999 resultados para FOLDING MODEL
Resumo:
Although the rates of chemical reactions become faster with increasing temperature, the converse may be observed with protein-folding reactions. The rate constant for folding initially increases with temperature, goes through a maximum, and then decreases. The activation enthalpy is thus highly temperature dependent because of a large change in specific heat (delta Cp). Such a delta Cp term is usually presumed to be a consequence of a large decrease in exposure of hydrophobic surfaces to water as the reaction proceeds from the denatured state to the transition state for folding: the hydrophobic side chains are surrounded by "icebergs" of water that melt with increasing temperature, thus making a large contribution to the Cp of the denatured state and a smaller one to the more compact transition state. The rate could also be affected by temperature-induced changes in the conformational population of the ground state: the heat required for the progressive melting of residual structure in the denatured state will contribute to delta Cp. By examining two proteins with different refolding mechanisms, we are able to find both of these two processes; barley chymotrypsin inhibitor 2, which refolds from a highly unfolded state, fits well to a hydrophobic interaction model with a constant delta Cp of activation, whereas barnase, which refolds from a more structured denatured state, deviates from this ideal behavior.
Resumo:
Evolutionary selection of sequences is studied with a knowledge-based Hamiltonian to find the design principle for folding to a model protein structure. With sequences selected by naive energy minimization, the model structure tends to be unstable and the folding ability is low. Sequences with high folding ability have only the low-lying energy minimum but also an energy landscape which is similar to that found for the native sequence over a wide region of the conformation space. Though there is a large fluctuation in foldable sequences, the hydrophobicity pattern and the glycine locations are preserved among them. Implications of the design principle for the molecular mechanism of folding are discussed.
Resumo:
Neurospora VS RNA performs an RNA-mediated self-cleavage reaction whose products contain 2',3'-cyclic phosphate and 5'-hydroxyl termini. This reaction is similar to those of hammerhead, hairpin, and hepatitis delta virus ribozymes; however, VS RNA is not similar in sequence to these other self-cleaving motifs. Here we propose a model for the secondary structure of the self-cleaving region of VS RNA, supported by site-directed mutagenesis and chemical modification structure probing data. The secondary structure of VS RNA is distinct from those of the other naturally occurring RNA self-cleaving domains. In addition to a unique secondary structure, several Mg-dependent interactions occur during the folding of VS RNA into its active tertiary conformation.
Resumo:
The paper presents a new theory for modeling flow in anisotropic, viscous rock. This theory has originally been developed for the simulation of large deformation processes including folding and kinking in multi-layered visco-elastic rock. The orientation of slip planes in the context of crystallographic slip is determined by the normal vector, the so-called director of these surfaces. The model is applied to simulate anisotropic natural mantle convection. We compare the evolution of the director and approximately steady states of isotropic and anisotropic convection. The isotropic case has a simple steady state solution, whereas the orthotropic convection model produces a continuously evolving patterning in tile core of the convection cell which makes only a near-steady condition possible, in which the thermal boundary layer appears to be well aligned with the flow and hence as observed in seismic tomomgraphy strong anistropic.
Resumo:
The dynamics of peptides and proteins generated by classical molecular dynamics (MD) is described by using a Markov model. The model is built by clustering the trajectory into conformational states and estimating transition probabilities between the states. Assuming that it is possible to influence the dynamics of the system by varying simulation parameters, we show how to use the Markov model to determine the parameter values that preserve the folded state of the protein and at the same time, reduce the folding time in the simulation. We investigate this by applying the method to two systems. The first system is an imaginary peptide described by given transition probabilities with a total folding time of 1 micros. We find that only small changes in the transition probabilities are needed to accelerate (or decelerate) the folding. This implies that folding times for slowly folding peptides and proteins calculated using MD cannot be meaningfully compared to experimental results. The second system is a four residue peptide valine-proline-alanine-leucine in water. We control the dynamics of the transitions by varying the temperature and the atom masses. The simulation results show that it is possible to find the combinations of parameter values that accelerate the dynamics and at the same time preserve the native state of the peptide. A method for accelerating larger systems without performing simulations for the whole folding process is outlined.
Resumo:
The question of significant deviations of protein folding times simulated using molecular dynamics from experimental values is investigated. It is shown that in the framework of Markov State Model (MSM) describing the conformational dynamics of peptides and proteins, the folding time is very sensitive to the simulation model parameters, such as forcefield and temperature. Using two peptides as examples, we show that the deviations in the folding times can reach an order of magnitude for modest variations of the molecular model. We, therefore, conclude that the folding rate values obtained in molecular dynamics simulations have to be treated with care.
Resumo:
One of the most widely studied protein structure prediction models is the hydrophobic-hydrophilic (HP) model, which explains the hydrophobic interaction and tries to maximize the number of contacts among hydrophobic amino-acids. In order to find a lower bound for the number of contacts, a number of heuristics have been proposed, but finding the optimal solution is still a challenge. In this research, we focus on creating a new integer programming model which is capable to provide tractable input for mixed-integer programming solvers, is general enough and allows relaxation with provable good upper bounds. Computational experiments using benchmark problems show that our formulation achieves these goals.
Resumo:
The physics of self-organization and complexity is manifested on a variety of biological scales, from large ecosystems to the molecular level. Protein molecules exhibit characteristics of complex systems in terms of their structure, dynamics, and function. Proteins have the extraordinary ability to fold to a specific functional three-dimensional shape, starting from a random coil, in a biologically relevant time. How they accomplish this is one of the secrets of life. In this work, theoretical research into understanding this remarkable behavior is discussed. Thermodynamic and statistical mechanical tools are used in order to investigate the protein folding dynamics and stability. Theoretical analyses of the results from computer simulation of the dynamics of a four-helix bundle show that the excluded volume entropic effects are very important in protein dynamics and crucial for protein stability. The dramatic effects of changing the size of sidechains imply that a strategic placement of amino acid residues with a particular size may be an important consideration in protein engineering. Another investigation deals with modeling protein structural transitions as a phase transition. Using finite size scaling theory, the nature of unfolding transition of a four-helix bundle protein was investigated and critical exponents for the transition were calculated for various hydrophobic strengths in the core. It is found that the order of the transition changes from first to higher order as the strength of the hydrophobic interaction in the core region is significantly increased. Finally, a detailed kinetic and thermodynamic analysis was carried out in a model two-helix bundle. The connection between the structural free-energy landscape and folding kinetics was quantified. I show how simple protein engineering, by changing the hydropathy of a small number of amino acids, can enhance protein folding by significantly changing the free energy landscape so that kinetic traps are removed. The results have general applicability in protein engineering as well as understanding the underlying physical mechanisms of protein folding. ^
Resumo:
A deep understanding of the proteins folding dynamics can be get quantifying folding landscape by calculating how the number of microscopic configurations (entropy) varies with the energy of the chain, Ω=Ω(E). Because of the incredibly large number of microstates available to a protein, direct enumeration of Ω(E) is not possible on realistic computer simulations. An estimate of Ω(E) can be obtained by use of a combination of statistical mechanics and thermodynamics. By combining different definitions of entropy that are valid for a system whose probability for occupying a state is given by the canonical Boltzmann probability, computers allow the determination of Ω(E). ^ The energy landscapes of two similar, but not identical model proteins were studied. One protein contains no kinetic tracks. Results show a smooth funnel for the folding landscape. That allows the contour determination of the folding funnel. Also it was presented results for the folding landscape for a modified protein with kinetic traps. Final results show that the computational approach is able to distinguish and explore regions of the folding landscape that are due to kinetic traps from the native state folding funnel.^
Resumo:
Almost all pharmaceutically relevant proteins and many extracellular proteins contain disulfide bonds, which are essential for protein functions. In many cases, disulfidecontaining proteins are produced via in vitro protein folding that involves the oxidation of reduced protein to native protein, a complex process. The in vitro folding of reduced lysozyme has been extensively studied as a model system because native lysozyme is small, inexpensive, and has only four disulfide bonds. The folding of reduced lysozyme is conducted with the aid of a redox buffer consisting of a small molecule disulfide and a small molecule thiol, such as oxidized and reduced glutathione. Herein, in vitro folding rates and yields of lysozyme obtained in the presence of a series of aromatic thiols and oxidized glutathione are compared to those obtained with reduced and oxidized glutathione. Results showed that aromatic thiols significantly increase the folding rate of lysozyme compared to glutathione.
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:
This project aims at deepening the understanding of the molecular basis of the phenotypic heterogeneity of prion diseases. Prion diseases represent the first and clearest example of “protein misfolding diseases”, that are all the neurodegenerative diseases caused by the accumulation of misfolded proteins in the central nervous system. In the field of protein misfolding diseases, the term “strain” describes the heterogeneity observed among the same disease in the clinical and pathologic progression, biochemical features of the aggregated protein, conformational memory and pattern of lesions. In this work, the two most common strains of Creutzfeldt-Jakob Disease (CJD), named MM1 and VV2, were analyzed. This thesis investigates the strain paradigm with the production of new multi omic data, and, on such data, appropriate computational analysis combining bioinformatics, data science and statistical approaches was performed. In this work, genomic and transcriptomic profiling allowed an improved characterization of the molecular features of the two most common strains of CJD, identifying multiple possible genetic contributors to the disease and finding several shared impaired pathways between the VV2 strain and Parkinson Disease. On the epigenomic level, the tridimensional chromatin folding in peripheral immune cells of CJD patients at onset and of healthy controls was investigated with Hi-C. While being the first application of this very advanced technology in prion diseases and one of the first in general in neurobiology, this work found a significant and diffuse loss of genomic interactions in immune cells of CJD patients at disease onset, particularly in the PRNP locus, suggesting a possible impairment of chromatin conformation in the disease. The results of this project represent a novelty in the state of the art in this field, both from a biomedical and technological point of view.
Resumo:
Understanding the molecular mechanisms of oral carcinogenesis will yield important advances in diagnostics, prognostics, effective treatment, and outcome of oral cancer. Hence, in this study we have investigated the proteomic and peptidomic profiles by combining an orthotopic murine model of oral squamous cell carcinoma (OSCC), mass spectrometry-based proteomics and biological network analysis. Our results indicated the up-regulation of proteins involved in actin cytoskeleton organization and cell-cell junction assembly events and their expression was validated in human OSCC tissues. In addition, the functional relevance of talin-1 in OSCC adhesion, migration and invasion was demonstrated. Taken together, this study identified specific processes deregulated in oral cancer and provided novel refined OSCC-targeting molecules.
Resumo:
Two single crystalline surfaces of Au vicinal to the (111) plane were modified with Pt and studied using scanning tunneling microscopy (STM) and X-ray photoemission spectroscopy (XPS) in ultra-high vacuum environment. The vicinal surfaces studied are Au(332) and Au(887) and different Pt coverage (θPt) were deposited on each surface. From STM images we determine that Pt deposits on both surfaces as nanoislands with heights ranging from 1 ML to 3 ML depending on θPt. On both surfaces the early growth of Pt ad-islands occurs at the lower part of the step edge, with Pt ad-atoms being incorporated into the steps in some cases. XPS results indicate that partial alloying of Pt occurs at the interface at room temperature and at all coverage, as suggested by the negative chemical shift of Pt 4f core line, indicating an upward shift of the d-band center of the alloyed Pt. Also, the existence of a segregated Pt phase especially at higher coverage is detected by XPS. Sample annealing indicates that the temperature rise promotes a further incorporation of Pt atoms into the Au substrate as supported by STM and XPS results. Additionally, the catalytic activity of different PtAu systems reported in the literature for some electrochemical reactions is discussed considering our findings.
Resumo:
Congenital diaphragmatic hernia (CDH) is associated with pulmonary hypertension which is often difficult to manage, and a significant cause of morbidity and mortality. In this study, we have used a rabbit model of CDH to evaluate the effects of BAY 60-2770 on the in vitro reactivity of left pulmonary artery. CDH was performed in New Zealand rabbit fetuses (n = 10 per group) and compared to controls. Measurements of body, total and left lung weights (BW, TLW, LLW) were done. Pulmonary artery rings were pre-contracted with phenylephrine (10 μM), after which cumulative concentration-response curves to glyceryl trinitrate (GTN; NO donor), tadalafil (PDE5 inhibitor) and BAY 60-2770 (sGC activator) were obtained as well as the levels of NO (NO3/NO2). LLW, TLW and LBR were decreased in CDH (p < 0.05). In left pulmonary artery, the potency (pEC50) for GTN was markedly lower in CDH (8.25 ± 0.02 versus 9.27 ± 0.03; p < 0.01). In contrast, the potency for BAY 60-2770 was markedly greater in CDH (11.7 ± 0.03 versus 10.5 ± 0.06; p < 0.01). The NO2/NO3 levels were 62 % higher in CDH (p < 0.05). BAY 60-2770 exhibits a greater potency to relax the pulmonary artery in CDH, indicating a potential use for pulmonary hypertension in this disease.