4,447 research outputs found
Design of Sequences with Good Folding Properties in Coarse-Grained Protein Models
Background: Designing amino acid sequences that are stable in a given target
structure amounts to maximizing a conditional probability. A straightforward
approach to accomplish this is a nested Monte Carlo where the conformation
space is explored over and over again for different fixed sequences, which
requires excessive computational demand. Several approximate attempts to remedy
this situation, based on energy minimization for fixed structure or high-
expansions, have been proposed. These methods are fast but often not accurate
since folding occurs at low .
Results: We develop a multisequence Monte Carlo procedure, where both
sequence and conformation space are simultaneously probed with efficient
prescriptions for pruning sequence space. The method is explored on
hydrophobic/polar models. We first discuss short lattice chains, in order to
compare with exact data and with other methods. The method is then successfully
applied to lattice chains with up to 50 monomers, and to off-lattice 20-mers.
Conclusions: The multisequence Monte Carlo method offers a new approach to
sequence design in coarse-grained models. It is much more efficient than
previous Monte Carlo methods, and is, as it stands, applicable to a fairly wide
range of two-letter models.Comment: 23 pages, 7 figure
Parallelization of Markov chain generation and its application to the multicanonical method
We develop a simple algorithm to parallelize generation processes of Markov
chains. In this algorithm, multiple Markov chains are generated in parallel and
jointed together to make a longer Markov chain. The joints between the
constituent Markov chains are processed using the detailed balance. We apply
the parallelization algorithm to multicanonical calculations of the
two-dimensional Ising model and demonstrate accurate estimation of
multicanonical weights.Comment: 15 pages, 5 figures, uses elsart.cl
A tractable genotype-phenotype map for the self-assembly of protein quaternary structure
The mapping between biological genotypes and phenotypes is central to the
study of biological evolution. Here we introduce a rich, intuitive, and
biologically realistic genotype-phenotype (GP) map, that serves as a model of
self-assembling biological structures, such as protein complexes, and remains
computationally and analytically tractable. Our GP map arises naturally from
the self-assembly of polyomino structures on a 2D lattice and exhibits a number
of properties: (genotypes vastly outnumber phenotypes),
(genotypic redundancy varies greatly between
phenotypes), (phenotypes consist
of disconnected mutational networks) and (most
phenotypes can be reached in a small number of mutations). We also show that
the mutational robustness of phenotypes scales very roughly logarithmically
with phenotype redundancy and is positively correlated with phenotypic
evolvability. Although our GP map describes the assembly of disconnected
objects, it shares many properties with other popular GP maps for connected
units, such as models for RNA secondary structure or the HP lattice model for
protein tertiary structure. The remarkable fact that these important properties
similarly emerge from such different models suggests the possibility that
universal features underlie a much wider class of biologically realistic GP
maps.Comment: 12 pages, 6 figure
Cooperativity and Stability in a Langevin Model of Protein Folding
We present two simplified models of protein dynamics based on Langevin's
equation of motion in a viscous medium. We explore the effect of the potential
energy function's symmetry on the kinetics and thermodynamics of simulated
folding. We find that an isotropic potential energy function produces, at best,
a modest degree of cooperativity. In contrast, a suitable anisotropic potential
energy function delivers strong cooperativity.Comment: 45 pages, 16 figures, 2 tables. LaTeX. Submitted to the Journal of
Chemical Physic
Fast Tree Search for Enumeration of a Lattice Model of Protein Folding
Using a fast tree-searching algorithm and a Pentium cluster, we enumerated
all the sequences and compact conformations (structures) for a protein folding
model on a cubic lattice of size . We used two types of amino
acids -- hydrophobic (H) and polar (P) -- to make up the sequences, so there
were different sequences. The total number
of distinct structures was 84,731,192. We made use of a simple solvation model
in which the energy of a sequence folded into a structure is minus the number
of hydrophobic amino acids in the ``core'' of the structure. For every
sequence, we found its ground state or ground states, i.e., the structure or
structures for which its energy is lowest. About 0.3% of the sequences have a
unique ground state. The number of structures that are unique ground states of
at least one sequence is 2,662,050, about 3% of the total number of structures.
However, these ``designable'' structures differ drastically in their
designability, defined as the number of sequences whose unique ground state is
that structure. To understand this variation in designability, we studied the
distribution of structures in a high dimensional space in which each structure
is represented by a string of 1's and 0's, denoting core and surface sites,
respectively.Comment: 18 pages, 10 figure
Soft Computing Techiniques for the Protein Folding Problem on High Performance Computing Architectures
The protein-folding problem has been extensively studied during the last
fifty years. The understanding of the dynamics of global shape of a protein and the influence
on its biological function can help us to discover new and more effective
drugs to deal with diseases of pharmacological relevance. Different computational approaches
have been developed by different researchers in order to foresee the threedimensional
arrangement of atoms of proteins from their sequences. However, the
computational complexity of this problem makes mandatory the search for new models,
novel algorithmic strategies and hardware platforms that provide solutions in a
reasonable time frame. We present in this revision work the past and last tendencies
regarding protein folding simulations from both perspectives; hardware and software.
Of particular interest to us are both the use of inexact solutions to this computationally hard problem as
well as which hardware platforms have been used for running this kind of Soft Computing techniques.This work is jointly supported by the FundaciónSéneca (Agencia Regional de Ciencia y Tecnología, Región de Murcia) under grants 15290/PI/2010 and 18946/JLI/13, by the Spanish MEC and European Commission FEDER under grant with reference TEC2012-37945-C02-02 and TIN2012-31345, by the Nils Coordinated Mobility under grant 012-ABEL-CM-2014A, in part financed by the European Regional Development Fund (ERDF). We also thank NVIDIA for hardware donation within UCAM GPU educational and research centers.Ingeniería, Industria y Construcció
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