Submitted by Caroline Xavier (caroline.xavier@pucrs.br) on 2017-08-25T13:27:56Z No. of bitstreams: 1 TES_THIAGO_LIPINSKI_PAES_COMPLETO.pdf: 7285473 bytes, checksum: 4dab05982a53386f1d5dd2202a2f9b21 (MD5) / Made available in DSpace on 2017-08-25T13:27:57Z (GMT). No. of bitstreams: 1 TES_THIAGO_LIPINSKI_PAES_COMPLETO.pdf: 7285473 bytes, checksum: 4dab05982a53386f1d5dd2202a2f9b21 (MD5) Previous issue date: 2017-03-27 / Among the main computational techniques currently applied to study proteins, classical molecular dynamics plays a important hole, specially its variation called replica exchange molecular dynamics or REMD, which provides efficient conformational sampling. Regular secondary structures elements of proteins are formed and maintained via stabilization by hydrogen bonds within helices and between strands of a -sheet. Packing of these structural elements, allowed by flexible turns and loops connecting them, leads to the formation of a structure that, in the successful cases, represents the native, functional state of a protein. Ionic, dipole, van der Waals, hydrophobic interactions, and hydrogen bonding are fundamental to these events. Most of these forces are strong up to a distance of 4.0 ?. Hence, these are the distances involved in the formation of local structural nubs that can further propagate and form whole elements of secondary structure. The common practice while simulating is, however, to keep fixed the cutoff at values higher or equal to 8.0 ?. Here a novel replica exchange molecular dynamics approach based on running cutoffs (varying from 4.0 ? to 8.0 ?) to enhance protein structure prediction is presented. We first proved the method as a reproducible one, as well as following a Boltzmann distribution and sampling different structures of conventional REMD. The human villin headpiece protein (PDB ID: 1UNC) was used as case study. We tested 9 different simulation protocols, in triplicate, and proved the use of incremental cutoff as an effective approach to enhance the quality and speed of protein structure predictions via replica exchange molecular dynamics. Applying the method to the protein test set, although of limited size, CuT-REMD showed good performance against the ab initio methods, most of the time being either as the best prediction method or with close results to the best ones. This made it possible to also compare CuT-REMD with de novo methods. Despite the difficulties, CuT-REMD maintained a good performance even surpassing certain servers for all tested proteins. The results obtained are encouraging, with the emergence of new questions to be addressed in the future. / Dentre os principais m?todos computacionais aplicados atualmente ao estudo de prote?nas, a din?mica molecular cl?ssica realiza importante papel, especialmente sua varia??o intitulada Replica Exchange Molecular Dynamics ou REMD, a qual prov? amostragem conformacional eficiente. Elementos de Estruturas Secund?rias (EES) regulares de prote?nas s?o formados e mantidos atrav?s de estabiliza??o por liga??es de hidrog?nio dentro de h?lices e entre fitas de uma folha . O empacotamento desses elementos estruturais, permitido por voltas e la?os flex?veis conectando-os, leva ? forma??o de uma estrutura que, nos casos bem sucedidos, representa o estado nativo, funcional de uma prote?na. Intera??es i?nicas, dipolo-dipolo, de van der Waals e hidrof?bicas, al?m de liga??es de hidrog?nio, s?o fundamentais para esses eventos. A maioria dessas for?as ? mais forte at? uma dist?ncia de 4,0 ?. Assim, essas (de 0,0 ? a 4,0 ?) s?o as dist?ncias envolvidas na forma??o de estruturas locais, que podem ainda se propagar e formar elementos inteiros de estrutura secund?ria. A pr?tica comum ao se executar simula??es por DM ?, no entanto, manter um raio de corte fixo em valores maiores ou iguais a 8,0 ?. Esta tese apresenta o m?todo CuTREMD, uma nova abordagem de REMD com base em raio de corte incremental (variando de 4,0 ? a 8,0 ?) testando a hip?tese de que tal abordagem pode otimizar a predi??o de estruturas terci?rias de prote?nas. Primeiramente, foi utilizada a prote?na villin headpiece humana (c?digo PDB 1UNC), como estudo de caso, e nove diferentes protocolos de simula??o foram testados, todos em triplicata. Posteriormente, com base nos resultados obtidos, um protocolo-padr?o foi escolhido como protocolo CuT-REMD, e um conjunto de nove prote?nas adicionais foi testado, sendo os resultados comparados com o m?todo REMD convencional. A utiliza??o de raio de corte incremental provou-se uma abordagem eficaz para melhorar a qualidade e velocidade das predi??es de estruturas de prote?nas via REMD. Aplicando o m?todo ao conjunto teste de prote?nas, embora de tamanho limitado, CuT-REMD mostrou bom desempenho em rela??o aos m?todos ab initio, colocando-se na grande maioria das vezes ou como o melhor m?todo de predi??o ou com resultados pr?ximos aos melhores m?todos. Isso possibilitou compar?-lo tamb?m com m?todos de novo e, embora com mais dificuldade, CuT-REMD manteve bom desempenho, inclusive superando certos servidores em todas as ocasi?es. Os resultados obtidos, em suma, mostram-se encorajadores, com o surgimento de novos questionamentos a serem abordados futuramente.

Submitted by PPG Ci?ncia da Computa??o (ppgcc@pucrs.br) on 2018-09-03T14:00:58Z No. of bitstreams: 1 RAFAEL CAUDURO OLIVEIRA MACEDO_DIS.pdf: 6178948 bytes, checksum: 6ed3599e31f122e78b11b322a8c0ac06 (MD5) / Approved for entry into archive by Sheila Dias (sheila.dias@pucrs.br) on 2018-09-04T12:17:04Z (GMT) No. of bitstreams: 1 RAFAEL CAUDURO OLIVEIRA MACEDO_DIS.pdf: 6178948 bytes, checksum: 6ed3599e31f122e78b11b322a8c0ac06 (MD5) / Made available in DSpace on 2018-09-04T12:47:15Z (GMT). No. of bitstreams: 1 RAFAEL CAUDURO OLIVEIRA MACEDO_DIS.pdf: 6178948 bytes, checksum: 6ed3599e31f122e78b11b322a8c0ac06 (MD5) Previous issue date: 2017-08-30 / Prote?nas executam um papel vital em todos os seres vivos, mediando uma s?rie de processos necess?rios para a vida. Apesar de existirem maneiras de determinar a composi??o dessas mol?culas, ainda falta-nos conhecimentos suficiente para determinar de uma maneira r?pida e barata a sua estrutura 3D, que desempenha um papel importante na suas fun??es. Um dos principais m?todos computacionais aplicados ao estudo das prote?nas e o seu processo de enovelamento, o qual determina a sua estrutura, ? Din?mica Molecular. Um aprimoramento deste m?todo, conhecido como Replica Exchange Molecular Dynamics (ou REMD), ? capaz de produzir resultados muito melhores, com o rev?s de significativamente aumentar o seu custo computacional e gerar um volume muito maior de dados. Esta disserta??o apresenta um novo m?todo de otimiza??o deste m?todo, intitulado Filtragem de Dados Anal?ticos, que tem como objetivo otimizar a an?lise p?s-simula??o filtrando as estruturas preditas insatisfat?rias atrav?s do uso de m?tricas de qualidade absolutas. A metodologia proposta tem o potencial de operar em conjunto com outras abordagens de otimiza??o e tamb?m cobrir uma ?rea ainda n?o abordada por elas. Adiante, a ferramenta SnapFi ? apresentada, a qual foi designada especialmente para o prop?sito de filtrar estruturas preditas insatisfat?rias e ainda operar em conjunto com as diferentes abordagens de otimiza??o do m?todo REMD. Um estudo foi ent?o conduzido sobre um conjunto teste de simula??es REMD de predi??o de estruturas de prote?nas afim de elucidar uma s?ries de hip?teses formuladas sobre o impacto das diferentes temperaturas na qualidade final do conjunto de estruturas preditas do processo REMD, a efici?ncia das diferentes m?tricas de qualidade absolutas e uma poss?vel configura??o de filtragem que utiliza essas m?tricas. Foi observado que as temperaturas mais altas do m?todo REMD para predi??o de estruturas de prote?nas podem ser descartadas de forma segura da an?lise posterior ao seu t?rmino e tamb?m que as m?tricas de qualidade absolutas possuem uma alta vari?ncia (em termos de qualidade) entre diferentes simula??es de predi??es de estruturas de prote?nas. Al?m disso, foi observado que diferentes configura??es de filtragem que utilize tais m?tricas carrega consigo esta vari?ncia. / Proteins perform a vital role in all living beings, mediating a series of processes necessary to life. Although we have ways to determine the composition of such molecules, we lack sufficient knowledge regarding the determination of their 3D structure in a cheap and fast manner, which plays an important role in their functions. One of the main computational methods applied to the study of proteins and their folding process, which determine its structure, is Molecular Dynamics. An enhancement of this method, known as Replica-Exchange Molecular Dynamics (or REMD) is capable of producing much better results, at the expense of a significant increase in computational costs and volume of raw data generated. This dissertation presents a novel optimization for this method, titled Analytical Data Filtering, which aims to optimize post-simulation analysis by filtering unsatisfactory predicted structures via the use of different absolute quality metrics. The proposed methodology has the potential of working together with other optimization approaches as well as covering an area still untouched at large by them to the best of the author knowledge. Further on, the SnapFi tool is presented, a tool designed specially for the purpose of filtering unsatisfactory structure predictions and also being able to work with the different optimization approaches of the Replica-Exchange Molecular Dynamics method. A study was then conducted on a test dataset of REMD protein structure prediction simulations aiming to elucidate a series of formulated hypothesis regarding the impact of the different temperatures of the REMD process in the final quality of the predicted structures, the efficiency of the different absolute quality metrics and a possible filtering configuration that take advantage of such metrics. It was observed that high temperatures may be safely discarded from post-simulation analysis of REMD protein structure prediction simulations, that absolute quality metrics posses a high variance of efficiency (regarding quality terms) between different protein structure prediction simulations and that different filtering configurations composed of such quality metrics carry on this inconvenient variance.

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Les Récepteurs Couplés aux Protéines-G forment la plus importante famille de protéines membranaires chez l’homme et sont impliqués dans de nombreux processus de signalisation cellulaire. Aussi, ils forment un vivier très important de cibles thérapeutiques, déjà identifiées ou potentielles. L’activation d’un RCPG est amorcée par la liaison d’un ligand dans sa partie extra-cellulaire, modifiant ainsi ses propriétés dynamiques intrinsèques. Ces changements structuraux vont alors se répercuter le long des domaines trans-membranaires et promouvoir la dissociation de la Protéine-G hétéro-trimérique, de l’autre côté de la membrane, propageant ainsi le signal au compartiment intra-cellulaire. Ce processus peut être modulé par la liaison de nombreux autres partenaires des RCPGs. Malgré de nombreuses données structurales existantes, ces mécanismes restent encore mal connus à l’échelle moléculaire. Ainsi, la dynamique moléculaire s’est révélée être un outil formidable pour mieux comprendre ces mécanismes. Toutefois, les échelles de taille et de temps requises pour discuter de la dynamique de ces systèmes membranaires limitent ces études aux laboratoires ayant accès à une très grande puissance de calcul. L’objectif des travaux présentés dans ce manuscrit a été de prédire et de mieux comprendre la dynamique d’interaction de différents récepteurs de cette famille avec leurs partenaires, en développant un protocole de dynamique moléculaire, peu coûteux en ressources de calcul, combinant le champ de forces gros-grains MARTINI à un protocole de dynamique moléculaire « Replica-Exchange ».Dans un premier temps, nous présentons la validation de notre protocole pour la prédiction de la liaison de peptides à leur récepteur avec l’étude des peptides Neurotensine, agoniste du Récepteur de la Neurotensine-1, et CVX15, antagoniste du Récepteur Chemokine C-X-C de type-4. Nous montrons également que notre protocole est capable de prédire la sélectivité de plusieurs peptides dérivés de la Neurotensine envers plusieurs récepteurs sauvages et mutés, ne présentant qu’un résidu de différence.Dans un second temps, nous nous sommes intéressés à la dynamique de formation d’un hétéro-dimère de RCPGs impliquant le Récepteur de la Ghréline et le récepteur de la Dopamine D2, couplés aux protéines Gq et Gi respectivement. Ce modèle validé au laboratoire par des mesures LRET montre une interface impliquant une forte complémentarité entre les protéines-G. En se basant sur notre modèle, nous avons conçu et synthétisé des peptides inhibiteurs de la formation de cet hétéro-dimère de protéines-G.Enfin, nous présentons d’autres exemples d’applications de notre protocole et comment il peut être utilisé de concert avec l’expérience avec : la prédiction de la liaison de toxines de serpents aux Récepteurs de la Vasopressine-1a et V2 ; la prédiction de la liaison des peptides Ghréline et Leap2 au Récepteur GHSR-1a et la prédiction de la sélectivité de couplage de différents récepteurs aux peptides C-terminaux de la sous-unité α des protéines-G. / G-Protein Coupled Receptors form the largest family of human membrane proteins and are involved in many cellular signaling processes. Thus, they constitute a pool of already identified or potential pharmacological targets. The activation of a GPCR starts with the binding of a ligand in its extra-cellular part, further modifying its intrinsic dynamical properties. These structural rearrangements are then transmitted along the transmembrane domains and promote the dissociation of the G-protein on the other side of the bilayer, thus propagating the signal into the intra-cellular compartment. This activation process can be modulated by the binding of many other partners of GPCRs. Despite many structural data now available, these mechanisms are still badly known at the molecular scale. In agreement, molecular dynamics simulations appear to be a method of choice to get a better description of these mechanisms. Nevertheless, the size and the time scales required for the simulation of these membrane systems limit such studies to laboratories having access to large computational facilities.The objective of this work was to predict and get a dynamical view of the interactions of several GPCRs with their partners, by developing an affordable molecular dynamics protocol that combines the coarse-grained MARTINI force field to Replica-Exchange MD simulations.In a first step, we validated our protocol by showing its ability to predict the dynamical binding of peptides to their receptors, through the study of Neurotensin, an agonist of the Neurotensin-1 receptor and CVX15, an antagonist of the CXCR4 chemokine receptor. We also show that the same protocol is able to predict the selectivity of several Neurotensin derived peptides against several wild-type/mutated receptors differing by a single residue.In a second step, we were concerned by the dynamical assembly of a GPCR heterodimer involving the Ghrelin and the Dopamine D2 receptors, respectively coupled to Gq and Gi proteins. Our model was validated by LRET measurements confirming a large protein:protein interface and a high complementarity between G-proteins. Based on this model, we designed and synthesized some peptides able to inhibit the assembly of this G-proteins heterodimer.Finally, we describe other applications of our protocol and how it can be employed and confronted to experiments to : predict the dynamical binding of toxins from snake’s venom to the Vasopressin-1a and Vasopressin-2 receptors ; predict the binding of the Ghrelin and Leap2 peptides to their GHSR-1a receptor and predict the coupling selectivity of several receptors to peptides mimicking the C-terminus of the α subunit of G-proteins.

Pétrole et gaz proviennent de la décomposition de la matière organique dans la croûte terrestre. En s’enfouissant, les résidus organiques se décomposent en un solide poreux et carboné, appelé kérogène et en un fluide composé d’hydrocarbures et de petites molécules telles que de l’eau. Le processus de formation du kérogène n’est pas totalement élucidé et une modélisation aiderait à une meilleure compréhension à la fois de sa structure et de sa composition et serait utile à l’industrie pétrolière.Dans le présent travail, nous adoptons une approche thermodynamique ayant pour but, à l’aide de simulations numériques, de d’étudier la décomposition de précurseurs de kérogène d’un type donné –ici le type III- dans les conditions d’un réservoir géologique. La méthode dite de Replica Exchange Molecular Dynamics (REMD) est appliquée pour étudier la décomposition de cristaux de cellulose et de lignine. Le potentiel d’interaction ReaxFF et le code LAMMPS sont utilisés. La REMD est une façon de surmonter de larges barrières d’énergie libre, en améliorant l’échantillonnage de configurations d’une dynamique moléculaire conventionnelle à température constante, en utilisant des états générés à températures supérieures.En fin de simulation, les systèmes ont atteint un état d’équilibre entre deux phases : une phase riche en carbone, composée d’amas de macromolécules, que nous appelons « solide » et d’une phase riche en oxygène et en hydrogène, composée de petites molécules, que nous dénommons « fluide ». L’évolution des parties solides de nos systèmes coïncide avec celle d’échantillons naturels de kérogènes de type III. / In deep underground, organic residues decompose into a carbonaceous porous solid, called kerogen and a fluid usually composed of hydrocarbons and other small molecules such as water, carbon monoxide. The formation process of the kerogen remains poorly understood. Modeling its geological maturation could widen the understanding of both structure and composition of kerogen, and could be useful to oil and gas industry.In this work we adopt a purely thermodynamic approach in which we aim, through molecular simulations, at determining the thermodynamic equilibrium corresponding to the decomposition of given organic precursors of a specific type of kerogen –namely type III- under reservoir conditions. Starting from cellulose and lignin crystal structures we use replica exchange molecular dynamics (REMD) simulations, using the reactive force field ReaxFF and the open-source code LAMMPS. The REMD method is a way ofovercoming large free energy barriers, by enhancing the configurational sampling of a conventional constant temperature MD using states from higher temperatures.At the end of the simulations, we have reached for both systems, a stage where they can clearly be cast into two phases: a carbon-rich phase made of large molecular clusters that we call here the "solid" phase, and a oxygen and hydrogen rich phase made of small molecules that we call "fluid" phase.The evolution of solid parts for both systems and the natural evolution of a type III kerogen clearly match. Evolution of our systems follows the one of natural samples, as well as the one of a type III kerogen submitted to an experimental confined pyrolysis.