2,209 research outputs found
Exploring the Free Energy Landscape: From Dynamics to Networks and Back
The knowledge of the Free Energy Landscape topology is the essential key to
understand many biochemical processes. The determination of the conformers of a
protein and their basins of attraction takes a central role for studying
molecular isomerization reactions. In this work, we present a novel framework
to unveil the features of a Free Energy Landscape answering questions such as
how many meta-stable conformers are, how the hierarchical relationship among
them is, or what the structure and kinetics of the transition paths are.
Exploring the landscape by molecular dynamics simulations, the microscopic data
of the trajectory are encoded into a Conformational Markov Network. The
structure of this graph reveals the regions of the conformational space
corresponding to the basins of attraction. In addition, handling the
Conformational Markov Network, relevant kinetic magnitudes as dwell times or
rate constants, and the hierarchical relationship among basins, complete the
global picture of the landscape. We show the power of the analysis studying a
toy model of a funnel-like potential and computing efficiently the conformers
of a short peptide, the dialanine, paving the way to a systematic study of the
Free Energy Landscape in large peptides.Comment: PLoS Computational Biology (in press
Complex-network analysis of combinatorial spaces: The NK landscape case
We propose a network characterization of combinatorial fitness landscapes by
adapting the notion of inherent networks proposed for energy surfaces. We use
the well-known family of NK landscapes as an example. In our case the inherent
network is the graph whose vertices represent the local maxima in the
landscape, and the edges account for the transition probabilities between their
corresponding basins of attraction. We exhaustively extracted such networks on
representative NK landscape instances, and performed a statistical
characterization of their properties. We found that most of these network
properties are related to the search difficulty on the underlying NK landscapes
with varying values of K.Comment: arXiv admin note: substantial text overlap with arXiv:0810.3492,
arXiv:0810.348
Fractal geometry of spin-glass models
Stability and diversity are two key properties that living entities share
with spin glasses, where they are manifested through the breaking of the phase
space into many valleys or local minima connected by saddle points. The
topology of the phase space can be conveniently condensed into a tree
structure, akin to the biological phylogenetic trees, whose tips are the local
minima and internal nodes are the lowest-energy saddles connecting those
minima. For the infinite-range Ising spin glass with p-spin interactions, we
show that the average size-frequency distribution of saddles obeys a power law
, where w=w(s) is the number of minima that can be
connected through saddle s, and D is the fractal dimension of the phase space
Fractal geometry of spin-glass models
Stability and diversity are two key properties that living entities share
with spin glasses, where they are manifested through the breaking of the phase
space into many valleys or local minima connected by saddle points. The
topology of the phase space can be conveniently condensed into a tree
structure, akin to the biological phylogenetic trees, whose tips are the local
minima and internal nodes are the lowest-energy saddles connecting those
minima. For the infinite-range Ising spin glass with p-spin interactions, we
show that the average size-frequency distribution of saddles obeys a power law
, where w=w(s) is the number of minima that can be
connected through saddle s, and D is the fractal dimension of the phase space
Levy Flights, Non-local Search and Simulated Annealing
We solve a problem of non-convex stochastic optimisation with help of
simulated annealing of Levy flights of a variable stability index. The search
of the ground state of an unknown potential is non-local due to big jumps of
the Levy flights process. The convergence to the ground state is fast due to a
polynomial decrease rate of the temperature
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