Locating a ligand-binding site is an important first step in structure-guided drug discovery, but current methods typically assess the pocket as a whole, doing little to suggest which regions and interactions are the most important for binding. This thesis introduces Fragment Hotspot Maps, a grid-based method that samples atomic propensities derived from interactions in the Cambridge Structural Database (CSD) with simple molecular probes. These maps specifically highlight fragment-binding sites and their corresponding pharmacophores, offering more precision over other binding site prediction methods. The method is validated by scoring the positions of 21 fragment and lead pairs. Fragment atoms are found in the highest scoring parts of the map corresponding to their atom type, with a median percentage rank of 98%. This is reduced to 72% for lead atoms, showing that the method can differentiate between the hotspots, and the warm spots later used during fragment elaboration. For ligand-bound structures, they provide an intuitive visual guide within the binding site, directing medicinal chemists where to grow the molecule and alerting them to suboptimal interactions within the original hit. These calculations are easily accessible through a simple to use web application, which only requires an input PDB structure or code. High scoring specific interactions predicted by the Fragment Hotspot Maps can be used to guide existing computer aided drug discovery methods. The Hotspots Python API has been created to allow these work flows to be executed programmatically through a single Python script. Two of the functions use scores from the Fragment Hotspot Maps to guide virtual screening methods, docking and field-based ligand screening. Docking virtual screening performance is improved by using a constraint selected from the highest scoring polar interaction. The field-based ligand screener uses modified versions of the Fragment Hotspot Maps directly to predict and score the binding pose. This workflow gave comparable results to docking, and for one target, Glucocorticoid receptor (GCR), showed much better results, highlighting its potential as an orthogonal approach. Fragment Hotspot Maps can be used at multiple stages of the drug discovery process, and research into these applications is ongoing. Their utility in the following areas are currently being explored: to assess ligandability for both individual structures and across proteomes, to aid in library design, to assess pockets throughout a molecular dynamics trajectory, to prioritise crystallographic fragment hits and to guide hit-to-lead development.

Mycobacterium tuberculosis (Mtb), a deadly pathogen, has scourged mankind for many centuries and has remained a major threat to global world health. Tuberculosis, the disease caused by this bacterium, is a major cause of death in developing nations and there is potential for its re-emergence in developed countries. An alarming rise in cases of multidrug-resistant and extremely-drug resistant tuberculosis (MDR-TB and XDR-TB) that do not respond to the customary first-line antibiotics necessitates the urgent need for development of new anti-TB drugs. Mtb becomes engulfed in human macrophages post infection of the host, but persists in the harsh environment of the human lungs by utilization of host cholesterol as a carbon source. The P450s CYP125A1, CYP142A1 and CYP124A1 are responsible for catalysing the side-chain degradation of cholesterol, which is critical for cholesterol to be used in the Mtb β-oxidation pathway for energy production. This PhD thesis focuses on understanding the structure/mechanism of the Mtb cholesterol 27-oxidases with the aim of facilitating the development of novel inhibitors of these P450s, which are crucial for Mtb to infect the host and to sustain infection. CYP142A1 and CYP124A1 were purified through three chromatographic steps with contaminating proteins successfully removed to give highly pure forms of these enzymes following the final purification step. Spectrophotometric titrations indicate that CYP142A1 and CYP124A1 bind tightly to cholesterol and cholestenone (and also to branched-chain methyl lipids for CYP124A1), highlighting their physiological roles in sterol and fatty acid metabolism, respectively. Binding analyses with a range of azole antibiotics revealed tight binding to bifonazole, clotrimazole, miconazole and econazole, and weak binding to fluconazole. Studies with compounds from a fragment screening library revealed weak binding to fragment hits for the cholesterol oxidases, but much tighter binding to these enzymes was found for ‘elaborated’ hits from a previous fragment screen on the Mtb cyclodipeptide oxidase CYP121A1, indicative of improved ligand potency achieved via ‘fragment merging’ strategies, and of structural similarities between these diverse Mtb P450s. Light scattering data indicate that CYP142A1 exists in dimeric form in solution, but becomes monomeric when treated with DTT; while CYP124A1 is completely monomeric. Crystal structures of CYP142A1 and CYP124A1 in complex with cholestenone, econazole and fragment library hits were determined. CYP142A1 crystal structures with econazole and fragment hits revealed heme coordination via the heterocyclic nitrogen in an azole group, and provide important data towards design of superior inhibitor drugs. The binding of cholestenone within the active site channels of CYP124A1 and CYP142A1 revealed an alignment favourable for C27 hydroxylation of the cholestenone side chain, which supports the physiological roles of CYP142A1 and CYP124A1 (as well as CYP125A1) in host cholesterol catabolism.

Accurate energetic modeling of large molecular systems is always desired by chemists. For example, ligand-protein binding simulations and enzymatic catalysis studies all involve with a small energy difference. The energetic accuracy depends largely on a proper handling of electronic correlations. Molecular mechanics (MM) methods deliver a parameterized Newtonian treatment to these problems. They show great capability in handling large calculations but give only qualitatively good results. Quantum mechanics (QM) methods solve Schrödinger equations and exhibit much better energy accuracy, though the computational cost can be prohibitive if directly applied to very large systems. Fragment-based methods have been developed to decompose large QM calculations into fragment calculations. However, most current schemes use a self- consistent field (SCF) method on fragments, in which no electronic correlation is accounted for. The super-system energy is computed as a sum of fragment energies plus two-body corrections and, possibly, three-body corrections (a "body" is a fragment). Higher order corrections can be added. Nevertheless, many problems require the treatment of high order electronic correlations. The coupled-cluster (CC) theory is the state-of-the-art QM method for handling electronic correlations. The CC wavefunction contains correlated excitations up to a given truncated level and coincidental excitations for all possible electronic excitations. It is a brilliant way of including more electronic correlations while maintaining a low-order scaling. In the proposed excitonic coupled-cluster (X-CC) theory, substantial modifications have been made to allow CC algorithms to act on the collective coordinates of fragment fluctuations to obtain super-system energy. The X-CC theory is designed to achieve accurate energetic modeling results for large chemical systems with much improved affordability and systematic improvability. The test system used in this work is a chain of beryllium atoms. A 30-fragment X-CCSD(2) calculation delivered matching accuracy with traditional CCSD method. An X-CCSD(2) calculation on a chain of 100 bonded fragments finished in 7 hours on a single 2.2 GHz CPU core. The X-CC scheme also demonstrates the ability in handling charge transfer problems. Due to the use of fluctuation basis in the test cases, the excitonic algorithms can be easily generalized to inhomogeneous systems. This will be investigated in future work.

<p>MurA catalyzes the first committed step of peptidoglycan biosynthesis and it is the target of the antibiotic fosfomycin. Due to a Cys-to-Asp substitution in the active site, MurAs from a number of pathogenic bacteria, including <em>Mycobacterium tuberculosis</em> and <em>Borrelia burgdorferi</em> (Lyme disease), are fosfomycin resistant. His-tagged <em>Borrelia burgdorferi</em> MurA (Bb_MurA) and its D116C mutant have been successfully expressed, purified and characterized. The <em>k</em>_cat value of wild-type Bb_MurA was 0.74 ± 0.01 s^-1. The D116C mutant’s <em>k</em>_cat decreased by 25-fold and was fosfomycin sensitive. The pH profiles of <em>k</em>_cat for both Bb_MurA and its mutant were characterized. There was little difference in p<em>K</em>_a1 values, but the p<em>K</em>_a2 value shifted from 7.4 ± 0.2 in wild-type enzyme to a value >11 in the mutant. This demonstrated that the p<em>K</em>_a2 of 7.4 was due to D116, and that it must be protonated for activity. Fosfomycin inactivation of Bb_MurA_H6(D116C) was time-dependent and only proceeded in the presence of UDP-GlcNAc. The dissociation constant, <em>K</em>_i, was 5.7 ± 0.4 µM and rate of covalent modification, <em>k</em>_inact, was 0.021 ± 0.003 s^-1.</p> <p>DAHP synthase catalyzes the first committed step in the shikimate pathway, and its catalysis has been proposed to proceed through two oxacarbenium ion intermediates. Pyruvate oxime, glyoxylate oxime and 4-imidazolecarboxylic acid have been evaluated as inhibitors of DAHP synthase. In the presence of glycerol 3-phosphate, the fitted <em>K</em>_i values of pyruvate oxime and glyoxylate oxime were 7.6 (± 0.9) × 10^-5 M and 7.4 (± 1.7) × 10^-5 M, respectively. 4-Imidazolecarboxylic acid’s inhibition was cooperative, and its binding was competitive with respect to PEP, and uncompetitive with respect to E4P. Its equilibrium dissociation constant was 3.0 (± 0.2) × 10^-3 M.</p> / Master of Science (MSc)

<p dir="ltr">Humans encode approximately 100 deubiquitinating enzymes (DUBs) which are categorized into seven distinct subfamilies. Each family and representative has a unique expression, function and binding topology to ubiquitin. In addition to human DUBs, parasites, bacteria, and viruses contain DUBs with unique structures and functions. One subfamily of DUBs, the ubiquitin C-terminal hydrolases (UCH), has four structurally similar human members and two known members within the <i>Plasmodium falciparum</i> genome. Human UCHL1 and UCHL3 are genetically validated targets in oncology and <i>Plasmodium falciparum</i><i> </i>UCHL3 (PfUCHL3) is a prospective target for antimalarial drug development. Though these three UCH enzymes have potential as therapeutic targets, there is a significant lack of quality small molecule chemical probes to understand the underlying biology and function of the enzymes, pharmacologically validate the targets, and serve as leads for drug development in oncology and malaria.</p><p dir="ltr">The UCH enzymes are cysteine proteases, which our lab has leveraged to identify novel covalent small molecule inhibitors of each enzyme. The workflow for each hit identification and optimization campaign is similar. Covalent fragment screening of electrophilic small molecule libraries against the respective recombinant enzyme was performed to identify chemical space around each enzyme. Subsequent medicinal chemistry hit-to-lead optimization was undertaken to improve upon the moderately potent hit molecules to provide improved small molecule inhibitors for each enzyme. Inhibitor identification and optimization for UCHL1 is described in Chapter 2, revealing a novel scaffold and a cocrystal structure reveals a unique binding pose for UCHL1 inhibitors. These molecules were also characterized in breast cancer cells to validate UCHL1 as a therapeutic target in breast cancer. First-in-class covalent inhibitors of UCHL3 are described in Chapter 3. Medicinal chemistry optimization along with a cocrystal structure of the initial hit has revealed the molecular interactions of this novel inhibitory scaffold. PfUCHL3 inhibitor identification is described in Chapter 4. Characterization of these molecules against Plasmodium falciparum is described along with a comparison to a recently identified reversible PfUCHL3 inhibitor. Finally, conclusions and future directions toward the development of potent, drug-like inhibitors of each UCH enzyme is presented in Chapter 5.</p>

Recent years have seen the emergence of Mycobacterium abscessus, a highly drug-resistant non-tuberculous mycobacterium, which causes life-threatening infections in people with chronic lung conditions like cystic fibrosis. This opportunistic pathogen is refractory to treatment with standard anti-tuberculosis drugs and most currently available antibiotics, often resulting in accelerated lung function decline. This project aims to use a structure-guided fragment-based drug discovery approach to develop effective drugs to treat M. abscessus infections. During the early stage of the project, three bacterial targets were identified, based on analysis of the structural proteome of M. abscessus and prior knowledge of M. tuberculosis drug targets, followed by gene knockout studies to determine target essentiality for bacterial survival. The three targets from M. abscessus were then cloned, expressed and purified and suitable crystallization conditions were identified leading to the determination of high resolution structures. Further, a large number of starting fragments that hit the three target proteins were determined, using a combination of biophysical screening methods and by defining crystal structures of the complexes. For target 3, PPAT (Phosphopantethiene adenylyl transferase), a chemical linking of two fragments followed by iterative fragment elaboration was carried out to obtain two compounds with low micromolar affinities in vitro. However, these compounds afforded only low inhibitory activity on M. abscessus whole cell. All starting fragments of target 2, PurC (SAICAR synthase), occupied the ATP indole pocket. Efforts were then made to identify further fragment hits by screening diverse libraries. Sub-structure searches of these initial fragment hits and virtual screening helped to identify potential analogues amenable to further medicinal chemistry intervention. While fragment hits of target 1, TrmD (tRNA-(N1G37) methyl transferase), were prioritized, whereby two chemical series were developed using fragment growing and merging approaches. Iterative fragment elaboration cycle, aided by crystallography, biophysical and biochemical assays led to the development of several potential lead candidates having low nano-molar range of in vitro affinities. Two such compounds afforded moderate inhibition of M. abscessus and stronger inhibition of M. tuberculosis and S. aureus cultures. Further chemical modifications of these compounds as well as others are now being done, to optimize cellular and in vivo activities, to be ultimately presented as early stage clinical candidates.

La méthode de conception de médicaments à partir de molécules « fragments » (connue sous le nom de « Fragment-Based Drug Design ») a été proposée au milieu des années 90, et a depuis été reconnue comme une alternative tangible aux techniques plus classiques de recherche de médicaments telles que le criblage à haut débit par exemple. La méthode des fragments consiste à cribler un petit nombre (< 10000) de composés organiques de faible poids moléculaire (< 300 Da) afin de détecter ceux qui se lient à la cible (protéine ou acides nucléiques). Du fait de leur faible complexité, les fragments présentent une affinité faible pour la cible, et la détection s'effectue généralement grâce à une technique biophysique (en particulier, résonance magnétique nucléaire (RMN), cristallographie aux rayons X, résonance plasmonique de surface). Les fragments « hits » sont ensuite modifiés par addition de nouvelles fonctions chimiques, ou par liaison de deux fragments, afin d'élaborer, étape par étape, une molécule capable d'établir des interactions plus nombreuses avec la cible, et d'améliorer ainsi l'affinité. Comparée aux méthodes classiques de criblage haut débit, la méthode des fragments offre divers avantages, notamment une meilleure exploration de l'espace chimique, une meilleure efficacité de liaison des molécules « hits », et une plus grande facilité d'optimisation des hits en molécules plus affines. Dans le cadre de ce projet de thèse, plusieurs aspects de la méthode des fragments ont été abordés : dans une première partie, nous étudions un cas concret d'application de la méthode des fragments à la recherche d'un inhibiteur de la peroxiredoxine 5 humaine, en utilisant la RMN comme outil de criblage des fragments ainsi que comme outil d'étude des interactions protéine-fragment. La découverte d'un inhibiteur de cette enzyme représente une avancée importante, qui devrait permettre de mieux comprendre son fonctionnement. Les autres parties de ce projet de thèse abordent des aspects plus méthodologiques de la méthode des fragments : les fragments conservent-ils leur site de liaison, leur efficacité de liaison et leur mode d'interaction au cours de leur élaboration en inhibiteur ? Les fragments peuvent-ils être spécifiques d'une protéine ? D'un site de liaison particulier ? Ces questions, rarement traitées, sont pourtant essentielles à la compréhension du comportement des molécules fragments, et sont abordées d'une part en défragmentant plusieurs inhibiteurs de la protéine Bcl-xL et en étudiant par RMN le comportement de ces fragments vis-à-vis de la protéine en termes d'affinité et de site de liaison, d'autre part en réalisant le criblage par RMN d'une série de fragments sur cinq protéines différentes (peroxiredoxine 5 humaine, sérum albumine humaine et trois protéines homologues de la famille Bcl-2). De manière générale, ce projet de thèse vise à étudier des aspects peu abordés de la méthode des fragments et à proposer des pistes permettant de mieux comprendre le comportement des fragments vis-à-vis de leur cible, au cours du criblage initial comme lors de leur optimisation / Fragment-Based Drug Design (FBDD) has been proposed in 1996 and has since been recognized as a tangible alternative to the more classical drug discovery methods such as High-Throuput Screening. FBDD consists of screening a small number (< 10 000) of low-molecular weight (< 300 Da) compounds and detect those that bind to the target (protein or nucleic acids). Because of their low complexity, fragment molecules usually display low affinities for their target, hence detecting fragment-protein interactions is mostly achieved using a biophysical technique (mostly Nuclear Magnetic Resonance (NMR), X-ray crystallography or Surface Plasmon Resonance). “Hit” fragments are then modified by addition of chemical substituents, or linked together, so as to elaborate a more complex molecule, forming more interactions with the target and hence displaying an improved affinity. As compared to the more classical High Throughput Screening method, fragment screening provides several advantages, including a better exploration of chemical space, highly ligand-efficient hits and easier optimization of the hits into more affine molecules. In this PhD project, several aspects of FDBB have been addressed : first, FBDD approaches were applied to the research of an inhibitor of the human peroxiredoxin 5 protein, using NMR not only as a screening method but also for the characterization of the protein-fragment interactions. The discovery of an inhibitor against this enzyme would allow to better understand its function. Next, methodological aspects of the FBDD method were addressed : Do fragments conserve their binding site, binding efficiency and mode of interaction upon optimization? Can the fragments display specificity towards a given target? Towards a given binding site? These issues, rarely studied, are yet essential to the understanding of the behavior of fragment molecules, and will be addressed firstly by defragmentating several Bcl-xL inhibitors into fragments and studying their behavior towards the protein in terms of a_nity and binding mode, secondly by screening a set of fragments against five different proteins (human peroxiredoxin 5, human serum albumin and three homologous proteins of the Bcl-2 family of proteins). More generally, this PhD project aims at studying less characterized aspects of the fragment methodology and proposing answers to better understand the behavior of fragment molecules towards their targets, both in the initial screening step and then during their optimization

Carbohydrates are abundant in nature and have functions ranging from energy storage to acting as structural components. Analysis of carbohydrate structures is important and can be used for, for instance, clinical diagnosis of diseases as well as in bacterial studies. The complexity of glycans makes it difficult to determine their structures. NMR spectroscopy is an advanced method that can be used to examine carbohydrates at the atomic level, but full assignments of the signals require much work. Reliable automation of this process would be of great help. Herein studies of Escherichia coli O-antigen polysaccharides are presented, both a structure determination by NMR and also research on glycosyltransferases which assemble the polysaccharides. The computer program CASPER has been improved to assist in carbohydrate studies and in the long run make it possible to automatically determine structures based only on NMR data. Detailed computer studies of glycans can shed light on their interactions with proteins and help find inhibitors to prevent unwanted binding. The WaaG glycosyltransferase is important for the formation of E. coli lipopolysaccharides. Molecular docking analyses of structures confirmed to bind this enzyme have provided information on how inhibitors could be composed. Noroviruses cause gastroenteritis, such as the winter vomiting disease, after binding human histo-blood group antigens. In one of the projects, fragment-based docking, followed by molecular dynamics simulations and binding free energy calculations, was used to find competitive binders to the P domain of the capsid of the norovirus VA387. These novel structures have high affinity and are a very good starting point for developing drugs against noroviruses. The protein targets in these two projects are carbohydrate binding, but the techniques are general and can be applied to other research projects. / At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 4: Submitted. Paper 5: Manuscript. Paper 6. Manuscript.

Fragment-based drug discovery is an emerging process that has gained popularity in recent years. The process starts from small molecules called fragments. One major step in fragment-based drug discovery is fragment screening, which is a strategy to screen libraries of small molecules to find hits. The strategy in theory is more efficient than traditional high-throughput screening that works with larger molecules. As fragments intrinsically possess weak affinity to a target, detection techniques of high sensitivity to affinity are required for fragment screening. Furthermore, the use of different screening methods is necessary to improve the likelihood of success in finding suitable fragments. Since no single method can work for all types of screening, there is a demand for new techniques. The aim of this thesis is to introduce weak affinity chromatography (WAC) as a novel technique for fragment screening. WAC is, as the name suggests, an affinity-based liquid chromatographic technique that separates compounds based on their different weak affinities to an immobilized target. The higher affinity a compound has towards the target, the longer it remains in the separation unit, and this will be expressed as a longer retention time. The affinity measure and ranking of affinity can be achieved by processing the obtained retention times of analyzed compounds. In this thesis, WAC is studied for fragment screening on two platforms. The first system comprised a 24-channel affinity cartridge that works in cooperation with an eight-needle autosampler and 24 parallel UV detector units. The second system was a standard analytical LC-MS platform that is connected to an affinity column, generally called WAC-MS or affinity LC-MS. The evaluation criteria in studying WAC for fragment screening using these platforms were throughput, affinity determination and ranking, specificity, operational platform characteristics and consumption of target protein and sample. The model target proteins were bovine serum albumin for the first platform, thrombin and trypsin for the latter. Screened fragments were either small molecule drugs, a thrombin-directed collection of compounds, or a general-purpose fragment library. To evaluate WAC for early stages of fragment elaboration, diastereomeric mixtures from a thrombin-directed synthesis project were screened. Although both analytical platforms can be used for fragment screening, WAC-MS shows more useful features due to easy access to the screening platform, higher throughput and ability to analyze mixtures. Affinity data from WAC are in good correlation with IC50 values from enzyme assay experiments. The possibility to distinguish specific from non- specific interactions plays an important role in the interpretation of WAC results. In this thesis, this was achieved by inhibiting the active site of the target protein to measure off-site interactions. WAC proves to be a sensitive, robust, moderate in cost and easy to access technique for fragment screening, and can also be useful in the early stages of fragment evolution. In conclusion, this thesis has demonstrated the proof of principle of using WAC as a new tool to monitor affinity and to select hits in fragment-based drug discovery. This thesis has indicated the primary possibilities, advantages as well as the limitations of WAC in fragment screening procedures.  In the future, WAC should be evaluated on other targets and fragment libraries in order to realize more fully the potential of the technology.

Advantages of cache cooperation on edge cache networks serving dynamic web content were studied. Design of cooperative edge cache grid a large-scale cooperative edge cache network for delivering highly dynamic web content with varying server update frequencies was presented. A cache clouds-based architecture was proposed to promote low-cost cache cooperation in cooperative edge cache grid. An Internet landmarks-based scheme, called selective landmarks-based server-distance sensitive clustering scheme, for grouping edge caches into cooperative clouds was presented. Dynamic hashing technique for efficient, load-balanced, and reliable documents lookups and updates was presented. Utility-based scheme for cooperative document placement in cache clouds was proposed. The proposed architecture and techniques were evaluated through trace-based simulations using both real-world and synthetic traces. Results showed that the proposed techniques provide significant performance benefits. A framework for automatically detecting cache-effective fragments in dynamic web pages was presented. Two types of fragments in web pages, namely, shared fragments and lifetime-personalization fragments were identified and formally defined. A hierarchical fragment-aware web page model called the augmented-fragment tree model was proposed. An efficient algorithm to detect maximal fragments that are shared among multiple documents was proposed. A practical algorithm for detecting fragments based on their lifetime and personalization characteristics was designed. The proposed framework and algorithms were evaluated through experiments on real web sites. The effect of adopting the detected fragments on web-caches and origin-servers is experimentally studied.