Global ETD Search

381	Structural Investigation of Processing α-Glucosidase I from Saccharomyces cerevisiae Barker, Megan 20 August 2012 (has links) N-glycosylation is the most common eukaryotic post-translational modification, impacting on protein stability, folding, and protein-protein interactions. More broadly, N-glycans play biological roles in reaction kinetics modulation, intracellular protein trafficking, and cell-cell communications. The machinery responsible for the initial stages of N-glycan assembly and processing is found on the membrane of the endoplasmic reticulum. Following N-glycan transfer to a nascent glycoprotein, the enzyme Processing α-Glucosidase I (GluI) catalyzes the selective removal of the terminal glucose residue. GluI is a highly substrate-specific enzyme, requiring a minimum glucotriose for catalysis; this glycan is uniquely found in biology in this pathway. The structural basis of the high substrate selectivity and the details of the mechanism of hydrolysis of this reaction have not been characterized. Understanding the structural foundation of this unique relationship forms the major aim of this work. To approach this goal, the S. cerevisiae homolog soluble protein, Cwht1p, was investigated. Cwht1p was expressed and purified in the methyltrophic yeast P. pastoris, improving protein yield to be sufficient for crystallization screens. From Cwht1p crystals, the structure was solved using mercury SAD phasing at a resolution of 2 Å, and two catalytic residues were proposed based upon structural similarity with characterized enzymes. Subsequently, computational methods using a glucotriose ligand were applied to predict the mode of substrate binding. From these results, a proposed model of substrate binding has been formulated, which may be conserved in eukaryotic GluI homologs. Biomolecular structure Eukaryotic glycosylation glycosylation N-glycan N-linked glycosylation Carbohydrate biochemistry Inhibitor antiviral therapeutic Structure-based drug design glucosidase glycosidase glycoside hydrolase post-translational modification enzyme enzyme mechanism inverting mechanism structural biology protein structure 6xHis tag Crystal packing sugar substrate X-ray crystallography single anomalous dispersion PHENIX heavy-atom phasing docking autodock autodock vina biophysical methods tryptophan fluorescence glucose oxidase activity assay enzyme inhibition Protein expression Protein purification Pichia pastoris Saccharomyces cerevisiae fondue AOX1 promoter glycoside hydrolysis substrate binding model molecular dynamics molecular dynamics Binding site Active site cleft Endoplasmic reticulum Glycan processing Glycan trimming protein-protein interactions cell-cell communication X-ray diffraction crystallization secreted protein substrate selectivity kojibiose glucotriose miglitol deoxynojirimycin Glc3Man9GlcNAc2 free oligosaccharide species GluI Cwh41 Cwh41p Cwht1p 0306 0307 0760
382	Development of high-performance algorithms for a new generation of versatile molecular descriptors. The Pentacle software Durán Alcaide, Ángel 04 March 2010 (has links) The work of this thesis was focused on the development of high-performance algorithms for a new generation of molecular descriptors, with many advantages with respect to its predecessors, suitable for diverse applications in the field of drug design, as well as its implementation in commercial grade scientific software (Pentacle). As a first step, we developed a new algorithm (AMANDA) for discretizing molecular interaction fields which allows extracting from them the most interesting regions in an efficient way. This algorithm was incorporated into a new generation of alignmentindependent molecular descriptors, named GRIND-2. The computing speed and efficiency of the new algorithm allow the application of these descriptors in virtual screening. In addition, we developed a new alignment-independent encoding algorithm (CLACC) producing quantitative structure-activity relationship models which have better predictive ability and are easier to interpret than those obtained with other methods. / El trabajo que se presenta en esta tesis se ha centrado en el desarrollo de algoritmos de altas prestaciones para la obtención de una nueva generación de descriptores moleculares, con numerosas ventajas con respecto a sus predecesores, adecuados para diversas aplicaciones en el área del diseño de fármacos, y en su implementación en un programa científico de calidad comercial (Pentacle). Inicialmente se desarrolló un nuevo algoritmo de discretización de campos de interacción molecular (AMANDA) que permite extraer eficientemente las regiones de máximo interés. Este algoritmo fue incorporado en una nueva generación de descriptores moleculares independientes del alineamiento, denominados GRIND-2. La rapidez y eficiencia del nuevo algoritmo permitieron aplicar estos descriptores en cribados virtuales. Por último, se puso a punto un nuevo algoritmo de codificación independiente de alineamiento (CLACC) que permite obtener modelos cuantitativos de relación estructura-actividad con mejor capacidad predictiva y mucho más fáciles de interpretar que los obtenidos con otros métodos. Diseño Factorial Fraccionado (FFD) Partial Least Squares (PLS) (PCA) Análisis de componentes principales Sonda Consistente Interacciones relevantes Velocidad Interpretación AMANDA Correlation (CLACC) Relación estructura actividad GRIND-2 (GRIND) GRID Independent Descritpors Campos de interacción molecular (MIF) Pentacle Métodos computacionales Qt Lenguajes de programación Interfaz de usuario Software Modelos software Modelo espiral Eficiencia Altas prestaciones Codificación Discretización Algoritmo Based Virtual Screening (LBVS) Ligand Drug Discovery (CADD) Computer Assisted Drug Design Prediction (SDEP) Standard Deviation of Error (FFD) Partial Least Squares (PLS) Analysis (PCA) Principal Component Probe Consistent Relevant Interactions Speed Interpretation AMANDA Correlation (CLACC) Screening (VS) Consistently Large Auto and Cross Virtual Relationship (QSAR) Quantitative Structure-Activity GRID INdependent Descriptors (GRIND) GRIND-2 GRID Alignment independent Molecular descriptors (MD) Pentacle Molecular Interaction Fields (MIF) Computational Methods Qt Programming Languages User Interface (UI) User-friendly Software Software models Spiral model Efficiency High-performance Encoding Discretizing Algorithm Descubrimiento de fármacos Cribado virtual basado en ligando (LBVS) 51 61
383	Homology modeling and structural analysis of the antipsychotic drugs receptorome López Muñoz, Laura 22 June 2010 (has links) Classically it was assumed that the compounds with therapeutic effect exert their action interacting with a single receptor. Nowadays it is widely recognized that the pharmacological effect of most drugs is more complex and involves a set of receptors, some associated to their positive effects and some others to the side effects and toxicity. Antipsychotic drugs are an example of effective compounds characterized by a complex pharmacological profile binding to several receptors (mainly G protein-coupled-receptors, GPCR). In this work we will present a detailed study of known antipsychotic drugs and the receptors potentially involved in their binding profile, in order to understand the molecular mechanisms of the antipsychotic pharmacologic effects.The study started with obtaining homology models for all the receptors putatively involved in the antipsychotic drugs receptorome, suitable for building consistent drug-receptor complexes. These complexes were structurally analyzed and compared using multivariate statistical methods, which in turn allowed the identification of the relationship between the pharmacological properties of the antipsychotic drugs and the structural differences in the receptor targets. The results can be exploited for the design of safer and more effective antipsychotic drugs with an optimum binding profile. / Tradicionalmente se asumía que los fármacos terapéuticamente efectivos actuaban interaccionando con un único receptor. Actualmente está ampliamente reconocido que el efecto farmacológico de la mayoría de los fármacos es más complejo y abarca a un conjunto de receptores, algunos asociados a los efectos terapéuticos y otros a los secundarios y toxicidad. Los fármacos antipsicóticos son un ejemplo de compuestos eficaces que se caracterizan por unirse a varios receptores simultáneamente (principalmente a receptores unidos a proteína G, GPCR). El trabajo de la presente tesis se ha centrado en el estudio de los mecanismos moleculares que determinan el perfil de afinidad de unión por múltiples receptores de los fármacos antipsicóticos.En primer lugar se construyeron modelos de homología para todos los receptores potencialmente implicados en la actividad farmacológica de dichos fármacos, usando una metodología adecuada para construir complejos fármaco-receptor consistentes. La estructura de estos complejos fue analizada y se llevó a cabo una comparación mediante métodos estadísticos multivariantes, que permitió la identificación de asociaciones entre la actividad farmacológica de los fármacos antipsicóticos y diferencias estructurales de los receptores diana. Los resultados obtenidos tienen interés para ser explotados en el diseño de fármacos antipsicóticos con un perfil farmacológico óptimo, más seguros y eficaces. Receptor 5-HT2A Receptor D3 Receptor D2 Ligando Clozapina Derivados Benzofuranonas Risperidona Olanzapina esquizofrenia métodos de regresión campos de interacción Molecular (MIF) Perfil Multireceptorial modelado por homología Docking sitio de unión interacciones moleculares selectividad afinidad de unión Diana Meta-Diana efectos secundarios fármaco antipsicótico típico fármaco antipsicótico atípico agonista antagonista membrana receptoroma rhodopsina estructura de rayos X descriptores moleculares farmacología análisis multivariante procedimiento integrado Computer-aided drug design Integrated approach Multivariate analysis Pharmacology Molecular descriptors X-ray structure Rhodopsin Receptorome Membrane Antagonist Agonist Atypical antipsychotic drug Typical antipsychotic drug Side effects Off-target Target Selectivity Binding affinity Molecular interactions Binding site Homology modeling Docking Multireceptor profile Molecular interaction Field (MIF) Partial Least Squares (PLS) Principal Component Analysis (PCA) Schizophrenia Benzolactam Derivatives Benzofuranone Derivatives Risperidone Olanzapine Clozapine Ligand Adrenergic receptors Muscarinic receptors Histamine receptors Serotonin receptors Dopamine receptors beta2-Adrenergic receptor D2 receptor D3 receptor 5-HT2A receptor G protein-coupled receptors (GPCR) 57

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