The overall objective of this thesis has been to develop accurate computational methods for the diffusion and adsorption of small gases in zeolites. Firstly, the effect of the zeolite framework flexiblity on the single component and binary diffusion of various gases were discussed. Results indicate that for tight fitting molecules the rigid framework approximation can produce order(s) of magnitude difference in diffusivities as compared to the simulations performed with a fully flexible framework. We proposed two simple methods in which the flexible structure of a zeolite is approximated as a set of discrete rigid snapshots. Both methods are orders of magnitude more efficient than the simulations with the fully flexible structure. Secondly, we use a combined classical and quantum chemistry based approach to systematically develop the force fields based on DFT calculations for interactions of simple molecules like CH4, N2, linear alkanes, and linear alkenes in zeolites. We used a higher level of theory known as the DFT/CC method to correct DFT energies that were used in the periodic DFT calculations to develop force fields. Our results show that DFT-derived force fields give good predictions of macroscopic properties like adsorption isotherms in zeolites. The force fields are transferrable across zeolites and hence can be further used to screen materials for different storage and separation applications.

We present results of molecular simulations, quantum mechanical calculations, and experimental data aimed towards the rational design of solvent formulations. In particular, we have found that the rate limitation of oxidation of methionine groups is determined by the breaking of O-O bonds in hydrogen peroxide, not by the rate of acidic catalysis as previously thought. We have used this understanding to design molecular level parameters which are correlated to experimental data. Rate data has been determined both for G-CSF and for hPTH(1-34). / Singapore-MIT Alliance (SMA)

Performing simulations of large-scale bio-molecular systems has long been one of the great challenges of molecular biophysics. Phenomena, such as the folding and conformational rearrangement of proteins, often takes place over the course milliseconds-to-seconds. The methods of traditional molecular dynamics used to simulate such systems are on the other hand typically limited to giving trajectories of nanosecond-to-microsecond duration. The failure of traditional methods has thus motivated the development of many special purpose techniques that propose to capture the essential characteristics of systems over conventionally inaccessible timescales. This dissertation first focuses on presenting a set of advances made on one such technique, Milestoning. Milestoning gives a statistical procedure for recovering long trajectories of the system based on observations of many short trajectories that start and end on hypersurfaces in the system’s phase space. Justification of the method’s validity typically relies on the assumption that trajectories of the system lose all memory between crossing successive milestones. We start by giving a modified milestoning procedure in which both the memory loss assumption is relaxed and reaction mechanisms are more easily extracted. We follow with numerical examples illustrating the success of new procedure. Then we show how milestoning may be used to compute an experimentally relevant timescale known as the transit time (also known as the reaction path time). Finally, we discuss how time reversal symmetry may be exploited to improve sampling of the trajectory fragments that connect milestones. After discussing milestoning, the dissertation shifts focus to a different way of approaching the problem of simulating long timescales. We consider two polymers models that are sufficiently simple to permit numerical integration of the desired long trajectories of the system. In some limiting cases, we see their simplicity even permits some questions about the dynamcis to be answered analytically. Using these models, we make a series of experimentally verifiable predictions about the dynamics of unfolded polymers. / text

No description available.

Establecer una cota global a las emisiones de gases de efecto invernadero ha sido imposibilitado por la complejidad que conlleva demostrar los efectos de la contribución humana al efecto invernadero. Para alcanzar un desarrollo sostenible es necesario, primero limitar y en lo posible eliminar las emisiones de dichos gases a la atmosfera. En este contexto, la adsorción de gases se ha establecido como una de las alternativas más efectivas a mediano plazo para la reducción de emisiones de gases de efecto invernadero. Por lo tanto, en esta tesis, el objetivo principal es estudiar a nivel molecular la adsorción de gases de efecto invernadero y comprender mejor la interacción entre las distintas variables que afectan el proceso de captura. En la primera parte de esta tesis se estudió, la separación de una mezcla de hexafluoruro de azufre (SF6) y nitrógeno (N2). El SF6 se emite en pequeñas cantidades, sin embargo por ser un potente gas de efecto invernadero con un tiempo de vida extremadamente alto se requiere un control estricto de sus emisiones. En este trabajo se estudió, empleando modelos simples, el efecto del tamaño de poro, la presión y la composición de la mezcla en la separación selectiva del SF6. Posteriormente, se realizaron simulaciones con modelos realistas de dos carbonos réplicas de zeolitas y se encontró que la selectividad predicha para el SF6 en dichos materiales es superior a la de los materiales previamente reportados en la literatura. En la segunda parte del trabajo se estudió el uso de estos materiales de carbono para la captura de dióxido de carbono (CO2) a temperatura ambiente, y se encontró que su capacidad de captura de CO2 a altas presiones es comparable a la de los mejores adsorbentes de CO2 reportados. Para comprender mejor la captura en los carbonos réplicas de zeolitas, se emplearon simulaciones moleculares para obtener información acerca de su compleja estructura interna y predecir las interacciones del CO2 con el interior de estos materiales. En la parte final de esta tesis se estudiaron materiales híbridos organo-inorgánicos, en particular, adsorbentes de sílica funcionalizados con grupos amino. Se desarrolló una nueva metodología de simulación para la generación de materiales de sílica funcionalizados con cadenas orgánicas y el cálculo de sus propiedades de adsorción. La metodología se evaluó empleando modelos de sílica gel y MCM-41 funcionalizados con diferentes cadenas orgánicas, comparando los resultados de las simulaciones de las isotermas de adsorción y la densidad de funcionalización con datos experimentales. Simultáneamente, se desarrolló un nuevo método que permite calcular adicionalmente a la fisisorción la quimisorción del CO2 en las aminas empleando simulaciones moleculares. En resumen, esta tesis de doctorado resalta diferentes posibilidades para la captura y separación de gases de efecto invernadero y proporciona nuevas herramientas de simulación para evaluar y optimizar sistemas de captura de gases. Esta tesis se enmarca dentro de la ciencia de materiales y muestra como la investigación básica en este campo puede ser usada como una herramienta para evaluar y optimizar procesos industriales. / The establishment of a global limit on the emissions of greenhouse gases has been hindered by the complexity to prove the effects of manmade greenhouse gases on a global scale. In order to achieve a sustainable development it is important to limit, and when possible eliminate, emissions of industrial greenhouse gases to the atmosphere. In this context, adsorption has been established as one of the best cost-effective means of reducing emissions of greenhouse gases in the short-term. Thus, in this thesis, the main objective is to study at a molecular level the adsorption of greenhouse gases and to obtain a better insight into the capture processes for their future optimization. Molecular simulations are used in order to find the optimal diameter for the separation of sulfur hexafluoride (SF6) from nitrogen (N2); this mixture is commonly used in electrical applications. SF6 is typically emitted in small quantities, but because it is a potent greenhouse gas and possesses extremely long lifetimes, there is a pressing need for a strict control of its emissions. The effect of pore size, pressure, and mixture compositions on the selective adsorption of SF6 was investigated using simple models. Subsequently, simulations using two atomistic models of zeolite templated carbons were performed. The separation selectivities compared favorably to the materials previously reported for the separation of this mixture. Moreover, the potential use of these two templated carbon materials to capture carbon dioxide (CO2) at room temperature is reported. Their high-pressure CO2 adsorption isotherms are among the highest carbon capture capacity for carbonaceous materials and are comparable to the best CO2 adsorbing materials. In addition, the simulated adsorption isotherms were used to obtain new insights into the adsorption process of the templated carbons. In the final part of the thesis hybrid organic-inorganic adsorbents were studied. For CO2 capture, solid adsorbents are functionalized with amino groups that largely increase their adsorption capabilities. However, the underlying mechanism of the adsorption process in the functionalized materials is not fully understood, limiting the possibility of designing optimal adsorbent materials for different applications. The adsorption of CO2 in aminefunctionalized silica materials was studied using Monte Carlo molecular simulations. A simulation methodology for the design of functionalized silica materials was proposed. The methodology was evaluated using models of silica gel and MCM-41 functionalized with different organic groups, comparing the resulting adsorption isotherms and grafting density to available experimental data. Furthermore, a new scheme that allows accounting for the chemisorbed CO2 on the adsorption isotherms is presented In summary, this PhD thesis highlights different possibilities for the capture and separation of greenhouse gases and provides new tools for evaluating and optimizing capture systems. Finally, this dissertation shows the use of basic research in Materials Science as an established tool for evaluating and optimizing thermodynamics of engineering processes.

Cytochrome c oxidase (CcO), the terminal enzyme in the electron transport chain, couples proton pumping to the reduction of dioxygen into water. The coupling mechanism remains to be elucidated. Previous studies have identified several mutations within CcO's primary proton uptake pathway (the D-channel) that decouple proton pumping from redox activity. Here, I examine the molecular basis for decoupling in single and double mutants of highly conserved residues, D132 and N139, in order to gain insight into the coupling mechanism. In particular, I use molecular dynamics and free energy simulations of a new, unconstrained model of bacterial CcO embedded in a solvated lipid bilayer to investigate how such mutants affect functional hydration and ionic selectivity in the D-channel. Results support earlier mechanistic insights obtained in our laboratory from simplified molecular models and predict a new, testable hypothesis by which cations such as K+ may inhibit proton pumping in charged mutants of N139.

Cytochrome c oxidase (CcO), the terminal enzyme in the electron transport chain, couples proton pumping to the reduction of dioxygen into water. The coupling mechanism remains to be elucidated. Previous studies have identified several mutations within CcO's primary proton uptake pathway (the D-channel) that decouple proton pumping from redox activity. Here, I examine the molecular basis for decoupling in single and double mutants of highly conserved residues, D132 and N139, in order to gain insight into the coupling mechanism. In particular, I use molecular dynamics and free energy simulations of a new, unconstrained model of bacterial CcO embedded in a solvated lipid bilayer to investigate how such mutants affect functional hydration and ionic selectivity in the D-channel. Results support earlier mechanistic insights obtained in our laboratory from simplified molecular models and predict a new, testable hypothesis by which cations such as K+ may inhibit proton pumping in charged mutants of N139.

L’acétylcholinestérase (AChE), une des enzymes les plus rapides dans la nature, est lacible d’un large nombre de toxiques, dont notamment les neurotoxiques organophosphorés.La première partie de ce manuscrit de thèse décrit le développement raisonné d’un nouveauréactivateur, qui présente des propriétés de réactivation supérieures aux moléculesactuellement sur le marché. Les interactions entre cette molécule, KM297, et l’AChE ontété étudiées par dynamique moléculaire, docking et cristallographie aux rayons X. La connaissancedes modes de liaison du KM297 dans l’AChE native ou inhibé par un OP ontpermis de développer la molécule JDS207, qui se lie de façon exclusive au site périphériquede l’AChE. La deuxième partie de la thèse est dédiée à l’analyse des simulations de laAChE par dynamique moléculaire. On observe que la combinaison de multiples trajectoiresgénérées avec des paramètres de vélocité initiale différents est une méthode fiablepour caractériser les conformations atteintes par les chaînes latérales des acides aminés. Encomparant la distribution des rotamères pour l’AChE humaine et celle du poisson Torpedocalifornica, on montre que des différences importantes existent entre les enzymes des deuxespèces. A partir de ces informations sur les conformations de résidus clés du site actif,une méthode a été développée pour générer des récepteurs utilisable pour des calcules dedocking flexible, de façon à prendre en compte la dynamique propre à chaque résidu del’enzyme. Cette méthode a été validé en comparent les résultats obtenues à des structurescristallographiques connues. / Acetylcholinesterase (AChE), one of nature fastest enzyme, is the target of multiple toxics,including organophosphate nerve agents (OP). In the first part of this thesis I present thestructure-based development of a new uncharged reactivator, which showed characteristicsbetter than any molecule commercially available to date. The molecule has been rationallydesigned to present both affinity to the inhibited enzyme and good reactivation capabilities.The interactions between the lead molecule KM297 and AChE has been characterizedby means of flexible docking, molecular dynamics simulations and X-ray protein crystallography.The deeper understanding of its binding modes to both native and OP-inhibitedAChE has helped in developing a derivative, JDS207, whose binding mode at the peripheralsite of AChE is optimized. This derivative has also been studied by flexible docking and Xraycrystallography. The design of this family of reactivators taught us that a deep insightof the AChE dynamics is necessary to optimize ligands. The second part of the thesis isdevoted to the analysis of molecular dynamics simulations of AChE. At first, we assessedthat combining multiple short simulations is a fast and reliable method to characterizethe dynamics of the amino-acids side-chains. By comparing dynamics of the side-chainsfrom hAChE and TcAChE, we confirm that some key dynamical differences exist betweenthe two enzyme. The knowledge of the rotamers issued of MD simulation has lead us todevelop a new method to generate flexible receptors for docking, which is specific to eachsingle residue in the enzyme. This method has been validated by comparing its outputstructures with the ones found on the PDB database.

Thanks to the advancement of the modern computer simulation systems, many scientific applications generate, and require manipulation of large volumes of data. Scientific exploration substantially relies on effective and accurate data analysis. The shear size of the generated data, however, imposes big challenges in the process of analyzing the system. In this dissertation we propose novel techniques as well as using some known designs in a novel way in order to improve scientific data analysis. We develop an efficient method to compute an analytical query called spatial distance histogram (SDH). Special heuristics are exploited to process SDH efficiently and accurately. We further develop a mathematical model to analyze the mechanism leading to errors. This gives rise to a new approximate algorithm with improved time/accuracy tradeoff. Known MS analysis systems follow a pull-based design, where the executed queries mandate the data needed on their part. Such a design introduces redundant and high I/O traffic as well as cpu/data latency. To remedy such issues, we design and implement a push-based system, which uses a sequential scan-based I/O framework that pushes the loaded data to a number of pre-programmed queries. The efficiency of the proposed system as well as the approximate SDH algorithms is backed by the results of extensive experiments on MS generated data.

Carbohydrate molecules are essential parts of living cells. They are used as energy storage and signal substances, and they can be found incorporated in the cell membranes as attachments to glycoproteins and glycolipids, but also as free molecules. In this thesis the effect of carbohydrate molecules on phospholipid model membranes have been investigated by the means of Molecular Dynamics (MD) computer simulations. The most abundant glycolipid in nature is the non-bilayer forming monogalactosyldiacylglycerol (MGDG). It is known to be important for the membrane stacking typical for the thylakoid membranes in plants, and has also been found essential for processes related to photosynthesis. In Paper I, MD simulations were used to characterize structural and dynamical changes in a lipid bilayer when MGDG is present. The simulations were validated by direct comparisons between dipolar couplings calculated from the MD trajectories, and those determined from NMR experiments on similar systems. We could show that most structural changes of the bilayer were a consequence of lipid packing and the molecular shape of MGDG. In certain plants and organisms, the enrichment of small sugars such as sucrose and trehalose close to the membrane interfaces, are known to be one of the strategies to survive freezing and dehydration. The cryoprotecting abilities of these sugar molecules are long known, but the mechanisms at the molecular level are still debated. In Papers II–IV, the interactions of trehalose with a lipid bilayer were investigated. Calculations of structural and dynamical properties, together with free energy calculations, were used to characterize the effect of trehalose on bilayer properties. We could show that the binding of trehalose to the lipid bilayer follows a simple two state binding model, in agreement with recent experimental investigations, and confirm some of the proposed hypotheses for membrane–sugar interactions. The simulations were validated by dipolar couplings from our NMR investigations of TRH in a dilute liquid crystal (bicelles). Furthermore, the assumption about molecular structure being equal in the ordered and isotropic phases was tested and verified. This assumption is central for the interpretation of experimentally determined dipolar couplings in weakly ordered systems. In addition, a coarse grain model was used to tackle some of the problems with slow dynamics that were encountered for trehalose in interaction with the bilayer. It was found that further developments of the interaction models are needed to properly describe the membrane–sugar interactions. Lastly, from investigations of trehalose curvature sensing, we concluded that it preferably interacts in bilayer regions with high negative curvature. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 4: Manuscript.</p>