Structural Analyses of Borna Disease Virus Nucleoprotein- Phosphoprotein and Nucleoprotein- RNA Interactions

Borna disease virus (BDV) is the only representative of the Bornaviridae in the order Mononegavirales. It is unique among the animal viruses of this order with respect to its transcription and replication in the nucleus, which provides access to the splicing machinery. BDV is noncytolytic, highly neurotropic and causes diseases of the central nervous system (CNS) in a wide range of vertebrates. As in other Mononegavirales, the BDV polymerase complex or ribonucleoprotein complex, consists of the nucleoprotein N, the phosphoprotein P, the polymerase L and viral genomic RNA. In the case of BDV another protein is involved, termed protein X. BVD N forms a homotetramer and does not spontaneously interact with cellular RNA. Each protomer consists of two helical domains and N- and C-terminal extensions, involved in domain exchange and tetramer stabilization. An open question remained how BVD N interacts with RNA, although overall structural similarities with nucleoproteins from rhabdoviruses and vesiculoviruses suggested similar modes of RNA interaction. Protein P plays an essential role in assembly and regulation of the polymerase complex via interactions with X, N, L and itself. Oligomerization of P is required for the formation of an active polymerase complex, similar to other negative strand RNA polymerase complexes. P requires an intact C-terminus for N interaction and may contact two different sites on N. Phosphoproteins from Rhabdoviruses and Sendai virus contain two different binding sites for N, one to keep N soluble and free from unspecific RNA and the other to bind to N-RNA complexes forming the polymerase complex together with the polymerase L. However, BVD N does not require P binding to prevent non-specific RNA interaction, since BDV N oligomerizes spontaneously into tetramers that do not complex RNA, thus the precise role of N-P interaction in the absence of RNA is not known. The aim of our study was to understand the interaction between the BDV nucleo- and the phosphoprotein as well as the nucleoprotein and the viral RNA. Even though, no conclusive data were obtained upon crystallographic approaches, concerning N in complex with different truncated P-constructs and BDV genomic RNA, we present data about N-P and N-RNA interactions. I show that P’, an N-terminally truncated isoform of the phosphoprotein, present in BDV infected cells, oligomerizes into tetramers. The tetrameric P’ interacts with BDV-N, thus forming hetero-octamers. The P’-N interaction requires five C-terminal amino acids of P’ to form a stable complex with a kD of 1.66 μM. Tetrameric N is destabilized in the presence of 5’ genomic BDV RNA, which leads to the formation of N-RNA polymers. Similar N-RNA polymers are formed in the presence of P’, leading to P’-N-RNA polymers. Electron microscopy analyses of N-RNA and N-P’-RNA complexes revealed large “open” ring-like and string-like assemblies with the RNA exposed and accessible for degradation. The N or N-P polymers remain intact after RNA degradation indicating that polymerization is not mainly stabilized by RNA interaction. The N-RNA interaction is mediated via recognition of basic residues within the cleft of the N-and C-terminal domains similar to the observed nucleoprotein-RNA recognition of other negative strand-RNA viruses. In conclusion, these data provide insight on the molecular interactions between the viral RNA and the nucleo- and phosphoprotein of the BDV ribonucleoprotein complex

Predicting multibody assembly of proteins

textThis thesis addresses the multi-body assembly (MBA) problem in the context of protein assemblies. [...] In this thesis, we chose the protein assembly domain because accurate and reliable computational modeling, simulation and prediction of such assemblies would clearly accelerate discoveries in understanding of the complexities of metabolic pathways, identifying the molecular basis for normal health and diseases, and in the designing of new drugs and other therapeutics. [...] [We developed] F²Dock (Fast Fourier Docking) which includes a multi-term function which includes both a statistical thermodynamic approximation of molecular free energy as well as several of knowledge-based terms. Parameters of the scoring model were learned based on a large set of positive/negative examples, and when tested on 176 protein complexes of various types, showed excellent accuracy in ranking correct configurations higher (F² Dock ranks the correcti solution as the top ranked one in 22/176 cases, which is better than other unsupervised prediction software on the same benchmark). Most of the protein-protein interaction scoring terms can be expressed as integrals over the occupied volume, boundary, or a set of discrete points (atom locations), of distance dependent decaying kernels. We developed a dynamic adaptive grid (DAG) data structure which computes smooth surface and volumetric representations of a protein complex in O(m log m) time, where m is the number of atoms assuming that the smallest feature size h is [theta](r[subscript max]) where r[subscript max] is the radius of the largest atom; updates in O(log m) time; and uses O(m)memory. We also developed the dynamic packing grids (DPG) data structure which supports quasi-constant time updates (O(log w)) and spherical neighborhood queries (O(log log w)), where w is the word-size in the RAM. DPG and DAG together results in O(k) time approximation of scoring terms where k << m is the size of the contact region between proteins. [...] [W]e consider the symmetric spherical shell assembly case, where multiple copies of identical proteins tile the surface of a sphere. Though this is a restricted subclass of MBA, it is an important one since it would accelerate development of drugs and antibodies to prevent viruses from forming capsids, which have such spherical symmetry in nature. We proved that it is possible to characterize the space of possible symmetric spherical layouts using a small number of representative local arrangements (called tiles), and their global configurations (tiling). We further show that the tilings, and the mapping of proteins to tilings on arbitrary sized shells is parameterized by 3 discrete parameters and 6 continuous degrees of freedom; and the 3 discrete DOF can be restricted to a constant number of cases if the size of the shell is known (in terms of the number of protein n). We also consider the case where a coarse model of the whole complex of proteins are available. We show that even when such coarse models do not show atomic positions, they can be sufficient to identify a general location for each protein and its neighbors, and thereby restricts the configurational space. We developed an iterative refinement search protocol that leverages such multi-resolution structural data to predict accurate high resolution model of protein complexes, and successfully applied the protocol to model gp120, a protein on the spike of HIV and currently the most feasible target for anti-HIV drug design.Computer Science

Bioinspired Origami: Information Retrieval Techniques for Design of Foldable Engineering Applications

The science of folding has inspired and challenged scholars for decades. Origami, the art of folding paper, has led to the development of many foldable engineering solutions with applications in manufacturing, materials, and product design. Interestingly, three fundamental origami crease patterns are analogous to folding observed in nature. Numerous folding patterns, structures, and behaviors exist in nature that have not been considered for engineering solutions simply because they are not well-known or studied by designers. While research has shown applying biological solutions to engineering problems is significantly valuable, various challenges prevent the transfer of knowledge from biology to the engineering domain. One of those challenges is the retrieval of useful design inspiration. In this dissertation work, information retrieval techniques are employed to retrieve useful biological design solutions and a text-based search algorithm is developed to return passages where folding in nature is observed. The search algorithm, called FoldSearch, integrates tailored biological keywords and filtering methods to retrieve passages from an extensive biological corpus. The performance of FoldSearch is evaluated using statistical methods for information retrieval and validated using inter-rater reliability analysis. The utility of FoldSearch is demonstrated through two case studies where the retrieved biological examples undergo a design abstraction process that leads to the development of bioinspired origami crease patterns and novel foldable structures. The design abstraction process is presented as an additional research contribution and demonstrates the potential to provide bioinspired design solutions for the growing research field of origami engineering

Statistical Mechanical Models Of Virus Capsid Assembly

Viruses have become an increasingly popular subject of physics investigation, particularly in the last decade. Advances in imaging of virus capsids-the protective protein shells-in a wide variety of stages of assembly have encouraged physical assembly models at a similarly wide variety of scales, while the apparent simplicity of the capsid system-typically, many identical units assembling spontaneously into an icosahedrally symmetric (rather than amorphous) shell-makes the problem particularly interesting. We take a look at the existing physical assembly models in light of the question of how a particular assembly target can be consistently achieved in the presence of so many possible incorrect results. This review leads us to pose our own model of fully irreversible virus assembly, which we study in depth using a large ensemble of simulated assembled capsids, generated under a variety of capsid shell elastic parameters. While this irreversible model (predictably) did not yield consistently symmetric results, we do glean some insight into the effect of elasticity on growth, as well as an understanding of common failure modes. In particular, we found that (i) capsid size depends strongly on the spontaneous curvature and weakly on the ratio of bending to stretching elastic stiffnesses, (ii) the probability of successful capsid completion decays exponentially with capsid size, and (iii) the degree of localization of Gaussian curvature depends heavily on the ratio of elastic stiffnesses. We then go on to consider more thoroughly the nature of the ensem- ble of symmetric and almost-symmetric capsids-ultimately computing a phase diagram of minimum-energy capsids as a function of the two above-mentioned elastic parameters-and also look at a number of modifications we can make to our irreversible model, finally putting forth a rather different type of model potentially appropriate for understanding immature HIV assembly, and concluding with a fit of this new model's parameters to recent experimental structures. A common thread between the coarse-grained models we discuss in the first part of the thesis is that they all depend explicitly on elastic parameters that are otherwise completely unmotivated. We thus devote the second part to the question of how (elastic) model parameters can be determined from ab initio methods. Modeling protein interactions as springs with very general quadratic potentials, we run atomistic molecular dynamics simulations and analyze the trajectories to determine stiffness tensors for these generalized springs. After a thorough examination of the mathematical structure of our springs-including transformations of the stiffness tensors into different reference frames and gauges, and an analytical formula for composing generalized springs in series-we go on to apply the technique to measure the elasticity of a mature HIV capsid lattice by simulating isolated pairs of interacting protein domains. We compute the relaxation times for each bond, and for the entire lattice, which both gives the stiffness as a physical, comparable timescale, and also provides a way to invalidate many simulations with too short a run time. Because calculation of the relaxation matrix requires a measurement of the diffusion of the individual proteins, we conclude with a brief study of the effects of finite box sizes and differing thermostat strengths on diffusion measurements from atomistic simulations

Surveying the Energy Landscapes of Multistable Elastic Structures

Energy landscapes analysis is a versatile approach to study multistable systems by identifying the network of stable states and reconfiguration pathways. Thus far, it has primarily been used in microscale systems, such as studying chemical reaction rates and to characterise the behaviour of how protein fold. Here, however, we aim to utilise energy landscape techniques to study multistable elastic structures, in particular, complex 3D structures that have been buckled from 2D patterns, which are of interest for applications such as flexible electronics and microelectromechanical systems. To this end we have developed new energy landscape methods and software that are well suited to continuous, macroscale systems with many degrees of freedom. The first is the binary image transition state search method (BITSS), which offers greater efficiency for large scale systems compared to traditional transition state search methods, and it is well suited to complex, non-linear pathways. Next, a new software library is introduced that contains a variety of energy landscape methods and potentials which are parallelised to study large-scale continuous systems. This library can be flexibly used for any chosen application, and has been designed to be easily extensible for new methods and potentials. Furthermore, we exploit energy landscape analysis to tailor the stable states and reconfiguration paths of various reconfigurable buckled mesostructures. We establish stability phase diagrams and identify the corresponding available reconfiguration pathways by varying essential structural parameters. Furthermore, we identify how the introduction of creases affects the multistability of the structures, finding that a small number can increase the number of distinct states, but more creases can lead to a loss of multistability. Taken together, these results and methodology can be used to influence the design of new structures for a variety of different applications

Dynamic Solvent Models and Exploring the Parameter Space of Hydrogen Fluoride, Hafnium, and Zirconium

Solvation is the interaction of solute and solvent. Every biological interaction hap- pens in a solvent. Most technical procedures occur within solvents and geological processes are too mediated by their solvents. Understanding these effects of solva- tion is therefore critical for the understanding of biology, technology, and geology. While static properties of solvation shells, like coordination numbers and radial dis- tribution functions, are well understood, the dynamic properties of these open sys- tems are rarely studied. Furthermore, an interesting solvation-based phenomenon is the separation of the geochemical twins Zirconium and Hafnium in fluoride-bearing media. In this work, I present a method for evaluating Markov models of solvation shells and investigate ways of combining the solvent models with solute models. Moreover, I attempt to find a suitable two-site and three-site model of hydrogen flu- oride, specialized for its interaction with metal ions. By simulating aqueous and pure HF for several combinations of q, σF , and ϵF and evaluating density, peaks of radial distribution functions as well the solvation free energy of NaF in HF, I hoped to find a suitable model. A three-site model for HF is parameterized by recreating the electrostatic potential of HF with a classical force field, focusing on the location of maximum potential which takes a conical shape around the tip of the ellipsoid and is not located at the poles. A new method is presented which allows the automatic detection of coordination polyhedra based on reference structures and Steinhardt-order parameters. The Lennard-Jones parameter space for tetravalent cations is explored and analyzed in terms of static solvation shell quantities. Finally, the thermal contraction of the solvation shells of Zr4+ and Hf4+ in 1 M HF was investigated using classical MD simulations. The Markov models of solvation shells indicated that solvent dynamics couple close to the solute. Additive combined models yielded slightly higher timescales compared to their individual components. The opposite is true for the multiplicative models which performed just as well or even worse than their components. The parameterization of HF, for the two-site model, yielded two parameter combi- nations that could reproduce three of the five target quantities, the relevant peaks of the F-H and H-H radial distribution functions, as well as the solvation free energy of NaF in HF. After choosing a topology for the three-site model, the Lennard-Jones parameter scans were unable to yield stable simulations of aqueous HF. The project was therefore discontinued and I settled for a recently published HF model. The parameterization of metal cations yielded a very robust result. Static solvation shell properties exist on continuous regions of similar value in the parameter space. These regions appear as a diagonal lines in the log(ϵ M ) − σM parameter space. This behavior is also observed in the coordination polyhedra found by the novel method. The thermal contractions of solvation shells of tetravalent cations could be observed for the four ionic ligands. The contractions are a result of water molecules increas- ing their distance to the central cation. Their missing repulsive Coulomb interaction allows the ionic ligands to move in closer to the central cation, thus causing the thermal contraction. Furthermore, we observed a two-state system for the solvation shells at high temperatures which consists of octahedral and tetrahedral solvation shells interchanging each other. The herein presented results offer new methods for analyzing solvation shells. Firstly by constructing Markov models of these open systems to study their dynamics. Secondly, by automatically determining the coor- dination polyhedron, which is essentially an analysis of the angular distribution of solvent molecules in the solvation shell. The parameterization attempts of HF depict the difficulty of finding parameter com- binations that match all fitting targets, albeit the searched parameter space was rather small. The parameter space for tetravalent cations shows an extremely robust result which can yield the basis for future parameterization attempts. Finally, the peculiar thermal contractions could be explained through classical MD simulations. This shows the power of this method for studying hard ionic systems

Geometry of symmetry

p. 325-412, [2] p. of plates : ill. ; 27 cm.Includes bibliographical references (p. 408-412)