<p>Polycomb repressive complex 1 (PRC1) is critical for mediating gene expression during development. Five chromobox (CBX) homolog proteins, CBX2,4,6,7,8, are incorporated into PRC1 complexes, where they mediate targeting to trimethylated lysine 27 of histone H3 (H3K27me3) via the N-terminal chromodomain (ChD). Individual CBX paralogs have been implicated as drug targets in cancer; however, high similarity in sequence and structure among the CBX ChDs provide a major obstacle in developing selective CBX ChD inhibitors. Here a selection of small, focused, DNA-encoded libraries (DELs) against multiple homologous ChDs was reported to identify modifications to a parental ligand that confer both selectivity and potency for the ChD of CBX8. This on-DNA, medicinal chemistry approach enabled the development of SW2_110A, a selective, cell-permeable inhibitor of the CBX8 ChD. SW2_110A binds CBX8 ChD with a Kd of 800 nM, with minimal 5-fold selectivity for CBX8 ChD over all other CBX paralogs in vitro. SW2_110A specifically inhibits the association of CBX8 with chromatin in cells and inhibits the proliferation of THP1 leukemia cells driven by the MLL-AF9 translocation. In THP1 cells, SW2_110A treatment significantly decreases expression of MLL-AF9 target genes, including HOXA9, validating the previously established role for CBX8 in MLL-AF9 transcriptional activation, and defining the ChD as necessary for this function. The success of SW2_110A provides great promise for the development of highly selective and cell permeable probes for the full CBX family. In addition, the approach taken provides a proof-of-principle demonstration of how DELs can be used iteratively for optimization of both ligand potency and selectivity.</p> <p>CBX2 is upregulated in a variety of cancers, particularly in advanced prostate cancers. Using CBX2 inhibitors to understand and target CBX2 in prostate cancer is highly desirable. Here, selections of focused DNA encoded libraries (DELs) were performed for the discovery of a selective CBX2 chromodomain probe, SW2_152F. SW2_152F binds to CBX2 ChD with a Kd of 80 nM and displays 24-1000-fold selectivity for CBX2 ChD over other CBX paralogs <em>in vitro</em>. SW2_152F is cell permeable, selectively inhibits CBX2 chromatin binding in cells, and blocks neuroendocrine differentiation of prostate cancer cell lines in response to androgen deprivation.</p> <p>Targeted covalent inhibitors (TCIs) are rationally designed inhibitors that bind to a target protein and specifically label a non-conserved amino acid on proteins by means of reactive moieties (warheads). TCIs typically function by two steps, in which inhibitors first non-covalently bind to the target protein and then covalent bond formation occurs between the inhibitor- warhead and a proximal nucleophile on protein. Covalent inhibitors or drugs have prolonged target engagement and enhanced pharmacokinetic potency in vivo, compared to non-covalent molecules. Strategies to develop effective warheads of TCIs have been reported for labeling different nucleophilic amino acid residues, of which cysteine and lysine are the most established for covalent labeling. Tyrosine is recently becoming an attractive nucleophile for TCIs as an alternative choice, yet currently developed warheads that label tyrosine do so with modest specificity over other side chains. Here, I report the development of novel Mannich electrophiles and use those electrophiles as covalent warheads on an inhibitor to specifically target tyrosine in protein labeling. To my knowledge, this is first demonstration of the use of Mannich electrophiles in covalent inhibitors. Specifically, I leveraged a previously developed CBX8 chromodomain inhibitor to specifically label a non-conserved tyrosine within CBX8 using cyclic imine derivatives as warheads. This ligand-directed, specific tyrosine conjugation on CBX8 but not on CBX2, significantly improves both the potency and selectivity of inhibition. Biochemical, proteomic, and cellular validation further showed the cyclic imine covalent inhibitors can increase both potency and selectivity to the target protein CBX8 in cells, serving as a robust chemical probe for target function evaluation and modulation. This new type of tyrosine labeling warhead is a useful addition to the toolbox of medicinal chemists for covalent inhibitor development.</p> <p>The following chapters are modified from following publications, with permissions from Sijie Wang, Emily C.Dykhuizen, and Casey J. Krusemark. </p> <p>Wang, S., Denton, K. E., Hobbs, K. F., Weaver, T., McFarlane, J. M., Connelly, K. E., Gignac, M.C., Milosevich, N., Hof, F., Paci, I., Musselman, C. A., Dykhuizen, E.C., Krusemark, C. J. Optimization of Ligands Using Focused DNA-Encoded Libraries To Develop a Selective, Cell-Permeable CBX8 Chromodomain Inhibitor. <em>ACS Chem Biol. </em>2020, 15, 112-131</p> <p>Wang, S., Alpsoy, A., Sood, S., Ordonez-Rubiano, S. C., Dhiman, A., Sun, Y., Krusemark, C. J., Dykhuizen, E. C. A Potent, Selective CBX2 Chromodomain Ligand and its Cellular Activity During Prostate Cancer Neuroendocrine Differentiation. <em>ChemBioChem.</em> 2021, 22, 2335-2344</p> <p>Wang, S., Ordonez-Rubiano, S. C., Dhiman, A., Jiao G., Strohmier B. P., Krusemark, C. J., Dykhuizen, E. C. Polycomb Group proteins in cancer: multifaceted functions and strategies for modulation Modulators. <em>NAR Cancer</em>. 2021, 3, zcab039</p>

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 dir="ltr">Cyclic peptides are a growing drug class with over 40 FDA-approved drugs, with natural product cyclic peptides being the inspiration for many of these medicines (e.g., the antibiotic daptomycin, the immunosuppressant cyclosporine A, and the antifungal caspofungin). Two major types of cyclic peptide natural products exist: (1) the ribosomally synthesized and post-translationally modified peptides (RiPPs) and (2) those made by nonribosomal peptide synthetases (NRPSs). Even though many uncharacterized cyclic peptide biosynthetic gene clusters (BGCs) exist, the discovery of new cyclic peptide natural products remains a challenge because many BGCs are cryptic. Herein, we describe the development of a new approach to access the products of these cryptic NRPS BGCs and the discovery of many novel bioactive compounds from this approach. Specifically, we utilized bioinformatics programs to predict the amino acid sequences associated with the multimodular NRPS and the presence of a nearby penicillin-binding protein (PBP)-like thioesterase (TE, PBP-TE) to determine that the predicted peptides are head-to-tail cyclized. Following the bioinformatics-guided predictions, solid phase peptide synthesis (SPPS) followed by solution phase cyclization enabled access to a library of predicted cyclic peptides that we then screened for interesting bioactivities. From this screening, we have identified molecules that stimulate the proteasome, inhibit the growth of free-living amoebas, selectively lyse Gram-negative bacteria, and suppress the immune system. Structure activity relationships for these molecules have been determined, with more potent analogs being discovered. Future directions include mechanism of action studies, as well as expanding the peptide library to include more off-loading methods and tailoring enzymes that might modify the peptide after release from the NRPS.</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.