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

Resource utilization of drinking water treatment aluminum sludge in green cementing materials: Hydration characteristics and hydration kinetics

As a byproduct of water treatment, drinking water treatment aluminum sludge (DWTAS) has challenges related to imperfect treatment and disposal, which has caused potential harm to human health and the environment. In this paper, heat treatment DWTAS as a supplement cementitious material was used to prepare a green cementing material. The results show that the 800°C is considered as the optimum heat treatment temperature for DWTAS. DWTAS-800°C is fully activated after thermal decomposition to form incompletely crystallized highly active γ-Al2O3 and active SiO2. The addition of DWTAS promoted the formation of ettringite and C-(A)-S-H gel, which could make up for the low early compressive strength of cementing materials to a certain extent. When cured for 90 days, the compressive strength of the mortar with 30% DWTAS-800°C reached 44.86 MPa. The dynamic process was well simulated by Krstulović-Dabić hydration kinetics model. This study provided a methodology for the fabrication of environmentally friendly and cost-effective compound cementitious materials and proposed a "waste-to-resource" strategy for the sustainable management of typical solid wastes.

Modelling ligand exchange in metal complexes with machine learning potentials

Metal ions are irreplaceable in many areas of chemistry, including (bio)catalysis, self-assembly and charge transfer processes. Yet, modelling their structural and dynamic properties in diverse chemical environments remains challenging for both force fields and ab initio methods. Here, we introduce a strategy to train machine learning potentials (MLPs) using MACE, an equivariant message-passing neural network, for metal-ligand complexes in explicit solvents. We explore the structure and ligand exchange dynamics of Mg2+ in water and Pd2+ in acetonitrile as two illustrative model systems. The trained potentials accurately reproduce equilibrium structures of the complexes in solution, including different coordination numbers and geometries. Furthermore, the MLPs can model structural changes between metal ions and ligands in the first coordination shell, and reproduce the free energy barriers for the corresponding ligand exchange. The strategy presented here provides a computationally efficient approach to model metal ions in solution, paving the way for modelling larger and more diverse metal complexes relevant to biomolecules and supramolecular assemblies.

Characterizing the Mechanisms of Ca and Mg Carbonate Ion-Pair Formation with Multi-Level Molecular Dynamics/Quantum Mechanics Simulations

The carbonate minerals of Ca and Mg are abundant throughout the lithosphere and have recently garnered significant research interest as possible long-term carbon sinks in the sequestration of atmospheric carbon dioxide. Nonetheless, an understanding of the atomic-level processes comprising their mineralization remains limited. Here, we characterize and contrast the mechanisms of contact ion-pair formation in aqueous Ca and Mg carbonate systems, which represents the most fundamental step leading to the formation of their mineral solids. Utilizing multilevel embedded correlated wavefunction-based ab initio molecular dynamics/quantum mechanics simulations, we characterize not only the dynamics of these processes but also factors arising from the electronic structure of the involved species, revealing further details of the fundamentally different mechanisms for the interconversion between the contact ion-pairs and solvent-shared ion-pairs of Ca versus Mg carbonate.

Mechanism of Fluoride Ion Encapsulation by Magnesium Ions in a Bacterial Riboswitch

Riboswitches sense various ions in bacteria and activate gene expression to synthesize proteins that help maintain ion homeostasis. The crystal structure of the aptamer domain (AD) of the fluoride riboswitch shows that the F- ion is encapsulated by three Mg2+ ions bound to the ligand-binding domain (LBD) located at the core of the AD. The assembly mechanism of this intricate structure is unknown. To this end, we performed computer simulations using coarse-grained and all-atom RNA models to bridge multiple time scales involved in riboswitch folding and ion binding. We show that F- encapsulation by the Mg2+ ions bound to the riboswitch involves multiple sequential steps. Broadly, two Mg2+ ions initially interact with the phosphate groups of the LBD using water-mediated outer-shell coordination and transition to a direct inner-shell interaction through dehydration to strengthen their interaction with the LBD. We propose that the efficient binding mode of the third Mg2+ and F- is that they form a water-mediated ion pair and bind to the LBD simultaneously to minimize the electrostatic repulsion between three Mg2+ bound to the LBD. The tertiary stacking interactions among the LBD nucleobases alone are insufficient to stabilize the alignment of the phosphate groups to facilitate Mg2+ binding. We show that the stability of the whole assembly is an intricate balance of the interactions among the five phosphate groups, three Mg2+, and the encapsulated F- ion aided by the Mg2+ solvated water. These insights are helpful in the rational design of RNA-based ion sensors and fast-switching logic gates.

Probing pH-Dependent Dehydration Dynamics of Mg and Ca Cations in Aqueous Solutions with Multi-Level Quantum Mechanics/Molecular Dynamics Simulations

The dehydration of aqueous calcium and magnesium cations is the most fundamental process controlling their reactivity in chemical and biological phenomena, such as the formation of ionic solids or passing through ion channels. It holds particular relevance in light of recent advancements in the development of carbon capture techniques that rely on mineralization for long-term carbon storage. Specifically, dehydration of Ca2+ and Mg2+ is a key step in proposed carbon capture processes aiming to exploit the relatively high concentration of dissolved carbon dioxide in seawater via the formation of carbonate minerals from solvated Ca2+ and Mg2+ cations for sequestration and storage. Nevertheless, atomic-scale understanding of the dehydration of aqueous Ca2+ and Mg2+ cations remains limited. Here, we utilize rare event sampling via density functional theory molecular dynamics and embedded wavefunction theory calculations to elucidate the dehydration dynamics of aqueous Ca2+ and Mg2+. Emphasis is placed on the investigation of the effect pH has on the stability of the different coordination environments. Our results reveal significant differences in the dehydration dynamics of the two cations and provide insight into how they may be modulated by pH changes.

Structural insights on ionizable Dlin-MC3-DMA lipids in DOPC layers by combining accurate atomistic force fields, molecular dynamics simulations and neutron reflectivity

Ionizable lipids such as the promising Dlin-MC3-DMA (MC3) are essential for the successful design of lipid nanoparticles (LNPs) as drug delivery agents. Combining molecular dynamics simulations with experimental data, such as neutron reflectivity experiments and other scattering techniques, is essential to provide insights into the internal structure of LNPs, which is not fully understood to date. However, the accuracy of the simulations relies on the choice of force field parameters and high-quality experimental data is indispensable to verify the parametrization. For MC3, different parameterizations in combination with the CHARMM and the Slipids force fields have recently emerged. Here, we complement the existing efforts by providing parameters for cationic and neutral MC3 compatible with the AMBER Lipid17 force field. Subsequently, we carefully assess the accuracy of the different force fields by providing a direct comparison to neutron reflectivity experiments of mixed lipid bilayers consisting of MC3 and DOPC at different pHs. At low pH (cationic MC3) and at high pH (neutral MC3) the newly developed MC3 parameters in combination with AMBER Lipid17 for DOPC give good agreement with the experiments. Overall, the agreement is similar compared to the Park-Im parameters for MC3 in combination with the CHARMM36 force field for DOPC. The Ermilova-Swenson MC3 parameters in combination with the Slipids force field underestimate the bilayer thickness. While the distribution of cationic MC3 is very similar, the different force fields for neutral MC3 reveal distinct differences ranging from strong accumulation in the membrane center (current MC3/AMBER Lipid17 DOPC), over mild accumulation (Park-Im MC3/CHARMM36 DOPC) to surface accumulation (Ermilova-Swenson MC3/Slipids DOPC). These pronounced differences highlight the importance of accurate force field parameters and their experimental validation.

Impacts of targeting different hydration free energy references on the development of ion potentials

Hydration free energy (HFE) as the most important solvation parameter is often targeted in ion model development, even though the reported values differ by dozens of kcal mol^-1 mainly due to the experimentally undetermined HFE of the proton ΔG°(H⁺). The choice of ΔG°(H⁺) obviously affects the hydration of single ions and the relative HFE between the ions with different (magnitude or sign) charges, and the impacts of targeted HFEs on the ion solvation and ion-ion interactions are largely unrevealed. Here we designed point charge models of K⁺, Mg²⁺, Al³⁺, and Cl^- ions targeting a variety of HFE references and then investigated the HFE influences on the simulations of dilute and concentrated ion solutions and of the salt ion pairs in gas, liquid, and solid phases. Targeting one more property of ion-water oxygen distances (IOD) leaves the ion-water binding distance invariant, while the binding strength increases with the decreasing (more negative) HFE of ions as a result of a decrease in ΔG°(H⁺) for the cation and an increase in ΔG°(H⁺) for the anion. The increase in ΔG°(H⁺) leads to strengthened cation-anion interactions and thus to close ion-ion contacts, low osmotic pressures, and small activity derivatives in concentrated ion solutions as well as too stable ion pairs of the salts in different phases. The ion diffusivity and water exchange rates around the ions are simply not HFE dependent but rather more complex. Targeting both the aqueous IOD and salt crystal properties of KCl was also attempted and the comparison between different models indicates the complexity and challenge in obtaining a balanced performance between different phases using classical force fields. Our results also support that a real ΔG°(H⁺) value of -259.8 kcal mol^-1 recommended by Hünenberger and Reif guides ion models to reproduce ion-water and ion-ion interactions reasonably at relatively low salt concentrations. Simulations of a metalloprotein show that a relatively more positive ΔG°(H⁺) for Mg²⁺ model is better for a reasonable description of the metal binding network.

Systematic Evaluation of Ion Diffusion and Water Exchange

As a fundamental property of all fluids, diffusion plays myriad roles in both science and our daily lives. Diffusive properties of many liquids including water have been extensively studied both experimentally and theoretically, while for transition metal ions, there exist significant experimental data that have not been extensively studied theoretically. Hence, high-confidence predictions for challenging systems like radioactive ions that are biohazardous cannot be reliably generated. In this work, a workflow named ISAIAH (Ion Simulation using AMBER for dIffusion Action when Hydrated) was designed to accurately simulate the diffusion coefficients of 15 monoatomic ions with charges varying from -1 to +3 in four water models. As the results indicate, good agreement with experimental values was achieved, leading us to select ²³⁹Pu⁴⁺ (for which no experimental data are available) as a candidate ion to make a theoretical prediction of its diffusion coefficient in water. Among all the force field parameter sets, the ones parametrized using an augmented 12-6-4 Lennard-Jones (LJ) potential showed lower average unsigned errors (AUE) for ions of various radii and electron configurations relative to some 12-6 LJ parameters. This observation agrees well with the fact that diffusion is affected by both the hydration free energy (HFE) and the ion-oxygen distance (IOD) between solute and solvent molecules, both of which are handled well by the 12-6-4 model.

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 twelve 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.

Artificial Intelligence Resolves Kinetic Pathways of Magnesium Binding to RNA

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.

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

Magnesium is essential in many vital processes. To correctly describe Mg2+ 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 Mg2+ parameters in combination with the SPC/E, TIP3P-fb, TIP4P/2005, TIP4P-Ew, and TIP4P-D water models. For each water model, the Mg2+ force fields reproduce the solvation free energy, the distance to oxygens in the first hydration shell, the hydration number, the activity coefficient derivative in MgCl2 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 106 to 108 exchanges per second. The nanoMg parameters can be used to enhance the sampling of binding events, to obtain converged distributions of Mg2+, or to predict ion binding sites in biomolecular simulations. The parameter files are freely available at https://github.com/bio-phys/optimizedMgFFs.