Lennard-Jones Parameters Determined to Reproduce the Solubility of NaCl and KCl in SPC/E, TIP3P, and TIP4P/2005 Water

Computational design of α-amylase from Bacillus licheniformis to increase its activity and stability at high temperatures

The thermostable α-amylase derived from Bacillus licheniformis (BLA) has multiple advantages, including enhancing the mass transfer rate and by reducing microbial contamination in starch hydrolysis. Nonetheless, the application of BLA is constrained by the accessibility and stability of enzymes capable of achieving high conversion rates at elevated temperatures. Moreover, the thermotolerance of BLA requires further enhancement. Here, we developed a computational strategy for constructing small and smart mutant libraries to identify variants with enhanced thermostability. Initially, molecular dynamics (MD) simulations were employed to identify the regions with high flexibility. Subsequently, FoldX, a computational design predictor, was used to design mutants by rigidifying highly flexible residues, whereas the simultaneous decrease in folding free energy assisted in improving thermostability. Through the utilization of MD and FoldX, residues K251, T277, N278, K319, and E336, situated at a distance of 5 Å from the catalytic triad, were chosen for mutation. Seventeen mutants were identified and characterized by evaluating enzymatic characteristics and kinetic parameters. The catalytic efficiency of the E271L/N278K mutant reached 184.1 g L-1 s-1, which is 1.88-fold larger than the corresponding value determined for the WT. Furthermore, the most thermostable mutant, E336S, exhibited a 1.43-fold improvement in half-life at 95 ℃, compared with that of the WT. This study, by combining computational simulation with experimental verification, establishes that potential sites can be computationally predicted to increase the activity and stability of BLA and thus provide a possible strategy by which to guide protein design.

Electrokinetic properties of NaCl solution via molecular dynamics simulations with scaled-charge electrolytes

Scaling ionic charges has become an alternative to polarizable force fields for representing indirect charge transfer effects in molecular simulations. In our work, we apply molecular dynamics simulations to investigate the properties of NaCl aqueous solutions in homogeneous and confined media. We compare classical integer- and scaled-charge force fields for the ions. In the bulk, we validate the force fields by computing equilibrium and transport properties and comparing them with experimental data. Integer-charge ions overestimate dielectric saturation and ionic association. Both force fields present an excess in ion-ion correlation, which leads to a deviation in the ionic conductivity at higher ionic strengths. Negatively charged quartz is used to simulate the confinement effect. Electrostatic interactions dominate counter-ion adsorption. Full-charge ions have stronger and more defined adsorption planes. We obtain the electroosmotic mobility of the solution by combining the shear plane location from non-equilibrium simulations with the ionic distribution from equilibrium simulations. From the Helmholtz-Smoluchowski equation, the zeta potential and the streaming potential coupling coefficient are computed. From an atomic-scale perspective, our molecular dynamics simulations corroborate the hypothesis of maximum packing of the Stern layer, which results in a stable and non-zero zeta potential at high salinity. The scaled-charge model representation of both properties is in excellent qualitative and quantitative agreement with experimental data. With our work, we demonstrate how useful and precise simple scaled-charge models for electrolytes can be to represent complex systems, such as the electrical double layer.

Accelerating QM/MM simulations of electrochemical interfaces through machine learning of electronic charge densities

A crucial aspect in the simulation of electrochemical interfaces consists in treating the distribution of electronic charge of electrode materials that are put in contact with an electrolyte solution. Recently, it has been shown how a machine-learning method that specifically targets the electronic charge density, also known as SALTED, can be used to predict the long-range response of metal electrodes in model electrochemical cells. In this work, we provide a full integration of SALTED with MetalWalls, a program for performing classical simulations of electrochemical systems. We do so by deriving a spherical harmonics extension of the Ewald summation method, which allows us to efficiently compute the electric field originated by the predicted electrode charge distribution. We show how to use this method to drive the molecular dynamics of an aqueous electrolyte solution under the quantum electric field of a gold electrode, which is matched to the accuracy of density-functional theory. Notably, we find that the resulting atomic forces present a small error of the order of 1 meV/Å, demonstrating the great effectiveness of adopting an electron-density path in predicting the electrostatics of the system. Upon running the data-driven dynamics over about 3 ns, we observe qualitative differences in the interfacial distribution of the electrolyte with respect to the results of a classical simulation. By greatly accelerating quantum-mechanics/molecular-mechanics approaches applied to electrochemical systems, our method opens the door to nanosecond timescales in the accurate atomistic description of the electrical double layer.

Revealing innovative JAK1 and JAK3 inhibitors: a comprehensive study utilizing QSAR, 3D-Pharmacophore screening, molecular docking, molecular dynamics, and MM/GBSA analyses

The heterocycle compounds, with their diverse functionalities, are particularly effective in inhibiting Janus kinases (JAKs). Therefore, it is crucial to identify the correlation between their complex structures and biological activities for the development of new drugs for the treatment of rheumatoid arthritis (RA) and cancer. In this study, a diverse set of 28 heterocyclic compounds selective for JAK1 and JAK3 was employed to construct quantitative structure-activity relationship (QSAR) models using multiple linear regression (MLR). Artificial neural network (ANN) models were employed in the development of QSAR models. The robustness and stability of the models were assessed through internal and external methodologies, including the domain of applicability (DoA). The molecular descriptors incorporated into the model exhibited a satisfactory correlation with the receptor-ligand complex structures of JAKs observed in X-ray crystallography, making the model interpretable and predictive. Furthermore, pharmacophore models ADRRR and ADHRR were designed for each JAK1 and JAK3, proving effective in discriminating between active compounds and decoys. Both models demonstrated good performance in identifying new compounds, with an ROC of 0.83 for the ADRRR model and an ROC of 0.75 for the ADHRR model. Using a pharmacophore model, the most promising compounds were selected based on their strong affinity compared to the most active compounds in the studied series each JAK1 and JAK3. Notably, the pharmacokinetic, physicochemical properties, and biological activities of the selected compounds (As compounds ZINC79189223 and ZINC66252348) were found to be consistent with their therapeutic effects in RA, owing to their non-toxic, cholinergic nature, absence of P-glycoprotein, high gastrointestinal absorption, and ability to penetrate the blood-brain barrier. Furthermore, ADMET properties were assessed, and molecular dynamics and MM/GBSA analysis revealed stability in these molecules.

Madrid-2019 force field: An extension to divalent cations Sr2+ and Ba2

In this work, we present a parameterization of Sr2+ and Ba2+ cations, which expands the alkali earth set of cations of the Madrid-2019 force field. We have tested the model against the experimental densities of eight different salts, namely, SrCl2, SrBr2, SrI2, Sr(NO3)2, BaCl2, BaBr2, BaI2, and Ba(NO3)2. The force field is able to reproduce the experimental densities of all these salts up to their solubility limit. Furthermore, we have computed the viscosities for two selected salts, finding that the experimental values are overestimated, but the predictions are still reasonable. Finally, the structural properties for all the salts have been calculated with this model and align remarkably well with experimental observations.

Exploring the Unusual Reactivity of the Hydrated Electron with CO2

Many questions remain about the reactions of the hydrated electron despite decades of study. Of particular note is that they do not appear to follow the Marcus theory of electron transfer reactions, a feature that is yet to be explained. To investigate these issues, we used ab initio molecular dynamics (AIMD) simulations to investigate one of the better studied reactions, the hydrated electron reduction of CO2. The rate constant for the hydrated electron-CO2 reaction complex to react to form CO2- is for the first time estimated from AIMD simulations. Results at 298 and 373 K show the rate constant is insensitive to temperature, consistent with the low measured activation energy for the reaction, and the implications of this behavior are examined. The sampling provided by the simulations yields insight into the reaction mechanism. The reaction is found to involve both solvent reorganization and changes in the carbon dioxide structure. The latter leads to significant vibrational excitation of the bending and symmetric stretch vibrations in the CO2- product, indicating the reaction is vibrationally nonadiabatic. The former is estimated from the calculation of an approximate collective solvent coordinate and the free energy in this coordinate is determined. These results indicate that AIMD simulations can reasonably estimate hydrated electron reaction activation energies and provide new insight into the mechanism that can help illuminate the features of this unusual chemistry.

Identification of active compounds as novel dipeptidyl peptidase-4 inhibitors through machine learning and structure-based molecular docking simulations

The enzyme dipeptidyl peptidase 4 (DPP4) is a potential therapeutic target for type 2 diabetes (T2DM). Many synthetic anti-DPP4 medications are available to treat T2DM. The need for secure and efficient medicines has been unmet due to the adverse side effects of existing DPP4 medications. The present study implemented a combined approach to machine learning and structure-based virtual screening to identify DPP4 inhibitors. Two ML models were trained based on DPP4 IC50 datasets. The ML models random forest (RF) and multilayer perceptron (MLP) neural network showed good accuracy, with the area under the curve being 0.93 and 0.91, respectively. The natural compound library was screened through ML models, and 1% (217) of compounds were selected for further screening. Structure-based virtual screening was performed along with positive control sitagliptin to obtain more specific and selective leads for DPP4. Based on binding affinity, drug-likeness properties, and interaction with DPP4, Z-614 and Z-997 compounds showed high binding affinity and specificity in the catalytic pocket of DPP4. Finally, the stability conformation of the DPP4 enzyme complex was checked by a molecular dynamics (MD) simulation. The MD simulation showed that both compounds bind better in the catalytic pocket, but the Z-614 compound altered the DPP4 native conformation. Therefore, Z-614 showed a high deviation in the backbone. This combined approach (ML and structure-based) study reported that Z-997 binds most stably to DPP4 in their catalytic pocket with a binding free energy of -70.3 kJ/mol, suggesting its therapeutic potential as a treatment option for T2DM disease.Communicated by Ramaswamy H. Sarma.

Targeting Cathepsin L in Cancer Management: Leveraging Machine Learning, Structure-Based Virtual Screening, and Molecular Dynamics Studies

Cathepsin L (CTSL) expression is dysregulated in a variety of cancers. Extensive empirical evidence indicates their direct participation in cancer growth, angiogenic processes, metastatic dissemination, and the development of treatment resistance. Currently, no natural CTSL inhibitors are approved for clinical use. Consequently, the development of novel CTSL inhibition strategies is an urgent necessity. In this study, a combined machine learning (ML) and structure-based virtual screening strategy was employed to identify potential natural CTSL inhibitors. The random forest ML model was trained on IC50 values. The accuracy of the trained model was over 90%. Furthermore, we used this ML model to screen the Biopurify and Targetmol natural compound libraries, yielding 149 hits with prediction scores >0.6. These hits were subsequently selected for virtual screening using a structure-based approach, yielding 13 hits with higher binding affinity compared to the positive control (AZ12878478). Two of these hits, ZINC4097985 and ZINC4098355, have been shown to strongly bind CTSL proteins. In addition to drug-like properties, both compounds demonstrated high affinity, ligand efficiency, and specificity for the CTSL binding pocket. Furthermore, in molecular dynamics simulations spanning 200 ns, these compounds formed stable protein-ligand complexes. ZINC4097985 and ZINC4098355 can be considered promising candidates for CTSL inhibition after experimental validation, with the potential to provide therapeutic benefits in cancer management.

Scaling Solute-Solvent Distances to Improve Solubility and Ion Paring Predictions in Rigid Ion Models

Force fields based on the rigid ion model (RIM) have been developed to accurately predict the various physical and chemical properties of salts and water. However, the combined use of these models often fails to accurately predict the solubility of salts in water. To address this issue, several approaches, such as charge scaling or reparameterization, have been proposed. Nevertheless, these methods require laborious reparameterization of nonbonded force field parameters. In this article, we propose a scaling solute-solvent distance (SSSD) method to improve force fields in predicting salt solubility without changing the solute-solute and solvent-solvent interactions in the original force fields. This method can also tune the ion pairing of salt in water. One main advantage of the SSSD method is that reparameterization of the crystal and water models is not needed. We use two RIMs for the NaCl-water system (JC-SPC/E and SD-SPC/E) and the CHARMM force field for the KCl-water system to demonstrate the improved accuracy in predicting solubility by the SSSD method. Furthermore, we use the RDG-SPC/Fw force field to show that the SSSD method can also be used to tune the ion pairing of CaCO3 in water. Limitations of this method are also discussed.

Chemical scanning of atomic oxygen at the gas-liquid interface of a NaCl solution via quantum mechanics/molecular mechanics molecular dynamics simulations

Atmospheric pressure plasmas can serve as double phase reactors to produce plasma activated water for water treatment. However, the physical-chemical processes involving plasma-supplied atomic oxygen and reactive oxygen species in an aqueous solution remain unclear. In this work, quantum mechanics (QM)/molecular mechanics (MM) molecular dynamics simulations (MDs) have been performed to directly observe the chemical reactions occurring between atomic oxygen and a NaCl solution at the gas-liquid interface using a model containing 10,800 atoms. During simulations, the atoms in the QM and MM Parts are dynamically adjusted. To examine the effects of local microenvironments on the chemical processes, atomic oxygen is used as a chemical probe to scan the gas-liquid interface. The excited atomic oxygen reacts with water molecules and Cl- ions to produce H2O2, OH, HOCl, ClO-, and HO2-/H3O+ species. The ground-state atomic oxygen is significantly more stable than the excited atomic oxygen, although it can react with water molecules to produce OH radicals. However, the branch ratio of ClO- computed for triplet atomic oxygen is significantly larger than that determined for singlet atomic oxygen. This study can help achieve a better understanding of the fundamental chemical processes during plasma-treated solution experiments and promotes advances in applications of QM/MM calculations at the gas-liquid interface.

Computation of Electrical Conductivities of Aqueous Electrolyte Solutions: Two Surfaces, One Property

In this work, we computed electrical conductivities under ambient conditions of aqueous NaCl and KCl solutions by using the Einstein-Helfand equation. Common force fields (charge q = ±1 e) do not reproduce the experimental values of electrical conductivities, viscosities, and diffusion coefficients. Recently, we proposed the idea of using different charges to describe the potential energy surface (PES) and the dipole moment surface (DMS). In this work, we implement this concept. The equilibrium trajectories required to evaluate electrical conductivities (within linear response theory) were obtained by using scaled charges (with the value q = ±0.75 e) to describe the PES. The potential parameters were those of the Madrid-Transport force field, which accurately describe viscosities and diffusion coefficients of these ionic solutions. However, integer charges were used to compute the conductivities (thus describing the DMS). The basic idea is that although the scaled charge describes the ion-water interaction better, the integer charge reflects the value of the charge that is transported due to the electric field. The agreement obtained with experiments is excellent, as for the first time electrical conductivities (and the other transport properties) of NaCl and KCl electrolyte solutions are described with high accuracy for the whole concentration range up to their solubility limit. Finally, we propose an easy way to obtain a rough estimate of the actual electrical conductivity of the potential model under consideration using the approximate Nernst-Einstein equation, which neglects correlations between different ions.

Self-Consistent Implementation of a Solvation Free Energy Framework to Predict the Salt Solubilities of Six Alkali Halides

To assess the salt solubilities of six alkali halides in aqueous systems, we proposed a thermodynamic cycle and an efficient molecular modeling methodology. The Gibbs free energy changes for vaporization, dissociation, and dissolution were calculated using the experimental data of ionic thermodynamic properties obtained from the NBS tables. Additionally, the Marcus' and Tissandier's solvation free energy data for Li+, Na+, K+, Cl-, and Br- ions were compared with the conventional solvation free energies by substituting into our self-consistent thermodynamic cycle. Furthermore, Tissandier's absolute solvation free energy data were used as the training set to refit the Lennard-Jones parameters of OPLS-AA force field for ions. To predict salt solubilities, an assumption of a pseudo-solvent was proposed to characterize the coupling work of a solute with its environment from infinitely diluted to saturated solutions, indicating that the Gibbs energy change of solvation process is a function of ionic strength. Following the self-consistency of the cycle, the newly derived formulas were used to determine the salt solubilities by interpolating the intersection of Gibbs free energy of dissolution and the zero free energy line. The refined ion parameters can also predict the structure and thermodynamic properties of aqueous electrolyte solutions, such as densities, pair correlation functions, hydration numbers, mean activity coefficients, vapor pressures, and the radial dependences of the net charge at 298.15 K and 1 bar. Our method can be used to characterize the solid-liquid equilibria of ions or charged particles in aqueous systems. Furthermore, for highly concentrated strong electrolyte systems, it is essential to introduce accurate water models and polarizable force fields.

Ions Speciation at the Water-Air Interface

In typical aqueous systems, including naturally occurring sweet and salt water and tap water, multiple ion species are co-solvated. At the water-air interface, these ions are known to affect the chemical reactivity, aerosol formation, climate, and water odor. Yet, the composition of ions at the water interface has remained enigmatic. Here, using surface-specific heterodyne-detected sum-frequency generation spectroscopy, we quantify the relative surface activity of two co-solvated ions in solution. We find that more hydrophobic ions are speciated to the interface due to the hydrophilic ions. Quantitative analysis shows that the interfacial hydrophobic ion population increases with decreasing interfacial hydrophilic ion population at the interface. Simulations show that the solvation energy difference between the ions and the intrinsic surface propensity of ions determine the extent of an ion's speciation by other ions. This mechanism provides a unified view of the speciation of monatomic and polyatomic ions at electrolyte solution interfaces.

Scaled charges for ions: An improvement but not the final word for modeling electrolytes in water

In this work, we discuss the use of scaled charges when developing force fields for NaCl in water. We shall develop force fields for Na⁺ and Cl^- using the following values for the scaled charge (in electron units): ±0.75, ±0.80, ±0.85, and ±0.92 along with the TIP4P/2005 model of water (for which previous force fields were proposed for q = ±0.85 and q = ±1). The properties considered in this work are densities, structural properties, transport properties, surface tension, freezing point depression, and maximum in density. All the developed models were able to describe quite well the experimental values of the densities. Structural properties were well described by models with charges equal to or larger than ±0.85, surface tension by the charge ±0.92, maximum in density by the charge ±0.85, and transport properties by the charge ±0.75. The use of a scaled charge of ±0.75 is able to reproduce with high accuracy the viscosities and diffusion coefficients of NaCl solutions for the first time. We have also considered the case of KCl in water, and the results obtained were fully consistent with those of NaCl. There is no value of the scaled charge able to reproduce all the properties considered in this work. Although certainly scaled charges are not the final word in the development of force fields for electrolytes in water, its use may have some practical advantages. Certain values of the scaled charge could be the best option when the interest is to describe certain experimental properties.

Molecular Dynamics Investigation of Giant Clustering in Small-Molecule Solutions: The Case of Aqueous PEHA

The importance of the formation of giant clusters in solution, in nature and industry, is increasingly recognized. However, relatively little attention has been paid to the formation of giant clusters in solutions of small, relatively soluble but nonamphiphilic molecules. In this work, we present a general methodology based on molecular dynamics that can be used to investigate such systems. As a case study, we focus on the formation of apparently stable clusters of pentaethylenehexamine (PEHA) in water. These clusters have been used as templates for the construction of bioinspired silica nanoparticles. To better understand clustering in this system, we study the effect of PEHA protonation state (neutral, +1, and +2) and counterion type (chloride or acetate) on PEHA clustering in dilute aqueous solutions (200 and 400 mM) using large-scale classical molecular dynamics. We find that large stable clusters are formed by singly charged PEHA with chloride or acetate as the counterion, although it is not clear for the case with acetate whether bulk phase separation, that might lead to precipitation, would eventually occur. Large clusters also appear to be stable for doubly charged PEHA with acetate, the less soluble counterion. We attribute this behavior to a form of complex coacervation, observed here for relatively small and highly soluble molecules (PEHA + counterion) rather than the large polyions usually found to form such coacervates. We discuss whether this behavior might also be described by an effective SALR (short-range attraction, long-range repulsion) interaction. This work might help future studies of additives for the design of novel bioinspired templated nanomaterials and of giant clustering in small-molecule solutions more generally.

Molecular dynamics study of the interactions between a hydrophilic polymer brush on graphene and amino acid side chain analogues in water

We perform all-atom molecular dynamics simulations of poly(2-hydroxyethyl methacrylate) (PHEMA) brushes in aqueous solutions of isobutane, propionamide, and sodium propionate. These solutes are side chain analogues to leucine, glutamine, and glutamic acid, respectively. We compute the Gibbs energy profile of the solute's adsorption to the polymer brush and decompose it into the contributions from the steric repulsion, van der Waals interaction, and Coulomb interaction to reveal the energetic origin of repulsion or attraction of the solute by the polymer brush. The Henry adsorption constant is the amount of adsorption normalized by the concentration in aqueous solution. We examine the dependence of this quantity on the grafting density and chain length. Our results suggest that the concurrent primary and ternary adsorption mechanism may be more important than previously expected when the solute is hydrophobic.

Nonpolarizable Force Fields through the Self-Consistent Modeling Scheme with MD and DFT Methods: From Ionic Liquids to Self-Assembled Ionic Liquid Crystals

A key to achieve the accuracy of molecular dynamics (MD) simulation is the set of force fields used to express the atomistic interactions. In particular, the electrostatic interaction remains the main issue for the precise simulation of various ionic soft materials from ionic liquids to their supramolecular compounds. In this study, we test the nonpolarizable force fields of ionic liquids (ILs) and self-assembled ionic liquid crystals (ILCs) for which the intermolecular charge transfer and intramolecular polarization are significant. The self-consistent modeling scheme is adopted to refine the atomic charges of ionic species in a condensed state through the use of density functional theory (DFT) under the periodic boundary condition. The atomic charges of the generalized amber force field (GAFF) are effectively updated to express the electrostatic properties of ionic molecules obtained by the DFT calculation in condensed phase, which improves the prediction accuracy of ionic conductivity with the obtained force field (GAFF-DFT). The derived DFT charges then suggest that the substitution of a hydrophobic liquid-crystalline moiety into IL-based cations enhances the charge localization of ionic groups in the amphiphilic molecules, leading to the amplification of the electrostatic interactions among the hydrophilic/ionic groups in the presence of hydrophobic moieties. In addition, we focus on an ion-conductive pathway hidden in the self-assembled nanostructure. The MD results indicate that the ionic groups of cation and anion interact strongly for keeping the bicontinuous nanosegregation of ionic nanochannel. The partial fractions of hydrophilic/ionic and hydrophobic nanodomains are then quantified with the volume difference from referenced IL systems, while the calculated ionic conductivity decreases in the self-assembled ILCs more than the occupied volume of ionic nanodomains. These analyses suggest that the mobility of ions in the self-assembled ILCs remains quite restricted even with small tetrafluoroborate anions because of strong attractive interaction among ionic moieties.

Where Lennard-Jones Potentials Fail: Iterative Optimization of Ion-Water Pair Potentials Based on Ab Initio Molecular Dynamics Data

The use of the Lennard-Jones (LJ) potential in computer simulations of aqueous electrolyte solutions is widespread. The standard approach is to parametrize LJ potential parameters against thermodynamic solution properties, but problems in representing the local structural and dynamic properties of ion hydration shells remain. The r^-12-term in the LJ potential is responsible for this as it leads to overly repulsive ion-water interactions at short range. As a result, the LJ potential predicts blue-shifted vibrational peaks of the cations' rattling mode and too large negative ion hydration entropies. We demonstrate that cation-water effective pair potentials derived from ab initio MD data have softer short-range repulsions and represent hydration shell properties significantly better. Our findings indicate that replacing the LJ potential with these effective pair potentials offers a promising route to represent thermodynamic solution properties and local interactions of specific ions with nonpolarizable force field models.

Maximum in density of electrolyte solutions: Learning about ion-water interactions and testing the Madrid-2019 force field

In this work, we studied the effect of Li⁺, Na⁺, K⁺, Mg²⁺, and Ca²⁺ chlorides and sulfates on the temperature of maximum density (TMD) of aqueous solutions at room pressure. Experiments at 1 molal salt concentration were carried out to determine the TMD of these solutions. We also performed molecular dynamics simulations to estimate the TMD at 1 and 2 m with the Madrid-2019 force field, which uses the TIP4P/2005 water model and scaled charges for the ions, finding an excellent agreement between experiment and simulation. All the salts studied in this work shift the TMD of the solution to lower temperatures and flatten the density vs temperature curves (when compared to pure water) with increasing salt concentration. The shift in the TMD depends strongly on the nature of the electrolyte. In order to explore this dependence, we have evaluated the contribution of each ion to the shift in the TMD concluding that Na⁺, Ca²⁺, and SO₄ ^2- seem to induce the largest changes among the studied ions. The volume of the system has been analyzed for salts with the same anion and different cations. These curves provide insight into the effect of different ions upon the structure of water. We claim that the TMD of electrolyte solutions entails interesting physics regarding ion-water and water-water interactions and should, therefore, be considered as a test property when developing force fields for electrolytes. This matter has been rather unnoticed for almost a century now and we believe it is time to revisit it.

Freezing point depression of salt aqueous solutions using the Madrid-2019 model

Salt aqueous solutions are relevant in many fields, ranging from biological systems to seawater. Thus, the availability of a force-field that is able to reproduce the thermodynamic and dynamic behavior of salt aqueous solutions would be of great interest. Unfortunately, this has been proven challenging, and most of the existing force-fields fail to reproduce much of their behavior. In particular, the diffusion of water or the salt solubility are often not well reproduced by most of the existing force-fields. Recently, the Madrid-2019 model was proposed, and it was shown that this force-field, which uses the TIP4P/2005 model for water and non-integer charges for the ions, provides a good description of a large number of properties, including the solution densities, viscosities, and the diffusion of water. In this work, we assess the performance of this force-field on the evaluation of the freezing point depression. Although the freezing point depression is a colligative property that at low salt concentrations depends solely on properties of pure water, a good model for the electrolytes is needed to accurately predict the freezing point depression at moderate and high salt concentrations. The coexistence line between ice and several salt aqueous solutions (NaCl, KCl, LiCl, MgCl₂, and Li₂SO₄) up to the eutectic point is estimated from direct coexistence molecular dynamics simulations. Our results show that this force-field reproduces fairly well the experimentally measured freezing point depression with respect to pure water freezing for all the salts and at all the compositions considered.

Structure and dynamics of aqueous NaCl solutions at high temperatures and pressures

The structure of a concentrated solution of NaCl in D₂O was investigated by in situ high-pressure neutron diffraction with chlorine isotope substitution to give site-specific information on the coordination environment of the chloride ion. A broad range of densities was explored by first increasing the temperature from 323 to 423 K at 0.1 kbar and then increasing the pressure from 0.1 to 33.8 kbar at 423 K, thus mapping a cyclic variation in the static dielectric constant of the pure solvent. The experimental work was complemented by molecular dynamics simulations using the TIP4P/2005 model for water, which were validated against the measured equation of state and diffraction results. Pressure-induced anion ordering is observed, which is accompanied by a dramatic increase in the Cl-O and O-O coordination numbers. With the aid of bond-distance resolved bond-angle maps, it is found that the increased coordination numbers do not originate from a sizable alteration to the number of either Cl⋯D-O or O⋯D-O hydrogen bonds but from the appearance of non-hydrogen-bonded configurations. Increased pressure leads to a marked decrease in the self-diffusion coefficients but has only a moderate effect on the ion-water residence times. Contact ion pairs are observed under all conditions, mostly in the form of charge-neutral NaCl⁰ units, and coexist with solvent-separated Na⁺-Na⁺ and Cl^--Cl^- ion pairs. The exchange of water molecules with Na⁺ adopts a concerted mechanism under ambient conditions but becomes non-concerted as the state conditions are changed. Our findings are important for understanding the role of extreme conditions in geochemical processes.

Influence of Monovalent Salts on α-Glycine Crystal Growth from Aqueous Solution: Molecular Dynamics Simulations at Constant Supersaturation Conditions

The growth of α-glycine crystals from aqueous solution is investigated at constant supersaturations by utilizing the constant chemical potential molecular dynamics method. The study considers two faces (010) and (011) that predominantly determine the α-glycine crystal morphology. The general Amber force field (GAFF) with two different charge sets derived from semi-empirical calculations using the complete neglect of differential overlap method (CNDO) and from density functional calculations using the double-numerical plus d- and p-polarization basis set (DNP) is applied to describe α-glycine. The extended simple point charge model is used to simulate water. It is observed that the GAFF/DNP set leads to a much slower integration of glycine molecules into the crystal structure than the GAFF/CNDO set. The GAFF/CNDO set, however, causes the growth even at concentrations well below the experimental solubility. For the GAFF/DNP set, the influence of potassium chloride (KCl) and sodium chloride (NaCl) on the face growth rates is investigated. The parameters recently proposed by Yagasaki et al. [J. Chem. Theory Comput. 2020, 16, 2460-2473] are used to describe salt ions, as standard GAFF parameters lead to the unexpected formation of salt clusters at a concentration lower than the experimental solubility value. According to our simulation results, both salts suppress the growth of the (011) and (010) faces. The inhibiting effect of NaCl is much stronger than that of KCl for the (011) face, while both salts have a similar inhibiting effect on the (010) face. The results are in line with the experimental observations of the impact of salt ions on the α-glycine growth rates for the (011) face reported in literature.

Interrogation of Bacillus anthracis SrtA active site loop forming open/close lid conformations through extensive MD simulations for understanding binding selectivity of SrtA inhibitors

Bacillus anthracis is a gram positive, deadly spore forming bacteria causing anthrax and these bacteria having the complex mechanism in the cell wall envelope, which can adopt the changes in environmental conditions. In this, the membrane bound cell wall proteins are said to progressive drug target for the inhibition of Bacillus anthracis. Among the cell wall proteins, the SrtA is one of the important mechanistic protein, which mediate the ligation with LPXTG motif by forming the amide bonds. The SrtA plays the vital role in cell signalling, cell wall formation, and biofilm formations. Inhibition of SrtA leads to rupture of the cell wall and biofilm formation, and that leads to inhibition of Bacillus anthracis and thus, SrtA is core important enzyme to study the inhibition mechanism. In this study, we have examined 28 compounds, which have the inhibitory activity against the Bacillus anthracis SrtA for developing the 3D-QSAR and also, compounds binding selectivity with both open and closed SrtA conformations, obtained from 100 ns of MD simulations. The binding site loop deviate in forming the open and closed gate mechanism is investigated to understand the inhibitory profile of reported compounds, and results show the closed state active site conformations are required for ligand binding specificity. Overall, the present study may offer an opportunity for better understanding of the mechanism of action and can be aided to further designing of a novel and highly potent SrtA inhibitors.

NaCl aggregation in water at elevated temperatures and pressures: Comparison of classical force fields

The properties of water vary dramatically with temperature and density. This can be exploited to control its effectiveness as a solvent. Thus, supercritical water is of keen interest as solvent in many extraction processes. The low solubility of salts in lower density supercritical water has even been suggested as a means of desalination. The high temperatures and pressures required to reach supercritical conditions can present experimental challenges during collection of required physical property and phase equilibria data, especially in salt-containing systems. Molecular simulations have the potential to be a valuable tool for examining the behavior of solvated ions at these high temperatures and pressures. However, the accuracy of classical force fields under these conditions is unclear. We have, therefore, undertaken a parametric study of NaCl in water, comparing several salt and water models at 200 bar-600 bar and 450 K-750 K for a range of salt concentrations. We report a comparison of structural properties including ion aggregation, hydrogen bonding, density, and static dielectric constants. All of the force fields qualitatively reproduce the trends in the liquid phase density. An increase in ion aggregation with decreasing density holds true for all of the force fields. The propensity to aggregate is primarily determined by the salt force field rather than the water force field. This coincides with a decrease in the water static dielectric constant and reduced charge screening. While a decrease in the static dielectric constant with increasing NaCl concentration is consistent across all model combinations, the salt force fields that exhibit more ionic aggregation yield a slightly smaller dielectric decrement.

Theory of electrolytes including steric, attractive, and hydration interactions

We present a continuum theory of electrolytes composed of a waterlike solvent and univalent ions. First, we start with a density functional F for the coarse-grained solvent, cation, and anion densities, including the Debye-Hückel free energy, the Coulombic interaction, and the direct interactions among these three components. These densities fluctuate obeying the distribution ∝exp(-F/k_BT). Eliminating the solvent density deviation in F, we obtain the effective non-Coulombic interactions among the ions, which consist of the direct ones and the solvent-mediated ones. We then derive general expressions for the ion correlation, the apparent partial volume, and the activity and osmotic coefficients up to linear order in the average salt density n_s. Second, we perform numerical analysis using the Mansoori-Carnahan-Starling-Leland model [J. Chem. Phys. 54, 1523 (1971)] for three-component hardspheres. The effective interactions sensitively depend on the cation and anion sizes due to competition between the steric and hydration effects, which are repulsive between small-large ion pairs and attractive between symmetric pairs. These agree with previous experiments and Collins' rule [Biophys. J. 72, 65 (1997)]. We also give simple approximate expressions for the ionic interaction coefficients valid for any ion sizes.