5 resultados para Mean-field model

em National Center for Biotechnology Information - NCBI


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We propose a general mean field model of ligand-protein interactions to determine the thermodynamic equilibrium of a system at finite temperature. The method is employed in structural assessments of two human immuno-deficiency virus type 1 protease complexes where the gross effects of protein flexibility are incorporated by utilizing a data base of crystal structures. Analysis of the energy spectra for these complexes has revealed that structural and thermo-dynamic aspects of molecular recognition can be rationalized on the basis of the extent of frustration in the binding energy landscape. In particular, the relationship between receptor-specific binding of these ligands to human immunodeficiency virus type 1 protease and a minimal frustration principle is analyzed.

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In this work, we used direct measurements with the surface force apparatus to determine the pH-dependent electrostatic charge density of a single binding face of streptavidin. Mean field calculations have been used with considerable success to model electrostatic potential fields near protein surfaces, but these models and their inherent assumptions have not been tested directly at the molecular level. Using the force apparatus and immobilized, oriented monolayers of streptavidin, we measured a pI of 5–5.5 for the biotin-binding face of the protein. This differs from the pI of 6.3 for the soluble protein and confirms that we probed the local electrostatic features of the macromolecule. With finite difference solutions of the linearized Poisson–Boltzmann equation, we then calculated the pH-dependent charge densities adjacent to the same face of the protein. These calculated values agreed quantitatively with those obtained by direct force measurements. Although our study focuses on the pH-dependence of surface electrostatics, this direct approach to probing the electrostatic features of proteins is applicable to investigations of any perturbations that alter the charge distribution of the surfaces of immobilized molecules.

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We introduce a computational method to optimize the in vitro evolution of proteins. Simulating evolution with a simple model that statistically describes the fitness landscape, we find that beneficial mutations tend to occur at amino acid positions that are tolerant to substitutions, in the limit of small libraries and low mutation rates. We transform this observation into a design strategy by applying mean-field theory to a structure-based computational model to calculate each residue's structural tolerance. Thermostabilizing and activity-increasing mutations accumulated during the experimental directed evolution of subtilisin E and T4 lysozyme are strongly directed to sites identified by using this computational approach. This method can be used to predict positions where mutations are likely to lead to improvement of specific protein properties.

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We have used Mössbauer and electron paramagnetic resonance (EPR) spectroscopy to study a heme-N-alkylated derivative of chloroperoxidase (CPO) prepared by mechanism-based inactivation with allylbenzene and hydrogen peroxide. The freshly prepared inactivated enzyme (“green CPO”) displayed a nearly pure low-spin ferric EPR signal with g = 1.94, 2.15, 2.31. The Mössbauer spectrum of the same species recorded at 4.2 K showed magnetic hyperfine splittings, which could be simulated in terms of a spin Hamiltonian with a complete set of hyperfine parameters in the slow spin fluctuation limit. The EPR spectrum of green CPO was simulated using a three-term crystal field model including g-strain. The best-fit parameters implied a very strong octahedral field in which the three 2T2 levels of the (3d)5 configuration in green CPO were lowest in energy, followed by a quartet. In native CPO, the 6A1 states follow the 2T2 ground state doublet. The alkene-mediated inactivation of CPO is spontaneously reversible. Warming of a sample of green CPO to 22°C for increasing times before freezing revealed slow conversion of the novel EPR species to two further spin S = ½ ferric species. One of these species displayed g = 1.82, 2.25, 2.60 indistinguishable from native CPO. By subtracting spectral components due to native and green CPO, a third species with g = 1.86, 2.24, 2.50 could be generated. The EPR spectrum of this “quasi-native CPO,” which appears at intermediate times during the reactivation, was simulated using best-fit parameters similar to those used for native CPO.

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Childhood exposure to low-level lead can permanently reduce intelligence, but the neurobiologic mechanism for this effect is unknown. We examined the impact of lead exposure on the development of cortical columns, using the rodent barrel field as a model. In all areas of mammalian neocortex, cortical columns constitute a fundamental structural unit subserving information processing. Barrel field cortex contains columnar processing units with distinct clusters of layer IV neurons that receive sensory input from individual whiskers. In this study, rat pups were exposed to 0, 0.2, 1, 1.5, or 2 g/liter lead acetate in their dam's drinking water from birth through postnatal day 10. This treatment, which coincides with the development of segregated columns in the barrel field, produced blood lead concentrations from 1 to 31 μg/dl. On postnatal day 10, the area of the barrel field and of individual barrels was measured. A dose-related reduction in barrel field area was observed (Pearson correlation = −0.740; P < 0.001); mean barrel field area in the highest exposure group was decreased 12% versus controls. Individual barrels in the physiologically more active caudoventral group were affected preferentially. Total cortical area measured in the same sections was not altered significantly by lead exposure. These data support the hypothesis that lead exposure may impair the development of columnar processing units in immature neocortex. We demonstrate that low levels of blood lead, in the range seen in many impoverished inner-city children, cause structural alterations in a neocortical somatosensory map.