The Impact of Dynamics in Protein Assembly

Predicting the assembly of multiple proteins into specific complexes is critical to understanding their biological function in an organism, and thus the design of drugs to address their malfunction. Consequently, a significant body of research and development focuses on methods for elucidating protein quaternary structure. In silico techniques are used to propose models that decode experimental data, and independently as a structure prediction tool. These computational methods often consider proteins as rigid structures, yet proteins are inherently flexible molecules, with both local side-chain motion and larger conformational dynamics governing their behaviour. This treatment is particularly problematic for any protein docking engine, where even a simple rearrangement of the side-chain and backbone atoms at the interface of binding partners complicates the successful determination of the correct docked pose. Herein, we present a means of representing protein surface, electrostatics and local dynamics within a single volumetric descriptor, before applying it to a series of physical and biophysical problems to validate it as representative of a protein. We leverage this representation in a protein-protein docking context and demonstrate that its application bypasses the need to compensate for, and predict, specific side-chain packing at the interface of binding partners for both water-soluble and lipid-soluble protein complexes. We find little detriment in the quality of returned predictions with increased flexibility, placing our protein docking approach as highly competitive versus comparative methods. We then explore the role of larger, conformational dynamics in protein quaternary structure prediction, by exploiting large-scale Molecular Dynamics simulations of the SARS-CoV-2 spike glycoprotein to elucidate possible high-order spike-ACE2 oligomeric states. Our results indicate a possible novel path to therapeutics following the COVID-19 pandemic. Overall, we find that the structure of a protein alone is inadequate in understanding its function through its possible binding modes. Therefore, we must also consider the impact of dynamics in protein assembly

Electron Thermal Runaway in Atmospheric Electrified Gases: a microscopic approach

Thesis elaborated from 2018 to 2023 at the Instituto de Astrofísica de Andalucía under the supervision of Alejandro Luque (Granada, Spain) and Nikolai Lehtinen (Bergen, Norway). This thesis presents a new database of atmospheric electron-molecule collision cross sections which was published separately under the DOI : With this new database and a new super-electron management algorithm which significantly enhances high-energy electron statistics at previously unresolved ratios, the thesis explores general facets of the electron thermal runaway process relevant to atmospheric discharges under various conditions of the temperature and gas composition as can be encountered in the wake and formation of discharge channels

Modelling and Identification of Immune Cell Migration during the Inflammatory Response

Neutrophils are the white blood cells that play a crucial role in the response of the innate immune system to tissue injuries or infectious threats. Their rapid arrival to the damaged area and timely removal from it define the success of the inflammatory process. Therefore, understanding neutrophil migratory behaviour is essential for the therapeutic regulation of multiple inflammation-mediated diseases. Recent years saw rapid development of various in vivo models of inflammation that provide a remarkable insight into the neutrophil function. The main drawback of the \textit{in vivo} microscopy is that it usually focuses on the moving cells and obscures the external environment that drives their migration. To evaluate the effect of a particular treatment strategy on neutrophil behaviour, it is necessary to recover the information about the cell responsiveness and the complex extracellular environment from the limited experimental data. This thesis addresses the presented inference problem by developing a dynamical modelling and estimation framework that quantifies the relationship between an individual migrating cell and the global environment. \par The first part of the thesis is concerned with the estimation of the hidden chemical environment that modulates the observed cell migration during the inflammatory response in the injured tail fin of zebrafish larvae. First, a dynamical model of the neutrophil responding to the chemoattractant concentration is developed based on the potential field paradigm of object-environment interaction. This representation serves as a foundation for a hybrid model that is proposed to account for heterogeneous behaviour of an individual cell throughout the migration process. An approximate maximum likelihood estimation framework is derived to estimate the hidden environment and the states of multiple hybrid systems simultaneously. The developed framework is then used to analyse the neutrophil tracking data observed in vivo under the assumption that each neutrophil at each time can be in one of three migratory modes: responding to the environment, randomly moving, and stationary. The second part of the thesis examines the process of neutrophil migration at the subcellular scale, focusing on the subcellular mechanism that translates the local environment sensing into the cell shape change. A state space model is formulated based on the hypothesis that links the local protrusions of the cell membrane and the concentration of the intracellular pro-inflammatory signalling protein. The developed model is tested against the local concentration data extracted from the in vivo time-lapse images via the classical expectation-maximisation algorithm

Experimental characterisation of bubbly flow using MRI

This thesis describes the first application of ultra-fast magnetic resonance imaging (MRI) towards the characterisation of bubbly flow systems. The principle goal of this study is to provide a hydrodynamic characterisation of a model bubble column using drift-flux analysis by supplying experimental closure for those parameters which are considered difficult to measure by conventional means. The system studied consisted of a 31 mm diameter semi-batch bubble column, with 16.68 mM dysprosium chloride solution as the continuous phase. This dopant served the dual purpose of stabilising the system at higher voidages, and enabling the use of ultra-fast MRI by rendering the magnetic susceptibilities of the two phases equivalent. Spiral imaging was selected as the optimal MRI scan protocol for application to bubbly flow on the basis of its high temporal resolution, and robustness to fluid flow and shear. A velocimetric variant of this technique was developed, and demonstrated in application to unsteady, single-phase pipe flow up to a Reynolds number of 12,000. By employing a compressed sensing reconstruction, images were acquired at a rate of 188 fps. Images were then acquired of bubbly flow for the entire range of voidages for which bubbly flow was possible (up to 40.8%). Measurements of bubble size distribution and interfacial area were extracted from these data. Single component velocity fields were also acquired for the entire range of voidages examined. The terminal velocity of single bubbles in the present system was explored in detail with the goal of validating a bubble rise model for use in drift-flux analysis. In order to provide closure to the most sophisticated bubble rise models, a new experimental methodology for quantifying the 3D shape of rising single bubbles was described. When closed using shape information produced using this technique, the theory predicted bubble terminal velocities within 9% error for all bubble sizes examined. Drift-flux analysis was then used to provide a hydrodynamic model for the present system. Good predictions were produced for the voidage at all examined superficial gas velocities (within 5% error), however the transition of the system to slug flow was dramatically overpredicted. This is due to the stabilising influence of the paramagnetic dopant, and reflects that while drift-flux analysis is suitable for predicting liquid holdup in electrolyte stabilised systems, it does not provide an accurate representation of hydrodynamic stability. Finally, velocity encoded spiral imaging was applied to study the dynamics of single bubble wakes. Both freely rising bubbles and bubbles held static in a contraction were examined. Unstable transverse plane vortices were evident in the wake of the static bubble, which were seen to be coupled with both the path deviations and wake shedding of the bubble. These measurements demonstrate the great usefulness for spiral imaging in the study of transient multiphase flow phenomena.This work was supported by the Cambridge Australia Trust and Trinity College, Cambridg

Low computational SLAM for an autonomous indoor aerial inspection vehicle

The past decade has seen an increase in the capability of small scale Unmanned Aerial Vehicle (UAV) systems, made possible through technological advancements in battery, computing and sensor miniaturisation technology. This has opened a new and rapidly growing branch of robotic research and has sparked the imagination of industry leading to new UAV based services, from the inspection of power-lines to remote police surveillance. Miniaturisation of UAVs have also made them small enough to be practically flown indoors. For example, the inspection of elevated areas in hazardous or damaged structures where the use of conventional ground-based robots are unsuitable. Sellafield Ltd, a nuclear reprocessing facility in the U.K. has many buildings that require frequent safety inspections. UAV inspections eliminate the current risk to personnel of radiation exposure and other hazards in tall structures where scaffolding or hoists are required. This project focused on the development of a UAV for the novel application of semi-autonomously navigating and inspecting these structures without the need for personnel to enter the building. Development exposed a significant gap in knowledge concerning indoor localisation, specifically Simultaneous Localisation and Mapping (SLAM) for use on-board UAVs. To lower the on-board processing requirements of SLAM, other UAV research groups have employed techniques such as off-board processing, reduced dimensionality or prior knowledge of the structure, techniques not suitable to this application given the unknown nature of the structures and the risk of radio-shadows. In this thesis a novel localisation algorithm, which enables real-time and threedimensional SLAM running solely on-board a computationally constrained UAV in heavily cluttered and unknown environments is proposed. The algorithm, based on the Iterative Closest Point (ICP) method utilising approximate nearest neighbour searches and point-cloud decimation to reduce the processing requirements has successfully been tested in environments similar to that specified by Sellafield Ltd

Extracting geodetically useful information from absolute gravimetry at a fundamental geodetic station

Measuring the acceleration due to gravity at the NERC Space Geodesy Facility (SGF), Herstmonceux, provides a complimentary geodetic technique to the long established satellite laser ranging and global navigation satellite system measurements. The gravimetry measurements at the SGF were added to conform to the gravity field objective of the Global Geodetic Observing System and the European Combined Geodetic Network. Since both SLR and GNSS measurements are used in the computation of the International Terrestrial Reference Frame any un-modelled movements in the ground stations are undesirable. Gravity measurements can be used in the identification of such signals. This thesis reports the establishment of the technique at the SGF and contains a description of the installation experiences, a maintenance guide for the instrument and a comprehensive analysis of the gravity measurements over the ten years of operation to date, from 2006- 2016. Environmentally driven influences on the gravity measurements are investigated. The precision of the measurements are shown to be seasonally dependent and of varying magnitude. The hydrological influence on the gravity data from groundwater variation is calculated to be approximately 3.14 µGal, determined from temporal measurement of groundwater depth and an estimation of soil properties. A maximum influence from soil moisture content is estimated resulting in an influence of less than a microgal, which confuses correlation studies between local tide gauge data and an intermittent periodic signal seen in the gravity data. The high frequency data taken at the SGF highlights bias corrections two explainable and one of unknown origin. The bias corrections, of magnitude +1.5, -2 and -7.33 µGal, are shown to be critical to the interpretation of the time series, and, simulated campaign style measurements, using one set of measurements on an annual basis, prove that the data would be easily misinterpreted if the bias offsets found are not applied

Entropie‐dominierte Selbstorganisationsprozesse birnenförmiger Teilchensysteme

The ambition to recreate highly complex and functional nanostructures found in living organisms marks one of the pillars of today‘s research in bio- and soft matter physics. Here, self-assembly has evolved into a prominent strategy in nanostructure formation and has proven to be a useful tool for many complex structures. However, it is still a challenge to design and realise particle properties such that they self-organise into a desired target configuration. One of the key design parameters is the shape of the constituent particles. This thesis focuses in particular on the shape sensitivity of liquid crystal phases by addressing the entropically driven colloidal self-assembly of tapered ellipsoids, reminiscent of „pear-shaped“ particles. Therefore, we analyse the formation of the gyroid and of the accompanying bilayer architecture, reported earlier in the so-called pear hard Gaussian overlap (PHGO) approximation, by applying various geometrical tools like Set-Voronoi tessellation and clustering algorithms. Using computational simulations, we also indicate a method to stabilise other bicontinuous structures like the diamond phase. Moreover, we investigate both computationally and theoretically(density functional theory) the influence of minor variations in shape on different pearshaped particle systems, including the stability of the PHGO gyroid phase. We show that the formation of the gyroid is due to small non-additive properties of the PHGO potential. This phase does not form in pears with a „true“ hard pear-shaped potential. Overall our results allow for a better general understanding of necessity and sufficiency of particle shape in regards to colloidal self-assembly processes. Furthermore, the pear-shaped particle system sheds light on a unique collective mechanism to generate bicontinuous phases. It suggests a new alternative pathway which might help us to solve still unknown characteristics and properties of naturally occurring gyroid-like nano- and microstructures.Ein wichtiger Bestandteil der heutigen Forschung in Bio- und Soft Matter Physik besteht daraus, Technologien zu entwickeln, um hoch komplexe und funktionelle Strukturen, die uns aus der Natur bekannt sind, nachzubilden. Hinsichtlich dessen ist vor allem die Methode der Selbstorganisation von Mikro- und Nanoteilchen hervorzuheben, durch die eine Vielzahl verschiedener Strukturen erzeugt werden konnten. Jedoch stehen wir bei diesem Verfahren noch immer vor der Herausforderung, Teilchen mit bestimmten Eigenschaften zu entwerfen, welche die spontane Anordnung der Teilchen in eine gewünschte Struktur bewirken. Einer der wichtigsten Designparameter ist dabei die Form der Bausteinteilchen. In dieser Dissertation konzentrieren wir uns besonders auf die Anfälligkeit von Flüssigkristallphasen bezüglich kleiner Änderungen der Teilchenform und nutzen dabei das Beispiel der Selbstorganisation von Entropie-dominierter Kolloide, die dem Umriss nach verjüngten Ellipsoiden oder "Birnen" ähneln. Mit Hilfe von geometrischen Werkzeugen wie z.B. Set-Voronoi Tessellation oder Cluster-Algorithmen analysieren wir insbesondere die Entstehung der Gyroidphase und der dazugehörigen Bilagenformation, welche bereits in Systemen von harten Birnen, die durch das pear hard Gaussian overlap (PHGO) Potential angenähert werden, entdeckt wurden. Des Weiteren zeigen wir durch Computersimulationen eine Strategie auf, um andere bikontinuierliche Strukturen, wie die Diamentenphase, zu stabilisieren. Schlussendlich betrachten wir sowohl rechnerisch (durch Simulationen) als auch theoretisch (durch Dichtefunktionaltheorie) die Auswirkungen kleiner Abweichungen der Teilchenform auf das Verhalten des kolloiden, birnenförmigen Teilchensystems, inklusive der Stabilität der PHGO Gyroidphase. Wir zeigen, dass die Entstehung des Gyroids auf kleinen nicht-additiven Eigenschaften des PHGO Birnenmodells beruhen. In ''echten'' harten Teilchensystemen entwickelt sich diese Struktur nicht. Insgesamt ermöglichen unsere Ergebnisse einen besseren Einblick auf das Konzept von notwendiger und hinreichender Teilchenform in Selbstorganistationsprozessen. Die birnenförmigen Teilchensysteme geben außerdem Aufschluss über einen ungewöhnlichen, kollektiven Mechanismus, um bikontinuierliche Phasen zu erzeugen. Dies deutet auf einen neuen, alternativen Konstruktionsweg hin, der uns möglicherweise hilft, noch unbekannte Eigenschaften natürlich vorkommender, gyroidähnlicher Nano- und Mikrostrukturen zu erklären

On the path integration system of insects: there and back again

Navigation is an essential capability of animate organisms and robots. Among animate organisms of particular interest are insects because they are capable of a variety of navigation competencies solving challenging problems with limited resources, thereby providing inspiration for robot navigation. Ants, bees and other insects are able to return to their nest using a navigation strategy known as path integration. During path integration, the animal maintains a running estimate of the distance and direction to its nest as it travels. This estimate, known as the `home vector', enables the animal to return to its nest. Path integration was the technique used by sea navigators to cross the open seas in the past. To perform path integration, both sailors and insects need access to two pieces of information, their direction and their speed of motion over time. Neurons encoding the heading and speed have been found to converge on a highly conserved region of the insect brain, the central complex. It is, therefore, believed that the central complex is key to the computations pertaining to path integration. However, several questions remain about the exact structure of the neuronal circuit that tracks the animal's heading, how it differs between insect species, and how the speed and direction are integrated into a home vector and maintained in memory. In this thesis, I have combined behavioural, anatomical, and physiological data with computational modelling and agent simulations to tackle these questions. Analysis of the internal compass circuit of two insect species with highly divergent ecologies, the fruit fly Drosophila melanogaster and the desert locust Schistocerca gregaria, revealed that despite 400 million years of evolutionary divergence, both species share a fundamentally common internal compass circuit that keeps track of the animal's heading. However, subtle differences in the neuronal morphologies result in distinct circuit dynamics adapted to the ecology of each species, thereby providing insights into how neural circuits evolved to accommodate species-specific behaviours. The fast-moving insects need to update their home vector memory continuously as they move, yet they can remember it for several hours. This conjunction of fast updating and long persistence of the home vector does not directly map to current short, mid, and long-term memory accounts. An extensive literature review revealed a lack of available memory models that could support the home vector memory requirements. A comparison of existing behavioural data with the homing behaviour of simulated robot agents illustrated that the prevalent hypothesis, which posits that the neural substrate of the path integration memory is a bump attractor network, is contradicted by behavioural evidence. An investigation of the type of memory utilised during path integration revealed that cold-induced anaesthesia disrupts the ability of ants to return to their nest, but it does not eliminate their ability to move in the correct homing direction. Using computational modelling and simulated agents, I argue that the best explanation for this phenomenon is not two separate memories differently affected by temperature but a shared memory that encodes both the direction and distance. The results presented in this thesis shed some more light on the labyrinth that researchers of animal navigation have been exploring in their attempts to unravel a few more rounds of Ariadne's thread back to its origin. The findings provide valuable insights into the path integration system of insects and inspiration for future memory research, advancing path integration techniques in robotics, and developing novel neuromorphic solutions to computational problems