For life to thrive, its fundamental units, i.e., the cells, need to reliably and robustly fulfill their function. However, cellular operability is challenged by the appearance of biological noise in the concentration of proteins and other cell components. This noise arises due to spontaneous fluctuations that are inherent to all chemical reactions. For small (mesoscopic) systems, like cells, these fluctuations can be significant and disturb cellular functions. Cells evolved mechanisms to control and reduce their internal noise. One way to reduce noise in eukaryotic cells is to exploit their internal structure and restrict noise to a particular organelle, thus reducing the noise in the rest of the cell. In recent years it was shown that many cell organelles could be formed by phase separation without the need for a membrane. Thus, it was suggested that phase separation could reduce concentration noise in cells. However, until now, any systematic investigation linking essential aspects of phase separation and concentration noise in cells has been lacking. This motivates the study of fluctuations in mesoscopic phase-separating systems. This thesis develops a generic theoretical model based on a thermodynamic description of phase separation. We consider a binary mixture that can phase separate into two phases - a liquid droplet surrounded by a phase, which we refer to as continuous phase. We merge this description with methods of stochastic chemical reactions in order to account for the active turnover of phase-separating material and, thus, for the non-equilibrium nature of living cells. The resulting framework allows us to study fluctuations due to chemical turnover and phase separation in and out of equilibrium of phase separation. We use this framework to investigate how a phase-separating system can reduce concentration noise for different reaction networks. We find that phase separation can reduce concentration noise in active mesoscopic systems like cells in both phases. When turnover dynamics are slow, concentration noise in the dilute phase can be lowered to the level of Poissonian fluctuations. For the dense phase, we find that noise can fall below the Poissonian threshold. When turnover rates become faster such that the system deviates from the equilibrium configuration, the noise reduction by phase separation becomes less efficient. We test our model on experimental data of an engineered protein expressed in living cells. We find a good agreement between the data and theory and demonstrate that phase separation is a viable mechanism for noise reduction in living cells. Thus, phase separation might play an essential part in ensuring the reliable control of cellular functions.

Blood vessels including the arteries, veins, and capillaries are a critical and indispensable component of various organisms. Some studies estimate that if all the blood vessels present in our body are arranged in line, they would amount to a total length of approximately 60,000 miles. This distance is enough to circle the world two and a half times! In addition to being all pervasive, blood vessels perform certain key functions such as delivery of oxygen and nutrients to various tissues in the body. They also assist in the spread of diseases such as cancer. Therefore, it is important to study vessels from the point of view of tissue engineering applications. In this study, I have adapted the design of an open-source 3D printed device to create channels in Poly (ethylene glycol) Maleimide (PEG-Mal) hydrogels using the subtractive technique. The PEG-Mal hydrogels can be formed in various formulations to mimic the biophysical and biochemical properties of various tissues such as bone marrow, brain, and lung. These channels created within hydrogels can be easily perfused with physiologically relevant flow rates found in blood vessels and capillaries. Additionally, I have also optimized the hydrogel formulations to improve channel reproducibility. It was found that the number of arms of PEG-Mal contributed the most to channel reproducibility with higher success rates of channel formation in 8-arm gels when compared to 4-arm gels. Therefore, this project delineates the formation of simple in vitro channels in hydrogels which combines properties of the tissue specific extracellular matrix with hemodynamics. It is expected that such a system will find potential use in various tissue engineering and disease modeling studies.

<p>The proteasome is a multi-catalytic, multiprotein enzymatic machinery that is responsible for most of the protein degradation in the cell. Cellular protein homeostasis through the proteasome is regulated through the ubiquitin-independent or ubiquitin-dependent degradation pathway, which both utilize different isoforms of the enzymatic machinery. Over the past twenty years, the proteasome has been a well-validated therapeutic target by inhibition of its catalytic particle function, and more recently, through targeted protein degradation with the use of proteolysis targeting chimeras (PROTACs). Inhibition of the proteasome’s catalytic function has been previously shown to be therapeutically advantageous due to the need for high proteasomal activity for the survival of hematological cancer cells, which produce an overabundance of misfolded and unwanted proteins. Despite this success, off-target toxicities and drug-resistant mechanisms remain as dose-limiting factors for proteasome catalytic inhibition. Herein, we describe a variety of peptidomimetic (or “peptide-like”) approaches that target the proteasome beyond standard catalytic inhibition to serve as alternative therapies for hematological cancer. We investigate <em>(1)</em> the preferential structural properties of peptide-conjugated unnatural substrates for different proteasome isoforms’ substrate channels, <em>(2)</em> the effectiveness of an immunoproteasome-targeting peptide-conjugated prodrug strategy, and <em>(3)</em> the unknown binding site of a peptoid probe on the proteasome’s non-catalytic ubiquitin receptor, Rpn-13. This work not only showcases novel strategies to target the proteasome system but also describes methods that could be applied to other challenging enzymes or non-catalytic protein targets.</p>

<p>Drug discovery and development has experienced a tremendous growth in the recent</p> <p>years, and methods to accelerate the process are necessary as the demand for effective drugs</p> <p>to treat a wide range of diseases continue to increase. Nevertheless, the majority of conventional</p> <p>techniques are labor-intensive or have relatively low yields. As a result, academia</p> <p>and the pharmaceutical industry are continuously seeking for rapid and efficient methods to</p> <p>accelerate the drug discovery pipeline. Therefore, in order to expedite the drug discovery</p> <p>process, recent developments in physical and artificial intelligence models have been utilized</p> <p>extensively. However, the overarching problem is how to use these cutting-edge advancements</p> <p>in artificial intelligence to enhance drug discovery? Therefore, this dissertation work</p> <p>focused on developing and applying artificial intelligence and physical models to accelerate</p> <p>the drug discovery pipeline at different stages. As the first study reported in the dissertation,</p> <p>the potential to apply graph neural network-based machine learning architectures</p> <p>with the assistance of molecular modeling features to identify plausible drug leads out of</p> <p>structurally similar chemical databases is assessed. Then, the capability of applying molecular</p> <p>modeling methods including molecular docking and molecular dynamics simulations to</p> <p>identify prospective targets and biological pathways for small molecular drugs is discussed</p> <p>and evaluated in the following chapter. Further, the capability of applying state-of-the-art</p> <p>deep learning architectures such as multi-layer perceptron and recurrent neural networks</p> <p>to optimize the formulation development stage has been assessed. Moreover, this dissertation</p> <p>has contributed to assist functionality identification of unknown compounds using</p> <p>simple machine learning based computational frameworks. The developed omics data analysis</p> <p>pipeline is then discussed in order to comprehend the effects of a particular treatment</p> <p>on the proteome and lipidome levels of cells. In conclusion, the potential for developing and</p> <p>utilizing various artificial intelligence-based approaches to accelerate the drug discovery and</p> <p>development process is explored in this research. Thus, these collaborative studies intend</p> <p>to contribute to ongoing acceleration efforts and advancements in the drug discovery and</p> <p>development field.</p>

This dissertation deals with the study of ancient diseases mentioned in the historical period of the Scriptures in the region of Syro-Palestine. The definition, history, methodology and etymology of the terms relating to biblical diseases are discussed. Leprosy, syphilis, plague and anaemia amongst other diseases leave skeletal signs and lesions. Paleopathologists may reveal these diseases by studying skeletal remains of the population of Syro-Palestine. Criticisms and recommendations are offered for the practical paleopathologist, anthropologist or archaeologist. More interest should be taken in the study of coprolite in every new discovery of human remains. The scarcity of skeletal remains in the region is well known. The past and present law structure, the Halakah, may partly be to blame. The future of paleopathology worldwide is undisputedly the biochemical science of DNA analysis. With this new science the role for macromorphological examination may diminish. The diseases mentioned in the Bible are finding it increasingly difficult to hide behind the words in the Scriptures. / Old Testament and Ancient Near Eastern Studies / MA (Biblical Archaeology)

L'auto-organisation des organismes vivants est d'une complexité et d'une efficacité étonnantes. Plus précisément, les systèmes biologiques abritent un nombre gigantesque de réactions très spécifiques qui nécessitent que la bonne biomolécule se retrouve à la bonne place, dans le bon ordre et en un temps suffisamment court pour permettre le fonctionnement cellulaire, et au-delà la vie cellulaire. D'un point de vue dynamique, cela pose la question fondamentale de savoir comment les biomolécules trouvent efficacement leur(s) cible(s) spécifique(s), ou encore, quels types de forces rassemblent tous ces partenaires de réaction spécifiques dans un environnement aussi dense et ionisé que les micro-environnements cellulaires. Dans cette thèse, nous explorons la possibilité que des biomolécules puissent interagir à travers des interactions électromagnétiques de longue-portée telles que ces dernières sont prédites à partir des premiers principes de la physique; ''longue-portée'' signifiant que les interactionsen question sont actives sur des distances bien plus larges que les dimensions typiques des molécules mises en jeu (i.e., plus grandes qu'environ 50 angströms dans les systèmes biologiques). Après avoir posé les fondements théoriques concernant les interactionsde longue-portée potentiellement actives sur de longue distances dans un contexte biologique, nous étudions la posssibilité de détecter leur éventuelle contribution à partir de dispositifs expérimentaux qui sont accessibles de nos jours. Sur ce dernier point, des résultats préliminaires encourageants tant sur le plan théorique qu'expérimental sont présentés. / Self-organization of living organisms is of an astonishing complexity and efficiency. More specifically, biological systems are the site of a huge number of very specific reactions thatrequire the right biomolecule to be at the right place, in the right order and in a reasonably short time to sustain cellular function and ultimately cellular life. From the dynamic point of view, this raises the fundamental question of how biomolecules effectively find their target(s); in other words, what kinds of forces bring all these specific cognate partners together in an environment as dense and ionized as cellular micro-environments. In the present thesis, we explore the possibility that biomolecules interact through long-range electromagnetic interactions as they are predicted from the first principles of physics; "long-range" meaning that the mentioned interactions are effective over distances much larger than the typical dimensions of the molecules involved (i.e., larger than about 50 angströms in biological systems).After laying the theoretical foundations about interactions that are potentially active over long distances in a biological context, we investigate the possibility of detecting their contribution from experimental devices which are nowadays available. On the latter point, encouraging preliminary results both at the theoretical and experimental levels are exposed.

Ce travail de thèse parti de l'observation que la maintenance des fonctions cellulaires est basée sur l'orchestration précise d'interactions fonctionnelles entre biomolécules telles que l'ADN, l'ARN et les protéines. Bien que ces processus basiques ne montrent pas généralement une organisation spatiale stricte, ils semblent néanmoins contraints par des schémas dynamiques ou spatiaux précis. Cela pose ainsi la question des forces pouvant, dans un microenvironnement cellulaire, diriger les différents acteurs de processus biochimiques complexes au bon endroit, au bon moment et dans le bon ordre afin d'assurer les fonctions cellulaires essentielles. L'existence de forces sélectives à longue portée de nature électromagnétique, pouvant être responsables de l'extraordinaire efficacité des machineries biomoléculaires, est prédite par la mécanique quantique et l'électrodynamique; par longue portée, nous entendons entre 0.1 à 1 micron, ce qui est bien au delà de celle des forces traditionnelles reconnues comme les forces électrostatiques, de van der Waals-London ou les liaisons hydrogènes. Aucune procédure expérimentale ne fut proposée à ce jour pour confirmer ou infirmer cette hypothèse d'une utilisation efficace de telles forces électromagnétiques dans la matière vivante. Si ces forces sélectives de recrutement à longue portée sont effectivement actives au niveau biomoléculaire, cela constituerait un pas important vers une compréhension des processus et mécanismes cellulaires fondamentaux (expression génique, division cellulaire, signalisation, etc.). / The main subject of the present thesis work stems from the observation that the maintenance of cell functions is based on a precise orchestration of functional interactions between biomolecules such as DNA, RNA and proteins. Although these basic processes generally do not exhibit strict spatial organization, they seem constrained into a very accurate temporal - or dynamic - pattern. This raises the question of what types of physical forces can, in the cellular microenvironments, bring the various actors of complex biochemical processes both in the right place, at the right time and in the right order so as to ensure the essential cellular functions. The existence of selective, long-range forces of electromagnetic nature that may be responsible for the extraordinary efficiency of the biomolecular machineries is predicted by quantum mechanics and electrodynamics ; long-range meaning here of the order of 0.1-1 micron, well beyond the traditionally recognized forces, electrostatic ones, hydrogen bonds, van der Waals-London, etc.). Yet, to date, no experimental test has been proposed to disprove or confirm the hypothesis of an effective exploitation of such electromagnetic forces in living matter. If these selective, long-range recruitment forces were found to be active at the biomolecular level, this would represent an important step forward to the understanding of fundamental cellular processes and mechanisms (gene expression, cell division, signalling, etc.).

Les modèles de la biologie des systèmes visent à comprendre le comportement d’une cellule à travers un réseau biomoléculaire complexe. Dans a littérature, la plupart des études ne se sont intéressés qu’à la modélisation des parties isolées du réseau biomoléculaire com les réseaux métaboliques, etc. Cependant, pour bien comprendre le comportement d’une cellule, nous devons modéliser et analyser le réseau biomoléculaire dans son ensemble. Les approches existantes ne répondent pas suffisamment à ces exigences. Dans ce projet de recherche,nous proposons une plate-forme qui permet aux biologistes de simuler les changements d’état des réseaux biomoléculaires dans le but de piloter leurs comportements et de les faire évoluer d’un état non désiré vers un état souhaitable. Cette plate-forme utilise des règles, des connaissances et de l’expérience, un peu comme celles que pourrait en tirer un biologiste expert. La plate-forme comprend quatre modules : un module de modélisation logique, un module de modélisation sémantique, un module de simulation qualitative à événements discrets etun module d’optimisation. Dans ce but, nous présentons d’abord une approche logique pour la modélisation des réseaux biomoléculaires complexes, incluant leurs aspects structurels, fonctionnels et comportementaux. Ensuite, nous proposons une approche sémantique basée sur quatre ontologies pour fournir une description riche des réseaux biomoléculaires et de leurs changements d’état. Ensuite, nous présentons une méthode de simulation qualitative à événements discrets pour simuler le comportement du réseau biomoléculaire dans le temps. Enfin, nous proposons une méthode d’optimisation multi-objectifs pour optimiser la transitabilité des réseaux biomoléculaires complexes dans laquelle nous prenons en compte différents critères tels que la minimisation du nombre de stimuli externes, la minimisation du coût de ces stimuli, la minimisation du nombre de noeuds cibles et la minimisation de l’inconfort du patient. En se fondant sur ces quatre contributions, un prototype appelé CBN-Simulateur a été développé. Nous décrivons nos approches et montrons leurs applications sur des études de cas réels, le bactériophage T4 gene 32, le phage lambda et le réseau de signalisation p53. Les résultats montrent que ces approches fournissent les éléments nécessaires pour modéliser, raisonner et analyser le comportement dynamique et les états de transition des réseaux biomoléculaires complexes. / Systems biology models aim to understand the behaviour of a cell trough a complex biomolecular network. In the literature, most research focuses on modelling isolated parts of this network, such as metabolic networks.However, to fully understand the cell’s behaviour we should analyze the biomolecular network as a whole. Avail-able approaches do not address these requirements sufficiently. In this context, we aim at developing a platform that enables biologists to simulate the state changes of biomolecular networks with the goal of steering their be-haviours. The platform employs rules, knowledge and experience, much like those that an expert biologist mightderive. This platform consists of four modules: a logic-based modelling module, a semantic modelling module,a qualitative discrete-event simulation module and an optimization module. For this purpose, we first present alogic-based approach for modelling complex biomolecular networks including the structural, functional and be-havioural aspects. Next, we propose a semantic approach based on four ontologies to provide a rich description of biomolecular networks and their state changes. Then, we present a method of qualitative discrete-event simulation to simulate the biomolecular network behaviour over time. Finally, we propose a multi-objective optimization method for optimizing the transittability of complex biomolecular networks in which we take into account various criteria such as minimizing the number of external stimuli, minimizing the cost of these stimuli, minimizing the number of target nodes and minimizing patient discomfort. Based on these four contributions, a prototype called the CBNSimulator was developed. We describe our approaches and show their applicability through real cases studies, the bacteriophage T4 gene 32, the phage lambda, and the p53 signaling network. Results demonstrate that these approaches provide the necessary elements to model, reason and analyse the dynamic behaviour and the transition states of complex biomolecular networks.

Our understanding of the folding of membrane proteins lags behind that of soluble proteins due to the challenges posed by the exposure of hydrophobic regions during in vitro chemical denaturation and refolding experiments. While different folding models are accepted for soluble proteins, only the two-stage model and the long-range interactions model have been proposed so far for helical membrane proteins. To address our knowledge gap on how different membrane proteins traverse their folding landscapes, Chapter 2 investigates the structural features of SDS-denatured states and the kinetics for reversible unfolding of sensory rhodopsin II (pSRII), a retinal-binding photophobic receptor from Natronomonas pharaonis. pSRII is difficult to denature, and only SDS can dislodge the retinal chromophore without rapid aggregation. Even in 30% SDS (0.998 $\mathit{\Chi}_{SDS}$), pSRII retains the equivalent of six out of seven transmembrane helices, while the retinal binding pocket is disrupted, with transmembrane residues becoming more solvent-exposed. Folding of pSRII from an SDS-denatured state harbouring a covalently-bound retinal chromophore shows deviations from an apparent two-state behaviour. SDS denaturation to form the sensory opsin apo-protein is reversible. This chapter establishes pSRII as a new model protein which is suitable for membrane protein folding studies and has a unique folding mechanism that differs from those of bacteriorhodopsin and bovine rhodopsin. In Chapter 3, SDS-denatured pSRII, acid-denatured pSRII and sensory opsin obtained by hydroxylamine-mediated bleaching of pSRII were characterised by solution state NMR. 1D $^1$H and $^{19}$F NMR were first used to characterise global changes in backbone amide protons and tryptophan side-chains. Residue-specific changes in backbone amide chemical shifts and peak intensities in 2D [$^1$H,$^{15}$N]-correlation spectra were analysed. While only small changes in the chemical environment of backbone amides were detected, changes in backbone amide dynamics were identified as an important feature of SDS- and acid-denatured pSRII and sensory opsin. $^{15}$N relaxation experiments were performed to study the backbone amide dynamics of SDS-denatured pSRII, reflecting motions on different timescales, including fast fluctuations of NH bond vectors on the ps-ns timescale and the lack of exchange contributions on the µs timescale. These studies shed insight on differences in the unfolding pathways under different denaturing conditions and the crucial role of the retinal chromophore in governing the structural integrity and dynamics of the pSRII helical bundle. Hydrogen bonds play fundamental roles in stabilising protein secondary and tertiary structure, and regulating protein function. Successful detection of hydrogen bonds in denatured states and during protein folding would contribute towards our understanding on the unfolding and folding pathways of the protein. Previous studies have demonstrated residue-specific detection of stable and transient hydrogen bonds in small globular proteins by measuring $^1{\it J}_{NH}$ scalar coupling constants using NMR. In Chapter 4, different methods for measuring $^1{\it J}_{NH}$ scalar coupling were explored using RalA, a small GTPase with a mixed alpha/beta fold, as proof-of-concept. Detection of hydrogen bonds was then attempted with OmpX, a beta-barrel membrane protein, both in its folded state in DPC micelles and in the urea-denatured state. While $^1{\it J}_{NH}$ measurement holds promise for studying hydrogen bond formation, further optimisation of NMR experiments and utilisation of perdeuterated samples are required to improve the precision of such measurements in large detergent-membrane protein complexes. Naturally occurring split inteins can mediate spontaneous trans-splicing both in vivo and in vitro. Previous studies have demonstrated successful assembly of proteorhodopsin from two separate fragments consisting of helices A-B and helices C-G via a splicing site in the BC loop. To complement the in vitro unfolding/folding studies, pSRII assembly in vivo was attempted by introducing a splicing site in the loop region of the beta-hairpin constituting the BC loop of pSRII. The expression conditions for the N- and C-terminal pSRII-intein segments were optimised, and the two segments co-expressed. However, the native chromophore was not observed. Further optimisation is required for successful in vivo trans-splicing of pSRII and application of this approach towards understanding the roles of helices and loops in the folding of pSRII.

The thesis, which contains nine chapters, reports extensive large scale atomistic molecular dynamics (MD) simulation studies of water structure and dynamics at the surface of an anionic micelle, hydration layer of two proteins, and in the grooves of a 38-base pairs long DNA. Understanding the structure and dynamics of water molecules at the surfaces of self-organized assemblies and complex biological macromolecules has become a subject of intense research in recent times. Chapter 1 contains a brief overview of the biomolecular hydration dynamics. Relevant experimental, computational, and theoretical studies of biomolecular hydration and the time scales associated with the water dynamics are discussed. In Chapters 2 and 3, the structure, environment, energetics, and dynamics of constrained water molecules in the aqueous anionic micelle of cesium perfluorooctanoate (CsPFO) have been studied using large scale atomistic molecular dynamics simulations. Based on the number of hydrogen bond (HB) that interfacial water molecule makes with the polar head group (PHG) oxygen of the micelle, we find the existence of three kinds of water at the interface. We introduce a nomenclature to identify the species as IBW2 (form two HBs with two different PHG), IBW1 (form one HB with PHG), and IFW (no HB with PHG). Despite of possessing two strong w-PHG bonds, the concentration of the IBW2 species is rather low due to entropic effect. The ion solvation dynamics study at the interface shows the presence of a slow component, with a relaxation time 1-2 order of magnitude slower than that in the corresponding bulk solvent in agreement with the experimental results. Both the translational and orientational dynamics of the water molecules near the micellar surface is found to be much slower than those in the bulk. The HB between the PHG of the micelle and the water molecule has almost 13 times longer life time than that in the bulk between two tagged water molecules. In Chapter 4, we present results of extensive atomistic MD simulation studies of the structure and dynamics of aqueous protein solution of the toxic domain of Enterotoxin (1ETN) and the chicken villin headpiece sub-domain containing 36 amino acid residues (HP-36). Reduced water structure and the faster water dynamics around the active site of these proteins have been observed which may have biological significance. Chapter 5 presents an extensive atomistic molecular dynamics simulations study of water dynamics in the hydration layer of a 38 base long hydrated DNA duplex. The computed rotational time correlation function (TCF) of the minor groove water dipoles is found to be markedly non-exponential with a slow component at long time. The constrained water molecule is also found to exhibit anisotropic diffusion in both the major and minor grooves. At short-to-intermediate times, translational motion of water molecules in minor groove is sub-diffusive. Chapter 6 presents the study of water entropy in both the grooves DNA. The average values of the entropy of water at 300K in both the grooves of DNA are found to be significantly lower than that in bulk water. We propose that the configurational entropy of water in the grooves can be used as a measure of the mobility (or micro viscosity) of water molecules in a given domain. In Chapter 7, we study the specific DNA base-water hydrogen bond lifetime (HBLT) dynamics at the major and the minor grooves of a hydrated duplex. The base-water HBLT correlation functions are in general multi-exponential and the average lifetime depends significantly on the specificity of the DNA sequence. The average HBLT is longer in the minor groove than that in the major groove by almost a factor of 2. Chapter 8 presents the solvation dynamics of constituent bases of aqueous DNA duplex. The solvation TCFs of the four individual bases display highly non-exponential decay with time. An interesting negative cross-correlation between water and counterions is observed which makes an important contribution to relaxation at intermediate to longer times. In the concluding note, Chapter 9 presents a brief summary of the outcome of the thesis and suggests several relevant problems that may prove w orthwhile to be addressed in future