1,572 research outputs found
A Hybrid Monte Carlo Ant Colony Optimization Approach for Protein Structure Prediction in the HP Model
The hydrophobic-polar (HP) model has been widely studied in the field of
protein structure prediction (PSP) both for theoretical purposes and as a
benchmark for new optimization strategies. In this work we introduce a new
heuristics based on Ant Colony Optimization (ACO) and Markov Chain Monte Carlo
(MCMC) that we called Hybrid Monte Carlo Ant Colony Optimization (HMCACO). We
describe this method and compare results obtained on well known HP instances in
the 3 dimensional cubic lattice to those obtained with standard ACO and
Simulated Annealing (SA). All methods were implemented using an unconstrained
neighborhood and a modified objective function to prevent the creation of
overlapping walks. Results show that our methods perform better than the other
heuristics in all benchmark instances.Comment: In Proceedings Wivace 2013, arXiv:1309.712
Is protein folding problem really a NP-complete one ? First investigations
To determine the 3D conformation of proteins is a necessity to understand
their functions or interactions with other molecules. It is commonly admitted
that, when proteins fold from their primary linear structures to their final 3D
conformations, they tend to choose the ones that minimize their free energy. To
find the 3D conformation of a protein knowing its amino acid sequence,
bioinformaticians use various models of different resolutions and artificial
intelligence tools, as the protein folding prediction problem is a NP complete
one. More precisely, to determine the backbone structure of the protein using
the low resolution models (2D HP square and 3D HP cubic), by finding the
conformation that minimize free energy, is intractable exactly. Both the proof
of NP-completeness and the 2D prediction consider that acceptable conformations
have to satisfy a self-avoiding walk (SAW) requirement, as two different amino
acids cannot occupy a same position in the lattice. It is shown in this
document that the SAW requirement considered when proving NP-completeness is
different from the SAW requirement used in various prediction programs, and
that they are different from the real biological requirement. Indeed, the proof
of NP completeness and the predictions in silico consider conformations that
are not possible in practice. Consequences of this fact are investigated in
this research work.Comment: Submitted to Journal of Bioinformatics and Computational Biology,
under revie
Hydrophobicity and Unique Folding of Selected Polymers
In suitable environments, proteins, nucleic acids and certain synthetic
polymers fold into unique conformations. This work shows that it is possible to
construct lattice models of foldable heteropolymers by expressing the energy
only in terms of individual properties of monomers, such as the exposure to the
solvent and the steric factor.Comment: 5 pages, RevTe
Sequential Monte Carlo Methods for Protein Folding
We describe a class of growth algorithms for finding low energy states of
heteropolymers. These polymers form toy models for proteins, and the hope is
that similar methods will ultimately be useful for finding native states of
real proteins from heuristic or a priori determined force fields. These
algorithms share with standard Markov chain Monte Carlo methods that they
generate Gibbs-Boltzmann distributions, but they are not based on the strategy
that this distribution is obtained as stationary state of a suitably
constructed Markov chain. Rather, they are based on growing the polymer by
successively adding individual particles, guiding the growth towards
configurations with lower energies, and using "population control" to eliminate
bad configurations and increase the number of "good ones". This is not done via
a breadth-first implementation as in genetic algorithms, but depth-first via
recursive backtracking. As seen from various benchmark tests, the resulting
algorithms are extremely efficient for lattice models, and are still
competitive with other methods for simple off-lattice models.Comment: 10 pages; published in NIC Symposium 2004, eds. D. Wolf et al. (NIC,
Juelich, 2004
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