This article presents an efficient heuristic for protein folding. The protein folding problem is to predict the compact three-dimensional structure of a protein based on its amino acid sequence. The focus is on an original integer programming model derived from a platform used for Contact Map Overlap problem.
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References
1.
AhnN., and ParkS.2010. Finding an upper bound for the number of contacts in hydrophobic-hydrophilic protein structure prediction model. J. Comput. Biol., 17, 647–656.
2.
AlbertsB., BrayD., JohnsonA., et al.1998. Essential Cell Biology: An Introduction to the Molecular Biology of the Cell. Garland Science Publishing, New York.
3.
BergerB., and LeightonT.1998. Protein folding in the hydrophobic-hydrophilic (hp) is np-complete. J. Comput. Biol., 5, 27–40.
4.
CarrR., HartW., and NewmanA.2003. Discrete optimization models for protein folding. Technical Report SAND2002. Sandia National Laboratories.
5.
ChenM., and HuangW.2005. A branch and bound algorithm for the protein folding problem in the HP Lattice Model. Genomics Proteomics Bioinformatics, 3, 225–230.
6.
ChandruV., RaoM., and SwaminathanG.2004. Protein folding on lattices: An integer programming approach. IIM Bangalore Research Paper No. 199.
7.
DillK.A.1985. Theory for the folding and stability of globular proteins. Biochemistry, 24, 1501–1509.
8.
DillK.A., BrombergS., YueK., et al.1995. Principles of protein folding. A perspective from simple exact models. Protein Sci. 4, 561–602.
9.
DuanY., and KollmanP.2001. Computational protein folding: From lattice to all-atom. IBM Syst. J., 40, 297–309.
10.
IstrailS., HurdA., LippertR., WalenzB., et al.2000. Prediction of self-assembly of energetic tiles and dominoes: Experiments, mathematics, and software. Technical Report SAND2002. Sandia National Laboratories.
11.
IstrailS., and LamF.2009. Combinatorial algorithms for protein folding in lattice models: A survey of mathematical results. Commun. Inf. Syst., 9, 303–346.
12.
JiangM., and ZhuB.2005. Protein folding in the hexagonal lattice in the hp model, J. Bioinform. Comput. Biol., 3, 19–34.
13.
Malod-DogninN., AndonovR., and YanevN.2008. Maximum cliques in protein structure comparison. 106–117. In: Experimental Algorithms, Lect. Notes. Comput. Sc. 6049.Springer-Verlag, Berlin.
14.
MichalewiczZ., and FogelD., 2004. How to Solve It: Modern Heuristics. Springer-Verlag, Berlin.
15.
ThachukC., ShmygelskaA., and HoosH. H.2007. A replica exchange Monte Carlo algorithm for protein folding in the HP model, BMC Bioinformatics, 8, 342–362.
16.
TomaL., and TomaS.1996. Contact interactions method: A new algorithm for protein folding simulations. Protein Sci. 5, 147–153.
17.
YanevN., AndonovR., VeberPh., et al.2008. Lagrangian approaches for a class of matching problems in computational biology. Comput. Math. Appl., 55, 1054–1067.
18.
YoonH.2006. Optimization approaches to protein folding [PhD Thesis]. School of Industrial and System Engineering, Institute of Technology, Georgia.
