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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]

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Peptides mediate up to 40% of protein interactions, their high specificity and ability to bind in places where small molecules cannot make them potential drug candidates. However, predicting peptide-protein complexes remains more challenging than protein-protein or protein-small molecule interactions, in part due to the high flexibility peptides have. In this review, we look at the advances in docking, molecular simulations and machine learning to tackle problems related to peptides such as predicting structures, binding affinities or even kinetics. Wespecifically focus on explaining the number of docking programmes and force fields used in molecular simulations, so a prospective user can have an educated guess as to why choose one modelling tool or another to address their scientific questions. [ABSTRACT FROM AUTHOR]

The interaction of oligonucleotides dA10, dC10, dG10, and dT10 with single-walled carbon nanotube was investigated using molecular dynamics simulation. The distance of the mass center of each of the oligonucleotides with the carbon nanotube axis was calculated. The results show that this distance is as dA10 > dG10 > dC10 > dT10. The conformation of the main chain and single-stranded DNA side chain were investigated using pseudo angles (η, θ) and (χ, P) respectively. The results show that the interaction of the CNT with the main chain of oligonucleotides occurs from the region , which is related to the angle η. The rotation of purine bases has also occurred more than the pyrimidine bases. The free energy analysis of interaction compared to the two distance criteria of end-to-end oligonucleotides and the number of residues that have π–π interaction with nanotubes shows that each of the four decamers has a π–π interaction with nanotubes. Nevertheless, their π–π interaction regions are at the end of the decamer for purine bases and in the first and middle regions for the pyrimidine bases. The results are in good agreement with the experimental data and the results of other simulations. [ABSTRACT FROM AUTHOR]

Peptides mediate up to 40% of protein interactions, their high specificity and ability to bind in places where small molecules cannot make them potential drug candidates. However, predicting peptide–protein complexes remains more challenging than protein–protein or protein–small molecule interactions, in part due to the high flexibility peptides have. In this review, we look at the advances in docking, molecular simulations and machine learning to tackle problems related to peptides such as predicting structures, binding affinities or even kinetics. We specifically focus on explaining the number of docking programmes and force fields used in molecular simulations, so a prospective user can have an educated guess as to why choose one modelling tool or another to address their scientific questions.

This review discusses the use of molecular modeling tools, together with existing experimental findings, to provide a complete atomic-level description of enzyme dynamics and function. We focus on functionally relevant conformational dynamics of enzymes and the protonation states of substrates. The conformational fluctuations of enzymes usually play a crucial role in substrate recognition and catalysis. Protein dynamics can be altered by a tiny change in a molecular system such as different protonation states of various intermediates or by a significant perturbation such as a ligand association. Here we review recent advances in applying atomistic molecular dynamics (MD) simulations to investigate allosteric and network regulation of tryptophan synthase (TRPS) and protonation states of its intermediates and catalysis. In addition, we review studies using quantum mechanics/molecular mechanics (QM/MM) methods to investigate the protonation states of catalytic residues of β-Ketoacyl ACP synthase I (KasA). We also discuss modeling of large-scale protein motions for HIV-1 protease with coarse-grained Brownian dynamics (BD) simulations.

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]

In this study, the interactions of two effective derivatives of the methotrexate anticancer drug with Single-wall carbon nanotubes (SWNTs) and Boron nitride nanotubes (BNNTs) in the gas phase were investigated using the DFT calculations. Through the DFT method, the effects of different solvents on the interaction of methotrexate derivatives with SWNTs and BNNTs within the Onsager self-consistent reaction field (SCRF) model, as well as the effects of temperature on the stability of interactions between compounds in various solvents were studied. Thermodynamic parameters, Frontier Molecular Orbitals (FMOs) and Total Density of States (DOS) of the title compounds were also studied using theoretical calculations. Molecular properties of the structures such as the ionization potential (I), electron affinity (A), chemical hardness (1), electronic chemical potential (µ) and electrophilicity (1) were investigated as well. SWNTs are more suitable carriers for L-MTX and BNNTs are more suitable carriers for L-FMTX. Also, the interaction of methotrexate derivatives with SWNTs and BNNTs was examined via Amber, Opls, Charmm and MM+ force fields through the molecular mechanic (MM) method. The calculations were carried out through the Monte Carlo simulation methods at different temperatures. The effects of gas phase and various solvent media with different dielectric constants (water, DMSO, methanol, ethanol, CH2Cl2 and DMF) on the interaction of methotrexate derivatives were investigated using the aforementioned force fields. The MM+ force field, which is an exclusive force field for calculations related to macromolecules, had the lowest amount of energy and featured the most stable form of connection for Methotrexate derivatives connected to SWNTs and BNNTs. The most significant finding is that with respect to both thermodynamic properties and conformer populations, the Monte Carlo and Molecular Mechanics-Quantum Mechanics results are in agreement. [ABSTRACT FROM AUTHOR]

The computational modeling field has vastly evolved over the past decades. The early developments of simplified protein systems represented a stepping stone towards establishing more efficient approaches to sample intricated conformational landscapes. Downscaling the level of resolution of biomolecules to coarser representations allows for studying protein structure, dynamics and interactions that are not accessible by classical atomistic approaches. The combination of different resolutions, namely hybrid modeling, has also been proved as an alternative when mixed levels of details are required. In this review, we provide an overview of coarse-grained/hybrid models focusing on their applicability in the modeling of biomolecular interactions. We give a detailed list of ready-to-use modeling software for studying biomolecular interactions allowing various levels of coarse-graining and provide examples of complexes determined by integrative coarse-grained/hybrid approaches in combination with experimental information.

The use of molecular simulation has been growing in the field of engineering, fueled not just by the advances in computational power but also on the availability of reliable software. One potential use of molecular simulation is related to the screening of materials for a specific application. The reliability of molecular simulation results depends on the trustworthiness of the force field used, which for engineering purposes should be as simple as possible. This work provides an evaluation of the potential accuracy cost of using simple generic force fields to predict the adsorption of CO2, CH4, N2 and their mixtures on MFI. We employed the GCMC technique for this investigation. Different models and force fields to describe adsorbates and adsorbent were tested. The force fields performances were estimated through comparison with available adsorption experimental data. Transferability was evaluated on the prediction of pure and mixtures adsorption on CHA, LTA and FER. The results showed that a simple force field presented similar performance when compared to a more sophisticated one.

One of the most investigated properties of porous crystalline metal-organic frameworks (MOFs) is their potential flexibility to undergo large changes in unit cell size upon guest adsorption or other stimuli, referred to as “breathing”. Computationally, such phase transitions are usually investigated using periodic boundary conditions, where the system’s volume can be controlled directly. However, we have recently shown that important aspects like the formation of a moving interface between the open and the closed pore form or the free energy barrier of the first-order phase transition and its size effects can best be investigated using non-periodic nanocrystallite (NC) models [Keupp et al. (Adv. Theory Simul., 2019, 2, 1900117)]. In this case, the application of pressure is not straightforward, and a distance constraint was used to mimic a mechanical strain enforcing the reaction coordinate. In contrast to this prior work, a mediating particle bath is used here to exert an isotropic hydrostatic pressure on the MOF nanocrystallites. The approach is inspired by the mercury nanoporosimetry used to compress flexible MOF powders. For such a mediating medium, parameters are presented that require a reasonable additional numerical effort and avoid unwanted diffusion of bath particles into the MOF pores. As a proof-of-concept, NCs of pillared-layer MOFs with different linkers and sizes are studied concerning their response to external pressure exerted by the bath. By this approach, an isotropic pressure on the NC can be applied in analogy to corresponding periodic simulations, without any bias for a specific mechanism. This allows a more realistic investigation of the breathing phase transformation of a MOF NC and further bridges the gap between experiment and simulation.

“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.

The longevity of asphalt pavements is a key focus of road engineering, which closely relates to the self-healing ability of bitumen. Our work aims to establish a CGMD model and matched force field for bitumen and break through the limitations of the research scale to further explore the microscopic mechanism of bitumen self-healing. In this study, a CGMD mapping scheme containing 16 kinds of beads is proposed, and the non-bond potential energy function and bond potential energy function are calculated based on all-atom simulation to construct and validate a coarse-grained model for bitumen. On this basis, a micro-crack model with a width of 36.6nm is simulated, and the variation laws of potential energy, density, diffusion coefficient, relative concentration and temperature in the process of bitumen self-healing are analyzed with the cracking rate parameter proposed to characterize the degree of bitumen crack healing. The results show that the computational size of the coarse-grained simulation is much larger than that of the all-atom, which can explain the self-healing mechanism at the molecular level. In the self-healing process, non-bonded interactions dominate the molecular movement, and differences in the decreased rate of diffusion among the components indicate that saturates and aromatics play a major role in self-healing. Meanwhile, the variations in crack rates reveal that healing time is inversely proportional to temperature. The impact of increasing temperature on reducing healing time is most obvious when the temperature approaches the glass transition temperature (300 K).

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.

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]

A protein may exist as an ensemble of different conformations in solution, which cannot be represented by a single static structure. Molecular dynamics (MD) simulation has become a useful tool for sampling protein conformations in solution, but force fields and water models are important issues. This work presents a case study of the bacteriophage T4 lysozyme (T4L). We have found that MD simulations using a classic AMBER99SB force field and TIP4P water model cannot well describe hinge-bending domain motion of the wild-type T4L at the timescale of one microsecond. Other combinations, such as a residue-specific force field called RSFF2+ and a dispersion-corrected water model TIP4P-D, are able to sample reasonable solution conformations of T4L, which are in good agreement with experimental data. This primary study may provide candidates of force fields and water models for further investigating conformational transition of T4L. [ABSTRACT FROM AUTHOR]

In the present manuscript, a mathematical model of steady and incompressible Casson fluid in a non-uniform tube having many stenoses in the presence of a force field is analyzed. Using mild stenosis approximation and appropriate boundary conditions, analytical expressions for velocity, pressure drop, impedance, and wall share stress have been computed due to their importance in the rheology of blood. The Casson fluid is used to depict the behavior of blood flow. The effects of different physical constraints on resistance to the flow and wall shear stress of the fluid are examined. The study ascertains that resistance to the flow and wall shear stress is maximum at duck of stenosis. It is also explored that an increase in the size of the stenosis in the artery affects the normal flow of the blood through vessels in the heart, body, and brain and this may lead to major cardiac disease problems like stroke, heart attack, etc. [ABSTRACT FROM AUTHOR]

Metal ions play important roles in various biological systems. Molecular dynamics (MD) using classical force field has become a popular research tool to study biological systems at the atomic level. However, meaningful MD simulations require reliable models and parameters. Previously we showed that the 12-6 Lennard-Jones nonbonded model for ions could not reproduce the experimental hydration free energy (HFE) and ion-oxygen distance (IOD) values simultaneously when ion has a charge of +2 or higher. We discussed that this deficiency arises from the overlook of the ion-induced dipole interaction in the 12-6 model, and this term is proportional to 1/r4 based on theory. Hence, we developed the 12-6-4 model and showed it could solve this deficiency in a physically meaningful way. However, our previous research also found that the 12-6-4 model overestimated the coordination numbers (CNs) for some highly charged metal ions. And we attributed this artifact to that the current 12-6-4 scheme lacks a correction for the interactions among the first solvation shell water molecules. In the present study, we considered the ion-included dipole interaction by using the 12-6 model with adjusting the atomic charges of the first solvation shell water molecules. This strategy not only considers the ion-induced dipole interaction between ion and the first solvation shell water molecules but also well accounts for the increased repulsion among these water molecules compared to the bulk water molecules. We showed this strategy could well reproduce the experimental HFE and IOD values for Mg2+, Zn2+, Al3+, Fe3+, and In3+ and solve the CN overestimation issue of the 12-6-4 model for Fe3+ and In3+. Moreover, our simulation results showed good agreement with previous ab initio MD simulations. In addition, we derived the physical relationship between the C4 parameter and induced dipole moment, which agreed well with our simulation results. Finally, we discussed the implications of the present work for simulating metalloproteins. Due to the fluctuating charge model uses a similar concept to the 12-6 model with adjusting atomic charges, we believe the present study builds a bridge between the 12-6-4 model and the fluctuating charge model.

Infrared (IR) spectroscopy is a valuable tool to obtain information about protein secondary structure. The far-infrared (FIR) spectrum is characterized by a complex combination of different molecular contributions which, for small molecules, may be interpreted with the help of quantum-mechanical (QM) calculations. Unfortunately, the high computational cost of QM calculations makes them inapplicable to larger molecules, such as proteins and peptides. In this work, we present a theoretical study on the secondary structure, molecular properties, and vibrational spectra of different peptides, using both a classical and a QM approach. Our results show that the amide I main peak value, and related quantities, such as dipole strength (DS) and transition dipole moment (TDM), depends on protein secondary structure; in particular, from QM calculations arises that α-rich molecular systems present lower intensities than β-rich ones. Furthermore, it is possible to decouple and identify the intensity of the different contributions of the inter- and intra-molecular motions which characterize the FIR spectrum, starting from the results obtained with QM calculations.

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.

The development of accurate and efficient potential energy functions for the molecular dynamics simulation of metalloproteins has long been a great challenge for the theoretical chemistry community. An artificial neural network provides the possibility to develop potential energy functions with both the efficiency of the classical force fields and the accuracy of the quantum chemical methods. In this work, neural network potentials were automatically constructed by using the ESOINN-DP method for typical zinc proteins. For the four most common zinc coordination modes in proteins, the potential energy, atomic forces, and atomic charges predicted by neural network models show great agreement with quantum mechanics calculations and the neural network potential can maintain the coordination geometry correctly. In addition, MD simulation and energy optimization with the neural network potential can be readily used for structural refinement. The neural network potential is not limited by the function form and complex parameterization process, and important quantum effects such as polarization and charge transfer can be accurately considered. The algorithm proposed in this work can also be directly applied to proteins containing other metal ions.

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]

Force fields are actively used to study RNA. Development of accurate force fields relies on a knowledge of how the variation of properties of molecules depends on their structure. Detailed scrutiny of RNA’s conformational preferences is needed to guide such development. Towards this end, minimum energy structures for each of a set of 16 small RNA-derived molecules were obtained by geometry optimization at the HF/6-31G(d,p), B3LYP/apc-1, and MP2/cc-pVDZ levels of theory. The number of minima computed for a given fragment was found to be related to both its size and flexibility. Atomic electrostatic multipole moments of atoms occurring in the [HO-P(O3)-CH2-] fragment of 30 sugar-phosphate-sugar geometries were calculated at the HF/6-31G(d,p) and B3LYP/apc-1 levels of theory, and the transferability of these properties between different conformations was investigated. The atomic multipole moments were found to be highly transferable between different conformations with small standard deviations. These results indicate necessary elements of the development of accurate RNA force fields. [ABSTRACT FROM AUTHOR]

Nuclear magnetic resonance spectroscopy is used routinely for studying the three-dimensional structures and dynamics of proteins and nucleic acids. Structure determination is usually done by adding restraints based upon NMR data to a classical energy function and performing restrained molecular simulations. Here we report on the implementation of a script to extract NMR restraints from a NMR-STAR file and export it to the GROMACS software. With this package it is possible to model distance restraints, dihedral restraints and orientation restraints. The output from the script is validated by performing simulations with and without restraints, including the ab initio refinement of one peptide. [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]

[Display omitted] • The importance of DL-accelerated MD simulation in petroleum engineering. • Evaluation of three open-source packages relevant to the DL force field. • Overview of applications of the three packages with hands-on testing. • Potential molecular dynamics for oil and gas problems evaluated with practical examples. In the last few decades, deep learning (DL) has afforded solutions to macroscopic problems in petroleum engineering, but mechanistic problems at the microscale have not benefited from it. Mechanism studies have been the strong demands for the emerging projects, such as the gas storage and hydrate production, and for some problems encountered in the storage process, which are common found as the chemical interaction between injected gas and mineral, and the formation of hydrate. Emerging advances in DL technology enable solving molecular dynamics (MD) with quantum accuracy. The conventional quantum chemical method is computational expensive, whereas the classical MD method cannot guarantee high accuracy because of its empirical force field parameters. With the help of the DL force field, precision at the quantum chemistry level can be achieved in MD. Moreover, the DL force field promotes the computational speed compared with first-principles calculations. In this review, the basic knowledge of the molecular force field and deep neural network (DNN) is first introduced. Then, three representative open-source packages relevant to the DL force field are introduced. As the most common components in the development of oil and gas reservoirs, water and methane are studied from the aspects of computational efficiency and chemical reaction respectively, providing the foundation of oil and gas researches. However, in the oil and gas problems, the complex molecular topo structures and various element types set a high challenge for the DL techniques in MD. Regarding the computational efficiency, it needs improvement via GPU and parallel accelerations to compete with classical MD. Even with such difficulties, the booming of this technique in the area of petroleum engineering can be predictable. [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]

[Display omitted] • Anhydrous, mono, di and trihydrate species were studied by using DFT calculations. • Mapped MEP surfaces show increase in the energies values from anhydrous to trihydrate. • Complete vibrational assignments of all the species are reported. • NBO studies reveal that the trihydrate in the gas phase is the most stable species. • The dihydrate is the most reactive species in gas phase and the anhydrous in solution. Theoretical structures of anhydrous (A), mono (M), di (D) and trihydrate (T) species of bronchodilator theophylline agent have been studied by using hybrid B3LYP/6–311++G** calculations to analyse the role of water molecules in its properties, reactivities and behaviours. The dipole moments increase with the number of water molecules (N) while the volumes (V) and solvation energies evidence behaviours lineal with N. D species shows higher V contraction, as T while A and M show slight V expansions. MEP surfaces show increase in energy from A to T. NBO studies reveal that T is most stable in the gas phase while A in solution. Gap values show that D is the most reactive species in gas phase while A in solution. Complete assignments of all the species and their scaled force constants are reported including librations of water molecules. [ABSTRACT FROM AUTHOR]

The development of accurate molecular mechanics force fields is a significant challenge that must be addressed for the continued success of molecular simulation. We developed the ForceBalance method to automatically derive accurate force field parameters using flexible combinations of experimental and theoretical reference data. The method is demonstrated in the parametrization of two rigid water models, yielding new parameter sets (TIP3P-FB and TIP4P-FB) that accurately describe many physical properties of water.

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.

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.

Background: Force fields are used in a wide variety of contexts for classical molecular simulation, including studies on protein-ligand binding, membrane permeation, and thermophysical property prediction. The quality of these studies relies on the quality of the force fields used to represent the systems. Methods: Focusing on small molecules of fewer than 50 heavy atoms, our aim in this work is to compare nine force fields: GAFF, GAFF2, MMFF94, MMFF94S, OPLS3e, SMIRNOFF99Frosst, and the Open Force Field Parsley, versions 1.0, 1.1, and 1.2. On a dataset comprising 22,675 molecular structures of 3,271 molecules, we analyzed force field-optimized geometries and conformer energies compared to reference quantum mechanical (QM) data. Results: We show that while OPLS3e performs best, the latest Open Force Field Parsley release is approaching a comparable level of accuracy in reproducing QM geometries and energetics for this set of molecules. Meanwhile, the performance of established force fields such as MMFF94S and GAFF2 is generally somewhat worse. We also find that the series of recent Open Force Field versions provide significant increases in accuracy. Conclusions: This study provides an extensive test of the performance of different molecular mechanics force fields on a diverse molecule set, and highlights two (OPLS3e and OpenFF 1.2) that perform better than the others tested on the present comparison. Our molecule set and results are available for other researchers to use in testing.

Abstract Marcasite mineral is a metastable iron sulphide, α-FeS2, less known and less abundant than pyrite β-FeS2. Their chemical compositions are similar, formed by S22- dimers and Fe2+ species, but the marcasite crystal structure is orthorhombic while pyrite is cubic. The thermodynamic stability of a range of selected surfaces and their kinetic growth are analysed with molecular mechanics simulations implemented in METADISE code. The most stable surface of marcasite corresponds to the (101) surface having the lowest surface energy (marcasite γ 101 = 1.06 Jm-2) and the most favoured kinetic growth rate is expected for the [010] direction (the attachment energy of (010) surface is 0.20 |eV|/at). Mirror twinning is another characteristic of the mineral contributing to a distinctive crystal growth forming different shapes such as striated needles or pseudo-pentagonal flowers. Similarities, differences and overgrowth between the two dimorphs are highlighted.