2,053 research outputs found
Elementary derivation of Spitzer's asymptotic law for Brownian windings and some of its physical applications
A simple derivation of Spitzer'z asymptotic law for Brownian windings
[Trans.Am.Math.Soc.87,187 (1958)]is presented along with its generalizations
>.These include the cases of planar Brownian walks interacting with a single
puncture and Brownian walks on a single truncated cone with variable conical
angle interacting with the truncated conical tip.Such situations are typical in
the theories of quantum Hall effect and 2+1 quantum gravity, respectively .They
also have some applications in polymer physic
Signaling switches and bistability arising from multisite phosphorylation in protein kinase cascades
Mitogen-activated protein kinase (MAPK) cascades can operate as bistable switches residing in either of two different stable states. MAPK cascades are often embedded in positive feedback loops, which are considered to be a prerequisite for bistable behavior. Here we demonstrate that in the absence of any imposed feedback regulation, bistability and hysteresis can arise solely from a distributive kinetic mechanism of the two-site MAPK phosphorylation and dephosphorylation. Importantly, the reported kinetic properties of the kinase (MEK) and phosphatase (MKP3) of extracellular signal–regulated kinase (ERK) fulfill the essential requirements for generating a bistable switch at a single MAPK cascade level. Likewise, a cycle where multisite phosphorylations are performed by different kinases, but dephosphorylation reactions are catalyzed by the same phosphatase, can also exhibit bistability and hysteresis. Hence, bistability induced by multisite covalent modification may be a widespread mechanism of the control of protein activity
Generating functional analysis of complex formation and dissociation in large protein interaction networks
We analyze large systems of interacting proteins, using techniques from the
non-equilibrium statistical mechanics of disordered many-particle systems.
Apart from protein production and removal, the most relevant microscopic
processes in the proteome are complex formation and dissociation, and the
microscopic degrees of freedom are the evolving concentrations of unbound
proteins (in multiple post-translational states) and of protein complexes. Here
we only include dimer-complexes, for mathematical simplicity, and we draw the
network that describes which proteins are reaction partners from an ensemble of
random graphs with an arbitrary degree distribution. We show how generating
functional analysis methods can be used successfully to derive closed equations
for dynamical order parameters, representing an exact macroscopic description
of the complex formation and dissociation dynamics in the infinite system
limit. We end this paper with a discussion of the possible routes towards
solving the nontrivial order parameter equations, either exactly (in specific
limits) or approximately.Comment: 14 pages, to be published in Proc of IW-SMI-2009 in Kyoto (Journal of
Phys Conference Series
Trading the micro-world of combinatorial complexity for the macro-world of protein interaction domains
Membrane receptors and proteins involved in signal transduction display numerous binding domains and operate as molecular scaffolds generating a variety of parallel reactions and protein complexes. The resulting combinatorial explosion of the number of feasible chemical species and, hence, different states of a network greatly impedes mechanistic modeling of signaling systems. Here we present novel general principles and identify kinetic requirements that allow us to replace a mechanistic picture of all possible micro-states and transitions by a macro-description of states of separate binding sites of network proteins. This domain-oriented approach dramatically reduces computational models of cellular signaling networks by dissecting mechanistic trajectories into the dynamics of macro- and meso-variables. We specify the conditions when the temporal dynamics of micro-states can be exactly or approximately expressed in terms of the product of the relative concentrations of separate domains. We prove that our macro-modeling approach equally applies to signaling systems with low population levels, analyzed by stochastic rather than deterministic equations. Thus, our results greatly facilitate quantitative analysis and computational modeling of multi-protein signaling networks
The role of long-chain acyl-CoA in the damage of oxidative phosphorylation in heart mitochondria
AbstractThe aim of this investigation was to study the effect of intramitochondrial acyl-CoA on the respiration of rabbit heart mitochondria over the whole range of stationary respiratory rates between States 4 and 3. The creatine phosphokinase system was used for stabilization of extramitochondrial adenine nucleotide concentration. It was shown that acyl-CoA depressed respiration more effectively in the intermediate range of respiration between States 4 and 3. The effect of acyl-CoA was negligible near State 4 and in State 3. These data are in line with our previous results concerning the dependence of the adenine nucleotide translocator control coefficient on the rate of mitochondrial respiration. Thus, our data suggest that long-chain acyl-CoA may regulate oxidative phosphorylation in heart mitochondria in vivo
Analysis of signalling pathways using continuous time Markov chains
We describe a quantitative modelling and analysis approach for signal transduction networks.
We illustrate the approach with an example, the RKIP inhibited ERK pathway [CSK+03]. Our models are high level descriptions of continuous time Markov chains: proteins are modelled by synchronous processes and reactions by transitions. Concentrations are modelled by discrete, abstract quantities. The main advantage of our approach is that using a (continuous time) stochastic logic and the PRISM model checker, we can perform quantitative analysis such as what is the probability that if a concentration reaches a certain level, it will remain at that level thereafter? or how does varying a given reaction rate affect that probability? We also perform standard simulations and compare our results with a traditional ordinary differential equation model. An interesting result is that for the example pathway, only a small number of discrete data values is required to render the simulations practically indistinguishable
Signaling Cascades Modulate the Speed of Signal Propagation through Space
Cells are not mixed bags of signaling molecules. As a consequence, signals must travel from their origin to distal locations. Much is understood about the purely diffusive propagation of signals through space. Many signals, however, propagate via signaling cascades. Here, we show that, depending on their kinetics, cascades speed up or slow down the propagation of signals through space, relative to pure diffusion.We modeled simple cascades operating under different limits of Michaelis-Menten kinetics using deterministic reaction-diffusion equations. Cascades operating far from enzyme saturation speed up signal propagation; the second mobile species moves more quickly than the first through space, on average. The enhanced speed is due to more efficient serial activation of a downstream signaling module (by the signaling molecule immediately upstream in the cascade) at points distal from the signaling origin, compared to locations closer to the source. Conversely, cascades operating under saturated kinetics, which exhibit zero-order ultrasensitivity, can slow down signals, ultimately localizing them to regions around the origin.Signal speed modulation may be a fundamental function of cascades, affecting the ability of signals to penetrate within a cell, to cross-react with other signals, and to activate distant targets. In particular, enhanced speeds provide a way to increase signal penetration into a cell without needing to flood the cell with large numbers of active signaling molecules; conversely, diminished speeds in zero-order ultrasensitive cascades facilitate strong, but localized, signaling
Long-range signaling by phosphoprotein waves arising from bistability in protein kinase cascades
A hallmark of protein kinase/phosphatase cascades, including mitogen-activated protein kinase (MAPK) pathways, is the spatial separation of their components within cells. The top-level kinase, MAP3K, is phosphorylated at the cell membrane, and cytoplasmic kinases at sequential downstream levels (MAP2K and MAPK) spread the signal to distant targets. Given measured protein diffusivity and phosphatase activities, signal propagation by diffusion would result in a steep decline of MAP2K activity and low bisphosphorylated MAPK (ppMAPK) levels near the nucleus, especially in large cells, such as oocytes. Here, we show that bistability in a two-site MAPK (de)phosphorylation cycle generates a novel type of phosphoprotein wave that propagates from the surface deep into the cell interior. Positive feedback from ppMAPK to cytoplasmic MAP2K enhances the propagation span of the ppMAPK wave, making it possible to convey phosphorylation signals over exceedingly long distances. The finding of phosphorylation waves traveling with constant amplitude and high velocity may solve a long-standing enigma of survival signaling in developing neurons
Analyticity of The Ground State Energy For Massless Nelson Models
We show that the ground state energy of the translationally invariant Nelson
model, describing a particle coupled to a relativistic field of massless
bosons, is an analytic function of the coupling constant and the total
momentum. We derive an explicit expression for the ground state energy which is
used to determine the effective mass.Comment: 33 pages, 1 figure, added a section on the calculation of the
effective mas
A transfer matrix approach to the enumeration of plane meanders
A closed plane meander of order is a closed self-avoiding curve
intersecting an infinite line times. Meanders are considered distinct up
to any smooth deformation leaving the line fixed. We have developed an improved
algorithm, based on transfer matrix methods, for the enumeration of plane
meanders. While the algorithm has exponential complexity, its rate of growth is
much smaller than that of previous algorithms. The algorithm is easily modified
to enumerate various systems of closed meanders, semi-meanders, open meanders
and many other geometries.Comment: 13 pages, 9 eps figures, to appear in J. Phys.
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