Time-multiscale methods for the simulation of slow transport problems in atomistic systems

En esta tesis presentamos una teoría adaptada a la simulación de fenómenos lentos de transporte en sistemas atomísticos. En primer lugar, desarrollamos el marco teórico para modelizar colectividades estadísticas de equilibrio. A continuación, lo adaptamos para construir modelos de colectividades estadísticas fuera de equilibrio. Esta teoría reposa sobre los principios de la mecánica estadística, en particular el principio de máxima entropía de Jaynes, utilizado tanto para sistemas en equilibrio como fuera de equilibrio, y la teoría de las aproximaciones del campo medio. Expresamos matemáticamente el problema como un principio variacional en el que maximizamos una entropía libre, en lugar de una energía libre. La formulación propuesta permite definir equivalentes atomísticos de variables macroscópicas como la temperatura y la fracción molar. De esta forma podemos considerar campos macroscópicos no uniformes. Completamos el marco teórico con reglas de cuadratura de Monte Carlo, gracias a las cuales obtenemos modelos computables. A continuación, desarrollamos el conjunto completo de ecuaciones que gobiernan procesos de transporte. Deducimos la desigualdad de disipación entrópica a partir de fuerzas y flujos termodinámicos discretos. Esta desigualdad nos permite identificar la estructura que deben cumplir los potenciales cinéticos discretos. Dichos potenciales acoplan las tasas de variación en el tiempo de las variables microscópicas con las fuerzas correspondientes. Estos potenciales cinéticos deben ser completados con una relación fenomenológica, del tipo definido por la teoría de Onsanger. Por último, aportamos validaciones numéricas. Con ellas ilustramos la capacidad de la teoría presentada para simular propiedades de equilibrio y segregación superficial en aleaciones metálicas. Primero, simulamos propiedades termodinámicas de equilibrio en el sistema atomístico. A continuación evaluamos la habilidad del modelo para reproducir procesos de transporte en sistemas complejos que duran tiempos largos con respecto a los tiempos característicos a escala atómica. ABSTRACT In this work, we formulate a theory to address simulations of slow time transport effects in atomic systems. We first develop this theoretical framework in the context of equilibrium of atomic ensembles, based on statistical mechanics. We then adapt it to model ensembles away from equilibrium. The theory stands on Jaynes' maximum entropy principle, valid for the treatment of both, systems in equilibrium and away from equilibrium and on meanfield approximation theory. It is expressed in the entropy formulation as a variational principle. We interpret atomistic equivalents of macroscopic variables such as the temperature and the molar fractions, wich are not required to be uniform, but can vary from particle to particle. We complement this theory with Monte Carlo summation rules for further approximation. In addition, we provide a framework for studying transport processes with the full set of equations driving the evolution of the system. We first derive a dissipation inequality for the entropic production involving discrete thermodynamic forces and fluxes. This discrete dissipation inequality identifies the adequate structure for discrete kinetic potentials which couple the microscopic field rates to the corresponding driving forces. Those kinetic potentials must finally be expressed as a phenomenological rule of the Onsanger Type. We present several validation cases, illustrating equilibrium properties and surface segregation of metallic alloys. We first assess the ability of a simple meanfield model to reproduce thermodynamic equilibrium properties in systems with atomic resolution. Then, we evaluate the ability of the model to reproduce a long-term transport process in complex systems.

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.

Molecular simulation of gas adsorption equilibria in nanoporous materials

This work is divided into two distinct parts. The first part consists of the study of the metal organic framework UiO-66Zr, where the aim was to determine the force field that best describes the adsorption equilibrium properties of two different gases, methane and carbon dioxide. The other part of the work focuses on the study of the single wall carbon nanotube topology for ethane adsorption; the aim was to simplify as much as possible the solid-fluid force field model to increase the computational efficiency of the Monte Carlo simulations. The choice of both adsorbents relies on their potential use in adsorption processes, such as the capture and storage of carbon dioxide, natural gas storage, separation of components of biogas, and olefin/paraffin separations. The adsorption studies on the two porous materials were performed by molecular simulation using the grand canonical Monte Carlo (μ,V,T) method, over the temperature range of 298-343 K and pressure range 0.06-70 bar. The calibration curves of pressure and density as a function of chemical potential and temperature for the three adsorbates under study, were obtained Monte Carlo simulation in the canonical ensemble (N,V,T); polynomial fit and interpolation of the obtained data allowed to determine the pressure and gas density at any chemical potential. The adsorption equilibria of methane and carbon dioxide in UiO-66Zr were simulated and compared with the experimental data obtained by Jasmina H. Cavka et al. The results show that the best force field for both gases is a chargeless united-atom force field based on the TraPPE model. Using this validated force field it was possible to estimate the isosteric heats of adsorption and the Henry constants. In the Grand-Canonical Monte Carlo simulations of carbon nanotubes, we conclude that the fastest type of run is obtained with a force field that approximates the nanotube as a smooth cylinder; this approximation gives execution times that are 1.6 times faster than the typical atomistic runs.

Comblike poly(a-alkyl g glutamate)s: computer simulation studies of an intermediate thermal phase.

Monte Carlo (MC) simulations have been used to study the structure of an intermediate thermal phase of poly(R-octadecyl ç,D-glutamate). This is a comblike poly(ç-peptide) able to adopt a biphasic structure that has been described as a layered arrangement of backbone helical rods immersed in a paraffinic pool of polymethylene side chains. Simulations were performed at two different temperatures (348 and 363 K), both of them above the melting point of the paraffinic phase, using the configurational bias MC algorithm. Results indicate that layers are constituted by a side-by-side packing of 17/5 helices. The organization of the interlayer paraffinic region is described in atomistic terms by examining the torsional angles and the end-to-end distances for the octadecyl side chains. Comparison with previously reported comblike poly(â-peptide)s revealed significant differences in the organization of the alkyl side chains.

Développement d’une méthode de simulation multi-échelle pour l’étude des grandes transformations dans les protéines

Les films de simulations qui accompagnent le document ont été réalisés avec Pymol.

Atomistic-continuum modeling of ultrafast laser-induced melting of silicon targets

In this work, we present an atomistic-continuum model for simulations of ultrafast laser-induced melting processes in semiconductors on the example of silicon. The kinetics of transient non-equilibrium phase transition mechanisms is addressed with MD method on the atomic level, whereas the laser light absorption, strong generated electron-phonon nonequilibrium, fast heat conduction, and photo-excited free carrier diffusion are accounted for with a continuum TTM-like model (called nTTM). First, we independently consider the applications of nTTM and MD for the description of silicon, and then construct the combined MD-nTTM model. Its development and thorough testing is followed by a comprehensive computational study of fast nonequilibrium processes induced in silicon by an ultrashort laser irradiation. The new model allowed to investigate the effect of laser-induced pressure and temperature of the lattice on the melting kinetics. Two competing melting mechanisms, heterogeneous and homogeneous, were identified in our big-scale simulations. Apart from the classical heterogeneous melting mechanism, the nucleation of the liquid phase homogeneously inside the material significantly contributes to the melting process. The simulations showed, that due to the open diamond structure of the crystal, the laser-generated internal compressive stresses reduce the crystal stability against the homogeneous melting. Consequently, the latter can take a massive character within several picoseconds upon the laser heating. Due to the large negative volume of melting of silicon, the material contracts upon the phase transition, relaxes the compressive stresses, and the subsequent melting proceeds heterogeneously until the excess of thermal energy is consumed. A series of simulations for a range of absorbed fluences allowed us to find the threshold fluence value at which homogeneous liquid nucleation starts contributing to the classical heterogeneous propagation of the solid-liquid interface. A series of simulations for a range of the material thicknesses showed that the sample width we chosen in our simulations (800 nm) corresponds to a thick sample. Additionally, in order to support the main conclusions, the results were verified for a different interatomic potential. Possible improvements of the model to account for nonthermal effects are discussed and certain restrictions on the suitable interatomic potentials are found. As a first step towards the inclusion of these effects into MD-nTTM, we performed nanometer-scale MD simulations with a new interatomic potential, designed to reproduce ab initio calculations at the laser-induced electronic temperature of 18946 K. The simulations demonstrated that, similarly to thermal melting, nonthermal phase transition occurs through nucleation. A series of simulations showed that higher (lower) initial pressure reinforces (hinders) the creation and the growth of nonthermal liquid nuclei. For the example of Si, the laser melting kinetics of semiconductors was found to be noticeably different from that of metals with a face-centered cubic crystal structure. The results of this study, therefore, have important implications for interpretation of experimental data on the kinetics of melting process of semiconductors.

Molecular dynamics simulation of interactions between a sodium dodecyl sulfate micelle and a poly(ethylene oxide) polymer

We have performed atomistic molecular dynamics simulations of an anionic sodium dodecyl sulfate (SDS) micelle and a nonionic poly(ethylene oxide) (PEO) polymer in aqueous solution. The micelle consisted of 60 surfactant molecules, and the polymer chain lengths varied from 20 to 40 monomers. The force field parameters for PEO were adjusted by using 1,2-dimethoxymethane (DME) as a model compound and matching its hydration enthalpy and conformational behavior to experiment. Excellent agreement with previous experimental and simulation work was obtained through these modifications. The simulated scaling behavior of the PEO radius of gyration was also in close agreement with experimental results. The SDS-PEO simulations show that the polymer resides on the micelle surface and at the hydrocarbon-water interface, leading to a selective reduction in the hydrophobic contribution to the solvent-accessible surface area of the micelle. The association is mainly driven by hydrophobic interactions between the polymer and surfactant tails, while the interaction between the polymer and sulfate headgroups on the micelle surface is weak. The 40-monomer chain is mostly wrapped around the micelle, and nearly 90% of the monomers are adsorbed at low PEO concentration. Simulations were also performed with multiple 20-monomer chains, and gradual addition of polymer indicates that about 120 monomers are required to saturate the micelle surface. The stoichiometry of the resulting complex is in close agreement with experimental results, and the commonly accepted "beaded necklace" structure of the SDS-PEO complex is recovered by our simulations.

Computer simulation of ordering and dynamics in liquid crystals in the bulk and close to the surface

The aim of this PhD thesis is to investigate the orientational and dynamical properties of liquid crystalline systems, at molecular level and using atomistic computer simulations, to reach a better understanding of material behavior from a microscopic point view. In perspective this should allow to clarify the relation between the micro and macroscopic properties with the objective of predicting or confirming experimental results on these systems. In this context, we developed four different lines of work in the thesis. The first one concerns the orientational order and alignment mechanism of rigid solutes of small dimensions dissolved in a nematic phase formed by the 4-pentyl,4 cyanobiphenyl (5CB) nematic liquid crystal. The orientational distribution of solutes have been obtained with Molecular Dynamics Simulation (MD) and have been compared with experimental data reported in literature. we have also verified the agreement between order parameters and dipolar coupling values measured in NMR experiments. The MD determined effective orientational potentials have been compared with the predictions of Maier­Saupe and Surface tensor models. The second line concerns the development of a correct parametrization able to reproduce the phase transition properties of a prototype of the oligothiophene semiconductor family: sexithiophene (T6). T6 forms two crystalline polymorphs largely studied, and possesses liquid crystalline phases still not well characterized, From simulations we detected a phase transition from crystal to liquid crystal at about 580 K, in agreement with available experiments, and in particular we found two LC phases, smectic and nematic. The crystal­smectic transition is associated to a relevant density variation and to strong conformational changes of T6, namely the molecules in the liquid crystal phase easily assume a bent shape, deviating from the planar structure typical of the crystal. The third line explores a new approach for calculating the viscosity in a nematic through a virtual exper- iment resembling the classical falling sphere experiment. The falling sphere is replaced by an hydrogenated silicon nanoparticle of spherical shape suspended in 5CB, and gravity effects are replaced by a constant force applied to the nanoparticle in a selected direction. Once the nanoparticle reaches a constant velocity, the viscosity of the medium can be evaluated using Stokes' law. With this method we successfully reproduced experimental viscosities and viscosity anisotropy for the solvent 5CB. The last line deals with the study of order induction on nematic molecules by an hydrogenated silicon surface. Gaining predicting power for the anchoring behavior of liquid crystals at surfaces will be a very desirable capability, as many properties related to devices depend on molecular organization close to surfaces. Here we studied, by means of atomistic MD simulations, the flat interface between an hydrogenated (001) silicon surface in contact with a sample of 5CB molecules. We found a planar anchoring of the first layers of 5CB where surface interactions are dominating with respect to the mesogen intermolecular interactions. We also analyzed the interface 5CB­vacuum, finding a homeotropic orientation of the nematic at this interface.

Scale bridging concepts in molecular simulation : coarse-graining and thermodynamic coupling

In dieser Arbeit wurden Simulation von Flüssigkeiten auf molekularer Ebene durchgeführt, wobei unterschiedliche Multi-Skalen Techniken verwendet wurden. Diese erlauben eine effektive Beschreibung der Flüssigkeit, die weniger Rechenzeit im Computer benötigt und somit Phänomene auf längeren Zeit- und Längenskalen beschreiben kann.rnrnEin wesentlicher Aspekt ist dabei ein vereinfachtes (“coarse-grained”) Modell, welches in einem systematischen Verfahren aus Simulationen des detaillierten Modells gewonnen wird. Dabei werden ausgewählte Eigenschaften des detaillierten Modells (z.B. Paar-Korrelationsfunktion, Druck, etc) reproduziert.rnrnEs wurden Algorithmen untersucht, die eine gleichzeitige Kopplung von detaillierten und vereinfachten Modell erlauben (“Adaptive Resolution Scheme”, AdResS). Dabei wird das detaillierte Modell in einem vordefinierten Teilvolumen der Flüssigkeit (z.B. nahe einer Oberfläche) verwendet, während der Rest mithilfe des vereinfachten Modells beschrieben wird.rnrnHierzu wurde eine Methode (“Thermodynamische Kraft”) entwickelt um die Kopplung auch dann zu ermöglichen, wenn die Modelle in verschiedenen thermodynamischen Zuständen befinden. Zudem wurde ein neuartiger Algorithmus der Kopplung beschrieben (H-AdResS) der die Kopplung mittels einer Hamilton-Funktion beschreibt. In diesem Algorithmus ist eine zur Thermodynamischen Kraft analoge Korrektur mit weniger Rechenaufwand möglich.rnrnAls Anwendung dieser grundlegenden Techniken wurden Pfadintegral Molekulardynamik (MD) Simulationen von Wasser untersucht. Mithilfe dieser Methode ist es möglich, quantenmechanische Effekte der Kerne (Delokalisation, Nullpunktsenergie) in die Simulation einzubeziehen. Hierbei wurde zuerst eine Multi-Skalen Technik (“Force-matching”) verwendet um eine effektive Wechselwirkung aus einer detaillierten Simulation auf Basis der Dichtefunktionaltheorie zu extrahieren. Die Pfadintegral MD Simulation verbessert die Beschreibung der intra-molekularen Struktur im Vergleich mit experimentellen Daten. Das Modell eignet sich auch zur gleichzeitigen Kopplung in einer Simulation, wobei ein Wassermolekül (beschrieben durch 48 Punktteilchen im Pfadintegral-MD Modell) mit einem vereinfachten Modell (ein Punktteilchen) gekoppelt wird. Auf diese Weise konnte eine Wasser-Vakuum Grenzfläche simuliert werden, wobei nur die Oberfläche im Pfadintegral Modell und der Rest im vereinfachten Modell beschrieben wird.

A novel computer simulation method for simulating the multiscale transduction dynamics of signal proteins

Signal proteins are able to adapt their response to a change in the environment, governing in this way a broad variety of important cellular processes in living systems. While conventional molecular-dynamics (MD) techniques can be used to explore the early signaling pathway of these protein systems at atomistic resolution, the high computational costs limit their usefulness for the elucidation of the multiscale transduction dynamics of most signaling processes, occurring on experimental timescales. To cope with the problem, we present in this paper a novel multiscale-modeling method, based on a combination of the kinetic Monte-Carlo- and MD-technique, and demonstrate its suitability for investigating the signaling behavior of the photoswitch light-oxygen-voltage-2-Jα domain from Avena Sativa (AsLOV2-Jα) and an AsLOV2-Jα-regulated photoactivable Rac1-GTPase (PA-Rac1), recently employed to control the motility of cancer cells through light stimulus. More specifically, we show that their signaling pathways begin with a residual re-arrangement and subsequent H-bond formation of amino acids near to the flavin-mononucleotide chromophore, causing a coupling between β-strands and subsequent detachment of a peripheral α-helix from the AsLOV2-domain. In the case of the PA-Rac1 system we find that this latter process induces the release of the AsLOV2-inhibitor from the switchII-activation site of the GTPase, enabling signal activation through effector-protein binding. These applications demonstrate that our approach reliably reproduces the signaling pathways of complex signal proteins, ranging from nanoseconds up to seconds at affordable computational costs.

Atomistic modeling of Ge damage accumulation, amorphization and solid phase epitaxial regrowth

En los últimos años, el Ge ha ganado de nuevo atención con la finalidad de ser integrado en el seno de las existentes tecnologías de microelectrónica. Aunque no se le considera como un canddato capaz de reemplazar completamente al Si en el futuro próximo, probalemente servirá como un excelente complemento para aumentar las propiedades eléctricas en dispositivos futuros, especialmente debido a su alta movilidad de portadores. Esta integración requiere de un avance significativo del estado del arte en los procesos de fabricado. Técnicas de simulación, como los algoritmos de Monte Carlo cinético (KMC), proporcionan un ambiente atractivo para llevar a cabo investigación y desarrollo en este campo, especialmente en términos de costes en tiempo y financiación. En este estudio se han usado, por primera vez, técnicas de KMC con el fin entender el procesado “front-end” de Ge en su fabricación, específicamente la acumulación de dañado y amorfización producidas por implantación iónica y el crecimiento epitaxial en fase sólida (SPER) de las capas amorfizadas. Primero, simulaciones de aproximación de clisiones binarias (BCA) son usadas para calcular el dañado causado por cada ión. La evolución de este dañado en el tiempo se simula usando KMC sin red, o de objetos (OKMC) en el que sólamente se consideran los defectos. El SPER se simula a través de una aproximación KMC de red (LKMC), siendo capaz de seguir la evolución de los átomos de la red que forman la intercara amorfo/cristalina. Con el modelo de amorfización desarrollado a lo largo de este trabajo, implementado en un simulador multi-material, se pueden simular todos estos procesos. Ha sido posible entender la acumulación de dañado, desde la generación de defectos puntuales hasta la formación completa de capas amorfas. Esta acumulación ocurre en tres regímenes bien diferenciados, empezando con un ritmo lento de formación de regiones de dañado, seguido por una rápida relajación local de ciertas áreas en la fase amorfa donde ambas fases, amorfa y cristalina, coexisten, para terminar en la amorfización completa de capas extensas, donde satura el ritmo de acumulación. Dicha transición ocurre cuando la concentración de dañado supera cierto valor límite, el cual es independiente de las condiciones de implantación. Cuando se implantan los iones a temperaturas relativamente altas, el recocido dinámico cura el dañado previamente introducido y se establece una competición entre la generación de dañado y su disolución. Estos efectos se vuelven especialmente importantes para iones ligeros, como el B, el cual crea dañado más diluido, pequeño y distribuido de manera diferente que el causado por la implantación de iones más pesados, como el Ge. Esta descripción reproduce satisfactoriamente la cantidad de dañado y la extensión de las capas amorfas causadas por implantación iónica reportadas en la bibliografía. La velocidad de recristalización de la muestra previamente amorfizada depende fuertemente de la orientación del sustrato. El modelo LKMC presentado ha sido capaz de explicar estas diferencias entre orientaciones a través de un simple modelo, dominado por una única energía de activación y diferentes prefactores en las frecuencias de SPER dependiendo de las configuraciones de vecinos de los átomos que recristalizan. La formación de maclas aparece como una consecuencia de esta descripción, y es predominante en sustratos crecidos en la orientación (111)Ge. Este modelo es capaz de reproducir resultados experimentales para diferentes orientaciones, temperaturas y tiempos de evolución de la intercara amorfo/cristalina reportados por diferentes autores. Las parametrizaciones preliminares realizadas de los tensores de activación de tensiones son también capaces de proveer una buena correlación entre las simulaciones y los resultados experimentales de velocidad de SPER a diferentes temperaturas bajo una presión hidrostática aplicada. Los estudios presentados en esta tesis han ayudado a alcanzar un mejor entendimiento de los mecanismos de producción de dañado, su evolución, amorfización y SPER para Ge, además de servir como una útil herramienta para continuar el trabajo en este campo. In the recent years, Ge has regained attention to be integrated into existing microelectronic technologies. Even though it is not thought to be a feasible full replacement to Si in the near future, it will likely serve as an excellent complement to enhance electrical properties in future devices, specially due to its high carrier mobilities. This integration requires a significant upgrade of the state-of-the-art of regular manufacturing processes. Simulation techniques, such as kinetic Monte Carlo (KMC) algorithms, provide an appealing environment to research and innovation in the field, specially in terms of time and funding costs. In the present study, KMC techniques are used, for the first time, to understand Ge front-end processing, specifically damage accumulation and amorphization produced by ion implantation and Solid Phase Epitaxial Regrowth (SPER) of the amorphized layers. First, Binary Collision Approximation (BCA) simulations are used to calculate the damage caused by every ion. The evolution of this damage over time is simulated using non-lattice, or Object, KMC (OKMC) in which only defects are considered. SPER is simulated through a Lattice KMC (LKMC) approach, being able to follow the evolution of the lattice atoms forming the amorphous/crystalline interface. With the amorphization model developed in this work, implemented into a multi-material process simulator, all these processes can be simulated. It has been possible to understand damage accumulation, from point defect generation up to full amorphous layers formation. This accumulation occurs in three differentiated regimes, starting at a slow formation rate of the damage regions, followed by a fast local relaxation of areas into the amorphous phase where both crystalline and amorphous phases coexist, ending in full amorphization of extended layers, where the accumulation rate saturates. This transition occurs when the damage concentration overcomes a certain threshold value, which is independent of the implantation conditions. When implanting ions at relatively high temperatures, dynamic annealing takes place, healing the previously induced damage and establishing a competition between damage generation and its dissolution. These effects become specially important for light ions, as B, for which the created damage is more diluted, smaller and differently distributed than that caused by implanting heavier ions, as Ge. This description successfully reproduces damage quantity and extension of amorphous layers caused by means of ion implantation reported in the literature. Recrystallization velocity of the previously amorphized sample strongly depends on the substrate orientation. The presented LKMC model has been able to explain these differences between orientations through a simple model, dominated by one only activation energy and different prefactors for the SPER rates depending on the neighboring configuration of the recrystallizing atoms. Twin defects formation appears as a consequence of this description, and are predominant for (111)Ge oriented grown substrates. This model is able to reproduce experimental results for different orientations, temperatures and times of evolution of the amorphous/crystalline interface reported by different authors. Preliminary parameterizations for the activation strain tensors are able to also provide a good match between simulations and reported experimental results for SPER velocities at different temperatures under the appliance of hydrostatic pressure. The studies presented in this thesis have helped to achieve a greater understanding of damage generation, evolution, amorphization and SPER mechanisms in Ge, and also provide a useful tool to continue research in this field.

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.

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.

Concurrent multiscale modelling of atomistic and hydrodynamic processes in liquids

Fluctuations of liquids at the scales where the hydrodynamic and atomistic descriptions overlap are considered. The importance of these fluctuations for atomistic motions is discussed and examples of their accurate modelling with a multi-space-time-scale fluctuating hydrodynamics scheme are provided. To resolve microscopic details of liquid systems, including biomolecular solutions, together with macroscopic fluctuations in space-time, a novel hybrid atomistic-fluctuating hydrodynamics approach is introduced. For a smooth transition between the atomistic and continuum representations, an analogy with two-phase hydrodynamics is used that leads to a strict preservation of macroscopic mass and momentum conservation laws. Examples of numerical implementation of the new hybrid approach for the multiscale simulation of liquid argon in equilibrium conditions are provided. © 2014 The Author(s) Published by the Royal Society.

Encapsulated membrane proteins:a simplified system for molecular simulation

Over the past 50 years there has been considerable progress in our understanding of biomolecular interactions at an atomic level. This in turn has allowed molecular simulation methods employing full atomistic modeling at ever larger scales to develop. However, some challenging areas still remain where there is either a lack of atomic resolution structures or where the simulation system is inherently complex. An area where both challenges are present is that of membranes containing membrane proteins. In this review we analyse a new practical approach to membrane protein study that offers a potential new route to high resolution structures and the possibility to simplify simulations. These new approaches collectively recognise that preservation of the interaction between the membrane protein and the lipid bilayer is often essential to maintain structure and function. The new methods preserve these interactions by producing nano-scale disc shaped particles that include bilayer and the chosen protein. Currently two approaches lead in this area: the MSP system that relies on peptides to stabilise the discs, and SMALPs where an amphipathic styrene maleic acid copolymer is used. Both methods greatly enable protein production and hence have the potential to accelerate atomic resolution structure determination as well as providing a simplified format for simulations of membrane protein dynamics.