919 resultados para WHAM, Molecular Dynamics, Umbrella Sampling, CUDA, GPU, C


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The phase diagram of cyclopentane has been studied by powder neutron diffraction, providing diffraction patterns for phases I, II, and III, over a range of temperatures and pressures. The putative phase IV was not observed. The structure of the ordered phase III has been solved by single-crystal diffraction. Computational modeling reveals that there are many equienergetic ordered structures for cyclopentane within a small energy range. Molecular dynamics simulations reproduce the structures and diffraction patterns for phases I and III and also show an intermediate disordered phase, which is used to interpret phase II.

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The self-assembly of a peptide based on a sequence from the amyloid beta peptide but incorporating the non-natural amino acid beta-2-thienylalanine (2-Thi) has been investigated in aqueous and methanol solutions. The peptide AAKLVFF was used as a design motif, replacing the phenylalanine residues (F) with 2-Thi units to yield (2-Thi)(2-Thi)VLKAA. The 2-Thi residues are expected to confer interesting electronic properties due to charge delocalization and pi-stacking. The peptide is shown to form beta-sheet-rich amyloid fibrils with a twisted morphology, in both water and methanol solutions at sufficiently high concentration. The formation of a self-assembling hydrogel is observed at high concentration. Detailed molecular modeling using molecular dynamics methods was performed using NOE constraints provided by 2D-NMR experiments. The conformational and charge properties of 2-Thi were modeled using quantum mechanical methods, and found to be similar to those previously reported for the beta-3-thienylalanine analogue. The molecular dynamics simulations reveal well-defined folded structures (turn-like) in dilute aqueous solution, driven by self-assembly of the hydrophobic aromatic units, with charged lysine groups exposed to water.

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The binding of NO to iron is involved in the biological function of many heme proteins. Contrary to ligands like CO and O-2, which only bind to ferrous (Fe-II) iron, NO binds to both ferrous and ferric (Fe-II) iron. In a particular protein, the natural oxidation state can therefore be expected to be tailored to the required function. Herein, we present an ob initio potential-energy surface for ferric iron interacting with NO. This potential-energy surface exhibits three minima corresponding to eta'-NO coordination (the global minimum), eta(1)-ON coordination and eta(2) coordination. This contrasts with the potential-energy surface for Fe-II-NO, which ex- hibits only two minima (the eta(2) coordination mode for Fe-II is a transition state, not a minimum). In addition, the binding energies of NO are substantially larger for Fe-III than for Fe-II. We have performed molecular dynamics simulations for NO bound to ferric myoglobin (Mb(III)) and compare these with results obtained for Mb(II). Over the duration of our simulations (1.5 ns), all three binding modes are found to be stable at 200 K and transiently stable at 300 K, with eventual transformation to the eta(1)-NO global-minimum conformation. We discuss the implication of these results related to studies of rebinding processes in myoglobin.

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Myoglobin has been studied in considerable detail using different experimental and computational techniques over the past decades. Recent developments in time-resolved spectroscopy have provided experimental data amenable to detailed atomistic simulations. The main theme of the present review are results on the structures, energetics and dynamics of ligands ( CO, NO) interacting with myoglobin from computer simulations. Modern computational methods including free energy simulations, mixed quantum mechanics/molecular mechanics simulations, and reactive molecular dynamics simulations provide insight into the dynamics of ligand dynamics in confined spaces complementary to experiment. Application of these methods to calculate and understand experimental observations for myoglobin interacting with CO and NO are presented and discussed.

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A new surface-crossing algorithm suitable for describing bond-breaking and bond-forming processes in molecular dynamics simulations is presented. The method is formulated for two intersecting potential energy manifolds which dissociate to different adiabatic states. During simulations, crossings are detected by monitoring an energy criterion. If fulfilled, the two manifolds are mixed over a finite number of time steps, after which the system is propagated on the second adiabat and the crossing is carried out with probability one. The algorithm is extensively tested (almost 0.5 mu s of total simulation time) for the rebinding of NO to myoglobin. The unbound surface ((FeNO)-N-...) is represented using a standard force field, whereas the bound surface (Fe-NO) is described by an ab initio potential energy surface. The rebinding is found to be nonexponential in time, in agreement with experimental studies, and can be described using two time constants. Depending on the asymptotic energy separation between the manifolds, the short rebinding timescale is between 1 and 9 ps, whereas the longer timescale is about an order of magnitude larger. NO molecules which do not rebind within 1 ns are typically found in the Xenon-4 pocket, indicating the high affinity of NO to this region in the protein.

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Molecular dynamics simulations of the photodissociated state of carbonmonoxy myoglobin (MbCO) are presented using a fluctuating charge model for CO. A new three-point charge model is fitted to high-level ab initio calculations of the dipole and quadrupole moment functions taken from the literature. The infrared spectrum of the CO molecule in the heme pocket is calculated using the dipole moment time autocorrelation function and shows good agreement with experiment. In particular, the new model reproduces the experimentally observed splitting of the CO absorption spectrum. The splitting of 3â7 cmâˆ1 (compared to the experimental value of 10 cmâˆ1) can be directly attributed to the two possible orientations of CO within the docking site at the edge of the distal heme pocket (the B states), as previously suggested on the basis of experimental femtosecond time-resolved infrared studies. Further information on the time evolution of the position and orientation of the CO molecule is obtained and analyzed. The calculated difference in the free energy between the two possible orientations (Fe···CO and Fe···OC) is 0.3 kcal molâˆ1 and agrees well with the experimentally estimated value of 0.29 kcal molâˆ1. A comparison of the new fluctuating charge model with an established fixed charge model reveals some differences that may be critical for the correct prediction of the infrared spectrum and energy barriers. The photodissociation of CO from the myoglobin mutant L29F using the new model shows rapid escape of CO from the distal heme pocket, in good agreement with recent experimental data. The effect of the protein environment on the multipole moments of the CO ligand is investigated and taken into account in a refined model. Molecular dynamics simulations with this refined model are in agreement with the calculations based on the gas-phase model. However, it is demonstrated that even small changes in the electrostatics of CO alter the details of the dynamics.

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To test the effectiveness of stochastic single-chain models in describing the dynamics of entangled polymers, we systematically compare one such model; the slip-spring model; to a multichain model solved using stochastic molecular dynamics(MD) simulations (the Kremer-Grest model). The comparison involves investigating if the single-chain model can adequately describe both a microscopic dynamical and a macroscopic rheological quantity for a range of chain lengths. Choosing a particular chain length in the slip-spring model, the parameter values that best reproduce the mean-square displacement of a group of monomers is determined by fitting toMDdata. Using the same set of parameters we then test if the predictions of the mean-square displacements for other chain lengths agree with the MD calculations. We followed this by a comparison of the time dependent stress relaxation moduli obtained from the two models for a range of chain lengths. After identifying a limitation of the original slip-spring model in describing the static structure of the polymer chain as seen in MD, we remedy this by introducing a pairwise repulsive potential between the monomers in the chains. Poor agreement of the mean-square monomer displacements at short times can be rectified by the use of generalized Langevin equations for the dynamics and resulted in significantly improved agreement.

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Self-assembly in aqueous solution has been investigated for two Fmoc [Fmoc ¼ N-(fluorenyl)-9-methoxycarbonyl] tetrapeptides comprising the RGDS cell adhesion motif from fibronectin or the scrambled sequence GRDS. The hydrophobic Fmoc unit confers amphiphilicity on the molecules, and introduces aromatic stacking interactions. Circular dichroism and FTIR spectroscopy show that the self-assembly of both peptides at low concentration is dominated by interactions among Fmoc units, although Fmoc-GRDS shows b-sheet features, at lower concentration than Fmoc-RGDS. Fibre X-ray diffraction indicates b-sheet formation by both peptides at sufficiently high concentration. Strong alignment effects are revealed by linear dichroism experiments for Fmoc-GRDS. Cryo-TEM and smallangle X-ray scattering (SAXS) reveal that both samples form fibrils with a diameter of approximately 10 nm. Both Fmoc-tetrapeptides form self-supporting hydrogels at sufficiently high concentration. Dynamic shear rheometry enabled measurements of the moduli for the Fmoc-GRDS hydrogel, however syneresis was observed for the Fmoc-RGDS hydrogel which was significantly less stable to shear. Molecular dynamics computer simulations were carried out considering parallel and antiparallel b-sheet configurations of systems containing 7 and 21 molecules of Fmoc-RGDS or Fmoc-GRDS, the results being analyzed in terms of both intermolecular structural parameters and energy contributions.

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A new approach to the study of the local organization in amorphous polymer materials is presented. The method couples neutron diffraction experiments that explore the structure on the spatial scale 1â20 Ã with the reverse Monte Carlo fitting procedure to predict structures that accurately represent the experimental scattering results over the whole momentum transfer range explored. Molecular mechanics and molecular dynamics techniques are also used to produce atomistic models independently from any experimental input, thereby providing a test of the viability of the reverse Monte Carlo method in generating realistic models for amorphous polymeric systems. An analysis of the obtained models in terms of single chain properties and of orientational correlations between chain segments is presented. We show the viability of the method with data from molten polyethylene. The analysis derives a model with average C-C and C-H bond lengths of 1.55 Ã and 1.1 Ã respectively, average backbone valence angle of 112, a torsional angle distribution characterized by a fraction of trans conformers of 0.67 and, finally, a weak interchain orientational correlation at around 4 Ã.

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We present molecular dynamics (MD) and slip-springs model simulations of the chain segmental dynamics in entangled linear polymer melts. The time-dependent behavior of the segmental orientation autocorrelation functions and mean-square segmental displacements are analyzed for both flexible and semiflexible chains, with particular attention paid to the scaling relations among these dynamic quantities. Effective combination of the two simulation methods at different coarse-graining levels allows us to explore the chain dynamics for chain lengths ranging from Z ∠2 to 90 entanglements. For a given chain length of Z ∠15, the time scales accessed span for more than 10 decades, covering all of the interesting relaxation regimes. The obtained time dependence of the monomer mean square displacements, g1(t), is in good agreement with the tube theory predictions. Results on the first- and second-order segmental orientation autocorrelation functions, C1(t) and C2(t), demonstrate a clear power law relationship of C2(t) C1(t)m with m = 3, 2, and 1 in the initial, free Rouse, and entangled (constrained Rouse) regimes, respectively. The return-to-origin hypothesis, which leads to inverse proportionality between the segmental orientation autocorrelation functions and g1(t) in the entangled regime, is convincingly verified by the simulation result of C1(t) g1(t)âˆ1 tâ1/4 in the constrained Rouse regime, where for well-entangled chains both C1(t) and g1(t) are rather insensitive to the constraint release effects. However, the second-order correlation function, C2(t), shows much stronger sensitivity to the constraint release effects and experiences a protracted crossover from the free Rouse to entangled regime. This crossover region extends for at least one decade in time longer than that of C1(t). The predicted time scaling behavior of C2(t) tâ1/4 is observed in slip-springs simulations only at chain length of 90 entanglements, whereas shorter chains show higher scaling exponents. The reported simulation work can be applied to understand the observations of the NMR experiments.

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OBJECTIVES: The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. METHODS: To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis. RESULTS: To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse. CONCLUSIONS: Web and grid services, especially pre-defined data mining services that can run on or 'near' the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data.

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Using molecular dynamics simulations, we find a reversible transition between the dispersion and aggregation states of solute molecules in aqueous solutions confined in nanoscale geometry, which is not observed in macroscopic systems. The nanoscale confinement also leads to a significant increase of the critical aggregation concentration (CAC). A theoretical model based on Gibbs free energy calculation is developed to describe the simulation results. It indicates that the reversible state transition is attributed to the low free energy barrier (of order kBT) in between two energy minima corresponding to the dispersion and aggregation states, and the enhancement of the CAC results from the fact that at lower concentrations the number of solute molecules is not large enough to allow the formation of a stable cluster in the confined systems.

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The structure of a ferrofluid under the influence of an external magnetic field is expected to become anisotropic due to the alignment of the dipoles into the direction of the external field, and subsequently to the formation of particle chains due to the attractive head to tail orientations of the ferrofluid particles. Knowledge about the structure of a colloidal ferrofluid can be inferred from scattering data via the measurement of structure factors. We have used molecular-dynamics simulations to investigate the structure of both monodispersed and polydispersed ferrofluids. The results for the isotropic structure factor for monodispersed samples are similar to previous data by Camp and Patey that were obtained using an alternative Monte Carlo simulation technique, but in a different parameter region. Here we look in addition at bidispersed samples and compute the anisotropic structure factor by projecting the q vector onto the XY and XZ planes separately, when the magnetic field was applied along the z axis. We observe that the XY- plane structure factor as well as the pair distribution functions are quite different from those obtained for the XZ plane. Further, the two- dimensional structure factor patterns are investigated for both monodispersed and bidispersed samples under different conditions. In addition, we look at the scaling exponents of structure factors. Our results should be of value to interpret scattering data on ferrofluids obtained under the influence of an external field.

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Using a Langevin molecular dynamics simulation, we show that the magnetic properties of a mono- and bi-dispersed ferrofluid system depend on the volume fraction and the dipolar coupling parameter. For the bi-dispersed system, most of the chains are formed by the large particles, but the aggregation behavior of the large particles is hindered by the presence of the small particles, which are predominantly attached to the end of the particle chain. To further elucidate the microscopic fluid structure, anisotropic structure factors are calculated.

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The magnetization properties of aggregated ferrofluids are calculated by combining the chain formation model developed by Zubarev with the modified mean-field theory. Using moderate assumptions for the inter- and intrachain interactions we obtain expressions for the magnetization and initial susceptibility. When comparing the results of our theory to molecular dynamics simulations of the same model we find that at large dipolar couplings (lambda>3) the chain formation model appears to give better predictions than other analytical approaches. This supports the idea that chain formation is an important structural ingredient of strongly interacting dipolar particles.