173 research outputs found
The kinesin walk: a dynamic model with elastically coupled heads
Recently individual two-headed kinesin molecules have been studied in in
vitro motility assays revealing a number of their peculiar transport
properties. In this paper we propose a simple and robust model for the kinesin
stepping process with elastically coupled Brownian heads showing all of these
properties. The analytic and numerical treatment of our model results in a very
good fit to the experimental data and practically has no free parameters.
Changing the values of the parameters in the restricted range allowed by the
related experimental estimates has almost no effect on the shape of the curves
and results mainly in a variation of the zero load velocity which can be
directly fitted to the measured data. In addition, the model is consistent with
the measured pathway of the kinesin ATPase.Comment: 6 pages, 3 figure
Effects of intermediate bound states in dynamic force spectroscopy
We revisit here some aspects of the interpretation of dynamic force
spectroscopy experiments. The standard theory predicts a typical unbinding
force linearly proportional to the logarithm of the loading rate when
a single energetical barrier controls the unbinding process; for a more complex
situation of barriers, it predicts at most linear segments for the
vs. curve, each segment characterizing a different barrier. We
here extend this existing picture using a refined approximation, we provide a
more general analytical formula, and show that in principle up to
segments can show up experimentally. As a consequence the interpretation of
data can be ambiguous, for the characteristics and even the number of barriers.
A further possible outcome of a multiple-barrier landscape is a bimodal or
multimodal distribution of the unbinding force at a given loading rate, a
feature recently observed experimentally.Comment: 7 pages, 5 figure
The maintenance of sex in bacteria is ensured by its potential to reload genes
Why sex is maintained in nature is a fundamental question in biology. Natural
genetic transformation (NGT) is a sexual process by which bacteria actively
take up exogenous DNA and use it to replace homologous chromosomal sequences.
As it has been demonstrated, the role of NGT in repairing deleterious mutations
under constant selection is insufficient for its survival, and the lack of
other viable explanations have left no alternative except that DNA uptake
provides nucleotides for food. Here we develop a novel simulation approach for
the long-term dynamics of genome organization (involving the loss and
acquisition of genes) in a bacterial species consisting of a large number of
spatially distinct populations subject to independently fluctuating ecological
conditions. Our results show that in the presence of weak inter-population
migration NGT is able to subsist as a mechanism to reload locally lost,
intermittently selected genes from the collective gene pool of the species
through DNA uptake from migrants. Reloading genes and combining them with those
in locally adapted genomes allow individual cells to re-adapt faster to
environmental changes. The machinery of transformation survives under a wide
range of model parameters readily encompassing real-world biological
conditions. These findings imply that the primary role of NGT is not to serve
the cell with food, but to provide homologous sequences for restoring genes
that have disappeared from or become degraded in the local population.Comment: 16 pages with 3 color figures. Manuscript accepted for publication in
Genetics (www.genetics.org
Tight coupling in thermal Brownian motors
We study analytically a thermal Brownian motor model and calculate exactly
the Onsager coefficients. We show how the reciprocity relation holds and that
the determinant of the Onsager matrix vanishes. Such condition implies that the
device is built with tight coupling. This explains why Carnot's efficiency can
be achieved in the limit of infinitely slow velocities. We also prove that the
efficiency at maximum power has the maximum possible value, which corresponds
to the Curzon-Alhborn bound. Finally, we discuss the model acting as a Brownian
refrigerator
Measuring the energy landscape roughness and the transition state location of biomolecules using single molecule mechanical unfolding experiments
Single molecule mechanical unfolding experiments are beginning to provide
profiles of the complex energy landscape of biomolecules. In order to obtain
reliable estimates of the energy landscape characteristics it is necessary to
combine the experimental measurements with sound theoretical models and
simulations. Here, we show how by using temperature as a variable in mechanical
unfolding of biomolecules in laser optical tweezer or AFM experiments the
roughness of the energy landscape can be measured without making any
assumptions about the underlying reaction oordinate. The efficacy of the
formalism is illustrated by reviewing experimental results that have directly
measured roughness in a protein-protein complex. The roughness model can also
be used to interpret experiments on forced-unfolding of proteins in which
temperature is varied. Estimates of other aspects of the energy landscape such
as free energy barriers or the transition state (TS) locations could depend on
the precise model used to analyze the experimental data. We illustrate the
inherent difficulties in obtaining the transition state location from loading
rate or force-dependent unfolding rates. Because the transition state moves as
the force or the loading rate is varied it is in general difficult to invert
the experimental data unless the curvature at the top of the one dimensional
free energy profile is large, i.e the barrier is sharp. The independence of the
TS location on force holds good only for brittle or hard biomolecules whereas
the TS location changes considerably if the molecule is soft or plastic. We
also comment on the usefulness of extension of the molecule as a surrogate
reaction coordinate especially in the context of force-quench refolding of
proteins and RNA.Comment: 44 pages, 7 figure
Fundamental statistical features and self-similar properties of tagged networks
We investigate the fundamental statistical features of tagged (or annotated)
networks having a rich variety of attributes associated with their nodes. Tags
(attributes, annotations, properties, features, etc.) provide essential
information about the entity represented by a given node, thus, taking them
into account represents a significant step towards a more complete description
of the structure of large complex systems. Our main goal here is to uncover the
relations between the statistical properties of the node tags and those of the
graph topology. In order to better characterise the networks with tagged nodes,
we introduce a number of new notions, including tag-assortativity (relating
link probability to node similarity), and new quantities, such as node
uniqueness (measuring how rarely the tags of a node occur in the network) and
tag-assortativity exponent. We apply our approach to three large networks
representing very different domains of complex systems. A number of the tag
related quantities display analogous behaviour (e.g., the networks we studied
are tag-assortative, indicating possible universal aspects of tags versus
topology), while some other features, such as the distribution of the node
uniqueness, show variability from network to network allowing for pin-pointing
large scale specific features of real-world complex networks. We also find that
for each network the topology and the tag distribution are scale invariant, and
this self-similar property of the networks can be well characterised by the
tag-assortativity exponent, which is specific to each system
A random walker on a ratchet potential: Effect of a non Gaussian noise
We analyze the effect of a colored non Gaussian noise on a model of a random
walker moving along a ratchet potential. Such a model was motivated by the
transport properties of motor proteins, like kinesin and myosin. Previous
studies have been realized assuming white noises. However, for real situations,
in general we could expect that those noises be correlated and non Gaussian.
Among other aspects, in addition to a maximum in the current as the noise
intensity is varied, we have also found another optimal value of the current
when departing from Gaussian behavior. We show the relevant effects that arise
when departing from Gaussian behavior, particularly related to current's
enhancement, and discuss its relevance for both biological and technological
situations.Comment: Submitted to Europ.Phys. J. B (LaTex, 16 pgs, 8 figures
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