Simulating the kinesin walk : towards a definitive theory

Dementia is a set of incurable, fatal diseases characterised by irreversible degeneration of the brain. One theory of its cause is the failure of intracellular transport in the axons of the neurons that compose the brain. Kinesin is a key motor transporting vital cargo along the axon. We know that this motor is a bipedal engine stepping forward along a polypeptide track but it is too small and fast for this motion to be observed using current experimental techniques. The stepping detail is therefore open to debate. This study firstly addresses the question of how kinesin steps and secondly pilots a possible method for investigating transport disruption in silico. To investigate the detail of stepping, a program has been designed and built to simulate kinesin traversing its track along a section of axon. The motor is modelled as simple, interacting agents obeying rules abstracted from known chemical and binding properties of its components. The agent-based method has proven useful and efficient on the small scale and has potential for simulating the larger and more complex system of axonal transport. This would enable investigation of transport failure in the context of finding a cure for dementia. A new model of kinesin stepping has been formulated as a consequence of performing virtual experiments using the simulation. Analysis of in vivo and in vitro experimental studies shows that the model accounts for a wide range of published results, explaining many findings. New experiments are suggested to test the model based on its falsifiable predictions. The principal conclusion of this study is that kinesin stepping is rectified Brownian motion

Simulating the kinesin walk : towards a definitive theory

Dementia is a set of incurable, fatal diseases characterised by irreversible degeneration of the brain. One theory of its cause is the failure of intracellular transport in the axons of the neurons that compose the brain. Kinesin is a key motor transporting vital cargo along the axon. We know that this motor is a bipedal engine stepping forward along a polypeptide track but it is too small and fast for this motion to be observed using current experimental techniques. The stepping detail is therefore open to debate. This study firstly addresses the question of how kinesin steps and secondly pilots a possible method for investigating transport disruption in silico. To investigate the detail of stepping, a program has been designed and built to simulate kinesin traversing its track along a section of axon. The motor is modelled as simple, interacting agents obeying rules abstracted from known chemical and binding properties of its components. The agent-based method has proven useful and efficient on the small scale and has potential for simulating the larger and more complex system of axonal transport. This would enable investigation of transport failure in the context of finding a cure for dementia. A new model of kinesin stepping has been formulated as a consequence of performing virtual experiments using the simulation. Analysis of in vivo and in vitro experimental studies shows that the model accounts for a wide range of published results, explaining many findings. New experiments are suggested to test the model based on its falsifiable predictions. The principal conclusion of this study is that kinesin stepping is rectified Brownian motion.EThOS - Electronic Theses Online ServiceEngineering and Physical Sciences Research Council (EPSRC)GBUnited Kingdo

Leveraging elasticity theory to calculate cell forces: From analytical insights to machine learning

Living cells possess capabilities to detect and respond to mechanical features of their surroundings. In traction force microscopy, the traction of cells on an elastic substrate is made visible by observing substrate deformation as measured by the movement of embedded marker beads. Describing the substrates by means of elasticity theory, we can calculate the adhesive forces, improving our understanding of cellular function and behavior. In this dissertation, I combine analytical solutions with numerical methods and machine learning techniques to improve traction prediction in a range of experimental applications. I describe how to include the normal traction component in regularization-based Fourier approaches, which I apply to experimental data. I compare the dominant strategies for traction reconstruction, the direct method and inverse, regularization-based approaches and find, that the latter are more precise while the former is more stress resilient to noise. I find that a point-force based reconstruction can be used to study the force balance evolution in response to microneedle pulling showing a transition from a dipolar into a monopolar force arrangement. Finally, I show how a conditional invertible neural network not only reconstructs adhesive areas more localized, but also reveals spatial correlations and variations in reliability of traction reconstructions

Investigation of putative regulatory loci relevant to the pathogenesis of psychiatric illness

The genetic contribution to the aetiology of psychiatric illness is well-established; however, few variants that alter the encoded protein have been irrefutably identified as causative, leading to the hypothesis that variants affecting gene regulation may play a pathogenic role. This thesis focuses on two genes, Neuregulin 1 (NRG1) and Disrupted in Schizophrenia 1 (DISC1), for which there is strong genetic evidence for involvement in psychiatric illness, as well as evidence for altered expression in patients. Association analysis was carried out to assess the involvement of six intronic NRG1 single nucleotide polymorphisms (SNPs) in schizophrenia and bipolar disorder in two independent samples from the Scottish (Scottish 2; n = 307 control subjects, 303 schizophrenic patients, and 239 bipolar disorder patients and German populations (n = 397 control subjects, 396 schizophrenic patients, and 400 bipolar disorder patients). These SNPs form two haplotypes, one encompassing the 5’ and promoter region of the gene and the other located at the 3’ end of the gene, that were previously associated with schizophrenia and bipolar disorder in a Scottish sample (Scottish 1). The location of these haplotypes, together with the prior evidence for altered NRG1 expression in schizophrenia, suggested the potential involvement of regulatory variants. On combining the Scottish 1 and Scottish 2 samples (combined n = 765 control subjects, 682 schizophrenic patients and 601 bipolar disorder patients), a two- SNP haplotype spanning both coding and non-coding regions in the 3’ region was associated with schizophrenia (p = 0.0037, OR=1.3, 95% CI: 1.1-1.6) and the combined schizophrenia and bipolar disorder case group (p = 0.0080, OR=1.2, 95% CI: 1.1-1.5), with both these associations remaining significant after permutation analysis (p = 0.022 and p = 0.044, respectively). To further understanding of how DISC1, a leading candidate gene for schizophrenia that has also been implicated in other psychiatric disorders, is regulated the previously uncharacterised promoter region was assessed both bioinformatically and in vitro using the dual luciferase reporter assay. The region was found to lack canonical promoter motifs but to contain a CpG island, consistent with DISC1’s ubiquitous pattern of expression. A region located 300bp to -177bp relative to the transcription start site (TSS) was identified as contributing positively to DISC1 promoter activity, whilst a region -982bp to -301bp relative to the TSS was found to confer a repressive effect. FOXP2, a transcription factor which is mutated in a rare speech and language disorder and implicated in autism pathogenesis, was found to repress transcription from the DISC1 promoter. Two pathogenic FOXP2 point mutations reduced this transcriptional repression. Preliminary evidence for a bi-directional regulatory relationship between DISC1 and FOXP2 was observed: a mouse model of schizophrenia that carries a Disc1 L100P amino acid substitution and shows altered developmental Disc1 expression was also found to show altered developmental expression of Foxp2. These results further understanding of two genes whose altered expression might contribute to the pathogenesis of psychiatric illness

Fitting small molecules to cryo-electron microscopy data

Recent innovations in the field of cryogenic-electron microscopy (cryo-EM) has enabled the visualisation of biological systems at atomic resolutions that rival that of X-ray crystallography. This is increasing the relevance of cryo-EM in the field of drug discovery, as it is now possible to solve high-resolution structures of biological complexes that may not have been amenable to crystallisation [1] and also in a more “native-like” state. However, it is not always possible to obtain structures to atomic resolutions with cryo-EM, currently only 16.28 % of structures deposited in the electron microscopy database [2] are at resolutions better than 3.0 Å, with the majority (45.05 %) at resolutions between 3.0 and 4.0 Å (correct as of December 2021). A vast body of work has been conducted with the aim of fitting biological macromolecules into cryo-EM at various resolutions [3–6]. However significantly less has been reported regarding the fitting of small molecules into cryo-EM maps. The work presented in this thesis aimed at developing methodologies that enable the fitting of small molecules to cryo-EM maps at resolutions from near atomic to 4.5Å. First, I used a fitting methodology that utilised consensus docking [7] in conjugation with a local difference mapping technique [8] to model the complex of the Eg5 kinesin motor domain with a novel inhibitor (GSK-1) in the presence of tubulin, into a 3.8 Å cryo-EM map (Chapter 2). The arrangement of structural elements within the protein allowed inferences to be made as to the mechanism of action of the drug [9]. Next, I present a new empirical molecular docking score for identifying correct ligand conformations within protein ligand complexes (Chapter 4). This score was integrated with goodness-of-fit scores commonly used for assessing the fit of biological molecules to cryo-EM maps [10]. Furthermore, we assessed the utility of this integrated score for fitting small molecules using simulated full maps and density difference maps (Chapter 4). This integrated score was then developed into a full methodology for fitting small molecules into cryo-EM maps, where its effectiveness was evaluated with experimental data at high (≤ 3.0 Å) and low (3.0 to 4.5 Å) resolution (Chapter 5). The accurate identification of protein ligand interactions from atomic models is an important consideration for drug discovery. To this end, a new software is presented that predicts protein ligand interactions using geometric parameters (Chapter 3). This software was benchmark using 35 high resolution protein-ligand complexes and compared to current state-of-the-art available software [11, 12]. Finally, I present the refined protein model of a Torpedo nicotinic acetylcholine receptor including the MX helix in a 6.6 Å cryo-EM map (Chapter 6). A combination of fitting software and bioinformatics identified the position of the MX helix relative to the cellular membrane. Our investigation suggested that the MX may function to entrap cholesterol, imposing rigidity to the receptor around the narrowest point of the central pore

Evaluation of in silico and in vitro screening methods for characterising endocrine disrupting chemical hazards

Anthropogenic activities have drastically altered chemical exposure, with traces of synthetic chemicals detected ubiquitously in the environment. Many of these chemicals are thought to perturb endocrine function, leading to declines in reproductive health and fertility, and increases in the incidence of cancer, metabolic disorders and diabetes. There are over 90 million unique chemicals registered under the Chemical Abstracts Service (CAS), of which only 308,000 were subject to inventory and/or regulation, in September 2013. However, as a specific aim of the EU REACH regulations, the UK is obliged to reduce the chemical safety initiatives reliance on in vivo apical endpoints, promoting the development and validation of alternative mechanistic methods. The human health cost of endocrine disrupting chemical (EDC) exposure in the EU, has been estimated at €31 billion per annum. In light of the EU incentives, this study aims to evaluate current in silico and in vitro tools for EDC screening and hazard characterisation; testing the hypothesis that in silico virtual screening accurately predicts in vitro mechanistic assays. Nuclear receptor binding interactions are the current focus of in silico and in vitro tools to predict EDC mechanisms. To the author’s knowledge, no single study has quantitatively assessed the relationship between in silico nuclear receptor binding and in vitro mechanistic assays, in a comprehensive manner. Tripos ® SYBYL software was used to develop 3D-molecular models of nuclear receptor binding domains. The ligand binding pockets of estrogen (ERα and ERβ), androgen (AR), progesterone (PR) and peroxisome proliferator activated (PPARγ) receptors were successfully modelled from X-ray crystal structures. A database of putative-EDC ligands (n= 378), were computationally ‘docked’ to the pseudo-molecular targets, as a virtual screen for nuclear receptor activity. Relative to in vitro assays, the in silico screen demonstrated a sensitivity of 94.5%. The SYBYL Surflex-Dock method surpassed the OECD Toolbox ER-Profiler, DfW and binary classification models, in correctly identifying endocrine active substances (EAS). Aiming to evaluate the current in vitro tools for endocrine MoA, standardised ERα transactivation (HeLa9903), stably transfected AR transactivation (HeLa4-11) assays in addition to novel transiently transfected reporter gene assays, predicted the mechanism and potency of test substances prioritised from the in silico results (n = 10 potential-EDCs and 10 hormone controls). In conclusion, in silico SYBYL molecular modelling and Surflex-Dock virtual screening sensitively predicted the binding of ERα/β, AR, PR and PPARγ potential EDCs, and was identified as a potentially useful regulatory tool, to support EAS hazard identification

Improved approaches to ligand growing through fragment docking and fragment-based library design

Die Fragment-basierte Wirkstoffforschung (“fragment-based drug discovery“ – FBDD) hat in den vergangenen zwei Jahrzehnten kontinuierlich an Beliebtheit gewonnen und sich zu einem dominanten Instrument der Erforschung neuer chemischer Moleküle als potentielle bioaktive Modulatoren entwickelt. FBDD ist eng mit Ansätzen zur Fragment-Erweiterung, wie etwa dem Fragment-„growing“, „merging“ oder dem „linking“, verknüpft. Diese Entwicklungsansätze können mit Hilfe von Computerprogrammen oder teilautomatischen Prozessen der „de novo“ Wirkstoffentwicklung beschleunigt werden. Obwohl Computer mühelos Millionen von Vorschlägen generieren können, geschieht dies allerdings oft auf Kosten unsicherer synthetischer Realisierbarkeit der Verbindungen mit einer potentiellen Sackgasse im Optimierungsprozess. Dieses Manuskript beschreibt die Entwicklung zweier computerbasierter Instrumente, PINGUI und SCUBIDOO, mit dem Ziel den FBDD Ausarbeitungs-Zyklus zu fördern. PINGUI ist ein halbautomatischer Arbeitsablauf zur Fragment-Erweiterung basierend auf der Proteinstruktur unter Berücksichtigung der synthetischen Umsetzbarkeit. SCUBIDOO ist eine freizugängliche Datenbank mit aktuell 21 Millionen verfügbaren virtuellen Produkten, entwickelt durch die Kombination kommerziell verfügbarer Bausteine („building blocks“) mit bewährten organischen Reaktionen. Zu jedem erzeugten virtuellen Produkt wird somit eine Synthesevorschrift geliefert. Die entscheidenden Funktionen von PINGUI, wie die Erzeugung abgeleiteter Bibliotheken oder das Anwenden organischer Reaktionen, wurden daraufhin in die SCUBIDOO Webseite integriert. PINGUI als auch SCUBIDOO wurden des Weiteren zur Erforschung Fragment-basierter Liganden („fragment-based ligand discovery“) mit dem β-2 adrenergen Rezeptor (β-2-AR) und der PIM1 Kinase als Zielproteine („targets“) eingesetzt. Im Rahmen einer ersten Studie zum β-2-AR wurden mit PINGUI acht unterschiedliche Erweiterungen für verschiedene Fragment-Treffer („hits“) vorhergesagt (ausgewählt?). Alle acht Verbindungen konnten dabei erfolgreich synthetisiert werden und vier der acht Produkte zeigten im Vergleich zu den Ausgangsfragmenten eine erhöhte Affinität zum target. Eine zweite Studie umfasste die Anwendung von SCUBIDOO zur schnellen Identifikation von Fragmenten und deren möglichen Erweiterungen mit potentieller Bindungsaktivität zur PIM-1 Kinase. Als Ergebnis ergab sich ein Fragment-Treffer mit der dazugehörigen Kristallstruktur. Weitere Folgeprodukte befinden sich derzeit in Synthese. Abschließend wurde SCUBIDOO an eine automatische Roboter- Synthese gekoppelt, wodurch hunderte von Verbindungen effizient parallel synthetisiert werden können. 127 der 240 vorhergesagten Produkte (53%) wurden mit dem Ziel an den β-2-AR zu binden bereits synthetisiert und werden in Kürze weitergehend getestet. Die beiden vorgestellten Computer-Tools könnten zur Verbesserung im Anfangsstadium befindlicher Projekte zur Fragment-basierten Wirkstoffentwicklung, vor allem hinsichtlich der Strategien im Bereich der Fragment Erweiterung, eingesetzt werden. PINGUI zum Beispiel generiert Vorschläge zur Fragment- Erweiterung, die sich mit hoher Wahrscheinlichkeit an die Zielstruktur anlagern, und stellt somit ein nützliches und kreatives Werkzeug zur Untersuchung von Struktur-Wirkungsbeziehungen („structure-activity relationship“ – SAR) dar. SCUBIDOO zeigte sich mit einem bisherigen 53-prozentigen Synthese-Erfolg als zugänglich für die Integration an die effiziente automatisierte Roboter-Synthese. Jede zukünftige Synthese liefert neue Kenntnisse innerhalb der Datenbank und wird somit nach und nach den Synthese-Erfolg erhöhen. Des Weiteren stellen alle synthetisierten Produkte neuartige Verbindungen dar, was umso mehr den möglichen Einfluss SCUBIDOOs bei der Entdeckung neuer chemischer Strukturen hervorhebt

Molecules, Cells and Minds: Aspects of Bioscientific Explanation

In this thesis I examine a number of topics that bear on explanation and understanding in molecular and cell biology, in order to shed new light on explanatory practice in those areas and to find novel angles from which to approach relevant philosophical debates. The topics I look at include mechanism, emergence, cellular complexity, and the informational role of the genome. I develop a perspective that stresses the intimacy of the relations between ontology and epistemology. Whether a phenomenon looks mechanistic, or complex, or indeed emergent, is largely an epistemic matter, yet has an objective basis in features of the world. After reviewing several concepts of mechanism I consider the influential recent account of Machamer, Darden and Craver (MDC). That account makes interesting proposals concerning the relationship between mechanistic explanation and intelligibility, which are consistent with the results of the investigation I undertake into the science surrounding protein folding. In relation to a number of other issues pertaining to biological systems I conclude that the MDC account is insufficiently nuanced, however, leading me to outline an alternative approach to mechanism. This emphasizes the importance of structure—function relations and addresses issues raised by reflection on the nature of cellular complexity. These include the distinction between structure and process and the different possible bases on which system organization may be maintained. The account I give of emergence construes the phenomenon in terms of psychological deficit: phenomena are emergent when we lack the capacity to trace through and model their causal structures using our cognitive schemas. I conclude by developing these ideas into a preliminary and partial account of explanation and understanding. This aspires to cover the significant fraction of work in molecular and cell biology that correlates biological structures, processes and functions by visualizing phenomena and making them imaginable