This work was supported by the European Research Council (ERC) under the European Union Horizon 2020 research and innovation program (grant agreement number 681818 IMPACT to RC), by the Extreme Physics and Chemistry Directorate of the Deep Carbon Observatory, and by the Research Council of Norway through its Centers of Excellence funding scheme, project number 223272. We acknowledge access to the GENCI supercomputers through the stl2816 series of eDARI computing grants, to the Irene AMD supercomputer through the PRACE RA4947 project, and the Fram supercomputer through the UNINETT Sigma2 NN9697K. FS was supported by a Marie Sk&#322;odowska-Curie project (grant agreement ABISSE No.750901).

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<li>Lin, S. T., Blanco, M., Goddard, W. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+two-phase+model+for+calculating+thermodynamic+properties+of+liquids+from+molecular+dynamics%3A+Validation+for+the+phase+diagram+of+Lennard-Jones+fluids%5BTitle%5D)+AND+%22The+Journal+of+Chemical+Physics%22%5BJournal%5D)">The two-phase model for calculating thermodynamic properties of liquids from molecular dynamics: Validation for the phase diagram of Lennard-Jones fluids.</a> The Journal of Chemical Physics. 119 (22), 11792-11805 (2003).</li>
<li>Meyer, E. R., Kress, J. D., Collins, L. A., Ticknor, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Effect+of+correlation+on+viscosity+and+diffusion+in+molecular-dynamics+simulations%5BTitle%5D)+AND+%22Physical+Review+E%22%5BJournal%5D)">Effect of correlation on viscosity and diffusion in molecular-dynamics simulations.</a> Physical Review E. 90 (4), 1198-1212 (2014).</li>
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<li>Elkins-Taton, L. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Magma+oceans+in+the+inner+solar+system%5BTitle%5D)+AND+%22Annual+Review+of+Earth+and+Planetary+Sciences%22%5BJournal%5D)">Magma oceans in the inner solar system.</a> Annual Review of Earth and Planetary Sciences. 40, 113-139 (2012).</li>
<li>Lock, S. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+origin+of+the+Moon+within+a+terrestrial+synestia%5BTitle%5D)+AND+%22J.+Geophysical+Research%3A+Planets%22%5BJournal%5D)">The origin of the Moon within a terrestrial synestia.</a> J. Geophysical Research: Planets. 123, 910-951 (2018).</li>
<li>Solomatova, N. V., Caracas, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Pressure-induced+coordination+changes+in+a+pyrolitic+silicate+melt+from+ab+initio+molecular+dynamics+simulations%5BTitle%5D)+AND+%22Journal+of+Geophysical+Research%3A+Solid+Earth%22%5BJournal%5D)">Pressure-induced coordination changes in a pyrolitic silicate melt from ab initio molecular dynamics simulations.</a> Journal of Geophysical Research: Solid Earth. 124, 11232-11250 (2019).</li>
</ol>

The authors have nothing to disclose.

The UMD package has been designed to work better with ab initio simulations, where the number of snapshots is typically limited to tens to hundreds of thousands of snapshots, with a few hundred atoms per unit cell. Larger simulations are also tractable provided the machine on which the post-processing runs has enough active memory resources. The code distinguishes itself by the variety of properties it can compute and by its open-source license.
The umd.dat files are appropriate to the ensembles that preserve the number of particles unchanged throughout the simulation. The UMD package can read files stemming from calculations where the shape and volume of the simulation box varies. These cover the most common calculations, like NVT and NPT, where the number of particles, N, temperature T, volume, V, and/or pressure, P, are kept constant.
For the time begin the pair distribution function as well as all the scripts needing to estimate the interatomic distances, like the speciation scripts, work only for orthogonal unit cells, meaning for cubic, tetragonal, and orthorhombic cells, where the angles between the axes are 90&#176;.
The major lines of development for version 2.0 are removal of the orthogonality restriction for distances and adding more features for the speciation scripts: to analyze individual chemical bonds, to analyze the interatomic angles, and to implement the second coordination sphere. With help from external collaboration, we are working on porting the code onto a GPU for faster analysis in larger systems.

Fluids and melts are active chemical and physical transport vectors in natural environments. The elevated rates of atomic diffusion favor chemical exchanges and reactions, the low viscosity coupled with varying buoyancy favor large mass transfer, and crystal-melt density relations favor layering inside planetary bodies. The absence of a periodic lattice, typical high-temperatures required to reach the molten state, and the difficulty for quenching make the experimental determination of a series of obvious properties, like density, diffusion, and viscosity, extremely challenging. These difficulties make alternative computational methods strong and useful tools for investigating this class of materials.
With the advent of computing power and the availability of supercomputers, two major numerical atomistic simulations techniques are currently employed to study the dynamical state of a non-crystalline atomistic system, Monte Carlo1 and molecular dynamics (MD)1,2. In Monte Carlo simulations the configurational space is randomly sampled; Monte Carlo methods show linear scaling in parallelization if all sampling observations are independent of each other. The quality of the results depends on the quality of the random number generator and the representativeness of the sampling. Monte Carlo methods show linear scaling in parallelization if the sampling is independent of each other. In molecular dynamics (MD) the configurational space is sampled by time-dependent atomic trajectories. Starting from a given configuration, the atomic trajectories are computed by integrating the Newtonian equations of motion. The interatomic forces can be computed using model interatomic potentials (in classical MD) or using first-principles methods (in ab initio, or first-principles, MD). The quality of the results depends on the length of the trajectory and its capability to not be attracted to local minima.
Molecular dynamics simulations contain a plethora of information, all related to the dynamical behavior of the system. Thermodynamic average properties, like internal energy, temperature, and pressure, are rather standard to compute. They can be extracted from the output file(s) of the simulations and averaged, whereas quantities related directly to the movement of the atoms as well as to their mutual relation need to be computed after extraction of the atomic positions and velocities.
Consequently, a lot of effort has been dedicated to visualizing the results, and various packages are available today, on different platforms, open source or not [Ovito3, VMD4, Vesta5, Travis6, etc.]. All these visualization tools deal efficiently with interatomic distances, and as such, they allow the efficient computation of pair distribution functions and diffusion coefficients. Various groups performing large-scale molecular dynamics simulations have proprietary software to analyze various other properties resulting from the simulations, sometimes in shareware or other forms of limited access to the community, and sometimes limited in scope and use to some specific packages. Sophisticated algorithms to extract information about interatomic bonding, geometrical patterns, and thermodynamics are developed and implemented in some of these packages3,4,5,6,7, etc.
Here we propose the UMD package -&#160;an open-source package written in Python to analyze the output of molecular dynamics simulations. The UMD package allows for the computation of a wide range of structural, dynamical, and thermodynamical properties (Figure 1). The package is available via the GitHub website (https://github.com/rcaracas/UMD_package) and via a dedicated page (http://moonimpact.eu/umd-package/) of the ERC IMPACT project as an open-access package.
To make it universal and easier to handle, our approach is to first extract all the information related to the thermodynamic state and the atomic trajectories from the output file of the actual molecular-dynamics run. This information is stored in a dedicated file, whose format is independent of the original MD package where the simulation was run. We name these files &#8220;umd&#8221; files, which stands for Universal Molecular Dynamics. In this way, our UMD package can be easily used by any ab initio group with any software, all with a minimum effort of adaptation. The only requirement to use the present package is to write the appropriate parser from the output of the particular MD software into the umd file format, if this is not yet existent. For the time being, we provide such parsers for the VASP8 and the QBox9 packages.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61534/61534fig01.jpg" /> 
Figure 1: Flowchart of the UMD library. 
Physical properties are in blue, and major Python scripts and their options are in red. <a href="https://www.jove.com/files/ftp_upload/61534/61534fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
The umd files are ASCII files; typical extension is &#8220;umd.dat&#8221; but not mandatory. All the analysis components can read ASCII files of the umd format, regardless of the actual name extension. However, some of the automatic scripts designed to perform fast large-scale statistics over several simulations specifically look for files with the umd.dat extension. Each physical property is expressed on one line. Every line starts with a keyword. In this way the format is highly adaptable and allows for new properties to be added to the umd file, all the while preserving its readability throughout versions. The first 30 lines of the umd file of the simulation of pyrolite at 4.6 GPa and 3000 K, used below in the discussion, are shown in Figure 2.
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/61534/61534fig02.jpg" /> 
Figure 2: The beginning of the umd file describing the simulation of liquid pyrolite at 4.6 GPa and 3000 K. 
The header is followed by the description of each snapshot. Each property is written on one line, containing the name of the physical property, the value(s), and the units, all separated by spaces. <a href="https://www.jove.com/files/ftp_upload/61534/61534fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
All umd files contain a header describing the content of the simulation cell: the number of atoms, electrons, and atomic types, as well as details for each atom, such as its type, chemical symbol, number of valence electrons, and its mass. An empty line marks the end of the header and separates it from the main part of the umd file.
Then each step of the simulation is detailed. First, the instantaneous thermodynamic parameters are given, each on a different line, specifying (i) the name of the parameter, like energy, stresses, equivalent hydrostatic pressure, density, volume, lattice parameters, etc., (ii) its value(s), and (iii) its units. A table describing the atoms comes next. A header line gives the different measures, like Cartesian positions, velocities, charges, etc., and their units. Then each atom is detailed on one line. By groups of three, corresponding to the three x, y, z axes, the entries are: the reduced positions, the Cartesian positions folded into the simulation cell, the Cartesian positions (that properly take into account the fact that atoms can traverse several unit cells during a simulation), the atomic velocities, and the atomic forces. The last two entries are scalars: charge and magnetic moment.
Two major libraries ensure the proper functioning of the entire package. The umd_process.py library deals with the umd files, like reading and printing. The crystallography.py library deals with all the information related to the actual atomic structure. The underlying philosophy of the crystallography.py library is to treat the lattice as a vectorial space. The unit cell parameters together with their orientation represent the basis vectors. The &#8220;Space&#8221; has a series of scalar attributes (specific volume, density, temperature, and specific number of atoms), thermodynamic properties (internal energy, pressure, heat capacity, etc.), and a series of tensorial properties (stress and elasticity). Atoms populate this space. The &#8220;Lattice&#8221; class defines this ensemble, alongside various few short calculations, like specific volume, density, obtaining the reciprocal lattice from the direct one, etc. The &#8220;Atoms&#8221; class defines the atoms. They are characterized by a series of scalar properties (name, symbol, mass, number of electrons, etc.) and a series of vectorial properties (the position in space, either relative to the vectorial basis described in the Lattice class, or relative to universal Cartesian coordinates, velocities, forces, etc.). Apart from these two classes, the crystallography.py library contains a series of functions to perform a variety of tests and calculations, such as atomic distances, or cell multiplication. The periodic table of the elements is also included as a dictionary.
The various components of the umd package write several output files. As a general rule, they are all ASCII files, all their entries are separated by tabs, and they are made as self-explanatory as possible. For example, they always clearly indicate the physical property and its units. The umd.dat files fully comply with this rule.

<table><tbody><tr><td>getopt library</td><td></td><td></td><td>open-source</td></tr><tr><td>glob library</td><td></td><td></td><td>open-source</td></tr><tr><td>matplotlib library</td><td></td><td></td><td>open-source</td></tr><tr><td>numpy library</td><td></td><td></td><td>open-source</td></tr><tr><td>os library</td><td></td><td></td><td>open-source</td></tr><tr><td>Python software</td><td>The Python Software Foundation</td><td>Version 2 and 3</td><td>open-source</td></tr><tr><td>random library</td><td></td><td></td><td>open-source</td></tr><tr><td>re library</td><td></td><td></td><td>open-source</td></tr><tr><td>scipy library</td><td></td><td></td><td>open-source</td></tr><tr><td>subprocess library</td><td></td><td></td><td>open-source</td></tr><tr><td>sys library</td><td></td><td></td><td>open-source</td></tr></tbody></table>

analyzing melts and fluids from ab initio molecular dynamics simulations with the umd package

We have developed a Python-based open-source package to analyze the results stemming from ab initio molecular-dynamics simulations of fluids. The package is best suited for applications on natural systems, like silicate and oxide melts, water-based fluids, and various supercritical fluids. The package is a collection of Python scripts that include two major libraries dealing with file formats and with crystallography. All the scripts are run at the command line. We propose a simplified format to store the atomic trajectories and relevant thermodynamic information of the simulations, which is saved in UMD files, standing for Universal Molecular Dynamics. The UMD package allows the computation of a series of structural, transport and thermodynamic properties. Starting with the pair-distribution function it defines bond lengths, builds an interatomic connectivity matrix, and eventually determines the chemical speciation. Determining the lifetime of the chemical species allows running a full statistical analysis. Then dedicated scripts compute the mean-square displacements for the atoms as well as for the chemical species. The implemented self-correlation analysis of the atomic velocities yields the diffusion coefficients and the vibrational spectrum. The same analysis applied on the stresses yields the viscosity. The package is available via the GitHub website and via its own dedicated page of the ERC IMPACT project as open-access package.

Pyrolite is a model multi-component silicate melt (0.5Na2O 2CaO 1.5Al2O3 4FeO 30MgO 24SiO2) that best approximates the composition of the bulk silicate Earth&#8212;the geochemical average or our entire planet, except for its iron-based core19. The early Earth was dominated by a series of large-scale melting events20, the last one might have engulfed the entire planet, after its condensation for the protolunar disk21. Pyrolite represents the best approximant to the composition of such planetary-scale magma oceans. Consequently, we extensively studied the physical properties of pyrolite melt in the 3,000&#8210;5,000 K temperature range and 0&#8210;150 GPa pressure range from ab initio molecular-dynamics simulations in the VASP implementation. These thermodynamic conditions entirely characterize the Earth&#8217;s most extreme magma ocean conditions. Our study is an excellent example of a successful use of the UMD package for the entire in-depth analysis of the melts22. We computed the distribution and the average bond lengths, we traced the changes in cation-oxygen coordination, and compared our results to previous experimental and computational studies on amorphous silicates of various compositions. Our in-depth analysis helped decompose standard coordination numbers into their basic constituents, outline the presence of exotic coordination polyhedra in the melt, and extract lifetimes for all the coordination polyhedra. It also outlined the importance of sampling in simulations in terms of both length of the trajectory and also number of atoms present in the system that is modeled. As for post-processing, the UMD analysis is independent of these factors, however, they should be taken into account when interpreting the results provided by the UMD package. Here, we show a few examples of how the UMD package can be used to extract several characteristic features of the melts, with an application to molten pyrolite.
The Si-O pair distribution function obtained from the gofrs_umd.py script shows that the radius of the first coordination sphere, which is the first minimum of the g(r) function, lies around 2.5 angstroms at T = 3000 K and P = 4.6 GPa. The maximum of the g(r) lies at 1.635 &#197;&#8212;this is the best approximation to the bend length. The long tail is due to the temperature. Using this limit as the Si-O bond distance, the speciation analysis shows that SiO4 units, which can last for up to a few picoseconds, dominate the melt (Figure 5). There is an important part of the melt that shows partial polymerization, as reflected by the presence of dimers like Si2O7, and trimers like Si3Ox units. Their corresponding lifetime is in the order of the picosecond. Higher-order polymers all have considerably shorter lifetime.
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/61534/61534fig05.jpg" /> 
Figure 5: Lifetime of the Si-O chemical species. 
The speciation is identified in a multi-component melt at 4.6 GPa and 3000 K. The labels mark the SiO3, SiO4, and SiO5 monomers and the various SixOy polymers. <a href="https://www.jove.com/files/ftp_upload/61534/61534fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
The different values of the vertical and horizontal steps, defined by the &#8211;z and &#8211;v flags above, yield various samplings of the MSD (Figure 6). Even large values of z and v are enough to define the slopes and thus the diffusion coefficients of the different atoms. The gain in time for the post-processing is remarkable when going to large values of z and v. The MSD offers a very strong validation criterion for the quality of the simulations. If the diffusion part of the MSD is not sufficiently long, that is a sign that the simulation is too short, and fails to reach the fluid state in a statistical sense. The minimum requirement for the diffusive part of the MSD highly depends on the system. One can require that all the atoms change their site at least once in the structure of the melt in order for it to be considered as a fluid10. An excellent example with applications in planetary sciences is complex silicate melts at high pressures close to or even below their liquidus line11. The Si atoms, the major network-forming cations, switch sites after more than two dozen picoseconds. Simulations shorter than this threshold would be considerably under-sampling the possible configurational space. However, as the coordinating anions, namely the O atoms, move faster than the central Si atoms, they can compensate for part of the slow mobility of Si. As such, the entire system could indeed cover a better sampling of the configurational space than assumed only from the Si displacements.
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/61534/61534fig06.jpg" /> 
Figure 6: Mean-square displacements (MSD). 
The MSD are illustrated for a few atomic types of a multi-component silicate melt. The sampling with various horizontal and vertical steps, z and v, yields consistent results. Solid circles: -z 50 &#8211;v 50. Open circles: -z 250 &#8211;v 500. <a href="https://www.jove.com/files/ftp_upload/61534/61534fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Finally, the atomic VAC functions yield the vibrational spectrum of the melt. Figure 7 shows the spectrum at the same pressure and temperature conditions as above. We represent the contributions of Mg, Si, and O atoms, as well as the total value. At zero frequency there is a finite value of the spectrum, which corresponds to the diffusion character of the melt. Extraction of the thermodynamic properties from the vibrational spectrum needs to remove this gas-like diffusive character from zero but also to properly take into account its decay at higher frequencies.
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/61534/61534fig07.jpg" /> 
Figure 7: The vibrational spectrum of pyrolite melt. 
The real part of the Fourier transform of the atomic velocity-velocity self-correlation function yields the vibrational spectrum. Here the spectrum is computed for a multi-component silicate melt. Fluids have a non-zero gas-like diffusive character at zero frequency. <a href="https://www.jove.com/files/ftp_upload/61534/61534fig07large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package at JoVE.com

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Melts and fluids are ubiquitous vectors of mass transport in natural systems. We have developed an open-source package to analyze ab initio molecular-dynamics simulations of such systems. We compute structural (bonding, clusterization, chemical speciation), transport (diffusion, viscosity) and thermodynamic properties (vibrational spectrum).

We have developed a Python-based open-source package to analyze the results stemming from ab initio molecular-dynamics simulations of fluids. The package ...

analyzing-melts-fluids-from-ab-initio-molecular-dynamics-simulations

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4.4K Views.  CNRS. De analyse van first-principles moleculaire dynamica simulaties stelt ons in staat om de fysische en chemische eigenschappen van vloeistoffen nauwkeurig te voorspellen. Deze methode kan worden toegepast op elke atoomanalyse in de natuurkunde en scheikunde. Pak om te beginnen elke specifieke set fysieke eigenschappen uit met behulp van een of meer speciale Python-scripts uit het pakket.Voer alle scripts uit op de opdrachtregel. Ze gebruiken allemaal een reeks vlaggen, die zo consistent ...

Video: Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Simulation of the Planetary Interior Differentiation Processes in the Laboratory

A planetary interior is under high-pressure and high-temperature conditions and it has a layered structure. There are two important processes that led to that layered structure, (1) percolation of liquid metal in a solid silicate matrix by planet differentiation, and (2) inner core crystallization by subsequent planet cooling. We conduct high-pressure and high-temperature experiments to simulate both processes in the laboratory. Formation of percolative planetary core depends on the efficiency of melt percolation, which is controlled by the dihedral (wetting) angle. The percolation simulation includes heating the sample at high pressure to a target temperature at which iron-sulfur alloy is molten while the silicate remains solid, and then determining the true dihedral angle to evaluate the style of liquid migration in a crystalline matrix by 3D visualization. The 3D volume rendering is achieved by slicing the recovered sample with a focused ion beam (FIB) and taking SEM image of each slice with a FIB/SEM crossbeam instrument. The second set of experiments is designed to understand the inner core crystallization and element distribution between the liquid outer core and solid inner core by determining the melting temperature and element partitioning at high pressure. The melting experiments are conducted in the multi-anvil apparatus up to 27 GPa and extended to higher pressure in the diamond-anvil cell with laser-heating. We have developed techniques to recover small heated samples by precision FIB milling and obtain high-resolution images of the laser-heated spot that show melting texture at high pressure. By analyzing the chemical compositions of the coexisting liquid and solid phases, we precisely determine the liquidus curve, providing necessary data to understand the inner core crystallization process.

The high-pressure and high-temperature experiments described here mimic planet interior differentiation processes. The processes are visualized and better understood by high-resolution 3D imaging and quantitative chemical analysis.

A planetary interior is under high-pressure and high-temperature conditions and it has a layered structure. There are two important processes that led to ...

Engineering

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

The increasing development of computing (hardware and software) in the last decades has impacted scientific research in many fields including materials science, biology, chemistry and physics among many others. A new computational system for the accurate and fast simulation and 3D/VR visualization of nanostructures is presented here, using the open-source molecular dynamics (MD) computer program LAMMPS. This alternative computational method uses modern graphics processors, NVIDIA CUDA technology and specialized scientific codes to overcome processing speed barriers common to traditional computing methods. In conjunction with a virtual reality system used to model materials, this enhancement allows the addition of accelerated MD simulation capability. The motivation is to provide a novel research environment which simultaneously allows visualization, simulation, modeling and analysis. The research goal is to investigate the structure and properties of inorganic nanostructures (e.g., silica glass nanosprings) under different conditions using this innovative computational system. The work presented outlines a description of the 3D/VR Visualization System and basic components, an overview of important considerations such as the physical environment, details on the setup and use of the novel system, a general procedure for the accelerated MD enhancement, technical information, and relevant remarks. The impact of this work is the creation of a unique computational system combining nanoscale materials simulation, visualization and interactivity in a virtual environment, which is both a research and teaching instrument at UC Merced.

A new computational system featuring GPU-accelerated molecular dynamics simulation and 3D/VR visualization, analysis and manipulation of nanostructures has been implemented, representing a novel approach to advance materials research and promote innovative investigation and alternative methods to learn about material structures with dimensions invisible to the human eye.

The increasing development of computing (hardware and software) in the last decades has impacted scientific research in many fields including materials ...

Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering

Protein-protein interactions involving proteins with multiple globular domains present technical challenges for determining how such complexes form and how the domains are oriented/positioned. Here, a protocol with the potential for elucidating which specific domains mediate interactions in multicomponent system through ab initio modeling is described. A method for calculating solution structures of macromolecules and their assemblies is provided that involves integrating data from small angle X-ray scattering (SAXS), chromatography, and atomic resolution structures together in a hybrid approach. A specific example is that of the complex of full-length nidogen-1, which assembles extracellular matrix proteins and forms an extended, curved nanostructure. One of its globular domains attaches to laminin &#947;-1, which structures the basement membrane. This provides a basis for determining accurate structures of flexible multidomain protein complexes and is enabled by synchrotron sources coupled with automation robotics and size exclusion chromatography systems. This combination allows rapid analysis in which multiple oligomeric states are separated just prior to SAXS data collection. The analysis yields information on the radius of gyration, particle dimension, molecular shape and interdomain pairing. The protocol for generating 3D models of complexes by fitting high-resolution structures of the component proteins is also given.

Here, we present how Small Angle X-Ray Scattering (SAXS) can be utilized to obtain information on low-resolution envelopes representing the macromolecular structures. When used in conjunction with high-resolution structural techniques such as X-Ray Crystallography and Nuclear Magnetic Resonance, SAXS can provide detailed insights into multidomain proteins and macromolecular complexes in-solution.

Protein-protein interactions involving proteins with multiple globular domains present technical challenges for determining how such complexes form and ...

Biochemistry

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

An analog, macroscopic method for studying molecular-scale hydrodynamic processes in dense gases and liquids is described. The technique applies a standard fluid dynamic diagnostic, particle image velocimetry (PIV), to measure: i) velocities of individual particles (grains), extant on short, grain-collision time-scales, ii) velocities of systems of particles, on both short collision-time- and long, continuum-flow-time-scales, iii) collective hydrodynamic modes known to exist in dense molecular fluids, and iv) short- and long-time-scale velocity autocorrelation functions, central to understanding particle-scale dynamics in strongly interacting, dense fluid systems. The basic system is composed of an imaging system, light source, vibrational sensors, vibrational system with a known media, and PIV and analysis software. Required experimental measurements and an outline of the theoretical tools needed when using the analog technique to study molecular-scale hydrodynamic processes are highlighted. The proposed technique provides a relatively straightforward alternative to photonic and neutron beam scattering methods traditionally used in molecular hydrodynamic studies.

An experimentally accessible analog method for studying molecular hydrodynamic processes in dense fluids is presented. The technique uses particle image velocimetry of vibrated, high-restitution grain piles and allows direct, macroscopic observation of dynamical processes known and predicted to exist in strongly interacting, high density gases and liquids.

An analog, macroscopic method for studying molecular-scale hydrodynamic processes in dense gases and liquids is described. The technique applies a ...

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation

Numerous somatic mutations occurring in the epidermal growth factor receptor (EGFR) family (ErbB) of receptor tyrosine kinases (RTK) have been reported from cancer patients, although relatively few have been tested and shown to cause functional changes in ErbBs. The ErbB receptors are dimerized and activated upon ligand binding, and dynamic conformational changes of the receptors are inherent for induction of downstream signaling. For two mutations shown experimentally to alter EGFR function, A702V and the &#916;746ELREA750 deletion mutation, we illustrate in the following protocol how molecular dynamics (MD) simulations can probe the (1) conformational stability of the mutant tyrosine kinase structure in comparison with wild-type EGFR; (2) structural consequences and conformational transitions and their relationship to observed functional changes; (3) effects of mutations on the strength of binding ATP as well as for binding between the kinase domains in the activated asymmetric dimer; and (4) effects of the mutations on key interactions within the EGFR binding site associated with the activated enzyme. The protocol provides a detailed step-by-step procedure as well as guidance that can be more generally useful for investigation of protein structures using MD simulations as a means to probe structural dynamics and the relationship to biological function.

The objective of this protocol is to use molecular dynamics simulations to examine the dynamic structural changes that occur due to activating mutations of the EGFR kinase protein.

Numerous somatic mutations occurring in the epidermal growth factor receptor (EGFR) family (ErbB) of receptor tyrosine kinases (RTK) have been reported ...

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

A significant number of heterogeneously-catalyzed chemical processes occur under liquid conditions, but simulating catalyst function under such conditions is challenging when it is necessary to include the solvent molecules. The bond breaking and forming processes modeled in these systems necessitate the use of quantum chemical methods. Since molecules in the liquid phase are under constant thermal motion, simulations must also include configurational sampling. This means that multiple configurations of liquid molecules must be simulated for each catalytic species of interest. The goal of the protocol presented here is to generate and sample trajectories of configurations of liquid water molecules around catalytic species on flat transition metal surfaces in a way that balances chemical accuracy with computational expense. Specifically, force field molecular dynamics (FFMD) simulations are used to generate configurations of liquid molecules that can subsequently be used in quantum mechanics-based methods such as density functional theory or ab initio molecular dynamics. To illustrate this, in this manuscript, the protocol is used for catalytic intermediates that could be involved in the pathway for the decomposition of glycerol (C3H8O3). The structures that are generated using FFMD are modeled in DFT in order to estimate the enthalpies of solvation of the catalytic species and to identify how H2O molecules participate in catalytic decompositions.

The goal of the protocol presented here is to generate and sample trajectories of configurations of liquid water molecules around catalytic species on a flat transition metal surface. The sampled configurations can be used as starting structures in quantum mechanics-based methods.

A significant number of heterogeneously-catalyzed chemical processes occur under liquid conditions, but simulating catalyst function under such conditions ...

Vibrational Spectra of a N719-Chromophore/Titania Interface from Empirical-Potential Molecular-Dynamics Simulation, Solvated by a Room Temperature Ionic Liquid

The accurate molecular simulation prediction of vibrational spectra, and other structural, energetic and spectral characteristics, of photo-active metal-oxide surfaces in contact with light-absorbing dyes is an ongoing thorny and elusive challenge in physical chemistry. With this in mind, a molecular-dynamics (MD) simulation were performed by using optimized empirical potentials for a well-representative and prototypical dye-sensitized solar cell (DSC) solvated by a widely-studied room temperature ionic liquid (RTIL), in the guise of a [bmim]+[NTf2]- RTIL solvating an N719-sensitizing dye adsorbed onto 101 anatase-titania. In doing so, important insights were gleaned into how using a RTIL as the electrolytic hole acceptor modulates the dynamical and vibrational properties of a N719 dye, estimating the spectra for the DSC photo-active interface via Fourier transformation of mass-weighted velocity autocorrelation functions from MD. The acquired vibrational spectra were compared with the experiment spectra and those sampled from ab initio molecular dynamics (AIMD); in particular, various empirical-potential spectra generated from MD provide insight into how partial-charge charge parameterization of the ionic liquid affects vibrational spectra prediction. In any event, careful fitting of empirical force-field models has been shown to be an effective tool in handling DSC vibrational properties, when validated by AIMD and an experiment.

A dye-sensitized solar cell was solvated by RTILs; using optimized empirical potentials, a molecular dynamics simulation was applied to compute vibrational properties. The obtained vibrational spectra were compared with experiment and ab initio molecular dynamics; various empirical potential spectra show how partial-charge charge parameterization of the ionic liquid affects vibrational spectra prediction.

The accurate molecular simulation prediction of vibrational spectra, and other structural, energetic and spectral characteristics, of photo-active ...

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

The computational study of the formation and growth of atmospheric aerosols requires an accurate Gibbs free energy surface, which can be obtained from gas phase electronic structure and vibrational frequency calculations. These quantities are valid for those atmospheric clusters whose geometries correspond to a minimum on their potential energy surfaces. The Gibbs free energy of the minimum energy structure can be used to predict atmospheric concentrations of the cluster under a variety of conditions such as temperature and pressure. We present a computationally inexpensive procedure built on a genetic algorithm-based configurational sampling followed by a series of increasingly accurate screening calculations. The procedure starts by generating and evolving the geometries of a large set of configurations using semi-empirical models then refines the resulting unique structures at a series of high-level ab initio levels of theory. Finally, thermodynamic corrections are computed for the resulting set of minimum-energy structures and used to compute the Gibbs free energies of formation, equilibrium constants, and atmospheric concentrations. We present the application of this procedure to the study of hydrated glycine clusters under ambient conditions.

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

The atmospheric concentrations of weakly bound molecular clusters can be computed from the thermochemical properties of low energy structures found through a multi-step configurational sampling methodology utilizing a genetic algorithm and semi-empirical and ab initio quantum chemistry.

The computational study of the formation and growth of atmospheric aerosols requires an accurate Gibbs free energy surface, which can be obtained from gas ...

Visual Dynamics: Simplifying Molecular Dynamics Simulations

New Features in Visual Dynamics 3.0

Visual Dynamics (VD) is a web tool that aims to facilitate the use and application of Molecular Dynamics (MD) executed in Gromacs, allowing users without computational familiarity to run short-time simulations for validation, demonstration, and teaching purposes. It is true that quantum methods are the most accurate. However, there is currently no computational feasibility to carry out the experiments that MD performs. The tool described here has continuously received improvements over the course of the last couple of years. This protocol will describe what is needed to run a simulation in VD with a protein-ligand complex previously prepared in ACPYPE and some general directions on the other simulation models available. For the detailed simulation, the FK506-binding protein from Plasmodium vivax complexed with the inhibitor D5 (PDB ID: 4mgv) will be used, and all files used will be provided. Note that this protocol will tell every option to be used to achieve the same results presented, but these options are not necessarily the only ones available.

Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs

Visual Dynamics is an open-source tool that accelerates implementations and learning in molecular dynamics simulation using Gromacs. The presented protocol will guide you through the steps to perform a protein-ligand simulation prepared in ACPYPE with ease and general steps to other simulation models.

Visual Dynamics (VD) is a web tool that aims to facilitate the use and application of Molecular Dynamics (MD) executed in Gromacs, allowing users without ...

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

One-dimensional (1-D) sliding of transcription factor (TF) protein along DNA is essential for facilitated diffusion of the TF to locate target DNA site for genetic regulation. Detecting base-pair (bp) resolution of the TF sliding or stepping on the DNA is still experimentally challenging. We have recently performed all-atom molecular dynamics (MD) simulations capturing spontaneous 1-bp stepping of a small WRKY domain TF protein along DNA. Based on the 10 &#181;s WRKY stepping path obtained from such simulations, the protocol here shows how to conduct more extensive conformational samplings of the TF-DNA systems, by constructing the Markov state model (MSM) for the 1-bp protein stepping, with various numbers of micro- and macro-states tested for the MSM construction. In order to examine processive 1-D diffusional search of the TF protein along DNA with structural basis, the protocol further shows how to conduct coarse-grained (CG) MD simulations to sample long-time scale dynamics of the system. Such CG modeling and simulations are particularly useful to reveal the protein-DNA electrostatic impacts on the processive diffusional motions of the TF protein above tens of microseconds, in comparison with sub-microseconds to microseconds protein stepping motions revealed from the all-atom simulations.

The goal of this protocol is to reveal structural dynamics of one-dimensional diffusion of protein along DNA, using a plant transcription factor WRKY domain protein as an exemplary system. To do this, both atomistic and coarse-grained molecular dynamics simulations along with extensive computational samplings have been implemented.

One-dimensional (1-D) sliding of transcription factor (TF) protein along DNA is essential for facilitated diffusion of the TF to locate target DNA site ...

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

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