Abstract
The HP model is one of the most popular discretized models for the protein folding problem, i.e., for computationally predicting the three-dimensional structure of a protein from its amino acid sequence. This model considers the interactions between hydrophobic amino acids to be the driving force in the folding process. Thus, it distinguishes between polar and hydrophobic amino acids only and asks for an embedding of the amino acid sequence into a rectangular grid lattice which maximizes the number of neighboring pairs (contacts) of hydrophobic amino acids in the lattice.
In this paper, we consider an HP-like model which uses a more appropriate grid structure, namely the 2D triangular grid and the face-centered cubic lattice in 3D. We consider a local-search approach for finding an optimal embedding. For defining the local-search neighborhood, we design a move set, the so-called pull moves, and prove its reversibility and completeness. We then use these moves for a tabu search algorithm which is experimentally shown to lead into optimum energy configurations and improve the current best results for several sequences in 2D and 3D.
Research partially supported by EPSRC Grant No. EP/D062012/1.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Agarwala, R., Batzoglou, S., Dancik, V., et al.: Local rules for protein folding on a triangular lattice and generalized hydrophobicity in the HP model. In: Proc. SODA 1997, pp. 390–399 (1997)
Anfinsen, C.B.: Principles that govern the folding of protein chains. Science 181, 223–230 (1973)
Böckenhauer, H.-J., Bongartz, D.: Protein folding in the HP model on grid lattices with diagonals. Discrete Applied Mathematics 155, 230–256 (2007)
Bagci, Z., Jernigan, R.L., Bahar, I.: Residue coordination in proteins conforms to the closest packing of spheres. Polymer 43, 451–459 (2002)
Crescenzi, P., Goldman, D., Papadimitriou, C., et al.: On the complexity of protein folding. Journal of Computational Biology 5, 423–465 (1998)
Dill, K.A., Bromberg, S., Yue, K., et al.: Principles of protein folding - A perspective from simple exact models. Protein Sci. 4, 561–602 (1995)
Glover, F.: Tabu search. ORSA J. Comput. 1, 190–206 (1989)
Govindarajan, S., Goldstein, R.A.: On the thermodynamic hypothesis of protein folding. Proc. Natl. Acad. Sci. USA 95, 5545–5549 (1998)
Hart, W.E., Istrail, S.: Fast protein folding in the hydrophobic-hydrophilic model within three-eights of optimal. Journal of Computational Biology 3, 53–96 (1996)
Hart, W.E., Istrail, S.: Robust proofs of NP-hardness for protein folding: General lattices and energy potentials. Journal of Computational Biology 4, 1–22 (1997)
Krasnogor, N.: Studies on the Theory and Design Space of Memetic Algorithms. Doctoral Dissertation, University of the West of England, UK (2002)
Levinthal, C.: Are there pathways for protein folding? J. de Chimie Physique et de Physico-Chimie Biologique 65, 44–45 (1968)
Lesh, N., Mitzenmacher, M., Whitesides, S.: A complete and effective move set for simplified protein folding. In: Proc. RECOMB 2003, pp. 188–195 (2003)
Hoque, M.T., Chetty, M., Dooley, L.S.: A Hybrid Genetic Algorithm for 2D FCC Hydrophobic-Hydrophilic Lattice Model to Predict Protein Folding. In: Sattar, A., Kang, B.-h. (eds.) AI 2006. LNCS (LNAI), vol. 4304, pp. 867–876. Springer, Heidelberg (2006)
Hoque, M.T., Chetty, M., Sattar, A.: Protein Folding Prediction in 3D FCC HP Lattice using Genetic Algorithm. In: Proc. IEEE Congress on Evolutionary Computation 2007, pp. 4138–4145 (2007)
Sloane, N.J.A.: Kepler’s conjecture confirmed. Nature 395, 435–436 (1998)
Steinhöfel, K., Skaliotis, A., Albrecht., A.A.: Stochastic protein folding simulation in the d-Dimensional HP-Model. In: Hochreiter, S., Wagner, R. (eds.) BIRD 2007. LNCS (LNBI), vol. 4414, pp. 381–394. Springer, Heidelberg (2007)
Unger, R., Moult, J.: Genetic algorithms for protein folding simulations. J. Mol. Biol. 231, 75–81 (1993)
Zhang, Y., Skolnick, J.: Parallel-Hat Tempering: A Monte Carlo Search Scheme for the Identification of Low-Energy Structures. Journal of Chemical Physics 115, 5027–5032 (2000)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Böckenhauer, HJ., Dayem Ullah, A.Z.M., Kapsokalivas, L., Steinhöfel, K. (2008). A Local Move Set for Protein Folding in Triangular Lattice Models. In: Crandall, K.A., Lagergren, J. (eds) Algorithms in Bioinformatics. WABI 2008. Lecture Notes in Computer Science(), vol 5251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87361-7_31
Download citation
DOI: https://doi.org/10.1007/978-3-540-87361-7_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87360-0
Online ISBN: 978-3-540-87361-7
eBook Packages: Computer ScienceComputer Science (R0)