7 resultados para Lattice QCD

em National Center for Biotechnology Information - NCBI


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The nuclear spin polarization of 129Xe can be enhanced by several orders of magnitude by using optical pumping techniques. The increased sensitivity of xenon NMR has allowed imaging of lungs as well as other in vivo applications. The most critical parameter for efficient delivery of laser-polarized xenon to blood and tissues is the spin-lattice relaxation time (T1) of xenon in blood. In this work, the relaxation of laser-polarized xenon in human blood is measured in vitro as a function of blood oxygenation. Interactions with dissolved oxygen and with deoxyhemoglobin are found to contribute to the spin-lattice relaxation time of 129Xe in blood, the latter interaction having greater effect. Consequently, relaxation times of 129Xe in deoxygenated blood are shorter than in oxygenated blood. In samples with oxygenation equivalent to arterial and venous blood, the 129Xe T1s at 37°C and a magnetic field of 1.5 T were 6.4 s ± 0.5 s and 4.0 s ± 0.4 s, respectively. The 129Xe spin-lattice relaxation time in blood decreases at lower temperatures, but the ratio of T1 in oxygenated blood to that in deoxygenated blood is the same at 37°C and 25°C. A competing ligand has been used to show that xenon binding to albumin contributes to the 129Xe spin-lattice relaxation in blood plasma. This technique is promising for the study of xenon interactions with macromolecules.

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An exact treatment of adsorption from a one-dimensional lattice gas is used to eliminate and correct a well-known inconsistency in the Brunauer–Emmett–Teller (B.E.T.) equation—namely, Gibbs excess adsorption is not taken into account and the Gibbs integral diverges at the transition point. However, neither model should be considered realistic for experimental adsorption systems.

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The conformational space annealing (CSA) method for global optimization has been applied to the 10-55 fragment of the B-domain of staphylococcal protein A (protein A) and to a 75-residue protein, apo calbindin D9K (PDB ID code 1CLB), by using the UNRES off-lattice united-residue force field. Although the potential was not calibrated with these two proteins, the native-like structures were found among the low-energy conformations, without the use of threading or secondary-structure predictions. This is because the CSA method can find many distinct families of low-energy conformations. Starting from random conformations, the CSA method found that there are two families of low-energy conformations for each of the two proteins, the native-like fold and its mirror image. The CSA method converged to the same low-energy folds in all cases studied, as opposed to other optimization methods. It appears that the CSA method with the UNRES force field, which is based on the thermodynamic hypothesis, can be used in prediction of protein structures in real time.

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A new class of experiments that probe folding of individual protein domains uses mechanical stretching to cause the transition. We show how stretching forces can be incorporated in lattice models of folding. For fast folding proteins, the analysis suggests a complex relation between the force dependence and the reaction coordinate for folding.

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Two of the most important models to account for the specificity and sensitivity of the T cell receptor (TCR) are the kinetic proofreading and serial ligation models. However, although kinetic proofreading provides a means for individual TCRs to measure accurately the length of time they are engaged and signal appropriately, the stochastic nature of ligand dissociation means the kinetic proofreading model implies that at high concentrations the response of the cell will be relatively nonspecific. Recent ligand experiments have revealed the phenomenon of both negative and positive crosstalk among neighboring TCRs. By using a Monte Carlo simulation of a lattice of TCRs, we integrate receptor crosstalk with the kinetic proofreading and serial ligation models and discover that receptor cooperativity can enhance T cell specificity significantly at a very modest cost to the sensitivity of the response.

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A full quantitative understanding of the protein folding problem is now becoming possible with the help of the energy landscape theory and the protein folding funnel concept. Good folding sequences have a landscape that resembles a rough funnel where the energy bias towards the native state is larger than its ruggedness. Such a landscape leads not only to fast folding and stable native conformations but, more importantly, to sequences that are robust to variations in the protein environment and to sequence mutations. In this paper, an off-lattice model of sequences that fold into a β-barrel native structure is used to describe a framework that can quantitatively distinguish good and bad folders. The two sequences analyzed have the same native structure, but one of them is minimally frustrated whereas the other one exhibits a high degree of frustration.

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Protein folding is a relatively fast process considering the astronomical number of conformations in which a protein could find itself. Within the framework of a lattice model, we show that one can design rapidly folding sequences by assigning the strongest attractive couplings to the contacts present in a target native state. Our protein design can be extended to situations with both attractive and repulsive contacts. Frustration is minimized by ensuring that all the native contacts are again strongly attractive. Strikingly, this ensures the inevitability of folding and accelerates the folding process by an order of magnitude. The evolutionary implications of our findings are discussed.