Structure optimization by heuristic algorithm in a coarse-grained off-lattice model |
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Authors: | Liu Jing-Fa |
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Institution: | Computer and Software Institute, Nanjing University of Information Science and Technology, Nanjing 210044, China |
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Abstract: | A heuristic algorithm is presented for a three-dimensional
off-lattice AB model consisting of hydrophobic (A) and hydrophilic
(B) residues in Fibonacci sequences. By incorporating extra energy
contributions into the original potential function, we convert the
constrained optimization problem of AB model into an unconstrained
optimization problem which can be solved by the gradient method.
After the gradient minimization leads to the basins of the local
energy minima, the heuristic off-trap strategy and subsequent
neighborhood search mechanism are then proposed to get out of local
minima and search for the lower-energy configurations. Furthermore,
in order to improve the efficiency of the proposed algorithm, we
apply the improved version called the new PERM with importance
sampling (nPERMis) of the chain-growth algorithm,
pruned-enriched-Rosenbluth method (PERM), to face-centered-cubic
(FCC)-lattice to produce the initial configurations. The numerical
results show that the proposed methods are very promising for
finding the ground states of proteins. In several cases, we found
the ground state energies are lower than the best values reported in
the present literature. |
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Keywords: | protein folding off-lattice
model heuristics FCC-lattice |
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