989 resultados para ENERGY LANDSCAPE


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Recent optical kerr effect (OKE) studies have demonstrated that orientational relaxation of rod-like nematogens exhibits temporal power law decay at intermediate times not only near the isotropic–nematic (I–N) phase boundary but also in the nematic phase. Such behaviour has drawn an intriguing analogy with supercooled liquids. We have investigated both collective and single-particle orientational dynamics of a family of model system of thermotropic liquid crystals using extensive computer simulations. Several remarkable features of glassy dynamics are on display including non-exponential relaxation, dynamical heterogeneity, and non-Arrhenius temperature dependence of the orientational relaxation time. Over a temperature range near the I–N phase boundary, the system behaves remarkably like a fragile glass-forming liquid. Using proper scaling, we construct the usual relaxation time versus inverse temperature plot and explicitly demonstrate that one can successfully define a density dependent fragility of liquid crystals. The fragility of liquid crystals shows a temperature and density dependence which is remarkably similar to the fragility of glass forming supercooled liquids. Energy landscape analysis of inherent structures shows that the breakdown of the Arrhenius temperature dependence of relaxation rate occurs at a temperature that marks the onset of the growth of the depth of the potential energy minima explored by the system. A model liquid crystal, consisting of disk-like molecules, has also been investigated in molecular dynamics simulations for orientational relaxation along two isobars starting from the high temperature isotropic phase. The isobars have been so chosen that the phase sequence isotropic (I)–nematic (N)–columnar (C) appears upon cooling along one of them and the sequence isotropic (I)–columnar(C) along the other. While the orientational relaxation in the isotropic phase near the I–N phase transition shows a power law decay at short to intermediate times, such power law relaxation is not observed in the isotropic phase near the I–C phase boundary. The origin of the power law decay in the single-particle second-rank orientational time correlation function (OTCF) is traced to the growth of the orientational pair distribution functions near the I–N phase boundary. As the system settles into the nematic phase, the decay of the single-particle second-rank orientational OTCF follows a pattern that is similar to what is observed with calamitic liquid crystals and supercooled molecular liquids.

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We report spontaneous translocation of small interfering RNA (siRNA) inside carbon nanotubes (CNTs) of various diameters and chirality using all atom molecular dynamics simulations with explicit solvent. We use umbrella sampling method to calculate the free energy landscape of the siRNA entry and translocation event. Free energy profiles show that siRNA gains free energy while translocating inside CNT, and barrier for siRNA exit from CNT ranges from 40 to 110 kcal/mol depending on CNT chirality and salt concentration. The translocation time tau decreases with the increase of CNT diameter with a critical diameter of 24 angstrom for the translocation. In contrast, double strand DNA of the same sequence does not translocate inside CNT due to large free energy barrier for the translocation. This study helps in understanding the nucleic acid transport through nanopores at microscopic level and may help designing carbon nanotube based sensor for siRNA. (C) 2013 American Institute of Physics. http://dx.doi.org/10.1063/1.4773302]

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As the beneficial effects of curcumin have often been reported to be limited to its small concentrations, we have undertaken a study to find the aggregation properties of curcumin in water by varying the number of monomers. Our molecular dynamics simulation results show that the equilibrated structure is always an aggregated state with remarkable structural rearrangements as we vary the number of curcumin monomers from 4 to 16 monomers. We find that the curcumin monomers form clusters in a very definite pattern where they tend to aggregate both in parallel and anti-parallel orientation of the phenyl rings, often seen in the formation of beta-sheet in proteins. A considerable enhancement in the population of parallel alignments is observed with increasing the system size from 12 to 16 curcumin monomers. Due to the prevalence of such parallel alignment for large system size, a more closely packed cluster is formed with maximum number of hydrophobic contacts. We also follow the pathway of cluster growth, in particular the transition from the initial segregated to the final aggregated state. We find the existence of a metastable structural intermediate involving a number of intermediate-sized clusters dispersed in the solution. We have constructed a free energy landscape of aggregation where the metatsable state has been identified. The course of aggregation bears similarity to nucleation and growth in highly metastable state. The final aggregated form remains stable with the total exclusion of water from its sequestered hydrophobic core. We also investigate water structure near the cluster surface along with their orientation. We find that water molecules form a distorted tetrahedral geometry in the 1st solvation layer of the cluster, interacting rather strongly with the hydrophilic groups at the surface of the curcumin. The dynamics of such quasi-bound water molecules near the surface of curcumin cluster is considerably slower than the bulk signifying a restricted motion as often found in protein hydration layer. (C) 2014 AIP Publishing LLC.

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We explore the potential energy landscape of structure breaking binary mixtures (SBBM) where two constituents dislike each other, yet remain macroscopically homogeneous at intermediate to high temperatures. Interestingly, we find that the origin of strong composition dependent non-ideal behaviour lies in its phase separated inherent structure. The inherent structure (IS) of SBBM exhibits bi-continuous phase as is usually formed during spinodal decomposition. We draw analogy of this correlation between non-ideality and phase separation in IS to explain observation of non-ideality in real aqueous mixtures of small amphiphilic solutes, containing both hydrophilic and hydrophobic groups. Although we have not been able to obtain IS of these liquids, we find that even at room temperature these liquids sustain formation of fluctuating, transient bi-continuous phase, with limited lifetime (tau less than or similar to 20 ps). While in the model (A, B) binary mixture, the non-ideal composition dependence can be considered as a fluctuation from a phase separated state, a similar scenario is expected to be responsible for the unusually strong non-ideality in these aqueous binary mixtures.

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The tripeptide glutathione (GSH) is one of the most abundant peptides and the major repository for nonprotein sulfur in both animal and plant cells. It plays a critical role in intracellular oxidative stress management by the reversible formation of glutathione disulfide with the thiol-disulfide pair acting as a redox buffer. The state of charge of the ionizable groups of GSH can influence the redox couple, and hence the pK(a) value of the cysteine residue of GSH is critical to its functioning. Here we report ab initio Car-Parrinello molecular dynamics simulations of glutathione solvated by 200 water molecules, all of which are considered in the simulation. We show that the free-energy landscape for the protonation-deprotonation reaction of the cysteine residue of GSH computed using metadynamics sampling provides shift in the dissociation constant values as compared with the isolated accurate estimates of the pK(a) and correctly predicts the cysteine amino acid.

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The propensity of protein molecules to self-assemble into highly ordered, fibrillar aggregates lies at the heart of understanding many disorders ranging from Alzheimer's disease to systemic lysozyme amyloidosis. In this paper we use highly accurate kinetic measurements of amyloid fibril growth in combination with spectroscopic tools to quantify the effect of modifications in solution conditions and in the amino acid sequence of human lysozyme on its propensity to form amyloid fibrils under acidic conditions. We elucidate and quantify the correlation between the rate of amyloid growth and the population of nonnative states, and we show that changes in amyloidogenicity are almost entirely due to alterations in the stability of the native state, while other regions of the global free-energy surface remain largely unmodified. These results provide insight into the complex dynamics of a macromolecule on a multidimensional energy landscape and point the way for a better understanding of amyloid diseases.

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Nanoindentation simulations on a binary metallic glass were performed under various strain rates by using molecular dynamics. The rate-dependent serrated plastic flow was clearly observed, and the spatiotemporal behavior of its underlying irreversible atomic rearrangement was probed. Our findings clearly validate that the serration is a temporally inhomogeneous characteristic of such rearrangements and not directly dependent on the resultant shear-banding spatiality. The unique spatiotemporal distribution of shear banding during nanoindentation is highlighted in terms of the potential energy landscape (PEL) theory.

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A systematic study on the available data of 26 metallic glasses shows that there is an intrinsic correlation between fragility of a liquid and bulk modulus of its glass. The underlying physics can be rationalized within the formalism of potential energy landscape thermodynamics. It is surprising to find that the linear correlation between the fragility and the bulk-shear modulus ratio exists strictly at either absolute zero temperature or very high frequency. Further analyses indicate that a real flow event in bulk metallic glasses is shear dominant, and fragility is in inverse proportion to shear-induced bulk dilatation. Finally, extension of these findings to nonmetallic glasses is discussed.

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Protein structure prediction has remained a major challenge in structural biology for more than half a century. Accelerated and cost efficient sequencing technologies have allowed researchers to sequence new organisms and discover new protein sequences. Novel protein structure prediction technologies will allow researchers to study the structure of proteins and to determine their roles in the underlying biology processes and develop novel therapeutics.

Difficulty of the problem stems from two folds: (a) describing the energy landscape that corresponds to the protein structure, commonly referred to as force field problem; and (b) sampling of the energy landscape, trying to find the lowest energy configuration that is hypothesized to be the native state of the structure in solution. The two problems are interweaved and they have to be solved simultaneously. This thesis is composed of three major contributions. In the first chapter we describe a novel high-resolution protein structure refinement algorithm called GRID. In the second chapter we present REMCGRID, an algorithm for generation of low energy decoy sets. In the third chapter, we present a machine learning approach to ranking decoys by incorporating coarse-grain features of protein structures.

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Over the last century, the silicon revolution has enabled us to build faster, smaller and more sophisticated computers. Today, these computers control phones, cars, satellites, assembly lines, and other electromechanical devices. Just as electrical wiring controls electromechanical devices, living organisms employ "chemical wiring" to make decisions about their environment and control physical processes. Currently, the big difference between these two substrates is that while we have the abstractions, design principles, verification and fabrication techniques in place for programming with silicon, we have no comparable understanding or expertise for programming chemistry.

In this thesis we take a small step towards the goal of learning how to systematically engineer prescribed non-equilibrium dynamical behaviors in chemical systems. We use the formalism of chemical reaction networks (CRNs), combined with mass-action kinetics, as our programming language for specifying dynamical behaviors. Leveraging the tools of nucleic acid nanotechnology (introduced in Chapter 1), we employ synthetic DNA molecules as our molecular architecture and toehold-mediated DNA strand displacement as our reaction primitive.

Abstraction, modular design and systematic fabrication can work only with well-understood and quantitatively characterized tools. Therefore, we embark on a detailed study of the "device physics" of DNA strand displacement (Chapter 2). We present a unified view of strand displacement biophysics and kinetics by studying the process at multiple levels of detail, using an intuitive model of a random walk on a 1-dimensional energy landscape, a secondary structure kinetics model with single base-pair steps, and a coarse-grained molecular model that incorporates three-dimensional geometric and steric effects. Further, we experimentally investigate the thermodynamics of three-way branch migration. Our findings are consistent with previously measured or inferred rates for hybridization, fraying, and branch migration, and provide a biophysical explanation of strand displacement kinetics. Our work paves the way for accurate modeling of strand displacement cascades, which would facilitate the simulation and construction of more complex molecular systems.

In Chapters 3 and 4, we identify and overcome the crucial experimental challenges involved in using our general DNA-based technology for engineering dynamical behaviors in the test tube. In this process, we identify important design rules that inform our choice of molecular motifs and our algorithms for designing and verifying DNA sequences for our molecular implementation. We also develop flexible molecular strategies for "tuning" our reaction rates and stoichiometries in order to compensate for unavoidable non-idealities in the molecular implementation, such as imperfectly synthesized molecules and spurious "leak" pathways that compete with desired pathways.

We successfully implement three distinct autocatalytic reactions, which we then combine into a de novo chemical oscillator. Unlike biological networks, which use sophisticated evolved molecules (like proteins) to realize such behavior, our test tube realization is the first to demonstrate that Watson-Crick base pairing interactions alone suffice for oscillatory dynamics. Since our design pipeline is general and applicable to any CRN, our experimental demonstration of a de novo chemical oscillator could enable the systematic construction of CRNs with other dynamic behaviors.

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Considerando-se este importante momento de transição em que as tradicionais matrizes energéticas são paulatinamente substituídas por um conjunto de fontes renováveis, das quais os biocombustíves sobressaem-se pela capacidade de contribuir para o meio ambiente, trazendo igualmente benefícios econômicos e sociais a seus produtores; o presente trabalho visa contribuir para o panorama energético global que se começa a se delinear. Diante da impotência do Estado em lidar hodiernamente com determinadas questões, testemunha-se a participação de atores privados (organizações não governamentais, empresas transnacionais e sociedade civil, entre outros) atuando como vetores na transmissão de compromissos internacionais junto a estruturas nacionais para a solução de problemas comuns da humanidade. A essa nova arquitetura jurídica e política convencionou-se designar de governança global. Diante da inexistência de uma governança energética global que opere no interesse de países importadores, exportadores e investidores do setor de energia, agindo também como promotora de desenvolvimento social e econômico junto a países em desenvolvimento; e, por fim, em face da ausência de uma regulação internacional exclusiva na área energética, o presente estudo se dedica a investigar as possibilidades de disciplinamento do comércio internacional dos biocombustíveis. Admitindo-se o relevante desempenho que o Brasil detém na produção e exportação deste produto, inclusive na área tecnológica, a presente tese busca identificar o foro adequado, condições justas de produção, investimento, concessão de subsídios, adoção de medidas técnicas, de compra e venda, concorrência entre outros itens que o tema relaciona.

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Kinetic measurements of amyloid growth provide insight into the free energy landscape of this supramolecular process and are crucial in the search for potent inhibitors of the main disorders with which it is associated, including Alzheimer's and Parkinson's diseases and Type II diabetes. In recent years, a new class of surface-bound biosensor assays, e.g., those based on surface plasmon resonance (SPR) and the quartz crystal microbalance (QCM) have been established as extremely valuable tools for kinetic measurements of amyloid formation. Here we describe detailed protocols of how QCM techniques can be used to monitor the elongation of amyloid fibrils in real time and to study the influence of external factors on the kinetics of amyloid growth with unprecedented accuracy.

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We developed a coarse-grained yet microscopic detailed model to study the statistical fluctuations of single-molecule protein conformational dynamics of adenylate kinase. We explored the underlying conformational energy landscape and found that the system has two basins of attractions, open and closed conformations connected by two separate pathways. The kinetics is found to be nonexponential, consistent with single-molecule conformational dynamics experiments. Furthermore, we found that the statistical distribution of the kinetic times for the conformational transition has a long power law tail, reflecting the exponential density of state of the underlying landscape. We also studied the joint distribution of the two pathways and found memory effects.

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We report here the investigation of a novel description of specificity in protein-ligand binding based on energy landscape theory. We define a new term, intrinsic specificity ratio (ISR), which describes the level of discrimination in binding free energies of the native basin for a protein-ligand complex from the weaker binding states of the same ligand. We discuss the relationship between the intrinsic specificity we defined here and the conventional definition of specificity. In a docking study of molecules with the enzyme COX-2, we demonstrate a statistical correspondence between ISR value and geometrical shapes of the small molecules binding to COX-2. We further observe that the known selective (nonselective) inhibitors of COX-2 have higher (lower) ISR values. We suggest that intrinsic specificity ratio may be a useful new criterion and a complement to affinity in drug screening and in searching for potential drug lead compounds.

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Biomolecular associations often accompanied by large conformational changes, sometimes folding and unfolding. By exploring an exactly solvable model, we constructed the free energy landscape and established a general framework for studying the biomolecular flexible binding process. We derived an optimal criterion for the specificity and function for flexible biomolecular binding where the binding and conformational folding are coupled.