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The presence of antibiotics in soils is increasing drastically in last decades due to the intensive farming industry and excessive human consumption. Clay minerals are one of the soil components with great adsorption capacity for organic pollutants. The study of interactions between antibiotics and mineral surfaces will give us scientific knowledge of these pollutants through soils. In this work, we study the adsorption of the antibiotic ciprofloxacin in the clay mineral fraction of soils from the Argentinian zone of Santa Rosa (Corrientes), in a collaborative research of experiments and atomistic modelling calculations of the intercalation of ciprofloxacin in the interlayer space of montmorillonite. Adsorption and desorption isotherms were performed and compared with different isotherm models. Additionally, enthalpy, entropy, and free energy were determined from equilibrium constants at a function of temperature. All these experiments and calculations lead to the conclusions that two adsorption types of ciprofloxacin are found on clay minerals: one weakly sorbed that is released during the desorption experiments, and other one strongly joined that remains in the soil. [ABSTRACT FROM AUTHOR]

The heat transfer and oxygen transport behaviors of Ti-6Al and Fe-12Cr alloys directly affect their aeronautical material application. In order to investigate the flame retardant mechanism in atomic scale, molecular dynamic (MD) simulations were performed to study the heat transfer and oxygen transport performances of Ti-6Al and Fe-12Cr alloys in the linear and uniform heating treatment. Next, the ignition performances of Ti-6Al and Fe-12Cr alloys were further verified by the frictional ignition tests. Therefore, this is a multi-scale research with a novel combination of MD simulations and ignition tests. Those obtained results show that the heat is more concentrated at the heating edge of Ti-6Al alloy while at the same heating rate. This leads to the intensification of atomic motion at the heating edge, and reduces the structural thermal stability of Ti-6Al alloy's heating edge. Therefore, the heat transfer performance of Fe-12Cr alloy at the same state is better than that of Ti-6Al alloy. When there is an oxide layer on the surface of these two alloys, Fe-12Cr alloy can inhibit the oxygen transfer more effectively than Ti-6Al alloy, and further improve its flame retardant property. In addition, the frictional ignition tests with Ti alloy rotor under the same airflow environment show that the critical airflow velocity of the Fe-12Cr alloy stator is about 114 m/s higher than that of Ti-6Al-4V alloy stator at 384∘. Generally, according to MD simulations and frictional ignition tests, it could be concluded that the flame retardancy of Fe-12Cr alloy is higher than Ti-6Al alloy. [ABSTRACT FROM AUTHOR]

Machine learning potentials, particularly the deep potential (DP) model, have revolutionized molecular dynamics (MD) simulations, striking a balance between accuracy and computational efficiency. To facilitate the DP model's integration with the popular MD engine OpenMM, we have developed a versatile OpenMM plugin. This plugin supports a range of applications, from conventional MD simulations to alchemical free energy calculations and hybrid DP/MM simulations. Our extensive validation tests encompassed energy conservation in microcanonical ensemble simulations, fidelity in canonical ensemble generation, and the evaluation of the structural, transport, and thermodynamic properties of bulk water. The introduction of this plugin is expected to significantly expand the application scope of DP models within the MD simulation community, representing a major advancement in the field. [ABSTRACT FROM AUTHOR]

Context: Ryanodine receptors (RyRs) are large intracellular ligand-gated calcium release ion channels. Mutations in human RyR1 in combination with a volatile anesthetic or muscle relaxant are known to cause leaky RyRs resulting in malignant hyperthermia (MH). This has long been primarily treated with the RyR inhibitory drug dantrolene. Alternatives to dantrolene as a RyR inhibitor may be found through computer-aided drug design. Additionally, molecular dynamics (MD) studies of dantrolene interacting with RyRs may reveal its full mechanism of action. The availability of accurate force field parameters is important for the success of both. Methods: In this study, force field parameters for dantrolene were obtained from the CHARMM General Force Field (CGenFF) program and optimized using the force field toolkit (FFTK) and FFParam programs. The obtained parameters were then validated by a comparison between calculated and experimental IR spectra and normal mode analysis, among other techniques. [ABSTRACT FROM AUTHOR]

The present study investigates the interaction between two alkylating agent drugs, cyclophosphamide (CP) and mechlorethamine (MC), with Single-Wall carbon nanotubes (SWCNTs) and Boron Nitride nanotubes (BNNTs). Calculations have been performed by using methods of quantum mechanics and molecular mechanics. The effects of different solvents on the interaction of CP and MC with SWCNTs and BNNTs within the Onsager self-consistent reaction field (SCRF) model, as well as the effects of temperature on the stability of the interactions between the compounds in various solvents have been investigated. Thermodynamic parameters, Frontier Molecular Orbitals (FMOs), and Total Density of States (DOS) of the title compounds have been evaluated by using theoretical calculations. Moreover, the interaction of CP and MC with SWCNTs and BNNTs have been examined through AMBER, OPLS, CHARMM, and MM+ force fields through the molecular mechanic (MM) method. The Monte Carlo simulation of CP and MC structures connected to carbon and boron nitride nanotubes in Water, Methanol, Ethanol, DMSO, and Chloroform solvents showed that Chloroform is the most stable solvent for simulation with the lowest energy, which is directly attributed to dielectric constant. Studies show that the results of Monte Carlo, molecular mechanics, and quantum mechanics are consistent with each other in terms of thermodynamic properties and conformer populations. [ABSTRACT FROM AUTHOR]

Electron paramagnetic resonance (EPR) has become a powerful probe of conformational heterogeneity and dynamics of biomolecules. In this Review, we discuss different computational modeling techniques that enrich the interpretation of EPR measurements of dynamics or distance restraints. A variety of spin labels are surveyed to provide a background for the discussion of modeling tools. Molecular dynamics (MD) simulations of models containing spin labels provide dynamical properties of biomolecules and their labels. These simulations can be used to predict EPR spectra, sample stable conformations and sample rotameric preferences of label sidechains. For molecular motions longer than milliseconds, enhanced sampling strategies and de novo prediction software incorporating or validated by EPR measurements are able to efficiently refine or predict protein conformations, respectively. To sample large‐amplitude conformational transition, a coarse‐grained or an atomistic weighted ensemble (WE) strategy can be guided with EPR insights. Looking forward, we anticipate an integrative strategy for efficient sampling of alternate conformations by de novo predictions, followed by validations by systematic EPR measurements and MD simulations. Continuous pathways between alternate states can be further sampled by WE‐MD including all intermediate states. [ABSTRACT FROM AUTHOR]

Crystallization of alkaline earth metal carbonates from water is important for biomineralization and environmental geochemistry. Here, large-scale computer simulations are a useful approach to complement experimental studies by providing atomistic insights and even by quantitatively determining the thermodynamics of individual steps. However, this is dependent on the existence of force field models that are sufficiently accurate while being computationally efficient enough to sample complex systems. Here, we introduce a revised force field for aqueous alkaline earth metal carbonates that reproduces both the solubilities of the crystalline anhydrous minerals, as well as the hydration free energies of the ions. The model is also designed to run efficiently on graphical processing units thereby reducing the cost of such simulations. The performance of the revised force field is compared against previous results for important properties relevant to crystallization, including ion-pairing and mineral–water interfacial structure and dynamics. This article is part of a discussion meeting issue 'Supercomputing simulations of advanced materials'. [ABSTRACT FROM AUTHOR]

Thermal conductivities of polybutadiene crosslinked with sulfur as a function of the heat flux autocorrelation function by using an equilibrium molecular dynamic (EMD) simulation were investigated. The Green–Kubo method was used to calculate thermal conductivities. All simulations were performed by applying the LAMMPS software (version 3 Mar 2020) package. The united-atom force field (OPLS-UA) from the Moltemplate software (version 2.20.3) was applied in the simulations. The influence of uniform and random distributions of sulfur in polybutadiene on the final value of thermal conductivities was studied by polymeric model structures with similar and variable degrees of crosslinking. The results showed that for identical degrees of crosslinking, the distribution of crosslinkers in the polymeric model structures significantly influenced the final value of thermal conductivity. Moreover, the influence of the crosslinking degree on the final value of thermal conductivity was studied by considering polymeric model structures with different degrees of crosslinking. The results demonstrate that by having a random distribution of sulfur, the thermal conductivity will be enhanced. However, by increasing the degree of crosslinking to the higher percentage in random crosslinked model structures, the value of thermal conductivity drops significantly due to possible higher crystallization of the model structures, which decrease the degree of freedom for phonon contributions. [ABSTRACT FROM AUTHOR]

One of the main concerns of Anfinsen was to reveal the connection between the amino-acid sequence and their biologically active conformation. This search gave rise to two crucial questions in structural biology, namely, why the proteins fold and how a sequence encodes its folding. As to the why, he proposes a plausible answer, namely, the thermodynamic hypothesis. As to the how, this remains an unsolved challenge. Consequently, the protein folding problem is examined here from a new perspective, namely, as an 'analytic whole'. Conceiving the protein folding in this way enabled us to (i) examine in detail why the force-field-based approaches have failed, among other purposes, in their ability to predict the three-dimensional structure of a protein accurately; (ii) propose how to redefine them to prevent these shortcomings, and (iii) conjecture on the origin of the state-of-the-art numerical-methods success to predict the tridimensional structure of proteins accurately. [ABSTRACT FROM AUTHOR]

The applicability of the three steps systematic parametrization procedure (3SSPP) to develop a force field for primary amines was evaluated in the present work. Previous simulations of primary amines show that current force fields (FF) can underestimate some experimental values under room conditions. Therefore, we propose a new set of parameters, for an united atom (UA) model, that can be used for short and long amines which predict correctly thermodynamic and dynamical properties. Following the 3SSPP methodology, the partial charges are chosen to match the experimental dielectric constant whereas the Lennard-Jones (LJ) parameters, 𝜖 and 𝜎, are fitted to reproduce the surface tension at the vapor-liquid interface and the liquid density, respectively. Simulations were initially conducted for the propylamine molecule by introducing three different types of carbon atoms, C𝛼 and C𝛽, with electric charges, and C𝑛, without charge. Then, modifying the charges of the carbons and using the transferable LJ parameters, the new set of constants for long amines were found. The results show good agreement for the experimental dielectric constant and mass density with a percentage error less than 1%, whereas for the surface tension the error is up to 4%. For the short amines, methylamine and ethylamine, the new charges were obtained from a fitting function calculated from the long amines results. For these molecules, the values of the dielectric constant and the surface tension present errors of the order of 10% with the experimental data. Miscibility of the amines was also tested with the new parameters and the results show reasonable agreement with experiments. [ABSTRACT FROM AUTHOR]

This paper reviews molecular dynamics (MD) concepts on heat transfer analysis of supercritical CO2, and highlights the major parameters that can affect the accuracy of respective thermal coefficients. Subsequently, the prime aspects of construction, transfer identification, and thermal performance are organized according to their challenges and prospective solutions associated with the mutability of supercritical CO2 properties. Likewise, the characteristics of bound force field schemes and thermal relaxation approaches are discussed on a case-by-case basis. Both convective and diffusive states of trans- and supercritical CO2 are debated, given their magnitude effects on molecular interactions. Following the scarcity of literature on similar enquiries, this paper recommended a future series of studies on molecular dynamics models in a large region of supercriticality and phase-interactions for coupled heat and mass transfer systems. This review recognizes that the foremost undertaking is to ascertain the thermo-hydraulic identity of supercritical CO2 for process feasibility of developed technology. [ABSTRACT FROM AUTHOR]

Boron containing compounds (BCCs) aroused increasing interest in the scientific community due to their wide application as drugs in various fields. In order to design new compounds hopefully endowed with pharmacological activity and also investigate their conformational behavior, the support of computational studies is crucial. Nevertheless, the suitable molecular mechanics parameterization and the force fields needed to perform these simulations are not completely available for this class of molecules. In this paper, Amber force field parameters for phenyl-, benzyl-, benzylamino-, and methylamino-boronates, a group of boron-containing compounds involved in different branches of the medicinal chemistry, were created. The robustness of the obtained data was confirmed through molecular dynamics simulations on ligand/β-lactamases covalent complexes. The ligand torsional angles, populated over the trajectory frames, were confirmed by values found in the ligand geometries, located through optimizations at the DFT/B3LYP/6-31g(d) level, using water as a solvent. In summary, this study successfully provided a library of parameters, opening the possibility to perform molecular dynamics simulations of this class of boron-containing compounds. [ABSTRACT FROM AUTHOR]

Host–guest binding, despite the relatively simple structural and chemical features of individual components, still poses a challenge in computational modelling. The extreme underperformance of standard end-point methods in host–guest binding makes them practically useless. In the current work, we explore a potentially promising modification of the three-trajectory realization. The alteration couples the binding-induced structural reorganization into free energy estimation and suffers from dramatic fluctuations in internal energies in protein–ligand situations. Fortunately, the relatively small size of host–guest systems minimizes the magnitude of internal fluctuations and makes the three-trajectory realization practically suitable. Due to the incorporation of intra-molecular interactions in free energy estimation, a strong dependence on the force field parameters could be incurred. Thus, a term-specific investigation of transferable GAFF derivatives is presented, and noticeable differences in many aspects are identified between commonly applied GAFF and GAFF2. These force-field differences lead to different dynamic behaviors of the macrocyclic host, which ultimately would influence the end-point sampling and binding thermodynamics. Therefore, the three-trajectory end-point free energy calculations are performed with both GAFF versions. Additionally, due to the noticeable differences between host dynamics under GAFF and GAFF2, we add additional benchmarks of the single-trajectory end-point calculations. When only the ranks of binding affinities are pursued, the three-trajectory realization performs very well, comparable to and even better than the regressed PBSA_E scoring function and the dielectric constant-variable regime. With the GAFF parameter set, the TIP3P water in explicit solvent sampling and either PB or GB implicit solvent model in free energy estimation, the predictive power of the three-trajectory realization in ranking calculations surpasses all existing end-point methods on this dataset. We further combine the three-trajectory realization with another promising modified end-point regime of varying the interior dielectric constant. The combined regime does not incur sizable improvements for ranks and deviations from experiment exhibit non-monotonic variations. [ABSTRACT FROM AUTHOR]

Machine learning was employed on the experimental crystal structures of the Cambridge Structural Database (CSD) to derive an intermolecular force field for all available types of atoms (general force field). The obtained pairwise interatomic potentials of the general force field allow for the fast and accurate calculation of intermolecular Gibbs energy. The approach is based on three postulates regarding Gibbs energy: the lattice energy must be below zero, the crystal structure must be a local minimum, and, if available, the experimental and the calculated lattice energy must coincide. The parametrized general force field was then validated regarding these three conditions. First, the experimental lattice energy was compared with the calculated energies. The observed errors were found to be in the order of experimental errors. Second, Gibbs lattice energy was calculated for all structures available in the CSD. Their energy values were found to be below zero in 99.86% of the cases. Finally, 500 random structures were minimized, and the change in density and energy was examined. The mean error in the case of density was below 4.06%, and for energy it was below 5.7%. The obtained general force field calculated Gibbs lattice energies of 259 041 known crystal structures within a few hours. Since Gibbs energy defines the reaction energy, the calculated energy can be used to predict chemical–physical properties of crystals, for instance, the formation of co‐crystals, polymorph stability and solubility. [ABSTRACT FROM AUTHOR]

Molecular representation learning is a crucial task to accelerate drug discovery and materials design. Graph neural networks (GNNs) have emerged as a promising approach to tackle this task. However, most of them do not fully consider the intramolecular interactions, i.e. bond stretching, angle bending, torsion, and nonbonded interactions, which are critical for determining molecular property. Recently, a growing number of 3D-aware GNNs have been proposed to cope with the issue, while these models usually need large datasets and accurate spatial information. In this work, we aim to design a GNN which is less dependent on the quantity and quality of datasets. To this end, we propose a force field-inspired neural network (FFiNet), which can include all the interactions by incorporating the functional form of the potential energy of molecules. Experiments show that FFiNet achieves state-of-the-art performance on various molecular property datasets including both small molecules and large protein–ligand complexes, even on those datasets which are relatively small and without accurate spatial information. Moreover, the visualization for FFiNet indicates that it automatically learns the relationship between property and structure, which can promote an in-depth understanding of molecular structure. [ABSTRACT FROM AUTHOR]

Hydration free energies of small molecules are commonly used as benchmarks for solvation models. However, errors in predicting hydration free energies are partially due to the force fields used and not just the solvation model. To address this, we have used the 3D reference interaction site model (3D-RISM) of molecular solvation and existing benchmark explicit solvent calculations with a simple element count correction (ECC) to identify problems with the non-bond parameters in the general AMBER force field (GAFF). 3D-RISM was used to calculate hydration free energies of all 642 molecules in the FreeSolv database, and a partial molar volume correction (PMVC), ECC, and their combination (PMVECC) were applied to the results. The PMVECC produced a mean unsigned error of 1.01 ± 0.04 kcal / mol and root mean squared error of 1.44 ± 0.07 kcal / mol , better than the benchmark explicit solvent calculations from FreeSolv, and required less than 15 s of computing time per molecule on a single CPU core. Importantly, parameters for PMVECC showed systematic errors for molecules containing Cl, Br, I, and P. Applying ECC to the explicit solvent hydration free energies found the same systematic errors. The results strongly suggest that some small adjustments to the Lennard–Jones parameters for GAFF will lead to improved hydration free energy calculations for all solvent models. [ABSTRACT FROM AUTHOR]

Charge scaling as an effective solution to the experiment–computation disagreement in molecular modelling of ionic liquids (ILs) could bring the computational results close to the experimental reference for various thermodynamic properties. According to the large-scale benchmark calculations of mass density, solvation, and water-ILs transfer-free energies in our series of papers, the charge-scaling factor of 0.8 serves as a near-optimal option generally applicable to most ILs, although a system-dependent parameter adjustment could be attempted for further improved performance. However, there are situations in which such a charge-scaling treatment would fail. Namely, charge scaling cannot really affect the simulation outcome, or minimally perturbs the results that are still far from the experimental value. In such situations, the vdW radius as an additional adjustable parameter is commonly tuned to minimize the experiment–calculation deviation. In the current work, considering two ILs from the quinuclidinium family, we investigate the impacts of this vdW-scaling treatment on the mass density and the solvation/partition thermodynamics in a fashion similar to our previous charge-scaling works, i.e., scanning the vdW-scaling factor and computing physical properties under these parameter sets. It is observed that the mass density exhibits a linear response to the vdW-scaling factor with slopes close to −1.8 g/mL. By further investigating a set of physiochemically relevant temperatures between 288 K and 348 K, we confirm the robustness of the vdW-scaling treatment in the estimation of bulk properties. The best vdW-scaling parameter for mass density would worsen the computation of solvation/partition thermodynamics, and a marginal decrease in the vdW-scaling factor is considered as an intermediate option balancing the reproductions of bulk properties and solvation thermodynamics. These observations could be understood in a way similar to the charge-scaling situation. i.e., overfitting some properties (e.g., mass density) would degrade the accuracy of the other properties (e.g., solvation free energies). Following this principle, the general guideline for applying this vdW-tuning protocol is by using values between the density-derived choice and the solvation/partition-derived solution. The charge and current vdW scaling treatments cover commonly encountered ILs, completing the protocol for accurate modelling of ILs with fixed-charge force fields. [ABSTRACT FROM AUTHOR]

"Plant-type" ferredoxins (Fds) in the thylakoid membranes of plants, algae, and cyanobacteria possess a single [2Fe-2S] cluster in active sites and mediate light-induced electron transfer from Photosystem I reaction centers to various Fd-dependent enzymes. Structural knowledge of plant-type Fds is relatively limited to static structures, and the detailed behavior of oxidized and reduced Fds has not been fully elucidated. It is important that the investigations of the effects of active-center reduction on the structures and dynamics for elucidating electron-transfer mechanisms. In this study, model systems of oxidized and reduced Fds were constructed from the high-resolution crystal structure of Chlamydomonas reinhardtii Fd1, and three 200 ns molecular dynamics simulations were performed for each system. The force field parameters of the oxidized and reduced active centers were independently obtained using quantum chemical calculations. There were no substantial differences in the global conformations of the oxidized and reduced forms. In contrast, active-center reduction affected the hydrogen-bond network and compactness of the surrounding residues, leading to the increased flexibility of the side chain of Phe61, which is essential for the interaction between Fd and the target protein. These computational results will provide insight into the electron-transfer mechanisms in the Fds. [ABSTRACT FROM AUTHOR]

The euhedral shapes of pyrite FeS2 are usually exposing three main surfaces: striated (001), smooth (111), and striated (210), leading to the cubical, octahedral, and pyritohedral morphology, respectively. The macroscopic striations, sometimes called triglyphs on cubic crystals, are parallel on specific surfaces and aligned to the <100> directions. Other types of striated and unstriated (hkl) surfaces can be observed on pyrite crystals from Peru, a country offering a rich diversity of pyrite shapes. A rare specimen from Elba Island (Italy) is a pyritohedron with uncommon directions of striations (so-called "negative" striations, first described in Japanese minerals). The Wulf kinetic growth and the periodic bond chain (PBC) theories were not relevant enough to explain crystal shapes, the texture of the surfaces, and twinning. To bring some new insights on crystal growth, twinning, and anisotropy, pyrite samples are analyzed using XRD, SEM, and EDS techniques coupled with atomistic simulations. A first analysis points out that sulfur terminations play a key role in the growth of striations in distinguishing the six <001> directions. The negative striated pyritohedral pyrite would be, in fact, a special case that has stabilized the {120} surfaces, which are structurally different from the {210} facets. The {120} surface has a slightly higher surface energy than the {210} surface (surface energies of 1.68 and 1.65 J/m2, respectively, calculated with force field methods). {120} pyritohedra from Elba, Italy, are growing next to micaceous iron oxides (a type of hematite), which are also peculiar specimens with magnetic properties. Another specificity is that some rare earth elements have been identified in the pyrite sample from Elba, which leads to a hypothesis that geothermal conditions favor "negative" striations (e.g., discernible in Akita prefecture-Japan, Boyacá-Colombia, and Cassandra-Greece). The striation directions become useful to distinguish (hkl) surfaces and to identify twinning as they follow the same patterns on each interpenetrated crystal. The most common twinning is the "iron cross," a penetration twin of two crystals defined by a rotation of 90° along an [001] axis with a coincidence in the iron sub-lattice (e.g., twinning by merohedry) and with a twin center. The sulfur network also plays a fundamental role in stabilizing the (001) interface and in keeping the chemical bulk properties at the boundary, as confirmed by additional ab initio simulations. The grain boundary is a 2D defect in which the (001) twinning is relatively stable as it is common. The calculated formation energy of the rotation twinning is 0.8 J/m2. The rotation twinning is associated with an apparent reflection on (110) planes. The formation energy of the (110) mirror grain boundary is 1.7 J/m2, and the interface at the atomic scale is relatively uniform in agreement with experimental observations. [ABSTRACT FROM AUTHOR]

This paper considers the narrow escape problem of a Brownian particle within a three‐dimensional Riemannian manifold under the influence of the force field. We compute an asymptotic expansion of mean sojourn time for Brownian particles. As a auxiliary result, we obtain the singular structure for the restricted Neumann Green's function which may be of independent interest. [ABSTRACT FROM AUTHOR]

Pupil diameter, under constant illumination, is known to reflect individuals' internal states, such as surprise about observation and environmental uncertainty. Despite the growing use of pupillometry in cognitive learning studies as an additional measure for examining internal states, few studies have used pupillometry in human motor learning studies. Here, we provide the first detailed characterization of pupil diameter changes in a short-term reach adaptation paradigm. We measured pupil changes in 121 human participants while they adapted to abrupt, gradual, or switching force field conditions. Sudden increases in movement error caused by the introduction/reversal of the force field resulted in strong phasic pupil dilation during movement accompanied by a transient increase in tonic premovement baseline pupil diameter in subsequent trials. In contrast, pupil responses were reduced when the force field was gradually introduced, indicating that large, unexpected errors drove the changes in pupil responses. Interestingly, however, error-induced pupil responses gradually became insensitive after experiencing multiple force field reversals. We also found an association between baseline pupil diameter and incidental knowledge of the gradually introduced perturbation. Finally, in all experiments, we found a strong co-occurrence of larger baseline pupil diameter with slower reaction and movement times after each rest break. Collectively, these results suggest that tonic baseline pupil diameter reflects one's belief about environmental uncertainty, whereas phasic pupil dilation during movement reflects surprise about a sensory outcome (i.e., movement error), and both effects are modulated by novelty. Our results provide a new approach for nonverbally assessing participants' internal states during motor learning. [ABSTRACT FROM AUTHOR]

Motivated by the problem of optimization of force-field systems in physics using large-scale computer simulations, we consider exploration of a deterministic complex multivariate response surface. The objective is to find input combinations that generate output close to some desired or “target” vector. Despite reducing the problem to exploration of the input space with respect to a 1-D loss function, the search is nontrivial and challenging due to infeasible input combinations, high dimensionalities of the input and output space and multiple “desirable” regions in the input space, and the difficulty of emulating the objective function well with a surrogate model. We propose an approach that is based on combining machine learning techniques with smart experimental design ideas to locate multiple good regions in the input space. Note to Practitioners—ReaxFF is a force field that incorporates complex functions with associated inputs in order to describe the inter- and intra-atomic interactions in materials systems. A typical ReaxFF force field consists of hundreds of parameters (inputs) per element type. During the development of a force field for a molecular system of interest, using computer simulations, these parameters are optimized to reproduce hundreds of material properties close to some benchmark reference values. Finding “good” combinations of hundreds of parameters that produce hundreds of reference values close to their gold standards is a challenging problem because there may be several parameter combinations that may be “almost equally good” or “equally desirable.” To add to the complication, several input combinations simply lead to a system crash, not producing any output at all. Standard global optimization methods do not address such a problem. We propose a novel framework that can address this problem. Beyond the ReaxFF optimization, it can be applied to multiobjective optimization in engineering and the physical sciences, where there are unknown constraints and the focus is on obtaining several good points that can serve as alternatives to a single global optimum. [ABSTRACT FROM AUTHOR]

Despite the massive application of end-point free energy methods in protein–ligand and protein–protein interactions, computational understandings about their performance in relatively simple and prototypical host–guest systems are limited. In this work, we present a comprehensive benchmark calculation with standard end-point free energy techniques in a recent host–guest dataset containing 13 host–guest pairs involving the carboxylated-pillar[6]arene host. We first assess the charge schemes for solutes by comparing the charge-produced electrostatics with many ab initio references, in order to obtain a preliminary albeit detailed view of the charge quality. Then, we focus on four modelling details of end-point free energy calculations, including the docking procedure for the generation of initial condition, the charge scheme for host and guest molecules, the water model used in explicit-solvent sampling, and the end-point methods for free energy estimation. The binding thermodynamics obtained with different modelling schemes are compared with experimental references, and some practical guidelines on maximizing the performance of end-point methods in practical host–guest systems are summarized. Further, we compare our simulation outcome with predictions in the grand challenge and discuss further developments to improve the prediction quality of end-point free energy methods. Overall, unlike the widely acknowledged applicability in protein–ligand binding, the standard end-point calculations cannot produce useful outcomes in host–guest binding and thus are not recommended unless alterations are performed. [ABSTRACT FROM AUTHOR]

Phosphorylation plays a key role in plant biology, such as the accumulation of plant cells to form the observed proteome. Statistical analysis found that many phosphorylation sites are located in disordered regions. However, current force fields are mainly trained for structural proteins, which might not have the capacity to perfectly capture the dynamic conformation of the phosphorylated proteins. Therefore, we evaluated the performance of ff03CMAP, a balanced force field between structural and disordered proteins, for the sampling of the phosphorylated proteins. The test results of 11 different phosphorylated systems, including dipeptides, disordered proteins, folded proteins, and their complex, indicate that the ff03CMAP force field can better sample the conformations of phosphorylation sites for disordered proteins and disordered regions than ff03. For the solvent model, the results strongly suggest that the ff03CMAP force field with the TIP4PD water model is the best combination for the conformer sampling. Additional tests of CHARMM36m and FB18 force fields on two phosphorylated systems suggest that the overall performance of ff03CMAP is similar to that of FB18 and better than that of CHARMM36m. These results can help other researchers to choose suitable force field and solvent models to investigate the dynamic properties of phosphorylation proteins. [ABSTRACT FROM AUTHOR]

The 3D-reference interaction site model (3D-RISM) molecular solvation theory in combination with the Kovalenko–Hirata (KH) closure is extended to seven heterocyclic liquids to understand their liquid states and to test the performance of the theory in solvation free energy (SFE) calculations of solutes in select solvents. The computed solvent site distribution profiles were compared with the all-atom molecular dynamics (MD) simulations, showing comparable performances. The computational results were compared against the structural parameters for liquids, whenever available, as well as against the experimental SFEs. The liquids are found to have local ordered structures held together via weak interactions in both the RISM and MD simulations. The 3D-RISM-KH computed SFEs are in good agreement with the benchmark values for the tetrahydrothiophene-S,S-dioxide, and showed comparatively larger deviations in the case of the SFEs in the tetrahydrofuran continuum. [ABSTRACT FROM AUTHOR]

In molecular modelling of novel solvents such as ionic liquids, it is common to scale atomic charges to improve the experiment‐simulation agreement for some selected properties. As these liquids are designed to solvate solutes, whether the solvation thermodynamics could be correctly described is of utmost importance. Therefore, we present a comprehensive large‐scale calculation of solvation free energies via nonequilibrium fast‐switching simulations for a spectrum of molecules in ionic liquids, the atomic charges of which are scaled to maximize the prediction‐experiment correlation. Further, the density‐derived choice is compared with the solvation‐thermodynamics‐derived one. When the scaling factor is decreased, the density exhibits a monotonically decreasing behavior due to weaker inter‐molecular interactions produced by scaled atomic charges. However, solvation free energies do not show consistent monotonic behaviors, which are caused by competing electrostatic and vdW responses to the scaling‐parameter variation. More intriguingly, the solvation‐free‐energy‐derived scaling factor is generally slightly higher than the density‐derived one. We further calculate partition coefficients ortransfer free energies of solutes from water to ionic liquids to provide another thermodynamic perspective of charge scaling. Another central result is the detailed evaluation of the widely used force fields for bonded and vdW terms, i.e., the GAFF derivatives. [ABSTRACT FROM AUTHOR]

In this work, Layered Double Hydroxide (LDH) materials carrying the worldwide administered non-steroidal anti-inflammatory drug naproxen (NAP), and the sodium naproxenate salt (NaNAP) for comparison, were studied by computational approaches aiming to model the structure of hybrid LDH-drug and shed light on NAP intercalation process. Atomic modeling calculations were performed at the quantum mechanical level based on Density Functional Theory and classical force fields based on empirical interatomic potentials. LDH NAP materials were prepared by ion exchange reaction from Mg 2 Al(OH) 6 Cl and Zn 2 Al(OH) 6 Cl pristine phases. The characterization of the materials confirmed NAP intercalation and also the permanence of the pristine phases in the isolated materials after ion exchange. Crystallographic lattice parameters, elemental analysis, and TGA experimental results were then employed in the calculations, which revealed that NAP anions can completely neutralize the positive charge of the LDH layers: both Mg 2 Al and Zn 2 Al LDH structures could be optimized with all Cl− anions substituted by NAP. The drug assumed different dispositions in the NaNAP crystal or when intercalated into LDH. Additionally, infrared wavenumbers calculations agreed with the experimental results and showed useful to support LDH NAP bands assignment. The employed theoretical models to represent the structure of LDH NAP systems are expected to assist the interpretation of future experimental results and to be used as auxiliary tools to tune properties of LDH-drug pharmaceutical formulations. [Display omitted] • Density functional theory and classical force fields based on empirical interatomic potentials were applied for the Mg 2 Al-NAP and Zn 2 Al-NAP LDH materials. • The crystal structure of the NaNAP was optimized and the main IR wavenumbers were calculated and agreed with the experimental results. • Calculations showed that the charge of the LDH layers can be completely neutralized by NAP, thus achieving maximum ion exchange capacity. • NAP assumed different dispositions in the NaNAP crystal or intercalated into LDH. [ABSTRACT FROM AUTHOR]

Metal–organic frameworks (MOFs) are a highly versatile group of porous materials suitable for a broad range of applications, which often crucially depend on the MOFs' heat transport properties. Nevertheless, detailed relationships between the chemical structure of MOFs and their thermal conductivities are still largely missing. To lay the foundations for developing such relationships, we performed non-equilibrium molecular dynamics simulations to analyze heat transport in a selected set of materials. In particular, we focus on the impact of organic linkers, the inorganic nodes and the interfaces between them. To obtain reliable data, great care was taken to generate and thoroughly benchmark system-specific force fields building on ab-initio-based reference data. To systematically separate the different factors arising from the complex structures of MOF, we also studied a series of suitably designed model systems. Notably, besides the expected trend that longer linkers lead to a reduction in thermal conductivity due to an increase in porosity, they also cause an increase in the interface resistance between the different building blocks of the MOFs. This is relevant insofar as the interface resistance dominates the total thermal resistance of the MOF. Employing suitably designed model systems, it can be shown that this dominance of the interface resistance is not the consequence of the specific, potentially weak, chemical interactions between nodes and linkers. Rather, it is inherent to the framework structures of the MOFs. These findings improve our understanding of heat transport in MOFs and will help in tailoring the thermal conductivities of MOFs for specific applications. [ABSTRACT FROM AUTHOR]

• Repurposing existing drugs for new diseases is cost effective and time saving. • In silico methods are crucial for rapid drug screening in the early stages. • Machine learning algorithms confer speed and accuracy to computational screening approaches. • Deep learning is immensely powerful to design molecules with desired properties. The current global health emergency in the form of the Coronavirus 2019 (COVID-19) pandemic has highlighted the need for fast, accurate, and efficient drug discovery pipelines. Traditional drug discovery projects relying on in vitro high-throughput screening (HTS) involve large investments and sophisticated experimental set-ups, affordable only to big biopharmaceutical companies. In this scenario, application of efficient state-of-the-art computational methods and modern artificial intelligence (AI)-based algorithms for rapid screening of repurposable chemical space [approved drugs and natural products (NPs) with proven pharmacokinetic profiles] to identify the initial leads is a powerful option to save resources and time. Structure-based drug repurposing is a popular in silico repurposing approach. In this review, we discuss traditional and modern AI-based computational methods and tools applied at various stages for structure-based drug discovery (SBDD) pipelines. Additionally, we highlight the role of generative models in generating molecules with scaffolds from repurposable chemical space. [ABSTRACT FROM AUTHOR]

[Display omitted] • All-atom simulations are impractical for bitumen microscale phenomena; we introduce a United Atom model alternative. • The force field surpasses other UA models when modelling large molecules, mirroring geometric, thermodynamic, and kinetic properties. • The force field features 17 bead types and 287 potentials, covering a variety of molecules for bitumen modelling. • The force field achieves a 100-fold increase in performance in MD simulations of bitumen. • The force field allows microsecond, micrometer MD simulations for bitumen SARA phase separation exploration. This paper presents a United Atom (UA) force field for simulating hydrocarbon molecules in bituminous materials, integrating explicit hydrogens into beads with their parent atom. This method simplifies all-atom molecular models, significantly accelerating Molecular Dynamics (MD) simulations of bitumen by 10 to 100 times. Key advantages include halving the particle count, eliminating complex hydrogen interactions, and decreasing the degrees of freedom of the molecules. Developed by mapping forces from an all-atom model to the centers of mass of UA model beads, the force field ensures accurate replication of energies, forces, and molecular conformations, mirroring properties like pressure and density. It features 17 bead types and 287 interaction types, encompassing various hydrocarbon molecules. The UA force field's stability, surpassing all-atom models, is a notable achievement. This stability, stemming from smoother potential energy surfaces, leads to consistent property measurements and improved stress tensor accuracy. It enables the extension of MD simulations to larger spatiotemporal scales, crucial for understanding complex phenomena such as phase separation in bituminous materials. This foundational work sets the stage for future developments, including refining parameters and introducing new bead types, to enhance the modeling capabilities of the force field, thereby advancing the application and understanding of bituminous materials. [ABSTRACT FROM AUTHOR]

Bonded (or valence) interactions, which directly determine the local structures of the molecules, are fundamental parts of molecular mechanics force fields (FFs). Most popular classical FFs adopt the simple harmonic models for bond stretching and angle bending and ignore cross-coupling effects among the valence terms. This may lead to less accurate vibrational properties and configurations in molecular dynamics (MD) simulations. AMOEBA models utilize an MM3(MM4)-style bonded interaction model, in which the vibrational anharmonicity, the coupling effects among different energy terms, and the out-of-plane bending for sp2-hybridized atoms are considered. In this work, we report the development of bonded interaction parameters for a wide range of chemistry based on quantum mechanics (QM). About 270 atomic types defined by SMARTS strings were used to model the valence interactions. Our results indicate that the resulting valence parameters produce accurate vibrational frequencies (RMSD from QM is less than ∼36.6cm−1) over a large set of molecules with diverse functional groups (445 molecules). By contrast, the harmonic models usually give an RMS error greater than 60cm−1. Meanwhile, this model accurately reflects the potential energy surface of the out-of-plane bending. Our model can generally be applied to the AMOEBA family and any MM3(MM4)-based molecular mechanics FFs. Bonded interactions are fundamental ingredients of molecular mechanics force fields because they directly determine the local structure of a molecule. In this work, we parametrize the advanced bonded energy functionals that consider the vibrational anharmonicity, the coupling effects, and the out-of-plane bending for sp2-hybridized atoms. It is expected that these models can describe the spectroscopic properties and overall structures of a molecule more accurately when they are used with polarizable AMOEBA-based force fields. [ABSTRACT FROM AUTHOR]

A new force field for 1-propanol, in the united and all atom models, has been obtained by combining two different empirical methodologies. The first was developed by scaling atom charges and Lennard-Jones parameters to fit the dielectric constant, surface tension, and density; this methodology is named three steps systematic parameterization procedure (3SSPP), as reported by Pérez de la Luz et al. (J Chem Theory Comput 14:5949–5958, 2018). The second methodology consists of moving these parameters and together with the bond distance to obtain the liquid-vapor phase diagram of the CO2 molecule as discussed by Harris and Yung (J Phys Chem 99:12021–12024, 1995). The last methodology is used to obtain the self-diffusion coefficient, which was not consider in the 3SSPP. The 3SSPP/bond methodology is the 3SSPP plus the bond distance scaling. With this new methodology, the experimental density, dielectric constant, surface tension, and self-diffusion coefficient at ambient temperature could be achieved. Furthermore, we show the temperature dependence of the aforementioned properties. The static structure factors are in accordance with the experimental spectrum. Solubility is increased to the experimental value for the united atom (UA) model after applying this methodology and for all atom (AA) scheme, the experimental solubility value is maintained. [ABSTRACT FROM AUTHOR]

Molecular dynamics (MD) simulation has been widely used in the field of biomedicine to study the conformational transition of proteins caused by mutation or ligand binding/unbinding. It provides some perspectives those are difficult to find in traditional biochemical or pathological experiments, for example, detailed effects of mutations on protein structure and protein–protein/ligand interaction at the atomic level. In this review, a broad overview on conformation changes and drug discovery by MD simulation is given. We first discuss the preparation of protein structure for MD simulation, which is a key step that determines the accuracy of the simulation. Then, we summarize the applications of commonly used force fields and MD simulations in scientific research. Finally, enhanced sampling methods and common applications of these methods are introduced. In brief, MD simulation is a powerful tool and it can be used to guide experimental study. The combination of MD simulation and experimental techniques is an a priori means to solve the biomedical problems and give a deep understanding on the relationship between protein structure and function. [ABSTRACT FROM AUTHOR]

Molecular mechanics force field calculations have historically shown significant limitations in modeling the energetic and conformational interconversions of highly substituted furanose rings. This is primarily due to the gauche effect that is not easily captured using pairwise energy potentials. In this study, we present a refinement to the set of torsional parameters in the General Amber Force Field (gaff) used to calculate the potential energy of mono, di-, and gem-fluorinated nucleosides. The parameters were optimized to reproduce the pseudorotation phase angle and relative energies of a diverse set of mono- and difluoro substituted furanose ring systems using quantum mechanics umbrella sampling techniques available in the IpolQ engine in the Amber suite of programs. The parameters were developed to be internally consistent with the gaff force field and the TIP3P water model. The new set of angle and dihedral parameters and partial charges were validated by comparing the calculated phase angle probability to those obtained from experimental nuclear magnetic resonance experiments. [ABSTRACT FROM AUTHOR]

We provide tailor-made GAFF2-type interaction potentials for modeling ammonium and amide ions in ammonia. Based on harmonic approximation of intra-molecular bond stretching and bending, our force fields nicely reproduce the vibrational modes of NH4+ and NH2−, respectively. Moreover, quantum calculations of pair-wise NH4+/NH2−–NH3 interactions were used for inter-molecular force field parameterization, while (NH3)n, [(NH4)(NH3)n]+, and [(NH2)(NH3)n]− complexes with n > 2, respectively, were reserved for benchmarking in terms of both structure and formation energy. Despite the limited reliability of molecular mechanics models for describing dimer complexes (n = 1), we find that GAFF2 reasonably reproduces [(NH4)(NH3)n]+ species for n = 2–4. For the assessment of [(NH2)(NH3)n]− complexes with n = 2–4, we however suggest the introduction of specific van der Waals parameters for amide-ammonia interactions. The application of the (extended) GAFF2 models is demonstrated for the study of ammonium and amide solvation in liquid ammonia at 240 K and 1 atm, respectively. On this basis, we suggest the applicability of our model for both gas phase and liquid states of ammonia. [ABSTRACT FROM AUTHOR]

The calibration of torsional interaction terms by fitting relative gas‐phase conformational energies against their quantum‐mechanical values is a common procedure in force‐field development. However, much less attention has been paid to the optimization of third‐neighbor nonbonded interaction parameters, despite their strong coupling with the torsions. This article introduces an algorithm termed LLS‐SC, aimed at simultaneously parametrizing torsional and third‐neighbor interaction terms based on relative conformational energies. It relies on a self‐consistent (SC) procedure where each iteration involves a linear least‐squares (LLS) regression followed by a geometry optimization of the reference structures. As a proof‐of‐principle, this method is applied to obtain torsional and third‐neighbor interaction parameters for aliphatic chains in the context of the GROMOS 53A6 united‐atom force field. The optimized parameter set is compared to the original one, which has been fitted manually against thermodynamic properties for small linear alkanes. The LLS‐SC implementation is freely available under http://github.com/mssm-labmmol/profiler. [ABSTRACT FROM AUTHOR]

Self-assembled cyclic peptide nanotubes with alternating D- and L-amino acid residues in the sequence of each subunit have attracted a great deal of attention due to their potential for new nanotechnology and biomedical applications, mainly in the field of antimicrobial peptides. Molecular dynamics simulations can be used to characterize these systems with atomic resolution at different time scales, providing information that is difficult to obtain via wet lab experiments. However, the performance of classical force fields typically employed in the simulation of biomolecules has not yet been extensively tested with this kind of highly constrained peptide. Four different classical force fields (AMBER, CHARMM, OPLS, and GROMOS), using a nanotube formed by eight D,L-α-cyclic peptides inserted into a lipid bilayer as a model system, were employed here to fill this gap. Significant differences in the pseudo-cylindrical cavities formed by the nanotubes were observed, the most important being the diameter of the nanopores, the number and location of confined water molecules, and the density distribution of the solvent molecules. Furthermore, several modifications were performed on GROMOS54a7, aiming to explore acceleration strategies of the MD simulations. The hydrogen mass repartitioning (HMR) and hydrogen isotope exchange (HIE) methods were tested to slow down the fastest degrees of freedom. These approaches allowed a significant increase in the time step employed in the equation of the motion integration algorithm, from 2 fs up to 5–7 fs, with no serious changes in the structural and dynamical properties of the nanopores. Subtle differences with respect to the simulations with the unmodified force fields were observed in the concerted movements of the cyclic peptides, as well as in the lifetime of several H-bonds. All together, these results are expected to contribute to better understanding of the behavior of self-assembled cyclic peptide nanotubes, as well as to support the methods tested to speed up general MD simulations; additionally, they do provide a number of quantitative descriptors that are expected to be used as a reference to design new experiments intended to validate and complement computational studies of antimicrobial cyclic peptides. [ABSTRACT FROM AUTHOR]

Accurate simulation of protein folding is a unique challenge in understanding the physical process of protein folding, with important implications for protein design and drug discovery. Molecular dynamics simulation strongly requires advanced force fields with high accuracy to achieve correct folding. However, the current force fields are inaccurate, inapplicable and inefficient. We propose a machine learning protocol, the inductive transfer learning force field (ITLFF), to construct protein force fields in seconds with any level of accuracy from a small dataset. This process is achieved by incorporating an inductive transfer learning algorithm into deep neural networks, which learn knowledge of any high-level calculations from a large dataset of low-level method. Here, we use a double-hybrid density functional theory (DFT) as a case functional, but ITLFF is suitable for any high-precision functional. The performance of the selected 18 proteins indicates that compared with the fragment-based double-hybrid DFT algorithm, the force field constructed by ITLFF achieves considerable accuracy with a mean absolute error of 0.0039 kcal/mol/atom for energy and a root mean square error of 2.57  |$\mathrm{kcal}/\mathrm{mol}/{\AA}$| for force, and it is more than 30 000 times faster and obtains more significant efficiency benefits as the system increases. The outstanding performance of ITLFF provides promising prospects for accurate and efficient protein dynamic simulations and makes an important step toward protein folding simulation. Due to the ability of ITLFF to utilize the knowledge acquired in one task to solve related problems, it is also applicable for various problems in biology, chemistry and material science. [ABSTRACT FROM AUTHOR]

Docking studies play a critical role in the current workflow of drug discovery. However, limitations may often arise through factors including inadequate ligand sampling, a lack of protein flexibility, scoring function inadequacies (e.g., due to metals, co‐factors, etc.), and difficulty in retaining explicit water molecules. Herein, we present a novel CHARMM‐based induced fit docking (CIFDock) workflow that can circumvent these limitations by employing all‐atom force fields coupled to enhanced sampling molecular dynamics procedures. Self‐guided Langevin dynamics simulations are used to effectively sample relevant ligand conformations, side chain orientations, crystal water positions, and active site residue motion. Protein flexibility is further enhanced by dynamic sampling of side chain orientations using an expandable rotamer library. Steps in the procedure consisting of fixing individual components (e.g., the ligand) while sampling the other components (e.g., the residues in the active site of the protein) allow for the complex to adapt to conformational changes. Ultimately, all components of the complex—the protein, ligand, and waters—are sampled simultaneously and unrestrained with SGLD to capture any induced fit effects. This modular flexible docking procedure is automated using CHARMM scripting, interfaced with SLURM array processing, and parallelized to use the desired number of processors. We validated the CIFDock procedure by performing cross‐docking studies using a data set comprised of 21 pharmaceutically relevant proteins. Five variants of the CHARMM‐based SWISSDOCK scoring functions were created to quantify the results of the final generated poses. Results obtained were comparable to, or in some cases improved upon, commercial docking program data. [ABSTRACT FROM AUTHOR]

Molten salt nuclear reactors are promising technologies for sustainable energy sources. In this context, understanding the physicochemical properties of molten salts is essential to the development, usage, and maintenance of reactors. Classical molecular simulations allow estimating the macroscopic properties of molten salts at a relatively low computational cost. In this work, we develop a new force field for plutonium-based molten salts. We validate our classical model by comparing molecular dynamics results with experimental measurements, obtaining a quantitative agreement. Our work demonstrates the reliability and transferability of classical force fields to represent the physicochemical properties of molten salts. [ABSTRACT FROM AUTHOR]

The main cysteine protease (Mpro) of coronavirus SARS-CoV-2 has become a promising target for computational development in anti-COVID-19 treatments. Here, we benchmarked the performance of six biomolecular molecular dynamics (MD) force fields (OPLS-AA, CHARMM27, CHARMM36, AMBER03, AMBER14SB and GROMOS G54A7) and three water models (TIP3P, TIP4P and SPC) for reproducing the native fold and the enzymatic activity of Mpro as monomeric and dimeric units. The MD sampling up to 1 μs suggested that the proper choice of the force fields and water models plays an essential role in reproducing the tertiary structure and the inter-residue distance between the catalytic dyad His41-Cys145. We found that while most benchmarked all-atom force fields reproduce well the native fold of Mpro, the CHARMM27/TIP3P and OPLS-AA/TIP4P setups revealed a good performance in reproducing the structure of the catalytic domain. In addition, these FF setups were also well-adopted for MD sampling of Mpro at the physiologic conditions by mimicking the presence of 100 mM NaCl and the elevated temperature of 310 K. Finally, both FFs were also performed well in reproducing the native fold of Mpro in a dimeric form. Therefore, comparing the preservation of the native fold of Mpro and the stability of its catalytic site architecture, our MD benchmarking suggests that the OPLS-AA/TIP4P and CHARMM27/TIP3P MD setups at the physiologic conditions may be well-suited for rapid in silico screening and developing broad-spectrum anti-coronaviral therapeutic agents. [Display omitted] • The main cysteine protease (Mpro) of coronavirus SARS-CoV-2 is a promising target. • Benchmarking six MD force fields, such as (OPLS-AA, CHARMM27, CHARMM36, AMBER03, AMBER14SB and GROMOS G54A7, is performed. • Native fold of monomeric and dimeric Mpro is considered. • Tertiary structure and the inter-residue distance between the catalytic dyad His41-Cys145 as key parameters. [ABSTRACT FROM AUTHOR]

The series of metal–organic frameworks M-MOF-74 gained popularity in the field of capture and separation of CO 2 due to the presence of numerous, highly reactive open-metal sites. The description of effective interactions between guest molecules and open-metal sites without accounting for polarization effects is challenging but it can significantly reduce the computational cost of simulations. In this study, we propose a non-polarizable force field for CO 2 , and H 2 adsorption in M-MOF-74 (M = Ni, Cu, Co, Fe, Mn, Zn) by scaling the Coulombic interactions of M-MOF-74 atoms, and Lennard-Jones interaction potentials between the center of mass of H 2 and the open-metal centers. The presented force field is based on UFF and DREIDING parameters, characterized by high transferability and efficiency. The quantum behavior of H 2 at cryogenic temperatures is considered by incorporating Feynman–Hibbs quantum corrections. To validate the force field, the experimental isotherms of CO 2 at 298 K and 10−1 – 10 2 kPa , the isotherms of H 2 at 77 K and 10−5 – 10 2 kPa , the corresponding enthalpy of adsorption, and the binding geometries in the M-MOF-74 series were reproduced using Monte Carlo simulations in the grand-canonical ensemble. The computed loadings, heats of CO 2 and H 2 adsorption, and binding geometries in M-MOF-74 are in very good agreement with the experimental values. The temperature transferability of the force field from 77 K to 87 K, and 298 K was shown for adsorption of H 2. The validated force field was used to study the adsorption and separation of CO 2 /H 2 mixtures at 298 K. The adsorption of H 2 practically does not occur when CO 2 is present in the mixture. As indicated from simulated breakthrough curves, the breakthrough time of CO 2 in M-MOF-74 follows the same order as the uptake and the heat of CO 2 adsorption: Ni ¿ Co ¿ Fe ¿ Mn ¿ Zn ¿ Cu. Increasing the feed mole fraction of CO 2 in the breakthrough simulations from 0.1 to 0.9 speeds up the saturation of the adsorbent, leading to a faster exit of CO 2 with the column effluent. The application of the non-polarizable force field allows full investigation of the capture and separation of CO 2 in M-MOF-74, and can be expanded to study multi-component mixtures or industrial reactions in future research. [Display omitted] • Non-polarizable force field for CO 2 /H 2 separation in M-MOF-74. • Scaling of Coulombic interactions and Lennard-Jones interaction potentials. • CO 2 and H 2 isotherms, heats of adsorption and binding geometries are reproduced. • Transferability of force field from cryogenic temperatures to 298 K. • Type of metal center in M-MOF-74 affects breakthrough time of CO 2 /H 2 mixtures. [ABSTRACT FROM AUTHOR]

The extraction of nitrogen and sulfur compounds from gasoline and diesel, using ionic liquids, is conducted through liquid-liquid molecular dynamics simulations. The novel united atom parameters of pyridine, benzene and thiophene which possess a constant dipole moment successfully reproduce the experimental dielectric constant and solubility in water. These molecular parameters are transferred to simulate toluene and dibenzothiophene. Regarding polar liquids, the coexisting densities and surface tension as functions of temperature align excellently with experimental data. The liquid density and surface tension of modeled diesel and gasoline also match experimental data well although the viscosity is underestimated. Ionic liquids comprise positive ions of imidazolium, pyrrolidinium, pyridinium and trimethyl ammonium varying in hydrocarbon chain length. The anion is bis(trifluoromethylsulfonyl)imide. It has been discovered that the new parameters significantly enhance the extraction of nitrogen and sulfur compounds from hydrocarbon mixtures compared to simulation results from TraPPE-UA force field where the molecules possess zero molecular dipole moment. The extraction efficiency of ionic liquids aligns excellently with experimental results at room temperature. • Extraction of N- and S-compounds is an important issue in industry, since they are related with health and economics. • Molecular dynamics is an important methodology to study extraction and the force field is the most important matter. • Many force fields available are not capable to reproduce miscibility and therefore they have to be re-parameterized. • Polarization of ring-like molecules in the force field is an essential issue to reproduce extraction of N- and S-compounds. [ABSTRACT FROM AUTHOR]

Patients with hemiplegia are usually restricted to performing general bilateral activities of daily life (gbADLs). Bilateral training has been verified to contribute to the rehabilitation of physical functions. Although robotic systems are gradually being employed in the field of rehabilitation, few studies have performed simulations with regards to gbADLs for training. Therefore, a novel end-effector bilateral rehabilitation robotic system (EBReRS) for the upper limb is developed in this article for the task rendering of gbADLs, in which the gbADL-corresponding workspace is obtained via modularly designed bilateral parallelogram mechanisms. In addition, the interaction rendering of multiple bimanual modes (uncoupled, trans-soft-coupled, trans-semi-coupled, and rotation-coupled) is achieved by implementing the admittance model, the inner force field between robotic end-effectors, and the outer force field distributed around. Experiments of the proposed four rehabilitation training modes were carried out on the healthy subject, with the results showing a feasible method of the EBReRS in the simulation of multiple bimanual coordinated rehabilitation training tasks. In the future, the constructed EBReRS is expected to be exploited for home rehabilitation as a coordinated training device. • A novel robotic system EBReRS with stretchable structure and modular design is built. • The active rehabilitation training with controllable difficulty is achieved. • Multifold bilateral training modes are achieved under inner and outer force fields. • Patient-centered adjustment of training intensity for the affected side is achieved. • Practical validation of the built prototype EBReRS is conducted. [ABSTRACT FROM AUTHOR]

The relevance of motions in biological macromolecules has been clear since the early structural analyses of proteins by X-ray crystallography. Computer simulations have been applied to provide a deeper understanding of the dynamics of biological macromolecules since 1976, and are now a standard tool in many labs working on the structure and function of biomolecules. In this mini-review we highlight some areas of current interest and active development for simulations, in particular all-atom molecular dynamics simulations. • We present our views on the importance of the following for molecular dynamics simulations • Force fields • Advanced sampling methods and applications • Relations to experiment [ABSTRACT FROM AUTHOR]

Synthesis of graphene with reduced use of chemical reagents is essential for manufacturing scale-up and to control its structure and properties. In this paper, we report the mechanism for exfoliating graphene from graphite slabs using laser impulse. We set up a molecular dynamics model that accounts for the charge-mediated inter-atomic potential along with the forces from electromagnetic fields of a laser pulse. The role of different laser fluences on the exfoliation process of graphene quantified in terms of the interlayer energy transition, inter-layer displacement jump, and thermal shock propagation in graphene-graphite system. The simulation results confirm the exfoliation of a single layer graphene sheet for the laser power ranging from 100 × 10 − 14 to 2000 × 10 − 14 J/nm2. With an increase of laser fluence from 2000 × 10 − 14 to 4000 × 10 − 14 J/nm2, there is an increase in the graphene yield via the layer-after-layer exfoliation. The bridging bond dynamics between the successive graphene layers govern the exfoliation of the second layer. The results indicate promises for producing chemical-free graphene on a large scale for industrial applications. [ABSTRACT FROM AUTHOR]

In this study, we firstly characterize modified magnetic particles and associated magnetic fields by considering the evolution of the charged particle together with its modified frame construction in 3D space. Then, we compute the energy flows of each modified magnetic particles in terms of its curvature and torsion in the space. Finally, we obtain energy flux density, the intensity of the light, power of modified magnetic particles in the space. [ABSTRACT FROM AUTHOR]

Computational investigations into the structure and function of metalloenzymes with transition metal cofactors require proper preparation of the model, which requires obtaining reliable force field parameters for the cofactor. Here, we present a test case where several methods were used to derive amber force field parameters for a bonded model of the Fe(II) cofactor of ectoine synthase. Moreover, the spin of the ground state of the cofactor was probed by DFT and post-HF methods, which consistently indicated the quintet state is lowest in energy and well separated from triplet and singlet. The performance of the obtained force field parameter sets, derived for the quintet spin state, was scrutinized and compared taking into account metrics focused on geometric features of the models as well as their energetics. The main conclusion of this study is that Hessian-based methods yield parameters which represent the geometry around the metal ion, but poorly reproduce energy variance with geometrical changes. On the other hand, the energy-based method yields parameters accurately reproducing energy-structure relationships, but with bad performance in geometry optimization. Preliminary tests show that admixing geometrical criteria to energy-based methods may allow to derive parameters with acceptable performance for both energy and geometry. [ABSTRACT FROM AUTHOR]

The ability to automatically extend and improve molecular force fields to accurately describe an ever wider range of compounds is a key enabler for the application of molecular modelling of chemicals and materials in industry. In this work we have developed a set of tools to process structural data available in well-known databases, to find deficiencies in the force field, and where necessary, automatically fit force- field parameters to on-the-fly calculated quantum data based on Density Functional Theory, supplemented by experimental data. The protocols have been applied to structures from the Maybridge, PoLyInfo and ILThermo databases, covering drug-like molecules, polymers and ionic liquids respectively. We demonstrate that the new version of the force field can type all structures in the extended data set without missing parameters, with a similar high-quality prediction of geometry (bonds, angles, torsions), energy and forces of earlier versions. [ABSTRACT FROM AUTHOR]

This paper deals with the effect of introducing an additional interaction site onto molecular-mechanical models of nitrogen-containing heterocyclic compounds. The introduction of only one additional site next to nitrogen atoms is shown to result in significant improvement of the quality of the models along with negligible slowdown of calculation speed. Concretely, it was proposed to introduce the site inside the aromatic ring at a distance of 0.4 Å from the nitrogen atom center. All the parametrization can be completely automated. The proposed force field allows predicting heats of evaporation of liquids of the compound under investigation with an accuracy of 1 kcal/mol. [ABSTRACT FROM AUTHOR]