Abstract
We propose a novel robotics-inspired algorithm to compute physically-realistic motions connecting thermodynamically-stable and semi-stable structural states in protein molecules. Protein motion computation is a challenging problem due to the high-dimensionality of the search space involved and ruggedness of the potential energy surface underlying the space. To handle the multiple local minima issue, we propose a novel algorithm that is not based on the traditional Molecular Dynamics or Monte Carlo frameworks but instead adapts ideas from robot motion planning. In particular, the algorithm balances computational resources between a global search aimed at obtaining a global view of the network of protein conformations and their connectivity and a detailed local search focused on realizing such connections with physically-realistic models. We present here promising results on a variety of proteins and demonstrate the general utility of the algorithm and its capability to improve the state of the art without employing system-specific insight.
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
Jenzler-Wildman, K., Kern, D.: Dynamic personalities of proteins. Nature 450, 964–972 (2007)
Wong, C.F., McCammon, J.A.: Protein simulation and drug design. Adv. Protein Chem. 66, 87–121 (2003)
Merkx, M., Golynskiy, M.V., Lindenburg, L.H., Vinkenborg, J.L.: Rational design of FRET sensor proteins based on mutually exclusive domain interactions. Biochem. Soc. Trans. 41, 128–134 (2013)
Amaro, R.E., Bansai, M.: Editorial overview: Theory and simulation: Tools for solving the insolvable. Curr. Opinion Struct. Biol. 25, 4–5 (2014)
Singh, A.P., Latombe, J.C., Brutlag, D.L.: A motion planning approach to flexible ligand binding. In: Schneider, R., Bork, P., Brutlag, D.L., Glasgow, J.I., Mewes, H.W., Zimmer, R. (eds.) Proc. Int. Conf. Intell. Sys. Mol. Biol (ISMB), vol. 7, pp. 252–261. AAAI, Heidelberg (1999)
Amato, N.M., Dill, K.A., Song, G.: Using motion planning to map protein folding landscapes and analyze folding kinetics of known native structures. J. Comp. Biol. 10, 239–255 (2002)
Thomas, S., Song, G., Amato, N.: Protein folding by motion planning. Physical Biology S148–S155 (2005)
Thomas, S., Tang, X., Tapia, L., Amato, N.M.: Simulating protein motions with rigidity analysis. J. Comput. Biol. 14, 839–855 (2007)
Tapia, L., Tang, X., Thomas, S., Amato, N.: Kinetics analysis methods for approximate folding landscapes. Bioinformatics 23, i539–i548 (2007)
Tapia, L., Thomas, S., Amato, N.: A motion planning approach to studying molecular motions. Communications in Information Systems 10, 53–68 (2010)
Haspel, N., Moll, M., Baker, M.L., Chiu, W., Kavraki, L.E.: Tracing conformational changes in proteins. BMC Struct. Biol. 10, S1 (2010)
Luo, D., Haspel, N.: Multi-resolution rigidity-based sampling of protein conformational paths. In: Proc. of ACM-BCB (ACM International Conference on Bioinformatics and Computational Biology), CSBW (Computational Structural Bioinformatics Workshop), pp. 787–793 (2013)
Cortés, J., Simeon, T., de Angulo, R., Guieysse, D., Remaud-Simeon, M., Tran, V.: A path planning approach for computing large-amplitude motions of flexible molecules. Bioinformatics 21, 116–125 (2005)
Jaillet, L., Corcho, F.J., Perez, J.J., Cortés, J.: Randomized tree construction algorithm to explore energy landscapes. J. Comput. Chem. 32, 3464–3474 (2011)
Al-Bluwi, I., Vaisset, M., Siméon, T., Cortés, J.: Modeling protein conformational transitions by a combination of coarse-grained normal mode analysis and robotics-inspired methods. BMC Structural Biology 13, S8 (2013)
Molloy, K., Shehu, A.: Elucidating the ensemble of functionally-relevant transitions in protein systems with a robotics-inspired method. BMC Struct. Biol. 13, S8 (2013)
Nielsen, C., Kavraki, L.: A two level fuzzy prm for manipulation planning. In: Proceedings of the 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2000, vol. 3, pp. 1716–1721 (2000)
McLachlan, A.D.: A mathematical procedure for superimposing atomic coordinates of proteins. Acta Crystallogr. A. 26, 656–657 (1972)
Yen, J.Y.: Finding the k shortest loop less paths in a network. Management Science 17, 712–716 (1971)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Molloy, K., Shehu, A. (2015). Interleaving Global and Local Search for Protein Motion Computation. In: Harrison, R., Li, Y., Măndoiu, I. (eds) Bioinformatics Research and Applications. ISBRA 2015. Lecture Notes in Computer Science(), vol 9096. Springer, Cham. https://doi.org/10.1007/978-3-319-19048-8_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-19048-8_15
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19047-1
Online ISBN: 978-3-319-19048-8
eBook Packages: Computer ScienceComputer Science (R0)