Abstract
The prediction of a protein’s conformation from its amino-acid sequence is one of the most prominent problems in computational biology. Here, we focus on a widely studied abstraction of this problem, the two dimensional hydrophobic-polar (2D HP) protein folding problem. We introduce an ant colony optimisation algorithm for this NP-hard combinatorial problem and demonstrate its ability to solve standard benchmark instances. Furthermore, we empirically study the impact of various algorithmic features and parameter settings on the performance of our algorithm. To our best knowledge, this is the first application of ACO to this highly relevant problem from bioinformatics; yet, the performance of our ACO algorithm closely approaches that of specialised, state-of-the methods for 2D HP protein folding.
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Bastolla U., H. Fravenkron, E. Gestner, P. Grassberger, and W. Nadler. Testing New Monte Carlo algorithm for the protein folding problem. Proteins-Structure Function and Genetics 32 (1): 52–66, 1998.
Beutler T., and K. Dill. A fast conformational search strategy for finding low energy structures of model proteins. Protein Science (5), pp. 2037–2043, 1996.
Dorigo, M., V. Maniezzo, and A. Colorni. Positive feedback as a search strategy. Technical Report 91-016, Dip. Elettronica, Politecnico di Milano, Italy, 1991.
Dorigo, M. and G. Di Caro. The ant colony optimization meta-heuristic. In New Ideas in Optimization, pp. 11–32. McGraw-Hill, 1999.
Dorigo, M., G. Di Caro and L.M. Gambardella. Ant Algorithms for Discrete Optimization. Artificial Life, 5,2, pp. 137–172, 1999.
Hoos, H.H., and T. Stützle. On the empirical evaluation of Las Vegas algorithms. Proc. of UAI-98, Morgan Kaufmann Publishers, 1998. IEICE Trans. Fundamentals, Vol. E83-A:2,Feb. 2000.
Krasnogor, N., D. Pelta, P. M. Lopez, P. Mocciola, and E. de la Canal. Genetic algorithms for the protein folding problem: a critical view. In C.F.E. Alpaydin, ed., Proc. Engineering of Intelligent Systems. ICSC Academic Press, 1998.
Krasnogor, N., W.E. Hart. J. Smith, and D.A. Pelta. Protein structure prediction with evolutionary algorithms. Proceedings of the genetic & evolutionary computation conference, 1999.
Lau, K.F., and K.A. Dill. A lattice statistical mechanics model of the conformation and sequence space of proteins. Macromolecules 22:3986–3997, 1989.
Patton, A.W.P. III, and E. Goldman. A standard GA approach to native protein conformation prediction. In Proc. 6th Intl. Conf Genetic Algorithms, pp. 574–581. Morgan Kauffman, 1995.
Liang F., and W.H. Wong. Evolutionary Monte Carlo for protein folding simulations. J. Chem. Phys. 115 (7), pp. 3374–3380, 2001.
Ramakrishnan R., B. Ramachandran, and J.F. Pekny. A dynamic Monte Carlo algorithm for exploration of dense conformational spaces in heteropolymers. J. Chem. Phys. 106 (6), 8 February, pp. 2418–2424, 1997.
Richards, F. M. Areas, volumes, packing, and protein structures. Annu. Rev. Biophys. Bioeng. 6:151–176, 1977.
Rose, G. D. Hierarchic organization of domains in globular proteins. J. Mol. Biol. 134:447–470, 1979.
Sali, A., E. Shakhnovich and M. Karplus, How Does a Protein Fold? Nature, 369, pp. 248–251, May 1994.
Stützle, T., and H.H. Hoos. Improvements on the ant system: Introducing MAXMIN ant system. In Proc. Intel. Conf. on Artificial Neural Networks and Genetic Algorithms, pp. 245–249. Springer Verlag, 1997.
Unger, R., and J. Moult. A genetic algorithm for three dimensional protein folding simulations. In Proc. 5th Intl. Conf. on Genetic Algorithms, pp. 581–588. Morgan Kaufmann, 1993.
Unger, R., and J. Moult. Genetic algorithms for protein folding simulations. J. of Molecular Biology 231 (1): 75–81, 1993.
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Shmygelska, A., Aguirre-Hernández, R., Hoos, H.H. (2002). An Ant Colony Optimization Algorithm for the 2D HP Protein Folding Problem. In: Dorigo, M., Di Caro, G., Sampels, M. (eds) Ant Algorithms. ANTS 2002. Lecture Notes in Computer Science, vol 2463. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45724-0_4
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DOI: https://doi.org/10.1007/3-540-45724-0_4
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