Abstract
This paper proposes an approach to the protein structure prediction (PSP) problem that inserts solutions provided by template-modeling procedures as individuals in the population of a multi-objective evolutionary algorithm. This way, our procedure represents a hybrid approach that takes advantage of previous knowledge about the known protein structures to improve the effectiveness of an ab initio procedure for the PSP problem. Moreover, the procedure benefits from a parallel and distributed implementation that allows faster and wider exploration of the conformation space. The experimental results obtained from the present implementation of our procedure show improvements with respect to previously proposed procedures in the proteins selected as benchmarks from the CASP8 set (up to 28% of RMSD improvement with respect to TASSER).
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References
Cutello, V., Narcisi, G., Nicosia, G.: A multi-objetive evolutionary approach to the protein structure prediction problem. J. R. Soc. Interface 3, 139–151 (2006)
Zhang, Y., Skolnick, J.: The protein structure prediction problem could be solved using the current pdb library. Proc. Natl. Acad. Sci. USA 102, 1029–1034 (2005)
Handl, J., Kell, D., Knowles, J.: Multiobjective optimization in bioinformatics and computational biology. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) 4(2), 279–292 (2007)
Rychlewski, L., Jaroszewski, L., Li, W., Godzik, A.: Comparison of sequence profiles. strategies for structural predictions using sequence information. Protein Science 9, 232–241 (2000)
Rohl, C., Strauss, C., Misura, K., Baker, D.: Protein structure prediction using rosetta. Methods in Enzymology 383, 66–93 (2004)
Raman, S., et al.: Advances in rosetta protein structure prediction on massivelly parallel systems. IBM J. Res. & Dev. 52(1/2) (2008)
Taufer, M., An, C., Kerstens, A., Brooks, C.: Predictor@home: A ’protein structure prediction supercomputer’ based on global computing. IEEE Transactions on Parallel and Distributed Systems 17(8), 786–796 (2006)
Bradley, P., Misura, K., Baker, D.: Toward high-resolution de novo structure prediction for small proteins. Science 309, 1868–1871 (2005)
Anderson, D.: Boinc: A system for public-resource computing and storage. In: Proc. Fifth IEEE/ACM Int’l Workshop Grid Computing (2004)
Sun, Z., Jiang, B.: Patterns and conformations of commonly occurring supersecondary structures (basic motifs) in protein data bank. Journal of Protein Chemistry 15(7) (1996)
Dunbrack, R.: Rotamer libraries in the 21st century. Curr. Opin. Struct. Biol. 12, 431–440 (2002)
Wu, S., Skolnick, J., Zhang, Y.: Ab initio modelling of small proteins by iterative tasser simulations. BMC Biol. 5 (2007)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: Nsga-ii. IEEE Trans. on Evol. Comp. 6, 182–197 (2002)
Day, R., Zydallis, J., Lamont, G.: Solving the protein structure prediction problem through a multiobjective genetic algorithm. Nanotech 2, 32–35 (2002)
Tantar, A.-A., Melab, N., Talbi, E.-G., Parent, B., Horvath, D.: A parallel hybrid genetic algorithm for protein structure prediction on the computational grid. Future Generation Computer Systems 23, 398–409 (2007)
Veldhuizen, D.V., Zidallis, J., Lamont, G.: Considerations in engineering parallel multiobjetive evolutionary algorithms. IEEE Transactions on Evolutionary Computation 7(2) (2003)
Calvo, J., Ortega, J., Anguita, M.: Comparison of parallel multi-objective approaches to protein structure prediction. The Journal of Supercomputing (2009)
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Calvo, J.C., Ortega, J., Anguita, M. (2010). A Hybrid Scheme to Solve the Protein Structure Prediction Problem. In: Rocha, M.P., Riverola, F.F., Shatkay, H., Corchado, J.M. (eds) Advances in Bioinformatics. Advances in Intelligent and Soft Computing, vol 74. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13214-8_30
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DOI: https://doi.org/10.1007/978-3-642-13214-8_30
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