parameters for biomolecular simulations with accurate solvation, ion-binding, and water-exchange properties in SPC/E, TIP3P-fb, TIP4P/2005, TIP4P-Ew, and TIP4P-D

[Image: see text] Magnesium is essential in many vital processes. To correctly describe Mg(2+) in physiological processes by molecular dynamics simulations, accurate force fields are fundamental. Despite the importance, force fields based on the commonly used 12-6 Lennard-Jones potential showed significant shortcomings. Recently progress was made by an optimization procedure that implicitly accounts for polarizability. The resulting microMg and nanoMg force fields (J. Chem. Theory Comput.2021, 17, 2530–2540) accurately reproduce a broad range of experimental solution properties and the binding affinity to nucleic acids in TIP3P water. Since countless simulation studies rely on available water models and ion force fields, we here extend the optimization and provide Mg(2+) parameters in combination with the SPC/E, TIP3P-fb, TIP4P/2005, TIP4P-Ew, and TIP4P-D water models. For each water model, the Mg(2+) force fields reproduce the solvation free energy, the distance to oxygens in the first hydration shell, the hydration number, the activity coefficient derivative in MgCl(2) solutions, and the binding affinity and distance to the phosphate oxygens on nucleic acids. We present two parameter sets: MicroMg yields water exchange on the microsecond time scale and matches the experimental exchange rate. Depending on the water model, nanoMg yields accelerated water exchange in the range of 10(6) to 10(8) exchanges per second. The nanoMg parameters can be used to enhance the sampling of binding events, to obtain converged distributions of Mg(2+), or to predict ion binding sites in biomolecular simulations. The parameter files are freely available at https://github.com/bio-phys/optimizedMgFFs

Magnesium force fields for OPC water with accurate solvation, ion-binding, and water-exchange properties: successful transfer from SPC/E

Magnesium plays a vital role in a large variety of biological processes. To model such processes by molecular dynamics simulations, researchers rely on accurate force field parameters for Mg2+ and water. OPC is one of the most promising water models yielding an improved description of biomolecules in water. The aim of this work is to provide force field parameters for Mg2+ that lead to accurate simulation results in combination with OPC water. Using 12 different Mg2+ parameter sets that were previously optimized with different water models, we systematically assess the transferability to OPC based on a large variety of experimental properties. The results show that the Mg2+ parameters for SPC/E are transferable to OPC and closely reproduce the experimental solvation free energy, radius of the first hydration shell, coordination number, activity derivative, and binding affinity toward the phosphate oxygens on RNA. Two optimal parameter sets are presented: MicroMg yields water exchange in OPC on the microsecond timescale in agreement with experiments. NanoMg yields accelerated exchange on the nanosecond timescale and facilitates the direct observation of ion binding events for enhanced sampling purposes

Optimized magnesium force field parameters for biomolecular simulations with accurate solvation, ion-binding, and water-exchange properties

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

Extended magnesium and calcium force field parameters for accurate ion–nucleic acid interactions in biomolecular simulations

Magnesium and calcium play an essential role in the folding and function of nucleic acids. To correctly describe their interactions with DNA and RNA in biomolecular simulations, an accurate parameterization is crucial. In most cases, the ion parameters are optimized based on a set of experimental solution properties such as solvation free energies, radial distribution functions, water exchange rates, and activity coefficient derivatives. However, the transferability of such bulk-optimized ion parameters to quantitatively describe biomolecular systems is limited. Here, we extend the applicability of our previous bulk-optimized parameters by including experimental binding affinities toward the phosphate oxygen on nucleic acids. In particular, we systematically adjust the combination rules that are an integral part of the pairwise interaction potentials of classical force fields. This allows us to quantitatively describe specific ion binding to nucleic acids without changing the solution properties in the most simple and efficient way. We show the advancement of the optimized Lorentz combination rule for two representative nucleic acid systems. For double-stranded DNA, the optimized combination rule for Ca2+>/sup> significantly improves the agreement with experiments, while the standard combination rule leads to unrealistically distorted DNA structures. For the add A-riboswitch, the optimized combination rule for Mg2+>/sup> improves the structure of two specifically bound Mg2+>/sup> ions as judged by the experimental distance to the binding site. Including experimental binding affinities toward specific ion binding sites on biomolecules, therefore, provides a promising perspective to develop a more accurate description of metal cations for biomolecular simulations

Reversed Hofmeister series - the rule rather than the exception

Over recent years, the supposedly universal Hofmeister series has been replaced by a diverse spectrum of direct, partially altered and reversed series. This review aims to provide a detailed understanding of the full spectrum by combining results from molecular dynamics simulations, Poisson–Boltzmann theory and AFM experiments. Primary insight into the origin of the Hofmeister series and its reversal is gained from simulation-derived ion–surface interaction potentials at surfaces containing non-polar, polar and charged functional groups for halide anions and alkali cations. In a second step, the detailed microscopic interactions of ions, water and functional surface groups are incorporated into Poisson–Boltzmann theory. This allows us to quantify ion-specific binding affinities to surface groups of varying polarity and charge, and to provide a connection to the experimentally measured long-ranged electrostatic forces that stabilize colloids, proteins and other particles against precipitation. Based on the stabilizing efficiency, the direct Hofmeister series is obtained for negatively charged hydrophobic surfaces. Hofmeister series reversal is induced by changing the sign of the surface charge from negative to positive, by changing the nature of the functional surface groups from hydrophobic to hydrophilic, by increasing the salt concentration, or by changing the pH. The resulting diverse spectrum reflects that alterations of Hofmeister series are the rule rather than the exception and originate from the variation of ion-surface interactions upon changing surface properties