35 resultados para Molecular Dynamics Simulation

em Aston University Research Archive


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We use molecular dynamics simulations to compare the conformational structure and dynamics of a 21-base pair RNA sequence initially constructed according to the canonical A-RNA and A'-RNA forms in the presence of counterions and explicit water. Our study aims to add a dynamical perspective to the solid-state structural information that has been derived from X-ray data for these two characteristic forms of RNA. Analysis of the three main structural descriptors commonly used to differentiate between the two forms of RNA namely major groove width, inclination and the number of base pairs in a helical twist over a 30 ns simulation period reveals a flexible structure in aqueous solution with fluctuations in the values of these structural parameters encompassing the range between the two crystal forms and more. This provides evidence to suggest that the identification of distinct A-RNA and A'-RNA structures, while relevant in the crystalline form, may not be generally relevant in the context of RNA in the aqueous phase. The apparent structural flexibility observed in our simulations is likely to bear ramifications for the interactions of RNA with biological molecules (e.g. proteins) and non-biological molecules (e.g. non-viral gene delivery vectors). © CSIRO 2009.

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Intracellular degradation of genes, most notably within the endo-lysosomal compartment is considered a significant barrier to (non-viral) gene delivery in vivo. Previous reports based on in vitro studies claim that carriers possessing a mixture of primary, secondary and tertiary amines are able to buffer the acidic environment within the endosome, allowing for timely release of their contents, leading to higher transfection rates. In this report, we adopt an atomistic molecular dynamics (MD) simulation approach, comparing the complexation of 21-bp siRNA with low-generation polyamidoamine (PAMAM) dendrimers (G0 and G1) at both neutral and acidic pHs, the latter of which mimics the degradative environment within maturing 'late-endosomes'. Our simulations reveal that the time taken for the dendrimer-gene complex (dendriplex) to reach equilibrium is appreciably longer at low pH and this is accompanied by more compact packaging of the dendriplex, as compared to simulations performed at neutral pH. We also note larger absolute values of calculated binding free energies of the dendriplex at low pH, indicating a higher dendrimer-nucleic acid affinity in comparison with neutral pH. These novel simulations provide a more detailed understanding of low molecular-weight polymer-siRNA behavior, mimicking the endosomal environment and provide input of direct relevance to the "proton sponge theory", thereby advancing the rational design of non-viral gene delivery systems.

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T-cell activation requires interaction of T-cell receptors (TCR) with peptide epitopes bound by major histocompatibility complex (MHC) proteins. This interaction occurs at a special cell-cell junction known as the immune or immunological synapse. Fluorescence microscopy has shown that the interplay among one agonist peptide-MHC (pMHC), one TCR and one CD4 provides the minimum complexity needed to trigger transient calcium signalling. We describe a computational approach to the study of the immune synapse. Using molecular dynamics simulation, we report here on a study of the smallest viable model, a TCR-pMHC-CD4 complex in a membrane environment. The computed structural and thermodynamic properties are in fair agreement with experiment. A number of biomolecules participate in the formation of the immunological synapse. Multi-scale molecular dynamics simulations may be the best opportunity we have to reach a full understanding of this remarkable supra-macromolecular event at a cell-cell junction.

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The process of binding of small ligands to dihydrofolate reductase protein has been investigated using all-atom molecular dynamics simulations. The existence of a mechanism that facilitates the search of the binding site by the ligand is demonstrated. The mechanism consists of ligand diffusing on the protein’s surface. It has been discussed in the literature before, but has not been explicitly confirmed for realistic molecular systems. The strength of this nonspecific binding is roughly estimated and found to be essential for the binding kinetics.

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The fracture process involves converting potential energy from a strained body into surface energy, thermal energy, and the energy needed to create lattice defects. In dynamic fracture, energy is also initially converted into kinetic energy. This paper uses molecular dynamics (MD) to simulate brittle frcture in silicon and determine how energy is converted from potential energy (strain energy) into other forms.

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Computer simulation has been used to study the structure and dynamics of methane in hydrated sodium montmorillonite clays under conditions encountered in sedimentary basins. Systems containing approximately one, two, three and four molecular layers of water have followed gradients of 150 bar km-1 and 30Kkm-1, to a maximum burial depth of 6 km (900 bar and 460 K). Methane is coordinated to approximately 19 oxygen atoms, of which typically 6 are provided by the clay surface. Only in the three- and four-layer hydrates is methane able to leave the clay surface. Diffusion depends strongly on the porosity (water content) and burial depth: self-diffusion coefficients are in the range 0.12 × 10-9m2s-1 for water and 0.04 × 10−9m2s−1 < D < 8.64 × 10−9m2s−1 for methane. Bearing in mind that porosity decreases with burial depth, it is estimated that maximum diffusion occurs at around 3 km. This is in good agreement with the known location of methane reservoirs in sedimentary basins.

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The design and synthesis of safe and efficient nonviral vectors for gene delivery has attracted significant attention in recent years. Previous experiments have revealed that the charge density of a polycation (the carrier) plays a crucial role in complexation and the release of the gene from the complex in the cytosol. In this work, we adopt an atomistic molecular dynamics simulation approach to study the complexation of short strand duplex RNA with six cationic carrier systems of varying charge and surface topology. The simulations reveal detailed molecular-level pictures of the structures and dynamics of the RNA-polycation complexes. Estimates for the binding free energy indicate that electrostatic contributions are dominant followed by van der Waals interactions. The binding free energy between the 8(+)polymers and the RNA is found to be larger than that of the 4(+)polymers, in general agreement with previously published data. Because reliable binding free energies provide an effective index of the ability of the polycationic carrier to bind the nucleic acid and also carry implications for the process of gene release within the cytosol, these novel simulations have the potential to provide us with a much better understanding of key mechanistic aspects of gene-polycation complexation and thereby advance the rational design of nonviral gene delivery systems.

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Understanding the molecular mechanism of gene condensation is a key component to rationalizing gene delivery phenomena, including functional properties such as the stability of the gene-vector complex and the intracellular release of the gene. In this work, we adopt an atomistic molecular dynamics simulation approach to study the complexation of short strand duplex RNA with four cationic carrier systems of varying charge and surface topology at different charge ratios. At lower charge ratios, polymers bind quite effectively to siRNA, while at high charge ratios, the complexes are saturated and there are free polymers that are unable to associate with RNA. We also observed reduced fluctuations in RNA structures when complexed with multiple polymers in solution as compared to both free siRNA in water and the single polymer complexes. These novel simulations provide a much better understanding of key mechanistic aspects of gene-polycation complexation and thereby advance progress toward rational design of nonviral gene delivery systems.

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Major histocompatibility complex (MHC) II proteins bind peptide fragments derived from pathogen antigens and present them at the cell surface for recognition by T cells. MHC proteins are divided into Class I and Class II. Human MHC Class II alleles are grouped into three loci: HLA-DP, HLA-DQ, and HLA-DR. They are involved in many autoimmune diseases. In contrast to HLA-DR and HLA-DQ proteins, the X-ray structure of the HLA-DP2 protein has been solved quite recently. In this study, we have used structure-based molecular dynamics simulation to derive a tool for rapid and accurate virtual screening for the prediction of HLA-DP2-peptide binding. A combinatorial library of 247 peptides was built using the "single amino acid substitution" approach and docked into the HLA-DP2 binding site. The complexes were simulated for 1 ns and the short range interaction energies (Lennard-Jones and Coulumb) were used as binding scores after normalization. The normalized values were collected into quantitative matrices (QMs) and their predictive abilities were validated on a large external test set. The validation shows that the best performing QM consisted of Lennard-Jones energies normalized over all positions for anchor residues only plus cross terms between anchor-residues.

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Two-dimensional 'Mercedes Benz' (MB) or BN2D water model (Naim, 1971) is implemented in Molecular Dynamics. It is known that the MB model can capture abnormal properties of real water (high heat capacity, minima of pressure and isothermal compressibility, negative thermal expansion coefficient) (Silverstein et al., 1998). In this work formulas for calculating the thermodynamic, structural and dynamic properties in microcanonical (NVE) and isothermal-isobaric (NPT) ensembles for the model from Molecular Dynamics simulation are derived and verified against known Monte Carlo results. The convergence of the thermodynamic properties and the system's numerical stability are investigated. The results qualitatively reproduce the peculiarities of real water making the model a visually convenient tool that also requires less computational resources, thus allowing simulations of large (hydrodynamic scale) molecular systems. We provide the open source code written in C/C++ for the BN2D water model implementation using Molecular Dynamics.

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Hydrogen bonds play important roles in maintaining the structure of proteins and in the formation of most biomolecular protein-ligand complexes. All amino acids can act as hydrogen bond donors and acceptors. Among amino acids, Histidine is unique, as it can exist in neutral or positively charged forms within the physiological pH range of 5.0 to 7.0. Histidine can thus interact with other aromatic residues as well as forming hydrogen bonds with polar and charged residues. The ability of His to exchange a proton lies at the heart of many important functional biomolecular interactions, including immunological ones. By using molecular docking and molecular dynamics simulation, we examine the influence of His protonation/deprotonation on peptide binding affinity to MHC class II proteins from locus HLA-DP. Peptide-MHC interaction underlies the adaptive cellular immune response, upon which the next generation of commercially-important vaccines will depend. Consistent with experiment, we find that peptides containing protonated His residues bind better to HLA-DP proteins than those with unprotonated His. Enhanced binding at pH 5.0 is due, in part, to additional hydrogen bonds formed between peptide His+ and DP proteins. In acidic endosomes, protein His79β is predominantly protonated. As a result, the peptide binding cleft narrows in the vicinity of His79β, which stabilizes the peptide - HLA-DP protein complex. © 2014 Bentham Science Publishers.

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Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics.

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The dynamics of peptides and proteins generated by classical molecular dynamics (MD) is described by using a Markov model. The model is built by clustering the trajectory into conformational states and estimating transition probabilities between the states. Assuming that it is possible to influence the dynamics of the system by varying simulation parameters, we show how to use the Markov model to determine the parameter values that preserve the folded state of the protein and at the same time, reduce the folding time in the simulation. We investigate this by applying the method to two systems. The first system is an imaginary peptide described by given transition probabilities with a total folding time of 1 micros. We find that only small changes in the transition probabilities are needed to accelerate (or decelerate) the folding. This implies that folding times for slowly folding peptides and proteins calculated using MD cannot be meaningfully compared to experimental results. The second system is a four residue peptide valine-proline-alanine-leucine in water. We control the dynamics of the transitions by varying the temperature and the atom masses. The simulation results show that it is possible to find the combinations of parameter values that accelerate the dynamics and at the same time preserve the native state of the peptide. A method for accelerating larger systems without performing simulations for the whole folding process is outlined.

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Molecular dynamics (MD) has been used to identify the relative distribution of dysprosium in the phosphate glass DyAl0.30P3.05O9.62. The MD model has been compared directly with experimental data obtained from neutron diffraction to enable a detailed comparison beyond the total structure factor level. The MD simulation gives Dy ... Dy correlations at 3.80(5) and 6.40(5) angstrom with relative coordination numbers of 0.8(1) and 7.3(5), thus providing evidence of minority rare-earth clustering within these glasses. The nearest neighbour Dy-O peak occurs at 2.30 angstrom with each Dy atom having on average 5.8 nearest neighbour oxygen atoms. The MD simulation is consistent with the phosphate network model based on interlinked PO4 tetrahedra where the addition of network modifiers Dy3+ depolymerizes the phosphate network through the breakage of P-(O)-P bonds whilst leaving the tetrahedral units intact. The role of aluminium within the network has been taken into explicit account, and A1 is found to be predominantly (78 tetrahedrally coordinated. In fact all four A1 bonds are found to be to P (via an oxygen atom) with negligible amounts of Al-O-Dy bonds present. This provides an important insight into the role of Al additives in improving the mechanical properties of these glasses.

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The aim of this research was to investigate the molecular interactions occurring in the formulation of non-ionic surfactant based vesicles composed monopalmitoyl glycerol (MPG), cholesterol (Chol) and dicetyl phosphate (DCP). In the formulation of these vesicles, the thermodynamic attributes and surfactant interactions based on molecular dynamics, Langmuir monolayer studies, differential scanning calorimetry (DSC), hot stage microscopy and thermogravimetric analysis (TGA) were investigated. Initially the melting points of the components individually, and combined at a 5:4:1 MPG:Chol:DCP weight ratio, were investigated; the results show that lower (90 C) than previously reported (120-140 C) temperatures could be adopted to produce molten surfactants for the production of niosomes. This was advantageous for surfactant stability; whilst TGA studies show that the individual components were stable to above 200 C, the 5:4:1 MPG:Chol:DCP mixture show ∼2% surfactant degradation at 140 C, compared to 0.01% was measured at 90 C. Niosomes formed at this lower temperature offered comparable characteristics to vesicles prepared using higher temperatures commonly reported in literature. In the formation of niosome vesicles, cholesterol also played a key role. Langmuir monolayer studies demonstrated that intercalation of cholesterol in the monolayer did not occur in the MPG:Chol:DCP (5:4:1 weight ratio) mixture. This suggests cholesterol may support bilayer assembly, with molecular simulation studies also demonstrating that vesicles cannot be built without the addition of cholesterol, with higher concentrations of cholesterol (5:4:1 vs 5:2:1, MPG:Chol:DCP) decreasing the time required for niosome assembly. © 2013 Elsevier B.V.