Structure, dynamics, and energetics of siRNA-cationic vector complexation:a molecular dynamics study

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.

Flexibility of short-strand RNA in aqueous solution as revealed by molecular dynamics simulation:are A′-RNA and A-RNA distinct conformational structures?

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.

Complex temporal patterns in molecular dynamics:a direct measure of the phase-space exploration by the trajectory at macroscopic time scales

Computer simulated trajectories of bulk water molecules form complex spatiotemporal structures at the picosecond time scale. This intrinsic complexity, which underlies the formation of molecular structures at longer time scales, has been quantified using a measure of statistical complexity. The method estimates the information contained in the molecular trajectory by detecting and quantifying temporal patterns present in the simulated data (velocity time series). Two types of temporal patterns are found. The first, defined by the short-time correlations corresponding to the velocity autocorrelation decay times (â‰0.1â€ps), remains asymptotically stable for time intervals longer than several tens of nanoseconds. The second is caused by previously unknown longer-time correlations (found at longer than the nanoseconds time scales) leading to a value of statistical complexity that slowly increases with time. A direct measure based on the notion of statistical complexity that describes how the trajectory explores the phase space and independent from the particular molecular signal used as the observed time series is introduced. © 2008 The American Physical Society.

Structure and dynamics of multiple cationic vectors-siRNA complexation by all-atomic molecular dynamics simulations

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.

The effect of pH on PAMAM dendrimer-siRNA complexation:endosomal considerations as determined by molecular dynamics simulation

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.

HLA-DP2 binding prediction by molecular dynamics simulations

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.

Controlling protein molecular dynamics:how to accelerate folding while preserving the native state

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.

Computational mechanics reveals nanosecond time correlations in molecular dynamics of liquid systems

Statistical complexity, a measure introduced in computational mechanics has been applied to MD simulated liquid water and other molecular systems. It has been found that statistical complexity does not converge in these systems but grows logarithmically without a limit. The coefficient of the growth has been introduced as a new molecular parameter which is invariant for a given liquid system. Using this new parameter extremely long time correlations in the system undetectable by traditional methods are elucidated. The existence of hundreds of picosecond and even nanosecond long correlations in bulk water has been demonstrated. © 2008 Elsevier B.V. All rights reserved.

Sensitivity of peptide conformational dynamics on clustering of a classical molecular dynamics trajectory

We investigate the sensitivity of a Markov model with states and transition probabilities obtained from clustering a molecular dynamics trajectory. We have examined a 500 ns molecular dynamics trajectory of the peptide valine-proline-alanine-leucine in explicit water. The sensitivity is quantified by varying the boundaries of the clusters and investigating the resulting variation in transition probabilities and the average transition time between states. In this way, we represent the effect of clustering using different clustering algorithms. It is found that in terms of the investigated quantities, the peptide dynamics described by the Markov model is sensitive to the clustering; in particular, the average transition times are found to vary up to 46%. Moreover, inclusion of nonphysical sparsely populated clusters can lead to serious errors of up to 814%. In the investigation, the time step used in the transition matrix is determined by the minimum time scale on which the system behaves approximately Markovian. This time step is found to be about 100 ps. It is concluded that the description of peptide dynamics with transition matrices should be performed with care, and that using standard clustering algorithms to obtain states and transition probabilities may not always produce reliable results.

T-cell epitope prediction and immune complex simulation using molecular dynamics:state of the art and persisting challenges

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.

A molecular dynamics model of the atomic structure of dysprosium alumino-phosphate glass

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.

Toward an atomistic understanding of the immune synapse:large-scale molecular dynamics simulation of a membrane-embedded TCR-pMHC-CD4 complex

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.

Ligand diffusion on protein surface observed in molecular dynamics simulation

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.

Molecular dynamics study of solvent transport in nanoscale osmosis

An ideal of osmotic equilibrium between an ideal solution and pure solvent separated by a semi-permeable membrane is studied numerically using the method of molecular dynamics. The osmotic flow is observed as the inflow of the solvent across the membrane from the dilute to the concentrated side. The validity of van't Hoff's law for osmotic pressure is confirmed over a wide range of concentrations. It is found that the law is established by a balance between non-uniform partial pressures of solute and solvent. Furthermore, the present model permits an understanding of the mechanism of the osmotic flow in the relaxation process as the liquids evolve from the initial state to the equilibrium state. We focus in particular on the interaction between solute and solvent. ©2008 The Physical Society of Japan.

Investigating the role of cholesterol in the formation of non-ionic surfactant based bilayer vesicles:thermal analysis and molecular dynamics

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.