A hybrid approach to protein folding problem integrating constraint programming with local search.

BMC Bioinformatics
Abu Dayem Ullah, Kathleen Steinhöfel

Abstract

The protein folding problem remains one of the most challenging open problems in computational biology. Simplified models in terms of lattice structure and energy function have been proposed to ease the computational hardness of this optimization problem. Heuristic search algorithms and constraint programming are two common techniques to approach this problem. The present study introduces a novel hybrid approach to simulate the protein folding problem using constraint programming technique integrated within local search. Using the face-centered-cubic lattice model and 20 amino acid pairwise interactions energy function for the protein folding problem, a constraint programming technique has been applied to generate the neighbourhood conformations that are to be used in generic local search procedure. Experiments have been conducted for a few small and medium sized proteins. Results have been compared with both pure constraint programming approach and local search using well-established local move set. Substantial improvements have been observed in terms of final energy values within acceptable runtime using the hybrid approach. Constraint programming approaches usually provide optimal results but become slow as the problem size ...Continue Reading

References

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Citations

Jun 28, 2014·Biomolecules·Brian MaherKathleen Steinhöfel
Nov 14, 2013·BioMed Research International·Mahmood A RashidAbdul Sattar
Feb 16, 2016·Computational Biology and Chemistry·Mahmood A RashidAbdul Sattar
Jul 8, 2015·International Journal of Molecular Sciences·Jyh-Jong TsayChin-Sheng Yu
Sep 12, 2015·Royal Society Open Science·Ahammed UllahM Sohel Rahman
May 31, 2014·Advances in Bioinformatics·Swakkhar ShatabdaAbdul Sattar
Apr 20, 2014·Advances in Bioinformatics·Mahmood A RashidAbdul Sattar

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Methods Mentioned

BETA
protein folding
NMR

Software Mentioned

Linux CentOS
COLA
gcc
CPSP

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