Electrostatic interactions between charged species play a prominent role in determining structures and states of physical system, leading to important technological and biological applications. In coarse-grained simulations, accurate description of electrostatic interactions is crucial in addressing physical phenomena at larger spatial and longer temporal scales. In this thesis, we implement ENUF method, an abbreviation for Ewald summation based on non-uniform fast Fourier transform technique, into dissipative particle dynamics (DPD) scheme. With determined suitable parameters, the computational complexity of ENUF-DPD method is approximately described as O(N logN). The ENUF-DPD method is further validated by investigating dependence of polyelectrolyte conformations on charge fraction of polyelectrolyte and counterion valency of added salts, and studying of specific binding structures of dendrimers on amphiphilic membranes. In coarse-grained simulations, electrostatic interactions are either explicitly calculated with suitable methods, or implicitly included in effective potentials. The effect of treatment fashion of electrostatic interactions on phase behavior of [BMIM][PF6] ionic liquid (IL) is systematically investigated. Our systematic analyses show that electrostatic interactions should be incorporated explicitly in development of effective potentials, as well as in coarse-grained simulations to improve reliability of simulation results. Detailed image of microscopic structures and orientations of [BMIM][PF6] at graphene and vacuum interfaces are investigated by using atomistic simulations. Imidazolium rings and alkyl side chains of [BMIM] lie preferentially flat on graphene surface. At IL-vacuum interface, ionic groups pack closely together to form polar domains, leaving alkyl side chains populated at interface and imparting hydrophobic character. With the increase of IL filmthickness, orientations of [BMIM] change gradually from dominant flat distributions along graphene surface to orientations where imidazolium rings are either parallel or perpendicular to IL-vacuum interface with tilted angles. The interfacial spatial ionic structural heterogeneity formed by ionic groups also contributes to heterogeneous dynamics in interfacial regions.

Proteínas desempenham uma grande variedade de funções biológicas. O conhecimento da estrutura tridimensional proteica pode ajudar no entendimento da função desempenhada. De acordo com a hipótese de Anfisen, a estrutura terciária nativa de uma proteína pode ser determinada a partir da informação contida na sequência primária, o que permitiria que métodos computacionais poderiam ser usados para predizer estruturas terciárias quando a primária estiver disponível. No entanto, ainda não existe uma ferramenta computacional capaz de predizer a estrutura tridimensional para uma grande variedade de proteínas. Desse modo, o problema de Predição de Estruturas de Proteínas (PEP) permanece como um desafio para a Biologia Molecular. A conformação nativa de uma proteína é frequentemente a configuração termodinamicamente mais estável, ou seja, que possui menor energia livre. Assim, PEP pode ser vista como um problema de otimização, onde a estrutura com menor energia livre deve ser encontrada dentre todas as possíveis. Entretanto, este é um problema NP-completo, no qual métodos tradicionais de otimização, em geral, não apresentam um bom desempenho. Algoritmos Genéticos (AGs), devido às suas características, são interessantes para essa classe de problemas. O principal objetivo desse trabalho é verificar se a adição de informação pode ser útil aos AGs aplicados em PEP, valendo-se dede modelos moleculares simplificados. Cada indivíduo do AG representa uma solução que, neste caso, é uma possível conformação que será avaliada por um campo de força. Dessa forma, o indivíduo é codificado por um conjunto de ângulos de torção de cada aminoácido. Para auxiliar no processo de busca, bases de dados compostas de ângulos determinados por cristalografia e RNM são utilizadas. Com o objetivo de guiar o processo de busca e manter a diversidade nos AGs, duas estratégias são aqui testadas: Imigrantes Aleatórios e Imigrantes por Similaridade. A última delas foi criada baseando-se na similaridade da sequência primária. Além disso, é investigado neste trabalho o uso de um campo de força coarse grained, que utiliza os átomos de carbono- para representar a cadeia proteica, para avaliar os indivíduos do AG. / Proteins exhibit an enormous variety of biology functions. The knowledge of tertiary structures can help the understanding of the proteins function. According to Anfisen, the native tertiary structure of a protein can be determined by its primary structure information, what could allow that computational methods could be used to predict the tertiary structure when the primary structure is available. However, there is still not a computational tool to solve the structure prediction problem for a large range of proteins. In this way, Protein Structure Prediction (PSP) has been a challenge to Molecular Biology. The conformation of native protein is usually the thermodynamically most stable configuration, i.e., the one having the lowest free energy. Hence, PSP can be viewed as a problem of optimization, where the structure with the lowest free energy should be found among all possible structures. However, this is an NP-problem, where traditional optimization methods, in general, do not have good performance. Genetic algorithms (GAs), due to their characteristics, are interesting for this class of problems. In recent years, there is a growing interest in using GAs for the protein structure prediction problem. The main objective of this work is to verify the addition of useful information to GAs employed in PSP. Each individual of the GA represents a solution for the optimization problem which is, in this case, a possible conformation that will be evaluated by a force field function. Thus, an individual is encoded by a set of torsion angles of each amino acid. In order to reduce the search space, a database composed of angles, determined by crystallography and NMR, is used. With the aim to guide the final search process and maintain diversity in GAs, two strategies were employed here: Random Immigrants and Similarity-based Immigrants. The last strategy was based on similarity of primary amino acid sequence. Furthermore, in this work, a coarse-grained force field, which uses -carbon to represent the protein backbone was employed to evaluate the individuals of GA.

"Recently, hydrogel have found to be promising biomaterials since their porous structure and hydrophilicity enables them to absorb a large amount of water. In this study the role of water on the mechanical properties of hydrogel are studied using ab-initio molecular dynamics (MD) and coarse-grained simulations. Condensed-Phased Optimized Molecular Potential (COMPASS) and MARTINI force fields are used in the all-atom atomistic models and coarse-grained simulations, respectively. The crosslinking process is modeled using a novel approach by cyclic NPT and NVT simulations starting from a high temperature, cooling down to a lower temperature to model the curing process. Radial distribution functions for different water contents (20%, 40%, 60% and 80%) have shown the crosslinks atoms are more hydrophilic than the other atoms. Diffusion coefficients are quantified in different water contents and the effect of crosslinking density on the water diffusion is studied. Elasticity parameters are computed by constant strain energy minimization in mechanical deformation simulations. It is shown that an increase in the water content results in a decrease in the elastic. Finally, continuum hyper elastic model of contact lens is studied for three different loading scenarios using Finite Element Model. "

Molecular dynamics simulations of the liquid crystal phases of 2-(4-butyloxyphenyl)-5-octyloxypyrimidine (2PhP) and 5-(4-butyloxyphenyl)-2-octyloxy-pyrimidine (5PhP) are the focus of this thesis. The 2PhP and 5PhP mesogens display different liquid crystalline phase sequences, despite having very similar molecular structures. Specifically, both mesogens consist of aromatic phenyl and pyrimidine cores in between two flexible alkoxy tails, but they differ in the preferred core conformation. A multi-site coarse-grained model, in which the aromatic rings are represented by soft quadrupolar ellipsoids and the alkoxy chains are given a united atom representation, is proposed in this thesis. A parameterization route for the intra- and intermolecular potentials appropriate for liquid crystal simulations is developed. The ab initio based derivation of suitable molecular models for the two mesogens is discussed in detail, with particular emphasis on capturing proper phenyl-pyrimidine interactions which proved to be essential to correctly represent core-core interactions between neighboring molecules. A systematic determination of suitable Gay-Berne (GB) parameters has been adopted for the aromatic rings of 2PhP and 5PhP. To account for the pi-electron cloud below and above the ring plane, a quadrupole was added perpendicular to the ring. In the end, four parameterizations for aromatic rings have been selected for the simulations. Model characterization via pair interactions proved to be valuable in identifying and analyzing the short range structure in the phases. Extensive molecular dynamics simulations of these fluids at various temperatures are performed. Intermolecular structure and order, in aromatic core and the flexible tail regions, are analyzed. Intermolecular structure is divided into contributions parallel and perpendicular to the layers, as indicated by a layer normal or by a director, to differentiate smectic A (SmA) from smectic C (SmC). The presence of a ring quadrupole in the molecular model is shown to be essential to the correct reproduction of the experimentally observed phases. Simulations correctly indicate phases in agreement with experiment: SmC and SmA phases for 2PhP, and only a SmA phase for 5PhP. / Thesis (Ph.D, Chemistry) -- Queen's University, 2009-10-27 20:23:37.89

Proteínas desempenham uma grande variedade de funções biológicas. O conhecimento da estrutura tridimensional proteica pode ajudar no entendimento da função desempenhada. De acordo com a hipótese de Anfisen, a estrutura terciária nativa de uma proteína pode ser determinada a partir da informação contida na sequência primária, o que permitiria que métodos computacionais poderiam ser usados para predizer estruturas terciárias quando a primária estiver disponível. No entanto, ainda não existe uma ferramenta computacional capaz de predizer a estrutura tridimensional para uma grande variedade de proteínas. Desse modo, o problema de Predição de Estruturas de Proteínas (PEP) permanece como um desafio para a Biologia Molecular. A conformação nativa de uma proteína é frequentemente a configuração termodinamicamente mais estável, ou seja, que possui menor energia livre. Assim, PEP pode ser vista como um problema de otimização, onde a estrutura com menor energia livre deve ser encontrada dentre todas as possíveis. Entretanto, este é um problema NP-completo, no qual métodos tradicionais de otimização, em geral, não apresentam um bom desempenho. Algoritmos Genéticos (AGs), devido às suas características, são interessantes para essa classe de problemas. O principal objetivo desse trabalho é verificar se a adição de informação pode ser útil aos AGs aplicados em PEP, valendo-se dede modelos moleculares simplificados. Cada indivíduo do AG representa uma solução que, neste caso, é uma possível conformação que será avaliada por um campo de força. Dessa forma, o indivíduo é codificado por um conjunto de ângulos de torção de cada aminoácido. Para auxiliar no processo de busca, bases de dados compostas de ângulos determinados por cristalografia e RNM são utilizadas. Com o objetivo de guiar o processo de busca e manter a diversidade nos AGs, duas estratégias são aqui testadas: Imigrantes Aleatórios e Imigrantes por Similaridade. A última delas foi criada baseando-se na similaridade da sequência primária. Além disso, é investigado neste trabalho o uso de um campo de força coarse grained, que utiliza os átomos de carbono- para representar a cadeia proteica, para avaliar os indivíduos do AG. / Proteins exhibit an enormous variety of biology functions. The knowledge of tertiary structures can help the understanding of the proteins function. According to Anfisen, the native tertiary structure of a protein can be determined by its primary structure information, what could allow that computational methods could be used to predict the tertiary structure when the primary structure is available. However, there is still not a computational tool to solve the structure prediction problem for a large range of proteins. In this way, Protein Structure Prediction (PSP) has been a challenge to Molecular Biology. The conformation of native protein is usually the thermodynamically most stable configuration, i.e., the one having the lowest free energy. Hence, PSP can be viewed as a problem of optimization, where the structure with the lowest free energy should be found among all possible structures. However, this is an NP-problem, where traditional optimization methods, in general, do not have good performance. Genetic algorithms (GAs), due to their characteristics, are interesting for this class of problems. In recent years, there is a growing interest in using GAs for the protein structure prediction problem. The main objective of this work is to verify the addition of useful information to GAs employed in PSP. Each individual of the GA represents a solution for the optimization problem which is, in this case, a possible conformation that will be evaluated by a force field function. Thus, an individual is encoded by a set of torsion angles of each amino acid. In order to reduce the search space, a database composed of angles, determined by crystallography and NMR, is used. With the aim to guide the final search process and maintain diversity in GAs, two strategies were employed here: Random Immigrants and Similarity-based Immigrants. The last strategy was based on similarity of primary amino acid sequence. Furthermore, in this work, a coarse-grained force field, which uses -carbon to represent the protein backbone was employed to evaluate the individuals of GA.

No description available.

No description available.

No description available.

Proteine spielen auf der zellulären Ebene eines Organismus eine fundamentale Rolle. Sie sind quasi die „Maschinen“ der Zelle. Ihre Bedeutung wird nicht zuletzt in ihrem Namen deutlich, welcher 1838 erstmals von J. Berzelius verwendet wurde und „das Erste“, „das Wichtigste“ bedeutet. Proteine sind aus Aminosäuren aufgebaute Moleküle. Unter physiologischen Bedingungen besitzen sie eine definierte dreidimensionale Gestalt, welche für ihre biologische Funktion bestimmend ist. Es wird heutzutage davon ausgegangen, dass diese dreidimensionale, stabile Struktur von Proteinen eindeutig durch die Abfolge der einzelnen Aminosäuren, der Sequenz, bestimmt ist. Diese Abfolge ist für jedes Protein in der Desoxyribonukleinsäure (DNS) gespeichert. Es ist allerdings eines der größten ungelösten Probleme der letzten Jahrzehnte, wie die Beziehung zwischen Sequenz und 3D-Struktur tatsächlich aussieht. Die Beantwortung dieser Fragestellung erfordert interdisziplinäre Ansätze aus Biologie, Informatik und Physik. In dieser Arbeit werden mit Hilfe von Methoden der theoretischen (Bio-) Physik einige der damit verbundenen Aspekte untersucht. Das Hauptaugenmerk liegt dabei auf Wechselwirkungen der einzelnen Aminosäuren eines Proteins untereinander, wofür in dieser Arbeit ein entsprechendes Energiemodell entwickelt wurde. Es werden Grundzustände sowie Energielandschaften untersucht und mit experimentellen Daten verglichen. Die Stärke der Wechselwirkung einzelner Aminosäuren erlaubt zusätzlich Aussagen über die Stabilität von Proteinen bezüglich mechanischer Kräfte. Die vorliegende Arbeit unterteilt sich wie folgt: Kapitel 2 dient der Einleitung und stellt Proteine und ihre Funktionen dar. Kapitel 3 stellt die Modellierung der Proteinstrukturen in zwei verschiedenen Modellen vor, welche in dieser Arbeit entwickelt wurden, um 3D-Strukturen von Proteinen zu beschreiben. Anschließend wird in Kapitel 4 ein Algorithmus zum Auffinden des exakten Energieminimums dargestellt. Kapitel 5 beschäftigt sich mit der Frage, wie eine geeignete diskrete Energiefunktion aus experimentellen Daten gewonnen werden kann. In Kapitel 6 werden erste Ergebnisse dieses Modells dargestellt. Der Frage, ob der experimentell bestimmte Zustand dem energetischen Grundzustand eines Proteins entspricht, wird in Kapitel 7 nachgegangen. Die beiden Kapitel 8 und 9 zeigen die Anwendung des Modells an zwei Proteinen, dem Tryptophan cage protein als dem kleinsten, stabilen Protein und Kinesin, einem Motorprotein, für welches 2007 aufschlussreiche Experimente zur mechanischen Stabilität durchgeführt wurden. Kapitel 10 bis 12 widmen sich Membranproteinen. Dabei beschäftigt sich Kapitel 10 mit der Vorhersage von stabilen Bereichen (sog. Entfaltungsbarrieren) unter externer Krafteinwirkung. Zu Beginn wird eine kurze Einleitung zu Membranproteinen gegeben. Im folgenden Kapitel 11 wird die Entfaltung mit Hilfe des Modells und Monte-Carlo-Techniken simuliert. Mit dem an Membranproteine angepassten Wechselwirkungsmodell ist es möglich, den Einfluss von Mutationen auch ohne explizite strukturelle Informationen vorherzusagen. Dieses Thema wird in Kapitel 12 diskutiert. Die Beziehung zwischen Primär- und Tertiärstruktur eines Proteins wird in Kapitel 13 behandelt. Es wird ein Ansatz skizziert, welcher in der Lage ist, Strukturbeziehungen zwischen Proteinen zu detektieren, die mit herkömmlichen Methoden der Bioinformatik nicht gefunden werden können. Die letzten beiden Kapitel schließlich geben eine Zusammenfassung bzw. einen Ausblick auf künftige Entwicklungen und Anwendungen des Modells.

Biological molecules are essential parts of organisms and participate in a variety of biological processes within cells. Understanding the relationship between sequence, structure, and function of biological molecules are of fundamental importance in life science and the health care industry. In this dissertation, a multi-scale approach was utilized to develop coarse-grained molecular models for protein and RNA simulations. By simplifying the atomistic representation of a biomolecular system, the coarse-grained approach enables the molecular dynamics simulations to reveal the biological processes, which occur on the time and length scales that are inaccessible to the all-atom models. For RNA, an "intermediate" coarse-grained model was proposed to provide both accuracy and efficiency for RNA 3D structure modeling and prediction. The overall potential parameters were derived based on structural statistics sampled from experimental structures. For protein, a general, transferable coarse-grain framework based on the Gay-Berne potential and electrostatic point multipole expansion was developed for polypeptide simulations. Next, an advanced atomistic model was developed to model electrostatic interaction with high resolution and incorporates electronic polarization effect that is ignored in conventional atomistic models. The last part of my thesis work involves applying all-atom molecular simulations to address important questions and problems in biophysics and structural biology. For example, the interaction between protein and miRNA, the recognition mechanism of antigen and antibody, and the structure dynamics of protein in mixed denaturants. / text