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We present an efficient polarizable electrostatic model based on direct polarization, SMIRNOFF specification, and bond charge corrections method for improved electrostatics in molecular dynamics (MD) simulations. We developed software to derive electrostatic parameters from quantum mechanical (QM) calculations and benchmarked our model on calculations of gas-phase and condensed-phase properties. Benchmark results show good agreements with reference values, in particular providing critical corrections to dielectric constants of nonpolar organic liquids. This resultsuggests that our model is a good starting point for developing a general and affordable polarizable force field for biomolecular simulations.

This is a keynote presentation at the 5th Open Force Field Workshop (virtual meeting) providing a progress update for the past year and the near-future plans for force field and infrastructure development., Research supported by NIH R01 GM132386.

In this research, a combined study on structures and vibrational spectra of antiviral rimantadine have been performed using hybrid B3LYP/6-311 thorn thorn G** calculations and the scaled quantum force field (SQMFF) proced-ure. Harmonic force fields and scaled force constants of Free Base (FB), Cationic (CA) and Hydrochloride (HCl) species derived from the antiviral rimantadine have been calculated in gas phase and in aqueous solution using normal internal coordinates and scaling factors. Good correlations were acquired comparing the theoretical IR, Raman, 1H- 13C-NMR and UV spectra of three species with the analogous experimental ones, suggesting probably, the presence of all them in both phases. The main force constants of three species have evidenced lower values than the corresponding to antiviral amantadine. The ionic character of N1-H33 center dot center dot center dot Cl36 bond of HCl species in aqueous solution evidence positive Mulliken charge on N1 atom indicating that this species is as CA one. Rimantadine presents higher solvation energies in water than other antiviral species, such as chloroquin, niclo-samide, cidofovir and brincidofovir. The FB and HCl species of rimantadine are slightly less reactive than the corresponding to amantadine while the opposite is observed for the CA species. The predicted ECD spectra for the FB and CA species show positive Cotton effect different from the negative observed for the HCl one. These different behaviours of three species of rimantadine could probably explain the differences observed in the in-tensities of bands predicted in the electronic spectra of these species.

We introduce TUPÃ, a Python-based algorithm to calculate and analyze electric fields in molecular simulations. To demonstrate the features in TUPÃ, we present three test cases in which the orientation and magnitude of the electric field exerted by biomolecules help explain biological phenomena or observed kinetics. As part of TUPÃ, we also provide a PyMOL plugin to help researchers visualize how electric fields are organized within the simulation system. The code is freely available and can be obtained at https://mdpoleto.github.io/tupa/. Accepted version

Electrostatic interactions have a determining role in the conformational and dynamic behavior of polyelectrolyte molecules. In this study, anionic polyelectrolyte molecules, poly(glutamic acid) (PGA) and poly(aspartic acid) (PASA), in a water solution with the most commonly used K+ or Na+ counterions, were investigated using atomistic molecular dynamics (MD) simulations. We performed a comparison of seven popular force fields, namely AMBER99SB-ILDN, AMBER14SB, AMBER-FB15, CHARMM22*, CHARMM27, CHARMM36m and OPLS-AA/L, both with their native parameters and using two common corrections for overbinding of ions, the non-bonded fix (NBFIX), and electronic continuum corrections (ECC). These corrections were originally introduced to correct for the often-reported problem concerning the overbinding of ions to the charged groups of polyelectrolytes. In this work, a comparison of the simulation results with existing experimental data revealed several differences between the investigated force fields. The data from these simulations and comparisons with previous experimental data were then used to determine the limitations and strengths of these force fields in the context of the structural and dynamic properties of anionic polyamino acids. Physical properties, such as molecular sizes, local structure, and dynamics, were studied using two types of common counterions, namely potassium and sodium. The results show that, in some cases, both the macroion size and dynamics depend strongly on the models (parameters) for the counterions due to strong overbinding of the ions and charged side chain groups. The local structures and dynamics are more sensitive to dihedral angle parameterization, resulting in a preference for defined monomer conformations and the type of correction used. We also provide recommendations based on the results.

Graphical abstract The synthetic cyclohexenecarboxylate ester antiviral Oseltamivir (O) have been theoretically studied by B3LYP/6–311 + + G** calculations to estimate its reactivity and behaviour in gas and aqueous media. The most stable structure obtained in above media is consistent with that reported experimental for Oseltamivir phosphate. The solvation energy value of (O) in aqueous media is between the predicted for antiviral Idoxuridine and Ribavirin. Besides, (O) containing a NH2 group and NH group reveals lower solvation energy compared with other antiviral agents with an NH2 group, such as Ribavirin, Cidofovir, and Brincidofovir. Atomic charges on N and O atoms in acceptors and donor groups reveal different behaviours in both media, while the natural bond orbital (NBO) studies show a raised stability of (O) in aqueous solution. This latter resulted is in concordance with the lower reactivity evidenced in water. Frontier orbital studies have revealed that (O) in gas phase has a very similar gap value to antiviral Cidofovir used against the ebola disease, while Chloroquine in the two media are more reactive than (O). This study will allow to identify (O) by using vibrational spectroscopy because the 144 vibration modes expected have been assigned using the harmonic force fields calculated from the scaled mechanical force field methodology (SQMFF). Scaled force constants for (O) in the mentioned media are also reported for first time. Due to hydration of the C = O and NH2 groups by solvent molecules, the calculations in solution produce variations not only in the IR wavenumbers bands, but also in their intensities. Supplementary Information The online version contains supplementary material available at 10.1007/s00894-021-04962-3.

Solving the dendrite growth problem is critical for the development of lithium metal anode for high-capacity batteries. In this work, a machine learning force field model in combination with a self-consistent continuum solvation model is used to simulate the morphology evolution of dendrites in a working electrolyte environment. The dynamic evolution of the dendrite morphology can be described in two stages. In the first stage, the energy reduction of the surface atoms induces localized reorientation of the originally single-crystal dendrite and the formation of multiple domains. In the second stage, the energy reduction of internal atoms drives the migration of grain boundaries and the slipping of crystal domains. The results indicate that the formation of multiple domains might help to stabilize the dendrite, as a higher temperature trajectory in a single crystal dendrite without domains shows a higher dendrite collapsing rate. Several possible modes of morphological evolutions are also investigated, including surface diffusion of adatoms and configuration twists from [100] exposed surfaces to [110] exposed surfaces. In summary, reducing the surface and grain boundary energy drives the morphology evolution. Based on the analysis of these driving forces, some guidelines are suggested for designing a more stable lithium metal anode.

Quantum chemistry in the form of density functional theory (DFT) calculations is a powerful numerical experiment for predicting intermolecular interaction energies. However, no chemical insight is gained in this way beyond predictions of observables. Energy decomposition analysis (EDA) can quantitatively bridge this gap by providing values for the chemical drivers of the interactions, such as permanent electrostatics, Pauli repulsion, dispersion, and charge transfer. These energetic contributions are identified by performing DFT calculations with constraints that disable components of the interaction. This review describes the second-generation version of the absolutely localized molecular orbital EDA (ALMO-EDA-II). The effects of different physical contributions on changes in observables such as structure and vibrational frequencies upon complex formation are characterized via the adiabatic EDA. Example applications include red- versus blue-shifting hydrogen bonds; the bonding and frequency shifts of CO, N2, and BF bound to a [Ru(II)(NH3)5]2 + moiety; and the nature of the strongly bound complexes between pyridine and the benzene and naphthalene radical cations. Additionally, the use of ALMO-EDA-II to benchmark and guide the development of advanced force fields for molecular simulation is illustrated with the recent, very promising, MB-UCB potential.

Many pairwise additive force fields are in active use for intrinsically disordered proteins (IDPs) and regions (IDRs), some of which modify energetic terms to improve the description of IDPs/IDRs but are largely in disagreement with solution experiments for the disordered states. This work considers a new direction—the connection to configurational entropy—and how it might change the nature of our understanding of protein force field development to equally well encompass globular proteins, IDRs/IDPs, and disorder-to-order transitions. We have evaluated representative pairwise and many-body protein and water force fields against experimental data on representative IDPs and IDRs, a peptide that undergoes a disorder-to-order transition, for seven globular proteins ranging in size from 130 to 266 amino acids. We find that force fields with the largest statistical fluctuations consistent with the radius of gyration and universal Lindemann values for folded states simultaneously better describe IDPs and IDRs and disorder-to-order transitions. Hence, the crux of what a force field should exhibit to well describe IDRs/IDPs is not just the balance between protein and water energetics but the balance between energetic effects and configurational entropy of folded states of globular proteins.

In this article, two main approaches to the prediction of thermal conductivities by molecular dynamics (MD) simulations are discussed, namely non-equilibrium molecular dynamics simulations (NEMD) and the application of the Green–Kubo formula, i.e., EMD. NEMD methods are more affected by size effects than EMD methods. The thermal conductivities of silicone rubbers in special were found as a function of the degree of crosslinking. Moreover, the thermal conductivities of thermoplastic polyurethane as function of the mass fraction of soft segments were obtained by those MD simulations. All results are in good agreement with data from the experimental literature. After the analysis of normalized heat flux autocorrelation functions, it has been revealed that heat in the polymers is mainly transferred by low-frequency phonons. Simulation details as well as advantages and disadvantages of the single methods are discussed in the article.

Background Many people with incomplete spinal cord injury (iSCI) have the ability to maneuver while walking. However, neuromuscular impairments create challenges to maintain stability. How people with iSCI maintain stability during walking maneuvers is poorly understood. Thus, this study compares maneuver performance in varying external conditions between persons with and without iSCI to better understand maneuver stabilization strategies in people with iSCI. Methods Participants with and without iSCI walked on a wide treadmill and were prompted to perform lateral maneuvers between bouts of straight walking. Lateral force fields applied to the participants’ center of mass amplified or attenuated the participants’ movements, thereby increasing the capability of the study to capture behavior at varied levels of challenge to stability. Results By examining metrics of stability, step width, and center of mass dynamics, distinct strategies emerged following iSCI. The minimum margin of stability (MOSmin) on each step during maneuvers indicated persons with iSCI generally adapted to amplified and attenuated force fields with increased stability compared to persons without iSCI, particularly using increased step width and reduced center of mass excursion on maneuver initiation. In the amplified field, however, persons with iSCI had a reduced MOSmin when terminating a maneuver, likely due to the challenge of the force field opposing the necessary lateral braking. Persons without iSCI were more likely to rely on or oppose the force field when appropriate for movement execution. Compared to persons with iSCI, they reduced their MOSmin to initiate maneuvers in the attenuated and amplified fields and increased their MOSmin to arrest maneuvers in the amplified field. Conclusions The different force fields were successful in identifying relatively subtle strategy differences between persons with and without iSCI. Specifically, persons with iSCI adopted increased step width and reduction in center of mass excursion to increase maneuver stability in the amplified field. The amplified field may provoke practice of stable and efficient initiation and arrest of walking maneuvers. Overall, this work allows better framing of the stability mechanisms used following iSCI to perform walking maneuvers.

This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in J. Chem. Phys. 153, 124109 (2020) and may be found at https://doi.org/10.1063/5.0023005., Modern machine learning force fields (ML-FF) are able to yield energy and force predictions at the accuracy of high-level ab initio methods, but at a much lower computational cost. On the other hand, classical molecular mechanics force fields (MM-FF) employ fixed functional forms and tend to be less accurate, but considerably faster and transferable between molecules of the same class. In this work, we investigate how both approaches can complement each other. We contrast the ability of ML-FF for reconstructing dynamic and thermodynamic observables to MM-FFs in order to gain a qualitative understanding of the differences between the two approaches. This analysis enables us to modify the generalized AMBER force field by reparametrizing short-range and bonded interactions with more expressive terms to make them more accurate, without sacrificing the key properties that make MM-FFs so successful.

Many molecular simulation methods use force fields to help model and simulate molecules and their behavior in various environments. Force fields are sets of functions and parameters used to calculate the potential energy of a chemical system as a function of the atomic coordinates. Despite the widespread use of force fields, their inadequacies are often thought to contribute to systematic errors in molecular simulations. Furthermore, different force fields tend to give varying results on the same systems with the same simulation settings. Here, we present a pipeline for comparing the geometries of small molecule conformers. We aimed to identify molecules or chemistries that are particularly informative for future force field development because they display inconsistencies between force fields. We applied our pipeline to a subset of the eMolecules database, and highlighted molecules that appear to be parameterized inconsistently across different force fields. We then identified over-represented functional groups in these molecule sets. The molecules and moieties identified by this pipeline may be particularly helpful for future force field parameterization.

O sulfeto de hidrogênio (H2S) está muito presente na produção de petróleo e gás natural, estima-se que cerca de 30% da produção mundial de gás natural contém esse contaminante (SKRITC, 2006). Assim, torna-se necessário o projeto de unidades de remoção de H2S para especificação de transporte e venda. Entretanto, nas condições de pressão que as unidades produtivas operam, há escassez de dados experimentais levando à dificuldade na validação de modelos termodinâmicos capazes de descrever esse sistema. O uso de simulação molecular tem permitido a avaliação de diversos fenômenos em condições de difícil obtenção experimental. Assim, o presente trabalho apresenta uma avaliação sobre a influência do modelo molecular e respectivos campos de força na predição do equilíbrio líquido vapor (ELV) de misturas binárias de H2S com CO2 e CH4. O trabalho utiliza os principais modelos de campos de força apresentados na literatura para representar o sulfeto de hidrogênio em combinação com o metano e o dióxido de carbono representados pelos modelos de átomos agrupados – United Atom (UA) e átomos explícitos – All Atom (AA). Os resultados foram comparados com dados experimentais e de simulação previamente reportados na literatura. Foi observado que o uso de modelos moleculares simplificados, do tipo United Atom, para representar o CH4 e o CO2, apresentaram desempenho satisfatório, com possibilidade de melhoria com o uso de novas regras de combinação. Também foi observado um bom desempenho na aplicação do modelo proposto por Zhang e Duan (2015) para o CO2 na descrição de misturas binárias e ternárias contendo H2S. It is usual to find hydrogen sulfide (H2S) in oil and natural gas production, it´s estimated that around 30% of the world's natural gas production contains this contaminant (SKRITC, 2006). Therefore, it is required the design of H2S removal units for transport and sales specification. However, under the pressure conditions of the productive units, there is a lack of experimental data leading to difficulty in validating thermodynamic models capable of describing this system. The use of molecular simulation has allowed the evaluation of several phenomena under conditions where experiments are difficult. Thus, the present work presents an evaluation on the influence of the force fields on the prediction of the liquid vapor equilibrium (ELV) of the binary mixtures H2S with CO2 and CH4. The work uses the popular force field models presented in the literature to represent hydrogen sulfide in combination with methane and carbon dioxide represented by grouped atom model - United Atom (UA) and explicit Atom (AA) models. The results were compared with experimental and simulation data previously reported in the literature. It was observed that the use of simplified United Atom molecular models to represent CH4 and CO2 presented satisfactory performance, with the possibility of improvement with the use of new combining rules. It was observed also a good performance with the application of the model proposed by Zhang e Duan (2015) for CO2 in binary and ternary mixtures with H2S. Dissertação (Mestrado)

International audience; Many key industrial processes, from electricity production, conversion, and storage to electrocatalysis or electrochemistry in general, rely on physical mechanisms occurring at the interface between a metallic electrode and an electrolyte solution, summarized by the concept of an electric double layer, with the accumulation/depletion of electrons on the metal side and of ions on the liquid side. While electrostatic interactions play an essential role in the structure, thermodynamics, dynamics, and reactivity of electrode-electrolyte interfaces, these properties also crucially depend on the nature of the ions and solvent, as well as that of the metal itself. Such interfaces pose many challenges for modeling because they are a place where quantum chemistry meets statistical physics. In the present review, we explore the recent advances in the description and understanding of electrode-electrolyte interfaces with classical molecular simulations, with a focus on planar interfaces and solvent-based liquids, from pure solvent to water-in-salt electrolytes.

This work came out of a CECAM discussion meeting.; International audience; Machine learning encompasses a set of tools and algorithms which are now becoming popular in almost all scientific and technological fields. This is true for molecular dynamics as well, where machine learning offers promises of extracting valuable information from the enormous amounts of data generated by simulation of complex systems. We provide here a review of our current understanding of goals, benefits, and limitations of machine learning techniques for computational studies on atomistic systems, focusing on the construction of empirical force fields from ab-initio databases and the determination of reaction coordinates for free energy computation and enhanced sampling.

A selection of several aromatic molecules, representative of the important class of heterocyclic compounds, has been considered for testing and validating an automated Force Field (FF) parametrization protocol, based only on Quantum Mechanical data. The parametrization is carried out separately for the intra- and intermolecular contributions, employing respectively the Joyce and Picky software packages, previously implemented and refined in our research group. The whole approach is here automated and integrated with a computationally effective yet accurate method, devised very recently ( J. Chem. Theory Comput., 2018, 14, 543-556) to evaluate a large number of dimer interaction energies. The resulting quantum mechanically derived FFs are then used in extensive molecular dynamics simulations, in order to evaluate a number of thermodynamic, structural, and dynamic properties of the heterocycle's gas and liquid phases. The comparison with the available experimental data is good and furnishes a validation of the presented approach, which can be confidently exploited for the design of novel and more complex materials.

Falk Hoffmann (Ruhr University Bochum) presented his work on improving torsional barriers associated with methyl group rotations in amino acid side-chains in AMBER and CHARMM force fields by using NMR relaxation rates. This study is available as a preprint on ChemrXiv. This talk is a part of OpenFF Webinars that took place on Sep 20, 2019. Abstract: The internal dynamics of proteins occurring on time scales from picoseconds to nanoseconds can be sensitively probed by nuclear magnetic resonance (NMR) spin relaxation experiments, as well as by molecular dynamics (MD) simulations. This complementarity offers unique opportunities, provided that the two methods are compared at a suitable level. Recently, several groups have used MD simulations to compute the spectral density of backbone and side-chain molecular motions, and to predict NMR relaxation rates from these. Unfortunately, in the case of methyl groups in protein side-chains, inaccurate energy barriers to methyl rotation were responsible for a systematic discrepancy in the computed relaxation rates. In this talk I will present how we used NMR relaxation rates to identify disagreements between simulation and experiment for these energy barriers. The corresponding dihedral angle terms in AMBER and CHARMM force fields which are responsible for these energy barriers are subsequently improved and correspondence between experiment and simulation could be regained by emending the MD force field with accurate coupled cluster quantum chemical calculations. Improved methyl group rotation barriers were derived, such that the NMR relaxation data obtained from the MD simulations now also display very good agreement with experiment. Furthermore, I will show how these energy barriers influence the validity of the Lipari-Szabo model for protein side-chains which is used to extract generalized order parameters from NMR relaxation experiments and MD simulations.

Chuan Tian presented his work on Amber ff19SB force field at the Chodera lab at MSKCC on Sep 12, 2019. The uploaded material contains presentation slides and video. Abstract: Molecular dynamics (MD) simulations have become increasingly popular in studying the motions and functions of biomolecules. The accuracy of the simulation, however, is highly determined by the classical force field (FF), a set of functions with adjustable parameters to compute the potential energy from atomic positions. The relatively simple terms in most of the current force fields are computationally advantageous which enable the simulation of biologically important macromolecules at biologically relevant timescale. However, the overall quality of the FF, including our previously published ff14SB, is limited by the assumptions that were made years ago. (1) An overly symmetric φ/ψ dihedral energy map arises from the uncoupled cosine functions used to model these two degrees of freedom in the protein backbone. (2) The model does not show sufficient dependence of the backbone energetics on the amino acids, probably because the parameters developed for the simple amino acid Ala were applied to all other amino acids without checking the quality of the transferability. (3) The fixed partial charges were trained for aqueous solution, but the dihedral parameters were all fit to gas-phase QM, thus the resulting dihedral parameters actually counteract the intended polarization effect and introduce significant internal inconsistency in the model. In our new force field ff19SB, we have significantly improved the backbone profiles for all 20 amino acids. We have developed an amino-acid specific CMAP term by fitting against in-solution QM data. Our results show that the new FF not only better reproduces various types of experimental data on amino-acid specific properties such as NMR scalar coupling and helical propensity, but it also improves secondary structure content in small peptides and maintains reasonably accurate protein NMR order parameters.

Рассмотрена структурная теория возникновения автоколебаний, особенности структуры базового силового поля, структурная теория автоколебаний с точки зрения создания анизотропных силовых полей при использовании структурированных державок токарных резцов. Рассмотрены траектории относительного колебания резца при точении., The structural theory of the occurrence of self-oscillations, features of the structure of the base force field, the structural theory of self-oscillations from the point of view of creating anisotropic force fields using structured holders of turning tools are considered. The trajectories of relative oscillation of the cutter during turning are considered.

Michael Schauperl and Hyesu Jang describe how molecules will be parameterized for fixed charge and polarizable SMIRNOFF force fields at Open Force Field Consortium Workshop in San Diego, Jan 8 2019.

Рассмотрена структурная теория возникновения автоколебаний, оценка сил резания и сил упругости в создании суммарных «базовых» силовых полей, образованных этими силами. Проведено исследование второго структурного критерия устойчивости. Разработаны конструкции державок токарных резцов для уменьшения проявления координатной связи., The structural theory of the occurrence of self-oscillations, evaluation of cutting forces and elastic forc-es in the creation of the total "basic" force fields formed by these forces are considered. The study of the second structural stability criterion is carried out. Designs of holders of turning tools for reduction of manifestation of coordinate communication are developed.

The use of Molecular Dynamics (MD) simulations for predicting subtle structural, thermomechanical and related characteristics of lignocellulosic systems is studied. A historical perspective and the current state of the art are discussed. The use of parameterised MD force fields, scaling up simulations via high performance computing and intrinsic molecular mechanisms influencing the mechanical, thermal and chemical characteristics of lignocellulosic systems and how these can be predicted and modelled using MD is shown. Individual discussions on the MD simulations of the lignin, cellulose, lignin-carbohydrate complex (LCC) and how MD can elucidate the role of water on the surface and microstructural characteristics of these lignocellulosic systems is shown. In addition, the use of MD for unearthing molecular mechanisms behind lignin-enzyme interactions during precipitation processes and the deforming/structure weakening brought about by cellulosic interactions in some lignocellulosic systems is both predicted and quantified. MD results from relatively smaller systems comprised of several hundred to a few thousand atoms and massive multi-million atom systems are both discussed. The versatility and effectiveness of MD based on its ability to provide viable predictions from both smaller and massive starting systems is presented in detail.

This review aims to examine literature where different force fields are compared by their performances in conformational analysis and searching of organic molecules. Conformational analysis studies are those where energies and/or geometries of conformers are evaluated with force fields; the closer the values are to experiment or ab initio calculations, the better the force field performance. In conformational searching, an algorithm alters the geometry of a chemical system, followed by force field energy minimisation, then the process repeats, ideally until all conformations of the system are found. For conformational analysis, MM2, MM3 and MMFF94 often showed strong performances and their use is recommended. The polarisable AMOEBA force field consistently had strong performance and further comparisons including AMOEBA are advised. UFF showed very weak performance and is not recommended. For conformational searching, a distinct lack of comparisons were found, and the need for more work is emphasised.

Atomic-scale modeling and understanding of materials have made remarkable progress, but they are still fundamentally limited by the large computational cost of explicit electronic-structure methods such as density-functional theory. This Progress Report shows how machine learning (ML) is currently enabling a new degree of realism in materials modeling: by “learning” electronic-structure data, ML-based interatomic potentials give access to atomistic simulations that reach similar accuracy levels but are orders of magnitude faster. A brief introduction to the new tools is given, and then, applications to some select problems in materials science are highlighted: phase-change materials for memory devices; nanoparticle catalysts; and carbon-based electrodes for chemical sensing, supercapacitors, and batteries. It is hoped that the present work will inspire the development and wider use of ML-based interatomic potentials in diverse areas of materials research.

International audience; Providing clean water and sufficient affordable energy to all without compromising the environment is a key priority in the scientific community. Many recent studies have focused on carbon-based devices in the hope of addressing this grand challenge, justifying and motivating detailed studies of water in contact with carbonaceous materials. Such studies are becoming increasingly important because of the miniaturization of newly proposed devices, with ubiquitous nanopores, large surface-to-volume ratio, and many, perhaps most of the water molecules in contact with a carbon-based surface. In this brief review, we discuss some recent advances obtained via simulations and experiments in the development of carbon-based materials for applications in water desalination. We suggest possible ways forward, with particular emphasis on the synergistic combination of experiments and simulations, with simulations now sometimes offering sufficient accuracy to provide fundamental insights. We also point the interested reader to recent works that complement our short summary on the state of the art of this important and fascinating field.

The behavior of guanidinium chloride at the surface of aqueous solutions is investigated using classical molecular dynamics simulation. It is found that the population of guanidinium ions oriented parallel to the interface is greater in the surface region than in bulk. The opposite is true for ions in other orientations. Overall, guanidinium chloride is depleted in the surface region, in agreement with the fact that addition of guanidinium chloride increases the surface tension of water. The orientational dependence of the surface affinity of the guanidinium cation appears to be related to its anisotropic hydration. To bring the ion to the surface in the parallel orientation does not require hydrogen bonds to be broken, in contrast to other orientations. The surface enrichment of parallelly oriented guanidinium indicates that its solvation is more favorable near the surface than in bulk solution for this orientation. The dependence of the bulk and surface properties of guanidinium on the force field parameters, including polarizability, is also investigated. Despite significant quantitative differences between the force fields, the surface behavior is qualitatively robust. The implications of the above findings for the behaviorof guanidinium groups near biological interfaces are demonstrated on the example of arginine side chain orientations in lysozyme.

cited By 8; International audience; Physical ageing of amorphous polymers well below their glass transition temperature leads to changes in almost all physical properties. Of particular interest is the increase in yield stress and post-yield strain softening that accompanies ageing of these materials. Moreover, at larger strain polymers seem to rejuvenate, i.e. aged and non-aged samples have identical stressstrain responses. Also, plastically deforming an aged sample seems to rejuvenate the polymer. In this work we use molecular dynamic simulations with a detailed force field suitable for macromolecular ensembles to simulate and understand the effects of ageing on the mechanical response of these materials. We show that within the timescales of these simulations it is possible to simulate both ageing and rejuvenation. The short range potentials play an important role in ageing and rejuvenation. A typical yield drop exhibited by glassy polymers is a manifestation of a sudden relaxation in the short range structure of an aged polymer. Moreover, the aged polymers are known to be brittle. We show that this is intimately related to its typical stressstrain response which allows it to carry arbitrarily large mean stresses ahead of a notch. © 2010 Elsevier Ltd. All rights reserved.

The origin of the stereochemical behavior experimentally found in a bile acid-derived biphenyl phosphite is studied by means of quantum mechanical methods. The molecular mechanisms driving the screw sense of the dihedral angle between the two phenyl rings of the biphenyl phosphite unit are investigated with density functional theory calculations. Energy, geometry, and circular dichroism spectra have been computed and compared between the two resulting diastereoisomers. We evaluated the solvent effect on the torsional energy profile by discussing the results obtained for the isolated molecule with those found with polarizable continuum model (PCM) calculations performed in different solvents. The results we obtain with the PCM model do not reproduce the solvent effect on the stereochemical equilibrium of this phosphite.

This article describes the application of our distributed computing framework for crystal structure prediction (CSP) the modified genetic algorithms for crystal and cluster prediction (MGAC), to predict the crystal structure of flexible molecules using the general Amber force field (GAFF) and the CHARMM program. The MGAC distributed computing framework includes a series of tightly integrated computer programs for generating the molecule's force field, sampling crystal structures using a distributed parallel genetic algorithm and local energy minimization of the structures followed by the classifying, sorting, and archiving of the most relevant structures. Our results indicate that the method can consistently find the experimentally known crystal structures of flexible molecules, but the number of missing structures and poor ranking observed in some crystals show the need for further improvement of the potential. © 2009 Wiley Periodicals, Inc. Fil: Seonah, Kim. University of Utah; Estados Unidos Fil: Orendt, Anita M.. University of Utah; Estados Unidos Fil: Ferraro, Marta Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina Fil: Facelli, Julio C.. University of Utah; Estados Unidos

Lattice kinetic equations incorporating the effects of external/internal force fields via a shift of the local fields in the local equilibria, are placed within the framework of continuum kinetic theory. The mathematical treatment reveals that, in order to be consistent with the correct thermo-hydrodynamical description, temperature must also be shifted, besides momentum. New perspectives for the formulation of thermo-hydrodynamic lattice kinetic models of non-ideal fluids are then envisaged. It is also shown that on the lattice, the definition of the macroscopic temperature requires the inclusion of new terms directly related to discrete effects. The theoretical treatment is tested against a controlled case with a non ideal equation of state., Comment: 10 pages, 1 figure

A multilevel approach is presented to assess the ability of several popular dispersion corrected density functionals (M06-2X, CAM-B3LYP-D3, BLYP-D3, and B3LYP-D3) to reliably describe two-body interaction potential energy surfaces (IPESs). To this end, the automated Picky procedure ( Cacelli et al. J. Comput. Chem. 2012 , 33 , 1055 ) was exploited, which consists in parametrizing specific intermolecular force fields through an iterative approach, based on the comparison with quantum mechanical data. For each of the tested functionals, the resulting force field was employed in classical Monte Carlo and Molecular Dynamics simulations, performed on systems of up to 1000 molecules in ambient conditions, to calculate a number of condensed phase properties. The comparison of the resulting structural and dynamic properties with experimental data allows us to assess the quality of each IPES and, consequently, even the quality of the DFT functionals. The methodology is tested on the benzene dimer, commonly used as a benchmark molecule, a prototype of aromatic interactions. The best results were obtained with the CAM-B3LYP-D3 functional. Besides assessing the reliability of DFT functionals in describing aromatic IPESs, this work provides a further step toward a robust protocol for the derivation of sound force field parameters from quantum mechanical data. This method can be relevant in all those cases where standard force fields fail in giving accurate predictions.

© Research India Publications 2015. During the oil production continuous scale build-up takes place by using any operation modes. Increases the pump wear on the working faces, presence of non-organic salts and results in seize of the shaft of electrical centrifugal pump (ECP) and plunger of the subsurface pump, impeller damage. Under these conditions of operation of the mechanized well stock the turnaround is reduced significantly. This is why fighting against scale build-up and prevention of formation thereof is essential. In practice, the main task is identification of the composition and location of salt deposits – the first step is removal thereof and design of efficient methods. Inhibitor removal time in some measure depends on the rate of absorption of salt deposits inhibitor on the productive stratum surface. At the same time the slower its desorption from the formation is and the higher the adsorption of the inhibiting matter is the more efficient and long-lasting is scaling prevention. Scaling prevention is achieved with the use of inhibitors at optimum dosages the values of which in formation water are determined by content of salt-forming ions ??2+ and ???3 -. On the basis of results of experimental works performed on analysis of efficiency of scaling for waters of different ion composition an inhibitor is selected and its optimum dosage is determined.

In this work, we develop coarse-grained (CG) force fields for water, where the effective CG intermolecular interactions between particles are estimated from an accurate description of the macroscopic experimental vapour-liquid equilibria data by means of a molecular-based equation of state. The statistical associating fluid theory for Mie (generalised Lennard-Jones) potentials of variable range (SAFT-VR Mie) is used to parameterise spherically symmetrical (isotropic) force fields for water. The resulting SAFT-γ CG models are based on the Mie (8-6) form with size and energy parameters that are temperature dependent; the latter dependence is a consequence of the angle averaging of the directional polar interactions present in water. At the simplest level of CG where a water molecule is represented as a single bead, it is well known that an isotropic potential cannot be used to accurately reproduce all of the thermodynamic properties of water simultaneously. In order to address this deficiency, we propose two CG potential models of water based on a faithful description of different target properties over a wide range of temperatures: our CGW1-vle model is parameterised to match the saturated-liquid density and vapour pressure; our other CGW1-ift model is parameterised to match the saturated-liquid density and vapour-liquid interfacial tension. A higher level of CG corresponding to two water molecules per CG bead is also considered: the corresponding CGW2-bio model is developed to reproduce the saturated-liquid density and vapour-liquid interfacial tension in the physiological temperature range, and is particularly suitable for the large-scale simulation of bio-molecular systems. A critical comparison of the phase equilibrium and transport properties of the proposed force fields is made with the more traditional atomistic models.

A variety of topics are reviewed in the area of mathematical and computational modeling in biology, covering the range of scales from populations of organisms to electrons in atoms. The use of maximum entropy as an inference tool in the fields of biology and drug discovery is discussed. Mathematical and computational methods and models in the areas of epidemiology, cell physiology and cancer are surveyed. The technique of molecular dynamics is covered, with special attention to force fields for protein simulations and methods for the calculation of solvation free energies. The utility of quantum mechanical methods in biophysical and biochemical modeling is explored. The field of computational enzymology is examined.

A quantum mechanics/molecular mechanics (QM/MM) implementation that uses the Gaussian electrostatic model (GEM) as the MM force field is presented. GEM relies on the reproduction of electronic density by using auxiliary basis sets to calculate each component of the intermolecular interaction. This hybrid method has been used, along with a conventional QM/MM (point charges) method, to determine the polarization on the QM subsystem by the MM environment in QM/MM calculations on 10 individual H(2)O dimers and a Mg(2+)-H(2)O dimer. We observe that GEM gives the correct polarization response in cases when the MM fragment has a small charge, while the point charges produce significant over-polarization of the QM subsystem and in several cases present an opposite sign for the polarization contribution. In the case when a large charge is located in the MM subsystem, for example, the Mg(2+) ion, the opposite is observed at small distances. However, this is overcome by the use of a damped Hermite charge, which provides the correct polarization response.

Polyoxovanadates currently present the most complex and most instructive series of structures of discrete inorganic host-guest species. A parameterization of the CERIUS force field derived from the structural data of examples of this type and of other polyoxovanadate clusters with a considerable variety of structures is reported. (C) 1997 Elsevier Science B.V.

We present an atomistic interatomic potential that with a single set of parameters is able to accurately describe at the same time the elastic, vibrational and thermodynamics properties of semiconductors. We also show that the correct inclusion in the potential of short and long range interactions provides a model for the force field that accurately performs Static Dynamics and Molecular Dynamics. ?? 2013 IEEE. cited By (since 1996)0; Conference of org.apache.xalan.xsltc.dom.DOMAdapter@187d1032 ; Conference Date: org.apache.xalan.xsltc.dom.DOMAdapter@3ab24f2d Through org.apache.xalan.xsltc.dom.DOMAdapter@106c3176; Conference Code:101147

An integrated computational approach built on quantum mechanical (QM) methods, purposely tailored inter- and intra-molecular force fields and continuum solvent models combined with time-independent and time- dependent schemes to account for nuclear motion effects is applied to the spectroscopic investigation of pyrimidine in the gas phase as well as in aqueous and CCl4 solutions. Accurate post-Hartree–Fock methodologies are employed to compute molecular structure, harmonic vibrational frequencies, energies and oscillator strengths for electronic transitions in order to validate the accuracy of approaches rooted into density functional theory with emphasis also on hybrid QM/QM0 models. Within the time-independent approaches, IR spectra are computed including anharmonicities through perturbative corrections while UV–vis line-shapes are simulated accounting for the vibrational structure; in both cases, the environmental effects are described by continuum models. The effects of conformational flexibility, including solvent dynamics, are described through time-dependent models based on purposely DFT-tailored force fields applied to molecular dynamics simulations and on QM computations of spectroscopic properties. Such procedures are exploited to simulate IR and UV–vis spectra of pyrimidine in the gas phase and in solutions, leading in all cases to good agreement with experimental observations and allowing to dissect different effects underlying spectral phenomena.

The prediction capabilities of atomistic simulations of peptides are hampered by different difficulties, including the reliability of force fields, the treatment of the solvent or the adequate sampling of the conformational space. In this work, we have studied the conformational profile of the 10 residue miniprotein CLN025 known to exhibit a β-hairpin in its native state to understand the limitations of implicit methods to describe solvent effects and how these may be compensated by using different force fields. For this purpose, we carried out a thorough sampling of the conformational space of CLN025 in explicit solvent using the replica exchange molecular dynamics method as a sampling technique and compared the results with simulations of the system modeled using the analytical linearized Poisson-Boltzmann (ALPB) method with three different AMBER force fields: parm94, parm96, and parm99SB. The results show the peptide to exhibit a funnel-like free energy landscape with two minima in explicit solvent. In contrast, the higher minimum nearly disappears from the energy surface when the system is studied with an implicit representation of the solvent. Moreover, the different force fields used in combination with the ALPB method do not describe the system in the same manner. The results of this work suggest that the balance between intra- and intermolecular interactions is the cause of the differences between implicit and explicit solvent simulations in this system, stressing the role of the environment to define properly the conformational profile of a peptide in solution.

A method to accelerate the computation of structure factors from an electron density described by anisotropic and aspherical atomic form factors via fast Fourier transformation is described for the first time., Recent advances in computational chemistry have produced force fields based on a polarizable atomic multipole description of biomolecular electrostatics. In this work, the Atomic Multipole Optimized Energetics for Biomolecular Applications (AMOEBA) force field is applied to restrained refinement of molecular models against X-ray diffraction data from peptide crystals. A new formalism is also developed to compute anisotropic and aspherical structure factors using fast Fourier transformation (FFT) of Cartesian Gaussian multipoles. Relative to direct summation, the FFT approach can give a speedup of more than an order of magnitude for aspherical refinement of ultrahigh-resolution data sets. Use of a sublattice formalism makes the method highly parallelizable. Application of the Cartesian Gaussian multipole scattering model to a series of four peptide crystals using multipole coefficients from the AMOEBA force field demonstrates that AMOEBA systematically underestimates electron density at bond centers. For the trigonal and tetrahedral bonding geometries common in organic chemistry, an atomic multipole expansion through hexadecapole order is required to explain bond electron density. Alternatively, the addition of inter­atomic scattering (IAS) sites to the AMOEBA-based density captured bonding effects with fewer parameters. For a series of four peptide crystals, the AMOEBA–IAS model lowered R free by 20–40% relative to the original spherically symmetric scattering model.

Rhythmic and discrete movements are frequently considered separately in motor control, probably because different techniques are commonly used to study and model them. Yet the increasing interest in finding a comprehensive model for movement generation requires bridging the different perspectives arising from the study of those two types of movements. In this article, we consider discrete and rhythmic movements within the framework of motor primitives, i.e., of modular generation of movements. In this way we hope to gain an insight into the functional relationships between discrete and rhythmic movements and thus into a suitable representation for both of them. Within this framework we can define four possible categories of modeling for discrete and rhythmic movements depending on the required command signals and on the spinal processes involved in the generation of the movements. These categories are first discussed in terms of biological concepts such as force fields and central pattern generators and then illustrated by several mathematical models based on dynamical system theory. A discussion on the plausibility of theses models concludes the work.

A combined linear-response-frozen electron-density model has been implemented in a molecular-dynamics scheme derived from an extended Lagrangian formalism. This approach is based on a partition of the electronic charge distribution into a frozen region described by Kim-Gordon theory [J. Chem. Phys. 56, 3122 (1972); J. Chem. Phys. 60, 1842 (1974)] and a response contribution determined by the instantaneous ionic configuration of the system. The method is free from empirical pair potentials and the parametrization protocol involves only calculations on properly chosen subsystems. We apply this method to a series of alkali halides in different physical phases and are able to reproduce experimental structural and thermodynamic properties with an accuracy comparable to Kohn-Sham density-functional calculations.

The interpretation of physico-chemical observables in terms of atomic motions is one of the primary objectives of atomistic simulations. Trajectories from a molecular simulation contain much valuable information about the relationship between motion of the atoms and physical observables related to them, provided that the interactions used to generate the trajectories are of sufficiently high quality. On the other hand, many experimental observables are averages over a large number of physical realizations of the system. Thus, a statistically large number of trajectories needs to be generated and analyzed in order to provide a meaningful basis for comparison with and interpretation of experiments. The preferred computational approach which allows such extensive averaging while retaining the quantitative aspects of the intermolecular interactions are accurate force field-based molecular dynamics simulations. This contribution provides an overview of our group's current technological improvements in force field technology and its application to fundamental physico-chemical questions.

The potential energy of polyethylene, polytetrafluoroethylene, polyoxymethylene, polyisobutylene, polyvinylidene chloride, and isotactic polypropylene with a helical conformation has been calculated as a function of the angles of rotation around the bonds of the backbone chain. The use of appropriate functions to describe the interaction between nonbonded atoms in the chains, has allowed prediction with surprising accuracy of the most stable conformation for the each polymer considered, in spite of the rather drastic assumptions involved in the calculations. The most prominent feature of the potential energy diagrams are discussed with reference to the possibility of predicting the allowed helical conformations for the isolated unperturbed polymer chains considered.

Motivation: The main challenge for structure-based computational protein design (CPD) remains the combinatorial nature of the search space. Even in its simplest fixed-backbone formulation, CPD encompasses a computationally difficult NP-hard problem that prevents the exact exploration of complex systems defining large sequence-conformation spaces. Results: We present here a CPD framework, based on cost function network (CFN) solving, a recent exact combinatorial optimization technique, to efficiently handle highly complex combinatorial spaces encountered in various protein design problems. We show that the CFN-based approach is able to solve optimality a variety of complex designs that could often not be solved using a usual CPD-dedicated tool or state-of-the-art exact operations research tools. Beyond the identification of the optimal solution, the global minimum-energy conformation, the CFN-based method is also able to quickly enumerate large ensembles of suboptimal solutions of interest to rationally build experimental enzyme mutant libraries. Availability: The combined pipeline used to generate energetic models (based on a patched version of the open source solver Osprey 2.0), the conversion to CFN models (based on Perl scripts) and CFN solving (based on the open source solver toulbar2) are all available at http://genoweb.toulouse.inra.fr/∼tschiex/CPD Contacts: thomas.schiex@toulouse.inra.fr or sophie.barbe@insa-toulouse.fr Supplementary information: Supplementary data are available at Bioinformatics online.