Proteins and DNA are essential to life as we know it and understanding their function is understanding their structure and dynamics. The importance of the latter is being appreciated more in recent years and has led to the development of novel interdisciplinary techniques and approaches to studying protein function. Three techniques to study protein structure and dynamics have been used and combined in different ways in the context of this thesis and have led to a better understanding of the three systems described herein. X-ray crystallography is the oldest and still arguably most popular technique to study macromolecular structures. Nuclear magnetic resonance (NMR) spectroscopy is a not much younger technique that is a powerful tool not only to probe molecular structure but also dynamics. The last technique described herein are molecular dynamics (MD) simulations, which are only just growing out of their infancy. MD simulations are computer simulations of macromolecules based on structures solved by X-ray crystallography or NMR spectroscopy, that can give mechanistic insight into dynamic processes of macromolecules whose amplitudes can be estimated by the former two techniques. MD simulations of the model protein GB3 (B3 immunoglobulin-binding domain of streptococcal protein G) were conducted to identify origins of discrepancies between order parameters derived from different sets of MD simulations and NMR relaxation experiments.The results highlight the importance of time scales as well as sampling when comparing MD simulations to NMR experiments. Discrepancies are seen for unstructured regions like loops and termini and often correspond to nanosecond time scale transitions between conformational substates that are either over- or undersampled in simulation. Sampling biases can be somewhat remedied by running longer (microsecond time scale) simulations. However, some discrepancies persist over even very long trajectories. We show that these discrepancies can be due to the choice of the starting structure and more specifically even differences in protonation procedures. A test for convergence on the nanosecond time scale is shown to be able to correct for many of the observed discrepancies. Next, MD simulations were used to predict in vitro thermostability of members of the bacterial Ribonuclease HI (RNase H) family of endonucleases. Thermodynamic stability is a central requirement for protein function and a goal of protein engineering is improvement of stability, particularly for applications in biotechnology. The temperature dependence of the generalized order parameter, S, for four RNase H homologs, from psychrotrophic, mesophilic and thermophilic organisms, is highly correlated with experimentally determined melting temperatures and with calculated free energies of folding at the midpoint temperature of the simulations. This study provides an approach for in silico mutational screens to improve thermostability of biologically and industrially relevant enzymes. Lastly, we used a combination of X-ray crystallography, NMR spectroscopy and MD simulations to study specificity of the interaction between Drosophila Hox proteins and their DNA target sites. Hox proteins are transcription factors specifying segment identity during embryogenesis of bilaterian animals. The DNA binding homeodomains have been shown to confer specificity to the different Hox paralogs, while being very similar in sequence and structure. Our results underline earlier findings about the importance of the N-terminal arm and linker region of Hox homeodomains, the cofactor Exd, as well as DNA shape, for specificity. A comparison of predicted DNA shapes based on sequence alone with the shapes observed for different DNA target sequences in four crystal structures when in complex with the Drosophila Hox protein AbdB and the cofactor Exd, shows that a combined ”induced fit”/”conformational selection” mechanism is the most likely mechanism by which Hox homeodomains recognize DNA shape and achieve specificity. The minor groove widths for all sequences is close to identical for all ternary complexes found in the different crystal structures, whereas predicted shapes vary between the different DNA sequences. The sequences that have shown higher affinity to AbdB in vitro have a predicted DNA shape that matches the observed DNA shape in the ternary complexes more closely than the sequences that show low in vitro affinity to AbdB. This strongly suggests that the AbdB-Exd complex selects DNA sequences with a higher propensity to adopt the final shape in their unbound form, leading to higher affinity. An additional AbdB monomer binding site with a strongly preformed binding competent shape is observed for one of the oligomers in the reverse complement strand of one of the canonical (weak) Hox-Exd complex binding site. The shape preference seems strong enough for AbdB monomer binding to compete with AbdB-Exd dimer binding to that same oligomer, suggested by the presence of both binding modes in the same crystal. The monomer binding site is essentially able to compete with the dimer binding site, even though binding with the cofactor is not possible, because its shape is very close to the ideal shape. A comparison of different crystal structures solved herein and in the literature as well as a set of molecular dynamics simulations was performed and led to insights about the importance of residues in the Hox N-terminal arm for the preference of certain Hox paralogs to certain DNA shapes. Taken together all these insights contribute to our understanding of Hox specificity in particular as well as protein-DNA interactions in general.

This thesis describes the development a new swarm-enhanced sampling methodology and its application to the exploration of biologically relevant molecules. First, the development of a new multi-dimensional swarm-enhanced sampling molecular dynamics (msesMD) approach is detailed. Relative to the original swarm-enhanced sampling molecular dynamics (sesMD) methodology, the msesMD method demonstrates improved parameter transferability, resulting in more extensive sampling when scaling to larger systems such as alanine heptapeptide. The implementation and optimisation of the swarm-enhanced sampling algorithms in the AMBER software suite are also described. Through the use of the newer pmemd molecular dynamics (MD) engine and asynchronous MPI routines, speedups of up to three times the original sesMD implementation were achieved. The msesMD method is then applied to the investigation of carbohydrates, first looking at rare conformational changes in Lewis oligosaccharides. Validating against multi-microsecond unbiased MD trajectories and other enhanced sampling methods, the msesMD simulations identified rare conformational changes leading to the adoption of non-canonical unstacked core trisaccharide structures. Next, the use of msesMD as a tool to probe pyranose ring pucker events is explored. Evaluating against four benchmark monosaccharide systems, msesMD simulations accurately recover puckering details not easily obtained via multi-microsecond unbiased MD. This was followed by an exploration of the impact of ring substituents on conformation in glycosaminoglycan monosaccharides: through msesMD simulations, the influence of specific sulfation patterns were explored, finding that in some cases, such as 4-O-sulfation in N-acetyl-galactosamine, large changes in the relative stability of ring conformers can arise. Finally, the msesMD method was coupled with a thermodynamic integration scheme and used to evaluate solvation free energies for small molecule systems. Comparing against independent trajectory TI simulations, it was found that although the correct solvation free energies were obtained, the msesMD based method did not offer an advantage over unbiased MD for these small molecule systems. However, interesting discrepancies in free energy estimates arising from the use of hydrogen mass repartitioning were found.

No description available.

No description available.

Cys-loop receptors are membrane proteins that are key players for the fast synaptic neurotransmission. Their ion transport initiates new nerve signals after activation by small agonist molecules, but this function is also highly sensitive to allosteric modulation by a number of compounds such as anesthetics, alcohol or anti-parasitic agents. For a long time, these modulators were believed to act primarily on the membrane, but the availability of high- resolution structures has made it possible to identify several binding sites in the transmembrane domains of the ion channels. It is known that ligand binding in the extracellular domain causes a conformational earthquake that interacts with the transmembrane domain, which leads to channel opening. The investigations carried out in this thesis aim at understanding the connection between ligand binding and channel opening. I present new models of the mammalian GABAA receptor based on the eukaryotic structure GluCl co-crystallized with an anti-parasitic agent, and show how these models can be used to study receptor-modulator interactions. I also show how removal of the bound modulator leads to gradual closing of the channel in molecular dynamics simulations. In contrast, simulations of the receptor with both the agonist and the modulator remain stable in an open-like conformation. This makes it possible to extract several key interactions, and I propose mechanisms for how the extracellular domain motion is initiated. The rapid increase in the number of cys-loop receptor structures the last few years has further made it possible to use principal component analysis (PCA) to create low-dimensional descriptions of the conformational landscape. By performing PCA on the crystal structure ensemble, I have been able to divide the structures into functional clusters and sample the transitions between them using various sampling methods. The studies presented in this thesis contribute to our understanding of the gating mechanism and the functional clustering of the cys-loop receptor structures, which both are important to design new allosteric modulator drugs that influence the channel function, in particular to treat neurological disorders. / <p>QC 20160518</p>

Nanoparticles (NP) offer great merits over controlling thermal, chemical and physical properties when compared to their micro-sized counterparts. The effectiveness of the dispersion of the NP is the key aspect of the applications in nanotechnology. The project studies the characterization and modification of functional NPs aided by the means of large scale molecular thermal dynamic computerized dispersing simulations, in the level of Nanoclusters (NC). Carrying out NP functionality characterisation in fluids can be enhanced, and analysed through computational simulation based on their interactions with fluidic media; in terms of thermo-mechanical, dynamic, physical, chemical and rheological properties. From the engineering perspective, effective characterizations of the nanofluids have also been carried out based on the particles sizes and particle-fluids Brownian motion (BM) theory. The study covered firstly, investigation of the pure CuO NP diffusion in water and hydrocarbon fluids, secondly, examination of the modified CuO NP diffusion in water. In both cases the studies were put under experiments and simulations for data collection and comparison. For simulation the COMPASS forcefield, smoothed particle hydrodynamic potential (SPH) and discrete particle dynamics potential (DPD) were implemented through the system. Excellent prediction of BM, Van der Waals interaction, electrostatic interaction and a number of force-fields in the system were exploited. The experimental results trend demonstrated high coherence with the simulation results. At first the diffusion coefficient was found to be 1.7e-8m2/s in the study of CuO NC in water based fluidic system. Secondly highly concurrent simulation results (i.e. data for viscosity and thermal conductivity) have been computed to experimental coherence. The viscosity trend of MD simulation and experimental results show a high level of convergence for temperatures between 303-323K. The simulated thermal conductivity of the water-CuO nanofluid was between 0.6—0.75W•m−1•K−1, showing a slight increase following a rise in temperature from 303 to 323 K. Moreover, the alkane-CuO nanofluid experimental and simulated work was also carried out, for analysing the thermo-physical quantities. The alkane-CuO nanofluid viscosity was found 0.9—2.7mpas and thermal conductivity is between 0.1—0.4W•m−1•K−1. Finally, the successful modification of the NPs on experimental and simulation platform has been analysed using different characterization variables. Experimental modification data has been quantified by using Fourier Transformation Infrared (FTIR) peak response, from particular ranges of interest i.e. 1667-1609cm-1 and 1668-1557cm-1. These FTIR peaks deduced Carboxylate attachment on the surface of NPs. Later, MD simulation was approached to mimic experimental setup of modification chemistry and similar agglomerations were observed as during experimental conditions. However, this approach has not been presented before; therefore this study has a significant impact on describing the agglomeration of modified NPs on simulation and experimental basis. Henceforth, the methodology established for metal oxide nanoparticle dispersion simulation is a novelty of this work.

Computer simulations have become a vital tool in modern science. The ability to reliably move beyond the capabilities of experiment has allowed great insights into the nature of matter. To enable the study of a wide range of systems and properties a plethora of simulation techniques have been developed and refined, allowing many aspects of complex systems to be demystified. I have used a range of these to study a variety of systems, utilising the latest technology in high performance computing (HPC) and novel, nanoscale models. Monte Carlo (MC) simulation is a commonly used method to study the properties of system using statistical mechanics and I have made use of it in published work [1] to study the properties of ferrogels in homogeneous magnetic fields using a simple microscopic model. The main phenomena of interest concern the anisotropy and enhancement of the elastic moduli that result from applying uniform magnetic fields before and after the magnetic grains are locked in to the polymer-gel matrix by cross-linking reactions. The positional organization of the magnetic grains is influenced by the application of a magnetic field during gel formation, leading to a pronounced anisotropy in the mechanical response of the ferrogel to an applied magnetic field. In particular, the elastic moduli can be enhanced to different degrees depending on the mutual orientation of the fields during and after ferrogel formation. Previously, no microscopic models have been produced to shed light on this effect and the main purpose of the work presented here is to illuminate the microscopic behaviour. The model represents ferrogels by ensembles of dipolar spheres dispersed in elastic matrices. Experimental trends are shown to be reflected accurately in the simulations of the microscopic model while shedding light on the microscopic mechanism causing these effects. These mechanisms are shown to be related to the behaviour of the dipoles during the production of the gels and caused by the chaining of dipoles in magnetic fields. Finally, simple relationships between the elastic moduli and the magnetization are proposed. If supplemented by the magnetization curve, these relationships yield the dependencies of the elastic moduli on the applied magnetic field, which are often measured directly in experiments. While MC simulations are useful for statistical studies, it can be difficult to use them to gather information about the dynamics of a system. In this case, Molecular Dynamics (MD) is more widely used. MD generally utilises the classical equations of motion to simulate the evolution of a system. For large systems, which are often of interest, and multi-species polymers, the required computer power still poses a challenge and requires the use of HPC techniques. The most recent development in HPC is the use of Graphical Processing Units (GPU) for the fast solution of data parallel problems. In further published work [2], I have used a bespoke MD code utilising GPU acceleration in order to simulate large systems of block copolymers(BC) in solvent over long timescales. I have studied thin films of BC solutions drying on a flat, smooth surface which requires long timescales due to the ’slow’ nature of the process. BC’s display interesting self-organisation behaviour in bulk solution and near surfaces and have a wide range of potential applications from semi-conductors to self-constructing fabrics. Previous studies have shown some unusual behaviour of PI-PEO diblock co-polymers adsorbing to a freshly cleaved mica surface. These AFM studies showed polymers increasing in height over time and proposed the change of affinity of mica to water and the loss of water layers on the surface as a driver for this change. The MD simulation aimed to illuminate the process involved in this phenomena. The process of evaporation of water layers from a surface was successfully simulated and gave a good indication that the process of solvent evaporation from the surface and the ingress of solvent beneath the adsorbed polymer caused the increase in height seen in experiment.

Self-assembly is a process of non-intrusive transformation of a system from a disordered to an ordered state. For engineering purposes, self-assembly of microscopic objects can benefit significantly from macroscopic guidance and control. This dissertation is concerned with controlling self-assembly in binary monolayers of electrically charged particles that follow basic laws of statistical mechanics. First, a simple macroscopic model is used to determine an optimal thermal control for self-assembly. The model assumes that a single rate-controlling mechanism is responsible for the formation of spatially ordered structures and that its rate follows an Arrhenius form. The model parameters are obtained using molecular dynamics simulations. The optimal control is derived in an analytical form using classical optimization methods. Two major lessons were learned from that work: (i) isothermal control was almost as effective as optimal time-dependent thermal control, and (ii) neither electrostatic interactions nor thermal control were particularly effective in eliminating voids formed during self-assembly. Accordingly, at the next stage, the focus is on temperature-pressure control under isothermal-isobaric conditions. In identifying optimal temperature and pressure conditions, several assumptions, that allow one to relate the optimal conditions to the phase diagram, are proposed. Instead of verifying the individual assumptions, the entire approach is verified using molecular dynamics simulations. It is estimated that under optimal isothermal-isobaric conditions the rate of self-assembly is about five time faster than that under optimal temperature control conditions. It is argued that the proposed approach of relating optimal conditions to the phase diagram is applicable to other systems. Further, the work reveals numerous and useful parallels between self-assembly and crystal physics, which are important to exploit for developing robust engineering self-assembly processes. / text

Aberrant JNK signaling can result in two main forms of disease in humans: 1) neurological, coronary, hepatobiliary, and respiratory diseases and 2) autoimmune, inflammatory, and cancer conditions. Enantiomers of the lignan zuonin A, (-)-zuonin A and (+)-zuonin A, have been shown to bind to JNK isoforms with similar affinity and disrupt protein-protein interactions at JNK's D-recruitment site, making them a good candidate for specific non-ATP competitive inhibitors. However, (-)-zuonin A inhibits 80% of JNK catalyzed reactions at saturating levels, while (+)-zuonin A only inhibits 15%. Molecular docking and molecular dynamics simulations were performed to gain a better understanding of how these inhibitors interact JNK. The results of this study provide an alternative binding mode for (-)-zuonin A, compared to one proposed in a previous study, that shows (-)-zuonin A interacting with JNK via an induced fit mechanism by forming a larger pocket for itself near the highly conserved [phi]A-X-[phi]B recognition site, a dynamic move not seen in (+)-zuonin A simulations, and may help explain their different inhibition patterns. / text

Domain swapping is a wide spread phenomenon which involves the association between two or more protein subunits such that intra-molecular interactions between domains in each subunit are replaced by equivalent inter-molecular interactions between the same domains in different subunits. This thesis is devoted to the analysis of the factors that drive proteins to undergo such association modes. The specific system analyzed is the monomer to swapped dimer formation of the B1 domain of the immunoglobulin G binding protein (GB1). The formation of this dimer was shown to be fostered by 4 amino acid substitutions (L5V, F30V, Y33F, A34F) (Byeon et al., 2003). In this work, computational protein design and molecular dynamics simulations, both with detailed atomic models, were used to gain insight into how these 4 mutations may promote the domain swapping reaction. The stability of the wt and quadruple mutant GB1 monomers was assessed using the software DESIGNER, a fully automatic procedure that selects amino acid sequences likely to stabilize a given backbone structure (Wernisch et al., 2000). Results suggest that 3 of the mutations (L5V, F30V, A34F) have a destabilizing effect. The first mutation (L5V) forms destabilizing interactions with surrounding residues, while the second (F30V) is engaged in unfavorable interactions with the protein backbone, consequently causing local strain. Although the A34F substitution itself is found to contribute favorably to the stability of the monomer, this is achieved only at the expense of forcing the wild type W43 into a highly strained conformation concomitant with the formation of unfavorable interactions with both W43 and V54. Finally, we also provide evidence that A34F mutation stabilizes the swapped dimer structure. Although we were unable to perform detailed protein design calculations on the dimer, due to the lower accuracy of the model, inspection of its 3D structure reveals that the 34F side chains pack against one another in the core of the swapped structure, thereby forming extensive non-native interactions that have no counterparts in the individual monomers. Their replacement by the much smaller Ala residue is suggested to be significantly destabilizing by creating a large internal cavity, a phenomenon, well known to be destabilizing in other proteins. Our analysis hence proposes that the A34F mutation plays a dual role, that of destabilizing the GB1 monomer structure while stabilizing the swapped dimer conformation. In addition to the above study, molecular dynamics simulations of the wild type and modeled quadruple mutant GB1 structures were carried out at room and elevated temperatures (450 K) in order to sample the conformational landscape of the protein near its native monomeric state, and to characterize the deformations that occur during early unfolding. This part of the study was aimed at investigating the influence of the amino acid sequence on the conformational properties of the GB1 monomer and the possible link between these properties and the swapping process. Analysis of the room temperature simulations indicates that the mutant GB1 monomer fluctuates more than its wild type counter part. In addition, we find that the C-terminal beta-hairpin is pushed away from the remainder of the structure, in agreement with the fact that this hairpin is the structural element that is exchanged upon domain swapping. The simulations at 450 K reveal that the mutant protein unfolds more readily than the wt, in agreement with its decreased stability. Also, among the regions that unfold early is the alpha-helix C-terminus, where 2 out of the 4 mutations reside. NMR experiments by our collaborators have shown this region to display increased flexibility in the monomeric state of the quadruple mutant. Our atomic scale investigation has thus provided insights into how sequence modifications can foster domain swapping of GB1. Our findings indicate that the role of the amino acid substitutions is to decrease the stability of individual monomers while at the same time increase the stability of the swapped dimer, through the formation of non-native interactions. Both roles cooperate to foster swapping.