55 research outputs found

    Thermodynamically Important Contacts in Folding of Model Proteins

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    We introduce a quantity, the entropic susceptibility, that measures the thermodynamic importance-for the folding transition-of the contacts between amino acids in model proteins. Using this quantity, we find that only one equilibrium run of a computer simulation of a model protein is sufficient to select a subset of contacts that give rise to the peak in the specific heat observed at the folding transition. To illustrate the method, we identify thermodynamically important contacts in a model 46-mer. We show that only about 50% of all contacts present in the protein native state are responsible for the sharp peak in the specific heat at the folding transition temperature, while the remaining 50% of contacts do not affect the specific heat.Comment: 5 pages, 5 figures; to be published in PR

    Nonlinearity of Mechanochemical Motions in Motor Proteins

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    The assumption of linear response of protein molecules to thermal noise or structural perturbations, such as ligand binding or detachment, is broadly used in the studies of protein dynamics. Conformational motions in proteins are traditionally analyzed in terms of normal modes and experimental data on thermal fluctuations in such macromolecules is also usually interpreted in terms of the excitation of normal modes. We have chosen two important protein motors - myosin V and kinesin KIF1A - and performed numerical investigations of their conformational relaxation properties within the coarse-grained elastic network approximation. We have found that the linearity assumption is deficient for ligand-induced conformational motions and can even be violated for characteristic thermal fluctuations. The deficiency is particularly pronounced in KIF1A where the normal mode description fails completely in describing functional mechanochemical motions. These results indicate that important assumptions of the theory of protein dynamics may need to be reconsidered. Neither a single normal mode, nor a superposition of such modes yield an approximation of strongly nonlinear dynamics.Comment: 10 pages, 6 figure

    Module M1 of Zebrafish Neuroglobin Acts as a Structural and Functional Protein Building Block for a Cell-Membrane-Penetrating Activity

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    Neuroglobin (Ngb) is a recently discovered vertebrate globin that is expressed in the brain and can reversibly bind oxygen. Mammalian Ngb is involved in neuroprotection during oxidative stress that occurs, for example, during ischemia and reperfusion. Recently, we found that zebrafish, but not human, Ngb can translocate into cells. Moreover, we demonstrated that a chimeric ZHHH Ngb protein, in which the module M1 of human Ngb is replaced by the corresponding region of zebrafish Ngb, can penetrate cell membranes and protect cells against oxidative stress-induced cell death, suggesting that module M1 of zebrafish Ngb is important for protein transduction. Furthermore, we recently showed that Lys7, Lys9, Lys21, and Lys23 in module M1 of zebrafish Ngb are crucial for protein transduction activity. In the present study, we have investigated whether module M1 of zebrafish Ngb can be used as a building block to create novel cell-membrane-penetrating folded proteins. First, we engineered a chimeric myoglobin (Mb), in which module M1 of zebrafish Ngb was fused to the N-terminus of full-length human Mb, and investigated its functional and structural properties. Our results showed that this chimeric Mb protein is stable and forms almost the same heme environment and α-helical structure as human wild-type Mb. In addition, we demonstrated that chimeric Mb has a cell-membrane-penetrating activity similar to zebrafish Ngb. Moreover, we found that glycosaminoglycan is crucial for the cell-membrane-penetrating activity of chimeric Mb as well as that of zebrafish Ngb. These results enable us to conclude that such module substitutions will facilitate the design and production of novel functional proteins

    Protein dynamics with off-lattice Monte Carlo moves

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    A Monte Carlo method for dynamics simulation of all-atom protein models is introduced, to reach long times not accessible to conventional molecular dynamics. The considered degrees of freedom are the dihedrals at Cα_\alpha-atoms. Two Monte Carlo moves are used: single rotations about torsion axes, and cooperative rotations in windows of amide planes, changing the conformation globally and locally, respectively. For local moves Jacobians are used to obtain an unbiased distribution of dihedrals. A molecular dynamics energy function adapted to the protein model is employed. A polypeptide is folded into native-like structures by local but not by global moves.Comment: 10 pages, 4 Postscript figures, uses epsf.sty and a4.sty; scheduled tentatively for Phys.Rev.E issue of 1 March 199

    An exact expression to calculate the derivatives of position-dependent observables in molecular simulations with flexible constraints

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    In this work, we introduce an algorithm to compute the derivatives of physical observables along the constrained subspace when flexible constraints are imposed on the system (i.e., constraints in which the hard coordinates are fixed to configuration-dependent values). The presented scheme is exact, it does not contain any tunable parameter, and it only requires the calculation and inversion of a sub-block of the Hessian matrix of second derivatives of the function through which the constraints are defined. We also present a practical application to the case in which the sought observables are the Euclidean coordinates of complex molecular systems, and the function whose minimization defines the constraints is the potential energy. Finally, and in order to validate the method, which, as far as we are aware, is the first of its kind in the literature, we compare it to the natural and straightforward finite-differences approach in three molecules of biological relevance: methanol, N-methyl-acetamide and a tri-glycine peptideComment: 13 pages, 8 figures, published versio

    Multiple Folding Pathways of the SH3 domain

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    Experimental observations suggest that proteins follow different pathways under different environmental conditions. We perform molecular dynamics simulations of a model of the SH3 domain over a broad range of temperatures, and identify distinct pathways in the folding transition. We determine the kinetic partition temperature --the temperature for which the SH3 domain undergoes a rapid folding transition with minimal kinetic barriers-- and observe that below this temperature the model protein may undergo a folding transition via multiple folding pathways. The folding kinetics is characterized by slow and fast pathways and the presence of only one or two intermediates. Our findings suggest the hypothesis that the SH3 domain, a protein for which only two-state folding kinetics was observed in previous experiments, may exhibit intermediates states under extreme experimental conditions, such as very low temperatures. A very recent report (Viguera et al., Proc. Natl. Acad. Sci. USA, 100:5730--5735, 2003) of an intermediate in the folding transition of the Bergerac mutant of the alpha-spectrin SH3 domain protein supports this hypothesis.Comment: 16 pages, 4 figures To be published in the "Journal of Molecular Biology

    The Energy Landscape, Folding Pathways and the Kinetics of a Knotted Protein

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    The folding pathway and rate coefficients of the folding of a knotted protein are calculated for a potential energy function with minimal energetic frustration. A kinetic transition network is constructed using the discrete path sampling approach, and the resulting potential energy surface is visualized by constructing disconnectivity graphs. Owing to topological constraints, the low-lying portion of the landscape consists of three distinct regions, corresponding to the native knotted state and to configurations where either the N- or C-terminus is not yet folded into the knot. The fastest folding pathways from denatured states exhibit early formation of the N-terminus portion of the knot and a rate-determining step where the C-terminus is incorporated. The low-lying minima with the N-terminus knotted and the C-terminus free therefore constitute an off-pathway intermediate for this model. The insertion of both the N- and C-termini into the knot occur late in the folding process, creating large energy barriers that are the rate limiting steps in the folding process. When compared to other protein folding proteins of a similar length, this system folds over six orders of magnitude more slowly.Comment: 19 page

    Static and dynamic characteristics of protein contact networks

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    The principles underlying protein folding remains one of Nature's puzzles with important practical consequences for Life. An approach that has gathered momentum since the late 1990's, looks at protein hetero-polymers and their folding process through the lens of complex network analysis. Consequently, there is now a body of empirical studies describing topological characteristics of protein macro-molecules through their contact networks and linking these topological characteristics to protein folding. The present paper is primarily a review of this rich area. But it delves deeper into certain aspects by emphasizing short-range and long-range links, and suggests unconventional places where "power-laws" may be lurking within protein contact networks. Further, it considers the dynamical view of protein contact networks. This closer scrutiny of protein contact networks raises new questions for further research, and identifies new regularities which may be useful to parameterize a network approach to protein folding. Preliminary experiments with such a model confirm that the regularities we identified cannot be easily reproduced through random effects. Indeed, the grand challenge of protein folding is to elucidate the process(es) which not only generates the specific and diverse linkage patterns of protein contact networks, but also reproduces the dynamic behavior of proteins as they fold. Keywords: network analysis, protein contact networks, protein foldingComment: Added Appendix

    Manipulating Biopolymer Dynamics by Anisotropic Nanoconfinement

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    How the geometry of nano-sized confinement affects dynamics of biomaterials is interesting yet poorly understood. An elucidation of structural details upon nano-sized confinement may benefit manufacturing pharmaceuticals in biomaterial sciences and medicine. The behavior of biopolymers in nano-sized confinement is investigated using coarse-grained models and molecular simulations. Particularly, we address the effects of shapes of a confinement on protein folding dynamics by measuring folding rates and dissecting structural properties of the transition states in nano-sized spheres and ellipsoids. We find that when the form of a confinement resembles the geometrical properties of the transition states, the rates of folding kinetics are most enhanced. This knowledge of shape selectivity in identifying optimal conditions for reactions will have a broad impact in nanotechnology and pharmaceutical sciences.Comment: to appear in Nano Letter

    Detection of Functional Modes in Protein Dynamics

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    Proteins frequently accomplish their biological function by collective atomic motions. Yet the identification of collective motions related to a specific protein function from, e.g., a molecular dynamics trajectory is often non-trivial. Here, we propose a novel technique termed “functional mode analysis” that aims to detect the collective motion that is directly related to a particular protein function. Based on an ensemble of structures, together with an arbitrary “functional quantity” that quantifies the functional state of the protein, the technique detects the collective motion that is maximally correlated to the functional quantity. The functional quantity could, e.g., correspond to a geometric, electrostatic, or chemical observable, or any other variable that is relevant to the function of the protein. In addition, the motion that displays the largest likelihood to induce a substantial change in the functional quantity is estimated from the given protein ensemble. Two different correlation measures are applied: first, the Pearson correlation coefficient that measures linear correlation only; and second, the mutual information that can assess any kind of interdependence. Detecting the maximally correlated motion allows one to derive a model for the functional state in terms of a single collective coordinate. The new approach is illustrated using a number of biomolecules, including a polyalanine-helix, T4 lysozyme, Trp-cage, and leucine-binding protein
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