Diverse fiber-forming proteins are found in nature that accomplish a wide range of functions including signaling, cell adhesion, and mechanical support. Unique sequence characteristics of these proteins often lead to their specialized roles. However, these proteins also share a common organizational hierarchy in primary and secondary structures that strongly influence both their intramolecular folding and intermolecular interactions. Based on what is known regarding protein fiber assembly of silk peptides, shear-induced elongation of the molecular strands drives interchain secondary structure crystallization via anisotropic alignment, which creates a molecular superstructure that forms the basis a fiber network. In this work, the hypothesis is this type of protein fiber assembly is not unique to silk sequences and that other proteins can be spun into fibers in similar fashion while maintaining unique functionality given by their specialized amino acid sequences such as RGD, GX1X2, and so forth. This was investigated by modeling the manner in which hydrophobic and hydrophilic blocks of amino acids create interacting secondary structures at the chain level when exposed to shear. It was determined computationally and then verified experimentally that fiber spinning success is most likely to occur after shear processing if the protein sequence exhibits a balance of hydrophobic and hydrophilic content and has sufficient length. Applied to the biological scale, both pure and mixed solutions of proteins such as fibronectin, laminin, and silk fibroin were spun into fibers. In particular, alloy protein fibers of silk fibroin mixed with fibronectin exhibited the characteristic mechanical integrity of silk and the bioactivity of fibronectin. This simple method of creating protein fibers with hybrid characteristics is significantly faster, less expensive, and less technically intensive than chimeric protein production, which purports to do the same. This finding also provides insight into a fundamental means by which protein fibers may be assembled in vivo by taking advantage of the thermodynamically favorable assembly of peptide sequences at the chain level under proper molecular orientation. Taken together, a high throughput means of producing a wide-range of pure and hybrid protein fibers has been developed for various biological applications and research investigations into the fibrous elements of biology.

Isoporous membranes manufactured from diblock copolymer are successfully produced at laboratory scale under controlled conditions. Because of the complex phenomena involved, membrane preparation requires trial and error methodologies to find the optimal conditions, leading to a considerable demand of resources. Experimental insights demonstrate that the self-assembly of the block copolymers in solution has an effect on the final membrane structure. Nevertheless, the complete understanding of these multi-scale phenomena is elusive. Herein we use the coarse-grained method Dissipative Particle Dynamics to study the self-assembly of block copolymers that are used for the preparation of the membranes. To simulate representative time and length scales, we introduce a framework for model reduction of polymer chain representations for dissipative particle dynamics, which preserves the properties governing the phase equilibria. We reduce the number of degrees of freedom by accounting for the correlation between beads in fine-grained models via power laws and the consistent scaling of the simulation parameters. The coarse-graining models are consistent with the experimental evidence, showing a morphological transition of the aggregates as the polymer concentration and solvent affinity change. We show that hexagonal packing of the micelles can occur in solution within different windows of polymer concentration depending on the solvent affinity. However, the shape and size dispersion of the micelles determine the characteristic arrangement. We describe the order of crew-cut micelles using a rigid-sphere approximation and propose different phase parameters that characterize the emergence of monodisperse-spherical micelles in solution. Additionally, we investigate the effect of blending asymmetric diblock copolymers (AB/AC) over the properties of the membranes. We observe that the co-assembly mechanism localizes the AC molecules at the interface of A and B domains, and induces the swelling of the B-rich domains. The B-C interactions control the curvature of the assemblies in these blends. Finally, we study the self-assembly triblock copolymers used for membranes fabrication. We show that the polymer concentration, the block-copolymer composition, and the swelling of the micelle are responsible for the formation of elongated micelles in the casting solution. The formation of nanoporous membranes arises from the network-like packing of those micelles.

The key results of this thesis are (1) an extension of N-mixture models to incorporate the additional layer of obfuscation brought by observing counts from a related auxiliary population (rather than the target population), (2) an extension of N-mixture models to allow for grouped counts, the purpose being two-fold: to extend the applicability of N-mixtures to larger population sizes, and to allow for the use of coarse counts in fitting N-mixture models, (3) a new R package allowing the easy application of the new N-mixture models, (4) a new R package allowing for optimization of multi-parameter functions using arbitrary precision arithmetic, which was a necessary tool for optimization of the likelihood in large population abundance N-mixture models, as well as (5) simulation studies validating the new grouped count models and comparing them to the classic N-mixtures models. / Graduate

This thesis consists of two papers considering different aspects of stochastic process modelling and the minimisation of computational cost. In the first paper, we analyse statistical signal properties and develop a Gaussian pro- cess model for scenarios with a moving receiver in a scattering environment, as in Clarke’s model, with the generalisation that noise is introduced through scatterers randomly flip- ping on and off as a function of time. The Gaussian process model is developed by extracting mean and covariance properties from the Multipath Fading Channel model (MFC) through coarse graining. That is, we verify that under certain assumptions, signal realisations of the MFC model converge to a Gaussian process and thereafter compute the Gaussian process’ covariance matrix, which is needed to construct Gaussian process signal realisations. The obtained Gaussian process model is under certain assumptions less computationally costly, containing more channel information and having very similar signal properties to its corresponding MFC model. We also study the problem of fitting our model’s flip rate and scatterer density to measured signal data. The second paper generalises a multilevel Forward Euler Monte Carlo method intro- duced by Giles [1] for the approximation of expected values depending on the solution to an Ito stochastic differential equation. Giles work [1] proposed and analysed a Forward Euler Multilevel Monte Carlo method based on realsiations on a hierarchy of uniform time discretisations and a coarse graining based control variates idea to reduce the computa- tional effort required by a standard single level Forward Euler Monte Carlo method. This work introduces an adaptive hierarchy of non uniform time discretisations generated by adaptive algorithms developed by Moon et al. [3, 2]. These adaptive algorithms apply either deterministic time steps or stochastic time steps and are based on a posteriori error expansions first developed by Szepessy et al. [4]. Under sufficient regularity conditions, our numerical results, which include one case with singular drift and one with stopped dif- fusion, exhibit savings in the computational cost to achieve an accuracy of O(T ol), from O(T ol−3 ) to O (log (T ol) /T ol)2 . We also include an analysis of a simplified version of the adaptive algorithm for which we prove similar accuracy and computational cost results.

Molecular Dynamics (MD) is a simulation technique widely used by computational chemists and biologists to simulate and observe the physical properties of a system of particles or molecules. The method provides invaluable three-dimensional structural and transport property data for macromolecules that can be used in applications such as the study of protein folding and drug design. The most time-consuming and inefficient routines in MD packages, particularly for large systems, are the ones involving the computation of intermolecular energy and forces for each molecule. Many fully atomistic systems such as CHARMM and NAMD have been refined over the years to improve their efficiency. But, simulating complex long-time events such as protein folding remains out reach for atomistic simulations. The consensus view amongst computational chemists and biologists is that the development of a coarse-grained (CG) MD package will make the long timescales required for protein folding simulations possible. The shortcoming of this method remains an inability to produce accurate dynamics and results that are comparable with atomistic simulations. It is the objective of this dissertation to develop a coarse-grained method that is computationally faster than atomistic simulations, while being dynamically accurate enough to produce structural and transport property data comparable to results from the latter. Firstly, the accuracy of the Gay-Berne potential in modelling liquid benzene in comparison to fully atomistic simulations was investigated. Following this, the speed of a course-grained condensed phase benzene simulation employing a Gay-Berne potential was compared with that of a fully atomistic simulation. While coarse-graining algorithmically reduces the total number of particles in consideration, the execution time and efficiency scales poorly for large systems. Both fully-atomistic and coarse-grained developers have accelerated packages using high-performance parallel computing platforms such as multi-core CPU clusters, Field Programmable Gate Arrays (FPGAs) and Graphics Processing Units (GPUs). GPUs have especially gained popularity in recent years due to their massively parallel architecture on a single chip, making them a cheaper alternative to a CPU cluster. Their relatively shorter development time also gives them an advantage over FPGAs. NAMD is perhaps the most popular MD package that employs efficient use of a single GPU or a multi-GPU cluster to conduct simulations. The Scientific Computing Research Unit’s in-house generalised CG code, the Free Energy Force Induced (FEFI) coarse-grained MD package, was accelerated using a GPU to investigate the achievable speed-up in comparison to the CPU algorithm. To achieve this, a parallel version of the sequential force routine, i.e. the computation of the energy, force and torque per molecule, was developed and implemented on a GPU. The GPU-accelerated FEFI package was then used to simulate benzene, which is almost exclusively governed by van der Waal’s forces (i.e. dispersion effects), using the parameters for the Gay-Berne potential from a study by Golubkov and Ren in their work “Generalized coarse-grained model based on point multipole and Gay-Berne potentials”. The coarse-grained condensed phase structural properties, such as the radial and orientational distribution functions, proved to be inaccurate. Further, the transport properties such as diffusion were significantly more unsatisfactory compared to a CHARMM simulation. From this, a conclusion was reached that the Gay-Berne potential was not able to model the subtle effects of dispersion as observed in liquid benzene. In place of the analytic Gay-Berne potential, a more accurate approach would be to use a multidimensional free energy-based potential. Using the Free Energy from Adaptive Reaction Coordinate Forces (FEARCF) method, a four-dimensional Free Energy Volume (FEV) for two interacting benzene molecules was computed for liquid benzene. The focal point of this dissertation was to use this FEV as the coarse-grained interaction potential in FEFI to conduct CG simulations of condensed phase liquid benzene. The FEV can act as a numerical potential or Look-Up Table (LUT) from which the interaction energy and four partial derivatives required to compute the forces and torques can be obtained via numerical methods at each step of the CG MD simulation. A significant component of this dissertation was the development and implementation of four-dimensional LUT routines to use the FEV for accurate condensed phase coarse-grained simulations. To compute the energy and partial derivatives between the grid points of the surface, an interpolation algorithm was required. A four-dimensional cubic B-spline interpolation was developed because of the method’s superior accuracy and resistance to oscillations compared with other polynomial interpolation methods. When The algorithm’s introduction into the FEFI CG MD package for CPUs exhausted the single-core CPU architecture with its large number of interpolations for each MD step. It was therefore impractical for the high throughput interpolation required for MD simulations. The 4D cubic B-spline algorithm and the LUT routine were then developed and implemented on a GPU. Following evaluation, the LUT was integrated into the FEFI MD simulation package. A FEFI CG simulation of liquid benzene was run using the 4D FEV for a benzene molecular pair as the numerical potential. The structural and transport properties outperformed the analytical Gay-Berne CG potential, more closely approximating the atomistic predicted properties. The work done in this dissertation demonstrates the feasibility of a coarse-grained simulation using a free energy volume as a numerical potential to accurately simulate dispersion effects, a key feature needed for protein folding.

The essential cellular functions of the mitochondrion require the exchange of a wide variety of molecules across its two membranes, which is carried out by different membrane proteins.The Voltage-Dependent Anion Channel (VDAC) located in the mitochondrial outer membrane (MOM) is responsible for the passage of various ions and small molecules to and from the intermembrane space. It is also involved in the regulation of cellular processes through its interactions with lipids or other proteins.At the MOM level, we studied the transport, through VDAC, of small inorganic ions and of thiamine pyrophosphate (TPP), an essential cofactor. Using different simulation methods such as Brownian dynamics (BD), All-Atom (AA) molecular dynamics (MD) and Coarse-Grained (CG) MD, we investigated the effect of two factors on the regulation of VDAC ion selectivity: ionic strength and membrane lipid composition. All simulation types show that VDAC becomes less selective towards anions with increasing salt concentration. The simulations further suggest that the selectivity mechanism occurs due to the filtering of some basic residues that point into the pore lumen. Furthermore, MD simulations show that the lipid composition of the membrane modulates the distribution of ions inside VDAC. In a comparison of POPE versus POPC bilayer, this regulation occurs through the more persistent interactions of some acidic residues located on both edges of the β-barrel with POPE head groups which, in turn, alters the electrostatic potential in the lumen which consequently affects the pore selectivity. CG MD simulations show that this mechanism also occurs in a mixed POPE/POPC bilayer by an enrichment of POPE on VDAC surface.In order to simulate the transport of the TPP, force field parameters have been developed and validated. Simulations of the translocation of TPP through VDAC show analogies with the mechanism used by other previously studied metabolites, in particular with ATP. At the mitochondrial inner membrane level, the mechanism of TPP transport by the specific thiamine pyrophosphate transporter (TPPT) shows significant similarities with the mechanism proposed for other members of the mitochondrial carrier family to which TPPT belongs. They mainly are the energetics arising from the alternating formation and disruption of two salt bridge networks, one on the matrix side and the other on the cytosolic side, and the interactions, of an ionic nature, formed by TPP during its binding in TPPT central cavity. Furthermore, the energy contribution provided by the cytosolic network establishes a weaker barrier than that of the matrix network, which may support the hypothesis of a uniport activity of TPPT. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

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Coal in the finer particle size ranges (below 1 mm) has always suffered from poor cleaning efficiencies. This problem has been exacerbated in recent years with the increased amount of high ash fines due to continuous mining machines and the mining of dirtier coal seams. In the present work, it is proposed to improve overall plant efficiencies by processing coarser coal in column flotation than is now commonly treated by that method. Column flotation for coarse coal is supported by actual lab and plant test data that result in a full-scale column plant installation. The fundamentals of coarse particle detachment from bubbles are reviewed and a new simplified model is developed which better handles cubical and rectangular coal particles. Much of the lower efficiency of fine coal cleaning is due to poor size separation of the fine-sized raw coal which results in misplaced high ash fines reporting to the coarser size streams. By sending coarser material to column flotation, the finest size separation that takes place in a plant can be as coarse as 0.5 mm or greater. The proper use of wash water in a flotation column then becomes the best mechanism for desliming of the high ash clays. This work quantifies the benefits of removing the high ash fines from the plant product and increasing overall plant yield by increasing the amount of near-gravity coarse material. The resulting yield gain is greater than that obtained from only the increased fine coal recovery. Methods of column operation for improved coarse coal recovery are also evaluated. / Ph. D.