Protein interactions are the basis of synaptic function, and studying these interactions on a molecular level is crucial for understanding basic brain function, as well as mechanisms underlying neurological disorders. In this thesis, kinetic and mechanistic characterization of synaptic protein interactions was performed by using surface plasmon resonance biosensor technology. Fragment library screening against the reverse transcriptase of HIV was included, as it served as an outlook for future drug discovery against ligand-gated ion channels. The protein-protein interaction studies of postsynaptic Ca2+ -binding proteins revealed caldendrin as a novel binding partner of AKAP79. Caldendrin and calmodulin bind and compete at similar binding sites but their interactions display different mechanisms and kinetics. In contrast to calmodulin, caldendrin binds to AKAP79 both in the presence and absence of Ca2+ suggesting distinct in vivo functional properties of caldendrin and calmodulin. Homo-oligomeric β3 GABAA receptors, although not yet identified in vivo, are candidates for a histamine-gated ion channel in the brain. To aid the identification of the receptor, 51 histaminergic ligands were screened and a unique pharmacology was determined. A further requirement for identifying β3 receptors in the brain, is the availability of specific high-affinity ligands. The developed biosensor assay displayed sufficient sensitivity and throughput for screening for such ligands, as well as for being employed for fragment-based drug discovery. AMPA receptors are excitatory ligand-gated ion channels, involved in synaptic plasticity, and modulated by auxiliary proteins. Previous results have indicated that Noelin1, a secreted glycoprotein, interacts with the AMPA receptor. By using biochemical methods, it was shown that Noelin1 interacts directly with the receptor. The kinetics of the interaction were estimated by biosensor analysis, thereby confirming the interaction and suggesting low nanomolar affinity. The results provide a basis for functional characterization of a novel AMPA receptor protein interaction. The results demonstrate how secrets of synaptic protein interactions and function were revealed by using a molecular based approach. Improving the understanding of such interactions is valuable for basic neuroscience. At the same time, the technical advancements that were achieved to study interactions of ligand-gated ion channels by surface plasmon resonance technology, provide an important tool for discovery of novel therapeutics against these important drug targets.

Marine organisms are widely recognized sources of an impressive array of structurally unusual compounds. Marine natural products have exhibited interesting biomedical activities, provided targets for synthetic organic chemists, and afforded opportunities for elucidation of enzymatic mechanisms involved in biosyntheses of these molecules. Secondary metabolite pathways probably evolved to mediate interactions between organisms in their natural habitats; however, the ecological functions of natural products remain poorly understood for the vast majority of cases. In the present series of investigations, I evaluate the hypothesis that macroalgal natural products play a role in defending these organisms against potentially pathogenic microbes in the marine environment. Further, I combine these ecology-driven investigations with evaluation of algal natural products as sources of novel human drugs. This combined approach resulted in discovery of 15 novel natural products from two tropical red algae, Callophycus serratus and an unidentified crustose red alga. These new molecules included seven novel carbon-carbon connectivity patterns, not previously reported in the synthetic or natural product literature, illustrating the abundance of secondary metabolite diversity among marine macroalgae. Further, many compounds exhibited both biomedical and ecological activities, suggesting the synergistic potential of combined biomedical/ecological investigations in providing drug leads as well as insights into the natural functions of secondary metabolites. Bromophycolides and callophycoic acids, natural products from C. serratus, inhibited growth of the marine fungal pathogen Lindra thalassiae. Spatially-resolved desorption ionization mass spectrometry (DESI-MS) revealed that antifungal natural products were found at specific sites on algal surfaces. The heterogeneous presentation of antimicrobial chemical defenses on host surfaces suggests the potential importance of spatial scale in understanding host-pathogen interactions, and illustrates the capacity of mass spectrometry imaging in understanding chemically-mediated biological processes. Finally, assessment of antimicrobial chemical defenses among extracts from 72 collections of tropical red algae revealed that nearly all algae were defended against at least one marine pathogen or saprophyte and further suggested the untapped potential of ecological investigations in the discovery of novel chemistry.

El trabajo presentado en esta tesis cubre varios campos de investigación relacionados con el desarrollo de moléculas bioactivas. Se compone de cinco partes distintas que se resumen aquí. Predicción de la utilidad farmacológica de dianas terapéuticas. El desarrollo de fármacos está generalmente dirigido a inhibir la función de una proteína específica. Pero para validar esta proteína como diana terapéutica, al principio de un proyecto de descubrimiento de fármacos se tiene que saber si una molécula de tipo fármaco puede unirse con suficiente afinidad a la proteína como para alterar su función. Existen métodos que predicen si una potencial diana terapéutica es tratable o no por vía farmacológica, lo que se ha dado en llamar ‘druggability’. El problema es que estos métodos no están accesibles libremente y su validación es discutible. En la primera parte de la tesis se ha compilado un conjunto extensivo de datos de cavidades en proteínas cuyo novel de ‘druggability’ es conocido, haciéndolo accesible en una plataforma web pública (http://fpocket.sourceforge.net/dcd). Estos datos pueden ser modificados por cualquier persona que quiera contribuir al desarrollo de este conjunto de datos, aumentando su volumen o mejorando su calidad. En estudios previos, los sitios druggable se han asociado a cavidades profundas e hidrofóbicas, ignorando la importancia que tiene los grupos polares en el sitio de unión y su posible relación con la ‘druggability’. Utilizando el set de datos compilado previamente, hemos encontrado que aunque las cavidades ‘druggables’ son mas hidrofóbicas, también tienen grupos polares más expuestos pero con poca superficie de interacción. Esta observación es objeto de posteriores investigaciones en la segunda parte de la tesis. Finalmente, se ha utilizado un algoritmo de búsqueda de sitios de unión, fpocket, que empecé a desarrollar como proyecto de master. Este programa se ha utilizado para extraer todas las características de las cavidades ‘druggables’ y no ‘druggables’ y estos parámetros se han utilizado para entrenar un modelo logístico capaz de predecir si un sitio es druggable o no. Demostramos que el algoritmo y la función de puntuación desarrollado durante esta primera parte predice la ‘druggability’ de manera fiable. Los resultados son de igual calidad a los obtenidos con el único otro programa accesible con funcionalidad parecida (SiteFinder, de Schrödinger), pero nuestro programa tiene las siguientes importantes ventajas: 1) es libre; 2) es mucho más eficiente computacionalmente; y 3) trabaja sobre cavidades detectadas automáticamente por el programa, lo que permite aplicaciones a gran escala. En otras partes de la tesis se verá como su aplicación al conjunto del PDB permite novedosas aplicaciones en el área del diseño de fármacos. Análisis de movilidad de cavidades de las proteínas Existen una gran variedad de algoritmos que permiten identificar posibles sitios de unión en las estructuras tridimensionales de las proteínas. El trabajo presentado en la sección anterior de esta tesis permitía extender uno de estos algoritmos para caracterizar la ‘druggability’ de las cavidades. Un problema de gran calado en el estado actual de la técnica, tanto de detección de sitios de unión como en diseño de fármacos en general,4 es que las proteínas se tratan como un cuerpo rígido a pesar de que en realidad gozan de una gran movilidad estructural. El objetivo de esta sección era otorgar todavía otra funcionalidad a fpocket, el programa de predicción de sitios de unión, para permitir también la detección y el análisis de cavidades de proteínas en movimiento. Habitualmente, los movimientos de las proteína se pueden simular usando la dinámica molecular (MD). Una herramienta capaz de analizar conjuntos de estructuras derivados de MD u otras fuentes puede ser, por tanto, extremadamente útil para observar la aparición de cavidades transitorias y su plasticidad. Como resultado final de este trabajo, se presenta un nuevo programa informático, llamado MDpocket y que se enmarca dentro del paquete fpocket. Para cada conformación de la proteína, se ejecuta un ciclo de detección de cavidades con fpocket. Los resultados de este proceso se plasman sobre una malla tridimensional superpuesta a la estructura de la proteína. La malla puede entonces ser visualizada o analizada en mayor detalle. Lo primero se puede llevar a cabo con programas de visualización molecular tales como PyMOL, VMD o Chimera. Otra funcionalidad dentro de MDpocket es la de seguir la evolución de las propiedades de una cavidad o zona de interés (definida por el usuario) a lo largo del tiempo. Cabe destacar que MDpocket es igualmente capaz de identificar sitios de unión de moléculas tipo fármaco como pequeños canales en la matriz proteica que pueden ser importantes para la migración de pequeños ligandos como gases o moléculas de agua. Las posibles aplicaciones de MDpocket se ejemplifican en tres casos distintos. El primero es la capacidad de identificar la apertura transitoria de cavidades en el sitio de unión de ATP en la proteína HSP90. En el segundo ejemplo, se muestra como MDpocket permite identificar un canal de migración de moléculas biatómicas en mioglobina, un sistema de referencia bien conocido. Aquí se demuestra que MDpocket puede, no tan solo identificar los sitios internos de unión a Xenón, sino también los canales que se abren de forma transitoria para permitir a los ligandos migrar de un sitio a otro. En el último ejemplo, las propiedades del sitio de unión a ATP de la proteína cinasa P38 se analizaron a lo largo de una trayectoria de MD, evaluando la capacidad de MDpocket para identificar aquellas conformaciones que pueden ser particularmente útiles para realizar docking molecular. Uno de los principales problemas en docking de proteína-ligando es que el receptor generalmente se considera rígido, mientras que si se utilizan múltiples conformaciones (cristalográficas o derivadas de MD) para representar al receptor es difícil decidir a priori cuales de ellas pueden dar mejores resultados. Aquí mostramos que MDpocket se puede utilizar para seleccionar conformaciones concretas de una trayectoria de MD para usarlas en procesos de docking. Concretamente, hemos observado que la densidad hidrofóbica promedio (previamente identificada como un descriptor importante para predecir ‘druggability’) correlaciona bien con la probabilidad de que el modo de unión de ligandos pueda ser predicho correctamente. Tal como en el trabajo anterior, MDpocket se incluye dentro del proyecto fpocket y se está accesible como una herramienta libre y de código abierto. Relaciones estructura-cinética de unión El control de los tiempos en interacciones moleculares es una propiedad esencial de los sistemas bioquímicos, pero poco se conoce sobre los factores estructurales que gobiernan la cinética de los procesos de reconocimiento molecular. Partiendo de una observación realizada durante el trabajo de predicción de ‘druggability’, aquí se ha investigado el papel que átomos con poca superficie expuesta a solvente pueden jugar en los sitios de unión de la proteína. En particular, encontramos que los átomos polares en los sitios druggable son minoritarios en comparación con los átomos apolares, pero si bien pueden tener poca superficie accesible, tienden a ser mas protuberantes, lo que los hace más accesibles para establecer interacciones. Hemos establecido que esta propiedad puede estar relacionada con la cinética de unión/disociación de un ligando a su cavidad en el receptor. En diseño de fármacos, la vida media del complejo formado entre el fármaco y su diana terapéutica determina en gran medida sus efectos biológicos, pero en ausencia de relaciones estructura cinética, se hace imposible optimizar esta propiedad de forma racional. Aquí se muestra que átomos polares prácticamente enterrados (ABPAs) – un elemento comúnmente encontrado en los sitios de unión de proteínas – tienden a formar puentes de hidrógeno que están protegidos de las moléculas de agua. La formación y ruptura de este tipo de puentes de hidrógeno implica un estado de transición penalizado energéticamente porque ocurre de modo asincrónico con el proceso de deshidratación/rehidratación. En consecuencia, los puentes de hidrógeno protegidos se intercambian a velocidades lentas. Estas conclusiones se basan en el estudio computacional del proceso de unión de un pequeño ligando a un sitio de unión modelo. El receptor modelo se construyó para permitir modular tanto el grado de exposición del átomo polar como la curvatura del entorno apolar. Mediante el uso de dinámicas moleculares con constricciones y la relación de Jarzinsky, se obtuvieron los perfiles de energía libre de unión para cada cavidad. La presencia de un estado de transición (y por tanto menor velocidad de asociación/disociación) puede anticiparse mediante un simple análisis estructural tal como la medición de la superficie accesible del átomo polar o su grado de protrusión. Esto constituye una nueva y valiosa clave para interpretar y predecir relaciones estructura-actividad, que se ha puesto a prueba investigando sistemas reales. En primer lugar, analizando tanto estructuras cristalográficas depositadas en el PDB como trayectorias de dinámica molecular, se ha demostrado que aquellas moléculas de agua que forman puentes de hidrógeno con ABPAs tienden a tener menor movilidad e intercambios más lentos. Posteriormente, la validez del principio se ha demostrado en dos pares de inhibidores de la proteína Hsp90, una diana terapéutica para cáncer, para los que se han obtenido datos estructurales, termodinámicos y cinéticos mediante distintas técnicas experimentales. El acuerdo entre observables macroscópicas y los resultados de simulaciones moleculares confirma la función de los puentes de hidrógeno protegidos de solvente como trampas cinéticas e ilustra como nuestro hallazgo puede ser usado para facilitar el proceso de diseño de fármacos basado en estructura. Base de datos de cavidades: hacia el ‘pocketoma’ El trabajo presentado en el principio de la tesis perseguía un objetivo muy especifico, que se enmarca en un proyecto mayor del grupo de investigación. La herramienta de predicción de ‘druggability’ se desarrolló con el fin de cribar grandes bases de datos estructurales, tales como el PDB, identificando complejos proteína-proteína no obligados (transitorios) que contengan en su interfase una cavidad potencialmente capaz de unir moléculas de tipo fármaco. Con ello se pretende estabilizar selectivamente dicha interacción y conseguir un efecto biológico que pueda ser terapéutico. Dado que la información sobre cavidades y su druggability asociada va a ser explotadas por otras personas en el grupo en este y otro tipo de proyectos encaminados a facilitar la explotación de nuevos mecanismos de acción, es necesario crear una base de datos que contenga esta información y sea fácilmente navegable. Para empezar, se ejecutó el programa para cada una de las estructuras depositadas en el PDB, identificando todas las cavidades y extrayendo sus descriptores, entre los que se incluye la función de puntuación de druggability. Esta información se guarda de forma organizada en una base de datos relacional (pocketDB), que se relaciona con otras bases de datos tales como Uniprot y Uniref, que contienen información sobre secuencias. Igualmente, se incluyeron información sobre la estructura cuaternaria y otros recursos tales como Kegg, haciendo de pocketDB un potente recurso para filtrar de modo eficiente millones de cavidades, identificando aquellas que tengan mayor interés para cada proyecto. De modo particular, cabe destacar la aplicación de pocketDB a la identificación de cavidades ‘druggable’ situadas en la interfase de complejos transitorios proteína-proteína, resultando en 39 complejos candidatos, entre los que se recobraron 3 casos conocidos previamente, lo que valida la metodología. Además otros tres sistemas identificados, después de una inspección minuciosa, han sido seleccionados en el grupo como candidatos para realizar la prueba de concepto que valide esta nueva estrategia farmacológica. Uno de ellos está actualmente en fase de validación experimental. El ‘pocketoma’ La última sección de mi tesis presenta un proyecto que hace un uso extensivo de la base de datos de cavidades (pocketDB) previamente presentada. Dos cuestiones importantes aún persisten hoy día en el proceso de descubrimiento de fármacos y, de algún modo, contribuyen a la alta tasa de fracasos en las fases tardías del desarrollo, que normalmente se explican por la baja eficacia o el exceso de efectos secundarios (normalmente tóxicos) para el organismo. Ambas situaciones pueden ser explicadas por un fenómeno común: la falta de selectividad. Las fármacos interaccionan en la célula con una diversa variedad de macromoléculas además de con la diana terapéutica, induciendo así efectos secundarios imprevistos. Asimismo, considerar solamente una diana para nuestro fármaco puede resultar menos efectivo de lo esperado, puesto que la pérdida de función de una sola proteína diana puede ser fácilmente reemplazada debido a los mecanismos homeostáticos controlados por robustas redes de interacciones, derivando en una pérdida de eficacia de nuestra molécula. Este trabajo pretende sentar las bases para poder establecer relaciones entre macromoléculas biológicas en base a su potencial para interaccionar con una misma entidad química (fármaco). El trabajo se basa en la asunción de que cavidades similares son capaces de unir ligandos similares. Existen varios métodos que calculan la similitud entre cavidades de unión, sin embargo, hasta la fecha no se ha realizado un análisis relacional profundo de todas las cavidades en el PDB que permita establecer relaciones entre ellos. Con el fin de cumplir con los requerimientos técnicos de unos objetivos tan ambiciosos, se ha desarrollado un novedoso método de comparación de cavidades. En este particular método se considera una representación muy abstracta de la cavidad. Dicha representación reúne información tanto sobre la forma de la cavidad cómo sobre la distribución por pares de los puntos de interacción en la superficie. No obstante, la información sobre la topología exacta de la cavidad es ignorada. Tal abstracción intenta relacionar cavidades que estructuralmente están alejadas, pero que se parecen entre ellas en términos de forma y propiedades fisicoquímicas globales. Usando varios ejemplos de validación en un conjunto de cavidades de referencia, el método resulta capaz de recuperar de un gran set de cavidades aquellas más similares y relacionadas entre sí. Del mismo modo, el método demuestra ser útil para encontrar relaciones entre cavidades previamente no relacionadas y que sin embargo unen los mismos ligandos o moléculas muy similares. Esta nueva implementación se ha utilizado en un experimento de exploración a gran escala para encontrar (i) las mismas cavidades en diferentes estructuras, (ii) cavidades relacionadas y (iii) cavidades con la misma estructura de ligando. Se obtuvieron excelentes resultados para estas tres categorías. Seguidamente, se compararon entre ellas todas las cavidades encontradas en el PDB. Se desarrolló una herramienta computacional novedosa para permitir la navegación en el 'pocketoma' resultante de las comparaciones, que será posible descargar gratuitamente. Los resultados presentados muestran por primera vez un espacio global interrelacionando cavidad-ligando para todas las cavidades del PDB. Finalmente, se señalan a continuación dos aplicaciones que ponen de manifiesto el posible impacto del ‘pocketoma’ y la herramienta de navegación. En el primer ejemplo, una cavidad no caracterizada encontrada en GSK3-β fue comparada contra todas las cavidades del PDB, permitiendo obtener una variedad de cavidades, y sistemas, supuestamente relacionadas. Entre los resultados se encontraban las subunidades de unión a ADP dhaL y dhaM de la PTS dependiente di-hidroacetona cinasa. Se encontró que el sitio de unión a ADP era muy similar a la cavidad investigada en GSK3-β con una sorprendente similitud estructural entre ambos. En el último ejemplo, se navegó por el ‘pocketoma’ utilizando la herramienta visual desarrollada para tal tarea. Durante la exploración se encontró una curiosa e importante relación entre el sitio de unión de la hormona del receptor de estrógenos y una cavidad no caracterizada en la proteína Caspasa-3. Seguidamente, se realizó un estudio de docking con ligandos similares a la hormona y se procedió a realizar una extensiva dinámica molecular con el ligando en la mejor posición para verificar la estabilidad del compuesto en la cavidad de Caspasa-3. El complejo proteína-ligando estudiado resultó ser muy estable. Actualmente, el compuesto identificado se encuentra bajo validación experimental por nuestros colaboradores.

The interferon (IFN) response is a crucial component of cellular innate immunity, vital for controlling virus infections. Dysregulation of the IFN response however can lead to serious medical conditions including autoimmune disorders. Modulators of IFN induction and signalling could be used to treat these diseases and as tools to further understand the IFN response and viral infections. We have developed cell-based assays to identify modulators of IFN induction and signalling, based on A549 cell lines where a GFP gene is under the control of the IFN-β promoter (A549/pr(IFN-β).GFP) and the ISRE containing MxA promoter (A549/pr(ISRE).GFP) respectively. The assays were optimized, miniaturized and validated as suitable for HTS by achieving Z' Factor scores >0.6. A diversity screen of 15,667 compounds using the IFN induction reporter assay identified 2 hit compounds (StA-IFN-1 and StA-IFN-4) that were validated as specifically inhibiting IFNβ induction. Characterisation of these molecules demonstrated that StA-IFN-4 potently acts at, or upstream, of IRF3 phosphorylation. We successfully expanded this HTS platform to target viral interferon antagonists acting upon IFN-signalling. An additional assay was developed where the A549/pr(ISRE).GFP.RBV-P reporter cell line constitutively expresses the Rabies virus phosphoprotein. A compound inhibiting viral protein function will restore GFP expression. The assay was successfully optimized for HTS and used in an in-house screen. We further expanded this assay by placing the expression of RBV-P under the control of an inducible promoter. This demonstrates a convenient approach for assay development and potentiates the targeting of a variety of viral IFN antagonists for the identification of compounds with the potential to develop a novel class of antiviral drugs.

Tracking the evolution of function in enzyme superfamilies is key in understanding how important biological functions and mechanisms have evolved. New genes are being sequenced at a rate that far surpasses the ability of characterization by wet-lab techniques. Moreover, bioinformatics allows for the use of methods not amenable to wet lab experimentation. We now face a situation in which we are aware of the existence of many gene families but are ignorant of what they do and how they function. Even for families with many structurally and functionally characterized members, the prediction of function of ancestral sequences can be used to elucidate past patterns of evolution and highlight likely future trajectories. In this thesis, we apply in silico structure and function methods to predict the functions of protein sequences from two diverse superfamily case studies. In the first, the metallo-β-lactamase superfamily, many members have been structurally and functionally characterised. In this work, we asked how many times the same function has independently evolved in the same superfamily using ancestral sequence reconstruction, homology modelling and alignment to catalytic templates. We found that in only 5% of evolutionary scenarios assessed, was there evidence of a lactam hydrolysing ancestor. This could be taken as strong evidence that metallo-β-lactamase function has evolved independently on multiple occasions. This finding has important implications for predicting the evolution of antibiotic resistance in this protein fold. However, as discussed, the interpretation of this statistic is not clear-cut. In the second case study, we analysed protein sequences of the DUF-62 superfamily. In contrast to the metallo-β-lactmase superfamily, very few members of this superfamily have been structurally and functionally characterised. We used the analysis of alignment, gene context, species tree reconciliation and comparison of the rates of evolution to ask if other functions or cellular roles might exist in this family other than the ones already established. We find that multiple lines of evidence present a compelling case for the evolution of different functions within the Archaea, and propose possible cellular interactions and roles for members of this enzyme family.

L’Institut National des Produits Chimiques de l’Académie des Sciences du Vietnam (INPC) développe depuis plusieurs années une activité autour de la recherche de nouveaux médicaments issus de la biodiversité. Le développement d’un nouveau médicament prend de l’ordre d’une dizaine d’années et passe par plusieurs phases. Dans la phase de découverte, l’activité des composés chimiques sur une cible biologique est mesurée afin de mettre en évidence une action inhibitrice. Le développement d’approches in silico pour le criblage virtuel des composés chimiques est une alternative aux approches classiques in vitro beaucoup plus coûteuses à mettre en œuvre. L’utilisation de la grille a été identifiée comme une voie économiquement prometteuse pour accompagner la recherche de nouveaux médicaments au Vietnam. En effet, le développement de nouvelles stratégies basées sur l’utilisation de plates-formes de soumission de tâches (DIRAC, HTCaaS) a permis d’améliorer considérablement le taux de succès et le confort des utilisateurs, ouvrant la voie à une démocratisation de la grille.Dans ce contexte, l’objectif poursuivi dans le cadre de cette thèse est d’étudier dans quelle mesure des plates-formes multidisciplinaires pouvaient répondre aux besoins des chimistes de l’INPC. Le travail s’est concentré sur les modalités d’un partage équitable d’une plate-forme de soumission de tâches sur la grille par une ou plusieurs communautés d’utilisateurs. L’ordonnancement des tâches sur un serveur commun doit permettre que les différents groupes aient une expérience positive et comparable. Sur les infrastructures de grille EGEE et EGI en Europe , on peut distinguer deux grandes catégories d’utilisateurs : les utilisateurs « normaux » qui vont solliciter les ressources pour des tâches requérant typiquement de quelques dizaines à quelques centaines d’heures de calcul, et les « gros » utilisateurs qui vont lancer des grandes productions nécessitant le traitement de plusieurs milliers de tâches pendant des dizaines, voire des centaines de milliers d’heures de calcul. Les stratégies d’ordonnancement déployées aujourd’hui sur les plates-formes comme DIRAC ou HTCaaS ne permettent pas de servir de façon optimale et simultanée ces deux familles d’utilisateurs.Le manuscrit présente une évaluation par simulation des performances de plusieurs stratégies d’ordonnancement des tâches d’une plate-forme soumettant des jobs pilotes. L’outil SimGrid a permis de simuler l’infrastructure de grille régionale déployée en Auvergne à partir de traces archivées de son utilisation. Après évaluation des performances de plusieurs politiques d’ordonnancement tirées de la littérature, une nouvelle politique a été proposée dans laquelle les utilisateurs normaux et les très gros utilisateurs sont gérés de façon indépendante. Grâce à cette politique, le ralentissement expérimenté par les très gros utilisateurs est réduit significativement sans pénaliser excessivement les utilisateurs normaux. L’étude a été étendue à une fédération de clouds utilisant les mêmes ressources et arrive aux mêmes conclusions. Les performances des politiques d’ordonnancement ont ensuite été évaluées sur des environnements de production, à savoir l’infrastructure de grille européenne EGI et l’infrastructure nationale de supercalculateurs de la Corée du Sud. Un serveur DIRAC a été adossé aux ressources de l’organisation virtuelle biomédicale d’EGI pour étudier les ralentissements observés par les utilisateurs de ce serveur. Pareillement, les ralentissements expérimentés par les utilisateurs de la plate-forme HTCaaS au KISTI ont été observés en excellent accord avec les résultats de simulation avec SimGrid.Ces travaux confirment la faisabilité et l’intérêt d’une plate-forme unique au Vietnam au service des communautés scientifiques consommatrices des ressources académiques de grille et de cloud, notamment pour la recherche de nouveaux médicaments. / Virtual Screening (VS) is a computational technique used in the drug discovery process to select the most promising candidate drugs for in vitro testing from millions of chemical compounds. This method can offer an efficient alternative to reduce the cost of drug discovery and platform. The Natural Products Chemistry Institute of the Academy of Sciences of Vietnam (INPC) collects samples from local biodiversity and determines the 3D structure of single molecules. Their challenge is to set up a virtual screening platform on grid computing for their chemists to process their data. However, as the number of users who might have a wide range of virtual screening applications (in terms of the number of tasks and execution time) increases with limited available computing resources, it becomes crucial to devise an effective scheduling policy that can ensure a certain degree of fairness, user satisfaction and overall system throughput. In this context, the thesis focuses on an effective scheduling policy for the virtual screening workflow where multiple users with varying numbers of tasks are actively sharing a common system infrastructure. We have researched in theory and proposed some candidate policies. With the simulation results and the experimentation results in real system, we proposed the best policy for the fairness between users, which can be applied to INPC virtual screening platform.

The current, grim world-TB scenario, with TB being the single largest infectious disease killer, warrants a more effective approach to tackle the deadly pathogen, Mycobacterium tuberculosis. The deadly synergy of this pathogen with HIV and the emergence of drugresistant strains of the organism present a challenge for disease treatment (Russell et al., 2010). Thus, there is a pressing need for newer drugs with faster killing-kinetics which can claim both the actively-multiplying and latent forms of this pathogen causing the oldest known disease to man. This thesis entitled “Mechanistic and Regulatory Aspects of the Mycobacterium tuberculosis Dephosphocoenzyme A Kinase” describes one such potential drug target, which holds promise in future drug development, in detail. The development of efficacious antimycobacterials now requires previously unexplored pathways of the pathogen and cofactor biosynthesis pathways present a good starting point. Therefore, the mycobacterial Coenzyme A (CoA) biosynthesis was chosen for investigation, with the last enzyme of this pathway, dephosphocoenzyme A kinase (CoaE) which was shown to be essential for M. tuberculosis survival, as the focus of the present study (Sassetti et al., 2003). This thesis presents a detailed biochemical and biophysical characterization of the enzymatic mechanism of mycobacterial CoaE, highlighting several hitherto-unknown, unique features of the enzyme. Mutagenic studies described herein have helped identify the critical residues of the kinase involved in substrate recognition, binding and catalysis. Further, a role has been assigned to the UPF0157 domain of unknown function found in the mycobacterial CoaE as well as in several organisms throughout the living kingdom. Detailed insights into the regulatory characteristics of this enzyme from this work further our current understanding of the regulation of the universal CoA biosynthetic pathway and call for the attribution of a greater role to the last enzyme in pathway regulation than has been previously accredited. The thesis begins with a survey of the current literature available on tuberculosis and where we stand today in our fight against this dreaded pathogen. Chapter 1 details the characteristic features of the causative organism M. tuberculosis, briefly describing its unique genome and the cellular envelope which the organism puts forward as a tough shield to its biology. This is followed by a brief description of the infection cycle in the host, the pathogen-host interplay in the lung macrophages, the deadly alliance of the disease with HIV and our current drug arsenal against tuberculosis. Further, emphasizing on the need for newer, faster-acting anti-mycobacterials, Chapter 1 presents the rationale for choosing the mycobacterial coenzyme A biosynthetic pathway as an effective target for newer drugs. A detailed description of our current understanding of the five steps constituting the pathway follows, including a comparison of all the five enzymatic steps between the human host and the pathogen. This chapter also sets the objectives of the thesis, describing the choice of the last enzyme of the mycobacterial CoA biosynthesis, dephosphocoenzyme A kinase, for detailed investigation. As described in Chapter 1, the mycobacterial CoaE is vastly different from its human counterpart in terms of its domain organization and regulatory features and is therefore a good target for future drug development. In this thesis, Rv1631, the probable mycobacterial dephosphocoenzyme A kinase annotated in the Tuberculist database (http://genolist.pasteur.fr/TubercuList), has been unequivocally established as the last enzyme of the tubercular CoA biosynthesis through several independent assays detailed in Chapter 2. The gene was cloned from the mycobacterial genomic DNA, expressed in E. coli and the corresponding recombinant protein purified via a single-step affinity purification method. The mechanistic details of the enzymatic reaction phosphorylating dephosphocoenzyme A (DCoA) to the ubiquitous cofactor, Coenzyme A, have been described in this chapter which presents a detailed biochemical and biophysical characterization of the mycobacterial enzyme, highlighting its novel features as well as unknown properties of this class of enzymes belonging to the Nucleoside Tri-Phosphate (NTP) hydrolase superfamily. The kinetics of the reaction have been biochemically elucidated via four separate assays and the energetics of the enzyme-substrate and enzymeproduct interactions have been detailed by isothermal titration Calorimetry (ITC). Further details on the phosphate donor specificity of the kinase and the order of substrate binding to the enzyme provide a complete picture of the enzymatic mechanism of the mycobacterial dephosphocoenzyme A kinase. Following on the leads generated in Chapter 2 on the unexpected strong binding of CTP to the enzyme but its inability to serve as a phosphate donor to CoaE, enzymatic assays described in Chapter 3 helped in the identification of a hitherto unknown, novel regulator of the last enzyme of CoA biosynthesis, the cellular metabolite CTP. This chapter outlines the remarkable interplay between the regulator, CTP and the leading substrate, dephosphocoenzyme A, possibly employed by the cell to modulate enzymatic activity. The interesting twist to the regulatory mechanisms of CoaE added by the involvement of various oligomeric forms of the enzyme and the influence of the regulator and the leading substrate on the dynamic equilibrium between the trimer and the monomer is further detailed. This reequilibration of the oligomeric states of the enzyme effected by the ligands and its role in activity regulation is further substantiated by the fact that CoaE oligomerization is not cysteine-mediated. Further, the effects of the cellular metabolites on the enzyme have been corroborated by limited proteolysis, CD and fluorescence studies which helped elucidate the conformational changes effected by CTP and DCoA on the enzyme. Thus, the third chapter discusses the novel regulatory features employed by the pathogen to regulate metabolite flow through a critical biosynthetic pathway. Results presented in this chapter highlight the fact that greater importance should be attributed to the last step of CoA biosynthesis in the overall pathway regulation mechanisms than has been previously accorded. The availability of only three crystal structures for a critical enzyme like dephosphocoenzyme A kinase (those from Escherichia. coli, Haemophilus influenzae and Thermus thermophilus) is indeed surprising (Obmolova et al., 2001; O’Toole et al., 2003; Seto et al., 2005). In search of a structural basis for the dynamic regulatory interplay between the leading substrate, DCoA and the regulator, CTP, a computational approach was adopted. Interestingly, the mycobacterial enzyme, unlike its other counterparts from the prokaryotic kingdom, is a bi-domain protein of which the C-terminal domain has no assigned function. Thus both the N- and C-terminal domains were independently modeled, stitched together and energy minimized to generate a three-dimensional picture of the mycobacterial dephosphocoenzyme A kinase, as described in Chapter 4. Ligand-docking analyses and a comprehensive analysis of the interactions of each ligand with the enzyme, in terms of the residues interacted with and the strength of the interaction, presented in this chapter provide interesting insights into the CTP-mediated regulation of CoaE providing a final confirmation of the enzymatic inhibition effected by CTP. These homology modeling and ligand-docking studies reveal that CTP binds the enzyme at the site overlapping with that occupied by the leading substrate, thereby potentially obscuring the active site and preventing catalysis. Further, very close structural homology of the modeled full-length enzyme to uridylmonophosphate/cytidylmonophosphate kinases, deoxycytidine kinases and cytidylate kinases from several different sources, with RMSD values in the range of 2.8-3 Å further lend credence to the strong binding of CTP detailed in Chapter 2 and the regulation of enzymatic activity described in Chapter 3. Computational analyses on the mycobacterial CoaE detailed in this chapter further threw up some interesting features of dephosphocoenzyme A kinases, such as the universal DXD motif in these enzymes, which appears to play a crucial role in catalysis as has been assessed in the next chapter. It is interesting to note that the P-loop-containing nucleoside monophosphate kinases (NMPK), with which the dephosphocoenzyme A kinases share significant homology, have three catalytic domains, the nucleotide-binding domain, the acceptor substrate-binding domain and the lid domain. Computational analyses detailed in Chapter 4 including the structural and sequential homology studies, helped in the delineation of the three domains in the mycobacterial enzyme as well as highly conserved residues potentially involved in crucial roles for substrate binding and catalysis. Therefore important residues from all three domains of the mycobacterial CoaE were chosen for mutagenesis to study their contributions to catalysis. Conservative and non-conservative replacements of these residues detailed in Chapter 5 helped in the identification of crucial residues involved in phosphate donor, ATP binding (Lys14 and Arg140); leading substrate, DCoA binding (Leu113); stabilization of the phosphoryl transfer reaction (Asp32 and Arg140) and catalysis (Asp32). Thus, the results reported here present a first attempt to identify the previously unknown functional roles of highly conserved residues in dephosphocoenzyme A kinases. Chapter 5 also delineates the dependence of this kinase on the divalent cation, magnesium, for catalysis, describing a comparison of the kinetic activity by the wild type and the mutants, in the presence and absence of Mg2+. Therefore, this chapter presents a thorough molecular dissection of the roles played by crucial amino acids of the protein and the results herein can serve as a good starting point for targeted drug development approaches. As described above, another unusual characteristic of the mycobacterial CoaE is the fact that it carries a domain of unknown function, UPF0157, C-terminal to the N-terminal dephosphocoenzyme A kinase domain. The function of this unique C-terminal domain carried by the mycobacterial CoaE has been explored in Chapter 6. The failure of the Nterminal domain (NTD) to be expressed and purified in the soluble fraction in the absence of a domain at its C-terminus (either the mycobacterial CoaE CTD or GST from the pETGEXCT vector) pointed out a possible chaperonic activity for the CTD. A universal chaperonic activity by this domain in the cell was ruled out by carrying out established chaperone assays with insulin, abrin and -crystallin. In order to delineate the CTD sequence involved in the NTD-specific chaperoning activity, deletion mutagenesis helped establish the residues 35-50 (KIACGHKALRVDHIG) of the CTD in the N-terminal domain-specific assistance in folding. Chapter 6 further details the several other potential roles of the mycobacterial CTD probed, including the 4’-phosphopantethienyl transfer, SAM-dependent methyltransferase activity, activation of the NTD via phospholipids among others. Thus the results presented in this chapter are a first attempt at investigating the role of this domain found in several unique architectures in several species across the living kingdom. Chapter 7 is an attempt to stitch together and summarize the results presented in all the preceding chapters, giving an overview of our present understanding of the mycobacterial CoaE and its novel features.

Noncovalent interactions are of great importance in studies on crystal design and drug discovery. One such noncovalent interaction, halogen bonding, is present between a covalently bound halogen atom and a Lewis base. A halogen bond is a directional interaction caused by the anisotropic distribution of charge on a halogen atom X covalently bound to A, which in turn forms a positive region called σ-hole on the A–X axis. Utilization of halogen bonds in lead optimization have been rarely considered in drug discovery until recently and yet more than 50% of the drug candidates are halogenated. To date, the halogen bond has not been subjected to practical molecular mechanical-molecular dynamics (MM-MD) study, where this noncovalent interaction cannot be described by conventional force fields because they do not account for the anisotropic distribution of the charge density on the halogen atoms. This problem was solved by the author and, for the first time, an extra-point of positive charge was used to represent the σ-hole on the halogen atom. This approach is called positive extra-point (PEP) approach. Interestingly, it was found that the performance of the PEP approach in describing halogen bond was better than the semiempirical methods including the recent halogen-bond corrected PM6 (PM6-DH2X) method. The PEP approach also gave promising results in describing other noncovalent halogen interactions, such as C–X···H and C–X···π-systems. The PEP resulted in an improvement in the accuracy of the electrostatic-potential derived charges of halogen-containing molecules, giving in turn better dipole moments and solvation free energies compared to high-level quantum mechanical and experimental data.With the aid of our PEP approach, the first MM-molecular dynamics (MM-MD) study of inhibitors that form a halogen bond with a receptor was performed for tetrahalobenzotriazole inhibitors complexed to cyclin-dependent protein kinase (CDK2). When the PEP approach was used, the calculated MM-generalized Born surface area (MM-GBSA)//MM-MD binding energies for halobenzimidazole and halobenzotriazole inhibitors complexed with protein kinase CK2 were found to correlate well with the corresponding experimental data, with correlation coefficients R2 of greater than 0.90. The nature and strength of halogen bonding in halo molecule···Lewis base complexes were studied in terms of molecular mechanics using our PEP approach. The contributions of the σ-hole (i.e., positively charged extra-point) and the halogen atom to the strength of this noncovalent interaction were clarified using the atomic parameter contribution to the molecular interaction approach. The molecular mechanical results revealed that the halogen bond is electrostatic and van der Waals in nature. The strength of the halogen bond increases with increasing the magnitude of the extra-point charge. The van der Waals interaction’s contribution to the halogen bond strength is most favorable in chloro complexes, whereas the electrostatic interaction is dominant in iodo complexes.The failure of the PM6 semiempirical method in describing noncovalent halogen interactions —not only halogen bonds, but also hydrogen bonds involving halogen atoms— was reported and corrected by the introduction of a second and third generation of noncovalent halogen interactions correction. The developed correction yielded promising results for the four examined noncovalent halogen interactions, namely: C–X···O, C–X···N, C–X···π-system, and C–X···H interactions.

The majority of drugs are small organic molecules, so-called ligands, that influence biochemical processes by interacting with proteins. The understanding of how and why they interact and form complexes is therefore a key component for elucidating the mechanism of action of drugs. The research presented in this thesis is based on studies of acetylcholinesterase (AChE). AChE is an essential enzyme with the important function of terminating neurotransmission at cholinergic synapses. AChE is also the target of a range of biologically active molecules including drugs, pesticides, and poisons. Due to the molecular and the functional characteristics of the enzyme, it offers both challenges and possibilities for investigating protein-ligand interactions. In the thesis, complexes between AChE and drug-like ligands have been studied in detail by a combination of experimental techniques and theoretical methods. The studies provided insight into the non-covalent interactions formed between AChE and ligands, where non-classical CH∙∙∙Y hydrogen bonds (Y = O or arene) were found to be common and important. The non-classical hydrogen bonds were characterized by density functional theory calculations that revealed features that may provide unexplored possibilities in for example structure-based design. Moreover, the study of two enantiomeric inhibitors of AChE provided important insight into the structural basis of enthalpy-entropy compensation. As part of the research, available computational methods have been evaluated and new approaches have been developed. This resulted in a methodology that allowed detailed analysis of the AChE-ligand complexes. Moreover, the methodology also proved to be a useful tool in the refinement of X-ray crystallographic data. This was demonstrated by the determination of a prereaction conformation of the complex between the nerve-agent antidote HI-6 and AChE inhibited by the nerve agent sarin. The structure of the ternary complex constitutes an important contribution of relevance for the design of new and improved drugs for treatment of nerve-agent poisoning. The research presented in the thesis has contributed to the knowledge of AChE and also has implications for drug discovery and the understanding of biochemical processes in general.

By formulating the task of property-based molecular optimization into a neural machine translation problem, researchers have been able to apply the Transformer model from the field of natural language processing to generate molecules with desirable properties by making a small modification to a given starting molecule. These results verify the capability of Transformer models in capturing the connection between properties and structural changes in molecular pairs. However, the current research only proposes a Transformer model with fixed parameters that can produce limit amount of optimized molecules. Additionally, the trained Transformer model does not always successfully generate optimized output for every molecule and desirable property constraint given. In order to push the Transformer model into real applications where different sets of desirable property constraints in combination of variety of molecules might need to be optimized, these obstacles need to be overcome first. In this work, we present a framework using reinforcement learning as a fine-tuning method for the pre-trained Transformer to induce various output and leverage the prior knowledge of the model for a challenging data point. Our results show that, based on the definition of the scoring function, the Transformer model can generate much larger numbers of optimized molecules for a data point that is considered challenging to the pre-trained model. Meanwhile, we also showcase the relation between the sampling size and the efficiency of the framework in yielding desirable outputs to demonstrate the optimal configuration for future users. Furthermore, we have chemists to inspect the generated molecules and find that the reinforcement learning fine-tuning causes the catastrophic forgetting problem that leads our model into generating unstable molecules. Through maintaining the prior knowledge or applying rule-based scoring component, we demonstrate two strategies that can successfully reduce the effect of catastrophic forgetting as a reference for future research.