940 resultados para Molecular Simulation
Resumo:
The structure and dynamics of methane in hydrated potassium montmorillonite clay have been studied under conditions encountered in sedimentary basin and compared to those of hydrated sodium montmorillonite clay using computer simulation techniques. The simulated systems contain two molecular layers of water and followed gradients of 150 barkm-1 and 30 Kkm-1 up to a maximum burial depth of 6 km. Methane particle is coordinated to about 19 oxygen atoms, with 6 of these coming from the clay surface oxygen. Potassium ions tend to move away from the center towards the clay surface, in contrast to the behavior observed with the hydrated sodium form. The clay surface affinity for methane was found to be higher in the hydrated K-form. Methane diffusion in the two-layer hydrated K-montmorillonite increases from 0.39×10-9 m2s-1 at 280 K to 3.27×10-9 m2s-1 at 460 K compared to 0.36×10-9 m2s-1 at 280 K to 4.26×10-9 m2s-1 at 460 K in Na-montmorillonite hydrate. The distributions of the potassium ions were found to vary in the hydrates when compared to those of sodium form. Water molecules were also found to be very mobile in the potassium clay hydrates compared to sodium clay hydrates. © 2004 Elsevier Inc. All All rights reserved.
Resumo:
Two-dimensional 'Mercedes Benz' (MB) or BN2D water model (Naim, 1971) is implemented in Molecular Dynamics. It is known that the MB model can capture abnormal properties of real water (high heat capacity, minima of pressure and isothermal compressibility, negative thermal expansion coefficient) (Silverstein et al., 1998). In this work formulas for calculating the thermodynamic, structural and dynamic properties in microcanonical (NVE) and isothermal-isobaric (NPT) ensembles for the model from Molecular Dynamics simulation are derived and verified against known Monte Carlo results. The convergence of the thermodynamic properties and the system's numerical stability are investigated. The results qualitatively reproduce the peculiarities of real water making the model a visually convenient tool that also requires less computational resources, thus allowing simulations of large (hydrodynamic scale) molecular systems. We provide the open source code written in C/C++ for the BN2D water model implementation using Molecular Dynamics.
Resumo:
In this paper we propose a model of encoding data into DNA strands so that this data can be used in the simulation of a genetic algorithm based on molecular operations. DNA computing is an impressive computational model that needs algorithms to work properly and efficiently. The first problem when trying to apply an algorithm in DNA computing must be how to codify the data that the algorithm will use. In a genetic algorithm the first objective must be to codify the genes, which are the main data. A concrete encoding of the genes in a single DNA strand is presented and we discuss what this codification is suitable for. Previous work on DNA coding defined bond-free languages which several properties assuring the stability of any DNA word of such a language. We prove that a bond-free language is necessary but not sufficient to codify a gene giving the correct codification.
Resumo:
We consider the effects of salt (sodium iodide) on pristine carbon nanotube (CNT) dispersions in an organic solvent, N-methyl-2-pyrrolidone (NMP). We investigate the molecular-scale mechanisms of ion interactions with the nanotube surface and we show how the microscopic ion-surface interactions affect the stability of CNT dispersions in NMP. In our study we use a combination of fully atomistic Molecular Dynamics simulations of sodium and iodide ions at the CNT-NMP interface with direct experiments on the CNT dispersions. In the experiments we analyze the effects of salt on the stability of the dispersions by photoluminescence (PL) and optical absorption spectroscopy of the samples as well as by visual inspection. By fully atomistic Molecular Dynamics simulations we investigate the molecular-scale mechanisms of sodium and iodide ion interactions with the nanotube surface. Our simulations reveal that both ions are depleted from the CNT surface in the CNT-NMP dispersions mainly due to the two reasons: (1) there is a high energy penalty for the ion partial desolvation at the CNT surface; (2) NMP molecules form a dense solvation layer at the CNT surface that prevents ions to come close to the CNT surface. As a result, an increase of the salt concentration increases the "osmotic" stress in the CNT-NMP system and, thus, decreases the stability of the CNT dispersions in NMP. Direct experiments confirm the simulation results: addition of NaI salt into the NMP dispersions of pristine CNTs leads to precipitation of CNTs (bundle formation) even at very small salt concentration (∼10 -3 mol L -1). In line with the simulation predictions, the effect increases with the increase of the salt concentration. Overall, our results show that dissolved salt ions have strong effects on the stability of CNT dispersions. Therefore, it is possible to stimulate the bundle formation in the CNT-NMP dispersions and regulate the overall concentration of nanotubes in the dispersions by changing the NaI concentration in the solvent. © 2012 The Royal Society of Chemistry.
Resumo:
Hydrogen bonds play important roles in maintaining the structure of proteins and in the formation of most biomolecular protein-ligand complexes. All amino acids can act as hydrogen bond donors and acceptors. Among amino acids, Histidine is unique, as it can exist in neutral or positively charged forms within the physiological pH range of 5.0 to 7.0. Histidine can thus interact with other aromatic residues as well as forming hydrogen bonds with polar and charged residues. The ability of His to exchange a proton lies at the heart of many important functional biomolecular interactions, including immunological ones. By using molecular docking and molecular dynamics simulation, we examine the influence of His protonation/deprotonation on peptide binding affinity to MHC class II proteins from locus HLA-DP. Peptide-MHC interaction underlies the adaptive cellular immune response, upon which the next generation of commercially-important vaccines will depend. Consistent with experiment, we find that peptides containing protonated His residues bind better to HLA-DP proteins than those with unprotonated His. Enhanced binding at pH 5.0 is due, in part, to additional hydrogen bonds formed between peptide His+ and DP proteins. In acidic endosomes, protein His79β is predominantly protonated. As a result, the peptide binding cleft narrows in the vicinity of His79β, which stabilizes the peptide - HLA-DP protein complex. © 2014 Bentham Science Publishers.
Resumo:
A new 3D implementation of a hybrid model based on the analogy with two-phase hydrodynamics has been developed for the simulation of liquids at microscale. The idea of the method is to smoothly combine the atomistic description in the molecular dynamics zone with the Landau-Lifshitz fluctuating hydrodynamics representation in the rest of the system in the framework of macroscopic conservation laws through the use of a single "zoom-in" user-defined function s that has the meaning of a partial concentration in the two-phase analogy model. In comparison with our previous works, the implementation has been extended to full 3D simulations for a range of atomistic models in GROMACS from argon to water in equilibrium conditions with a constant or a spatially variable function s. Preliminary results of simulating the diffusion of a small peptide in water are also reported.
Resumo:
Chloroperoxidase (CPO), a 298-residue glycosylated protein from the fungus Caldariomyces fumago, is probably the most versatile heme enzyme yet discovered. Interest in CPO as a catalyst is based on its power to produce enantiomerically enriched products. Recent research has focused its attention on the ability of CPO to epoxidize alkenes in high regioselectivity and enantioselectivity as an efficient and environmentally benign alternative to traditional synthetic routes. There has been little work on the nature of ligand binding, which probably controls the regio- and enantiospecifity of CPO. Consequently it is here that we focus our work. We report docking calculations and computer simulations aimed at predicting the enantiospecificity of CPO-catalyzed epoxidation of three model substrates. On the basis of this work candidate mutations to improve the efficiency of CPO are predicted. In order to accomplish these aims, a simulated annealing and molecular dynamics protocol is developed to sample potentially reactive substrate/CPO complexes.
Resumo:
The heavy part of the oil can be used for numerous purposes, e.g. to obtain lubricating oils. In this context, many researchers have been studying alternatives such separation of crude oil components, among which may be mentioned molecular distillation. Molecular distillation is a forced evaporation technique different from other conventional processes in the literature. This process can be classified as a special distillation case under high vacuum with pressures that reach extremely low ranges of the order of 0.1 Pascal. The evaporation and condensation surfaces must have a distance from each other of the magnitude order of mean free path of the evaporated molecules, that is, molecules evaporated easily reach the condenser, because they find a route without obstacles, what is desirable. Thus, the main contribution of this work is the simulation of the falling-film molecular distillation for crude oil mixtures. The crude oil was characterized using UniSim® Design and R430 Aspen HYSYS® V8.5. The results of this characterization were performed in spreadsheets of Microsoft® Excel®, calculations of the physicochemical properties of the waste of an oil sample, i.e., thermodynamic and transport. Based on this estimated properties and boundary conditions suggested by the literature, equations of temperature and concentration profiles were resolved through the implicit finite difference method using the programming language Visual Basic® (VBA) for Excel®. The result of the temperature profile showed consistent with the reproduced by literature, having in their initial values a slight distortion as a result of the nature of the studied oil is lighter than the literature, since the results of the concentration profiles were effective allowing realize that the concentration of the more volatile decreases and of the less volatile increases due to the length of the evaporator. According to the transport phenomena present in the process, the velocity profile tends to increase to a peak and then decreases, and the film thickness decreases, both as a function of the evaporator length. It is concluded that the simulation code in Visual Basic® language (VBA) is a final product of the work that allows application to molecular distillation of petroleum and other similar mixtures.
Resumo:
Vegetable oils are characterized as important raw materials in the supplying of natural substances of interest pharmaceutical, food and cosmetic industry. Sunflower oil stands out for its important composition present in unsaturated fatty acids such as oleic acid (C18:1) and linoleic (C18:2), responsible for many health benefits. The main objective of this study is obtain enriched fractions in unsaturated compounds from refined sunflower oil. The oil used in this study was characterized by the determination of some properties, like iodine number, acid number and viscosity. A transesterification was done to transform the triglycerides into their corresponding methyl esters of fatty acids. These was submitted the molecular distillation process, for present as an efficient alternative to separation and purification of these substances, using high vacuum and low temperatures. Of the esters fractions that was obtained, were analyzed by gas chromatography. The experimental design technique was used to evaluate the influence of the temperature variation of evaporation and condensation system on the percentage obtained residue. The evaporator temperature proved to be the most influential variable on the studied response. The optimized conditions for the answer was studied at 100 °C for evaporator temperature and 10 °C for the condenser temperature. The graph of "split ratio" showed that for the lowest flow feed (1 mL/min) and higher evaporator temperature (110 °C) was obtained in the largest fraction of distillate. It also used the study of the influence of evaporator temperature on the concentration of unsaturated compounds. The best operating conditions for temperature was 90 °C reached 82.21 % of unsaturated compounds. Elimination curves of the unsaturated compounds present in the distillate stream were obtained. The simulation results of the molecular distillation process of sunflower oil showed the concentration profiles for three different feed flow rates. The speed, temperature and thickness profiles of the liquid film were obtained. The speed of the film increases as the fluid flows through the walls of the evaporator, reaching a maximum on length of 0.075 m. The film thickness decreases on the route, since many compounds are volatilized. The result of the temperature profile had to be consistent with the literature reproduced, being constant after reaching the maximum operating temperature in the length of 0.15 m. This study allowed characterizing and focusing, through experimental analysis, unsaturated compounds and observing the sunflower oil´s behavior through process simulation.
Resumo:
Vegetable oils are characterized as important raw materials in the supplying of natural substances of interest pharmaceutical, food and cosmetic industry. Sunflower oil stands out for its important composition present in unsaturated fatty acids such as oleic acid (C18:1) and linoleic (C18:2), responsible for many health benefits. The main objective of this study is obtain enriched fractions in unsaturated compounds from refined sunflower oil. The oil used in this study was characterized by the determination of some properties, like iodine number, acid number and viscosity. A transesterification was done to transform the triglycerides into their corresponding methyl esters of fatty acids. These was submitted the molecular distillation process, for present as an efficient alternative to separation and purification of these substances, using high vacuum and low temperatures. Of the esters fractions that was obtained, were analyzed by gas chromatography. The experimental design technique was used to evaluate the influence of the temperature variation of evaporation and condensation system on the percentage obtained residue. The evaporator temperature proved to be the most influential variable on the studied response. The optimized conditions for the answer was studied at 100 °C for evaporator temperature and 10 °C for the condenser temperature. The graph of "split ratio" showed that for the lowest flow feed (1 mL/min) and higher evaporator temperature (110 °C) was obtained in the largest fraction of distillate. It also used the study of the influence of evaporator temperature on the concentration of unsaturated compounds. The best operating conditions for temperature was 90 °C reached 82.21 % of unsaturated compounds. Elimination curves of the unsaturated compounds present in the distillate stream were obtained. The simulation results of the molecular distillation process of sunflower oil showed the concentration profiles for three different feed flow rates. The speed, temperature and thickness profiles of the liquid film were obtained. The speed of the film increases as the fluid flows through the walls of the evaporator, reaching a maximum on length of 0.075 m. The film thickness decreases on the route, since many compounds are volatilized. The result of the temperature profile had to be consistent with the literature reproduced, being constant after reaching the maximum operating temperature in the length of 0.15 m. This study allowed characterizing and focusing, through experimental analysis, unsaturated compounds and observing the sunflower oil´s behavior through process simulation.
Resumo:
In this study, our goal was develop and describe a molecular model of the enzyme-inhibiting interaction which can be used for an optimized projection of a Microscope Force Atomic nanobiosensor to detect pesticides molecules, used in agriculture, to evaluate its accordance with limit levels stipulated in valid legislation for its use. The studied herbicide (imazaquin) is a typical member of imidazolinone family and is an inhibitor of the enzymatic activity of Acetohydroxiacid Synthase (AHAS) enzyme that is responsible for the first step of pathway for the synthesis of side-chains in amino acids. The analysis of this enzyme property in the presence of its cofactors was made to obtain structural information and charge distribution of the molecular surface to evaluate its capacity of became immobilized on the Microscopy Atomic Force tip. The computational simulation of the system, using Molecular Dynamics, was possible with the force-field parameters for the cofactor and the herbicides obtained by the online tool SwissParam and it was implemented in force-field CHARMM27, used by software GROMACS; then appropriated simulations were made to validate the new parameters. The molecular orientation of the AHAS was defined based on electrostatic map and the availability of the herbicide in the active site. Steered Molecular Dynamics (SMD) Simulations, followed by quantum mechanics calculations for more representative frames, according to the sequential QM/MM methodology, in a specific direction of extraction of the herbicide from the active site. Therefore, external harmonic forces were applied with similar force constants of AFM cantilever for to simulate herbicide detection experiments by the proposed nanobiosensor. Force value of 1391 pN and binding energy of -14048.52 kJ mol-1 were calculated.
Resumo:
Proteins are specialized molecules that catalyze most of the reactions that can sustain life, and they become functional by folding into a specific 3D structure. Despite their importance, the question, "how do proteins fold?" - first pondered in in the 1930's - is still listed as one of the top unanswered scientific questions as of 2005, according to the journal Science. Answering this question would provide a foundation for understanding protein function and would enable improved drug targeting, efficient biofuel production, and stronger biomaterials. Much of what we currently know about protein folding comes from studies on small, single-domain proteins, which may be quite different from the folding of large, multidomain proteins that predominate the proteomes of all organisms.
In this thesis I will discuss my work to fill this gap in understanding by studying the unfolding and refolding of large, multidomain proteins using the powerful combination of single-molecule force-spectroscopy experiments and molecular dynamic simulations.
The three model proteins studied - Luciferase, Protein S, and Streptavidin - lend insight into the inter-domain dependence for unfolding and the subdomain stabilization of binding ligands, and ultimately provide new insight into atomistic details of the intermediate states along the folding pathway.
Resumo:
A RET network consists of a network of photo-active molecules called chromophores that can participate in inter-molecular energy transfer called resonance energy transfer (RET). RET networks are used in a variety of applications including cryptographic devices, storage systems, light harvesting complexes, biological sensors, and molecular rulers. In this dissertation, we focus on creating a RET device called closed-diffusive exciton valve (C-DEV) in which the input to output transfer function is controlled by an external energy source, similar to a semiconductor transistor like the MOSFET. Due to their biocompatibility, molecular devices like the C-DEVs can be used to introduce computing power in biological, organic, and aqueous environments such as living cells. Furthermore, the underlying physics in RET devices are stochastic in nature, making them suitable for stochastic computing in which true random distribution generation is critical.
In order to determine a valid configuration of chromophores for the C-DEV, we developed a systematic process based on user-guided design space pruning techniques and built-in simulation tools. We show that our C-DEV is 15x better than C-DEVs designed using ad hoc methods that rely on limited data from prior experiments. We also show ways in which the C-DEV can be improved further and how different varieties of C-DEVs can be combined to form more complex logic circuits. Moreover, the systematic design process can be used to search for valid chromophore network configurations for a variety of RET applications.
We also describe a feasibility study for a technique used to control the orientation of chromophores attached to DNA. Being able to control the orientation can expand the design space for RET networks because it provides another parameter to tune their collective behavior. While results showed limited control over orientation, the analysis required the development of a mathematical model that can be used to determine the distribution of dipoles in a given sample of chromophore constructs. The model can be used to evaluate the feasibility of other potential orientation control techniques.
Resumo:
The protein folding problem has been one of the most challenging subjects in biological physics due to its complexity. Energy landscape theory based on statistical mechanics provides a thermodynamic interpretation of the protein folding process. We have been working to answer fundamental questions about protein-protein and protein-water interactions, which are very important for describing the energy landscape surface of proteins correctly. At first, we present a new method for computing protein-protein interaction potentials of solvated proteins directly from SAXS data. An ensemble of proteins was modeled by Metropolis Monte Carlo and Molecular Dynamics simulations, and the global X-ray scattering of the whole model ensemble was computed at each snapshot of the simulation. The interaction potential model was optimized and iterated by a Levenberg-Marquardt algorithm. Secondly, we report that terahertz spectroscopy directly probes hydration dynamics around proteins and determines the size of the dynamical hydration shell. We also present the sequence and pH-dependence of the hydration shell and the effect of the hydrophobicity. On the other hand, kinetic terahertz absorption (KITA) spectroscopy is introduced to study the refolding kinetics of ubiquitin and its mutants. KITA results are compared to small angle X-ray scattering, tryptophan fluorescence, and circular dichroism results. We propose that KITA monitors the rearrangement of hydrogen bonding during secondary structure formation. Finally, we present development of the automated single molecule operating system (ASMOS) for a high throughput single molecule detector, which levitates a single protein molecule in a 10 µm diameter droplet by the laser guidance. I also have performed supporting calculations and simulations with my own program codes.
A new age of fuel performance code criteria studied through advanced atomistic simulation techniques
Resumo:
A fundamental step in understanding the effects of irradiation on metallic uranium and uranium dioxide ceramic fuels, or any material, must start with the nature of radiation damage on the atomic level. The atomic damage displacement results in a multitude of defects that influence the fuel performance. Nuclear reactions are coupled, in that changing one variable will alter others through feedback. In the field of fuel performance modeling, these difficulties are addressed through the use of empirical models rather than models based on first principles. Empirical models can be used as a predictive code through the careful manipulation of input variables for the limited circumstances that are closely tied to the data used to create the model. While empirical models are efficient and give acceptable results, these results are only applicable within the range of the existing data. This narrow window prevents modeling changes in operating conditions that would invalidate the model as the new operating conditions would not be within the calibration data set. This work is part of a larger effort to correct for this modeling deficiency. Uranium dioxide and metallic uranium fuels are analyzed through a kinetic Monte Carlo code (kMC) as part of an overall effort to generate a stochastic and predictive fuel code. The kMC investigations include sensitivity analysis of point defect concentrations, thermal gradients implemented through a temperature variation mesh-grid, and migration energy values. In this work, fission damage is primarily represented through defects on the oxygen anion sublattice. Results were also compared between the various models. Past studies of kMC point defect migration have not adequately addressed non-standard migration events such as clustering and dissociation of vacancies. As such, the General Utility Lattice Program (GULP) code was utilized to generate new migration energies so that additional non-migration events could be included into kMC code in the future for more comprehensive studies. Defect energies were calculated to generate barrier heights for single vacancy migration, clustering and dissociation of two vacancies, and vacancy migration while under the influence of both an additional oxygen and uranium vacancy.