Dong Luo
ABSTRACT
We present a geometry-based, sampling based method to explore conformational pathways in medium and large proteins which undergo large-scale conformational transitions. In a past work we developed a coarse-grained geometry-based method that was able to trace large-scale conformational motions in proteins using residues between secondary structure elements as hinges, and a simple yet effective energy function. In this work we apply a rigidity-analysis tool to determine the rigid and flexible regions in protein structures, since hinges may not always lie on loops between secondary structure elements. This method allows for better accuracy in determining the rotational degrees of freedom of the proteins. We conducted a multi-resolution search scheme, as both C-α and backbone representations are used for sampling the protein conformational paths. Characteristic conformations detected by clustering the paths are converted to full atom protein structures and minimized to detect interesting intermediate conformations that may correspond to transition states or other events. Our algorithm was able to run efficiently on a proteins of various sizes and the results agree with experimentally determined intermediate protein structures.
- I. Al-Bluwi, M. Vaisset, T. Simeon, and J. Cortes. Coarse-grained elastic networks, normal mode analysis and robotics-inspired methods for modeling protein conformational transitions. In proc. of Comput Struct Bioinf. Workshop (CSBW), pages 40--47, Philadelphia, PA, October 2012. Google Scholar
Digital Library
- M. S. Apaydin, D. L. Brutlag, C. Guestrin, D. Hsu, and J.-C. Latombe. Stochastic conformational roadmaps for computing ensemble properties of molecular motion. In J. D. Boissonnat, J. Burdick, K. Goldberg, and S. Hutchinson, editors, Algorithmic Foundations of Robotics V, pages 131--147. Springer, 2004.Google ScholarCross Ref
- D. A. Case, T. Cheatham, T. Darden, H. Gohlke, R. Luo, K. M. Merz Jr., A. Onufriev, C. Simmerling, B. Wang, and R. Woods. The Amber biomolecular simulation programs. J. Computat. Chem., 26:1668--1688, 2005.Google ScholarCross Ref
- J. Cortés, T. Siméon, V. R. de Angulo, D. Guieysse, M. Remauld-Siméon, and V. Tran. A path planning approach for computing large-amplitude motions of flexible molecules. Bioinformatics, 21 Suppl. 1:i116--i125, 2005. Google ScholarDigital Library
- A. Dhanik, P. Yao, N. Marz, R. Propper, C. Kou, G. L. H. van den Bedem, and J.-C. Latombe. Efficient algorithms to explore conformation spaces of flexible protein loops. In 7th Workshop on Algorithms in Bioinformatics (WABI), pages 265--276, Philadelphia, PA, September 2007. Google ScholarDigital Library
- Y. Duan, C. Wu, S. Chowdhury, M. Lee, G. Xiong, W. Zhang, R. Yang, P. Cieplak, R. Luo, and T. Lee. A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations. J. Comput. Chem., 24:1999--2012, 2003.Google ScholarCross Ref
- Y. Feng, L. Yang, A. Kloczkowski, and R. Jernigan. The energy profiles of atomic conformational transition intermediates of adenylate kinase. Proteins, 77(3):551--558, 2009.Google ScholarCross Ref
- N. Fox, F. Jagodzinski, Y. Li, and I. Streinu. KINARI-Web: A server for protein rigidity analysis. Nucleic Acids Research, 39 (Web Server Issue):W177--W183, 2011.Google Scholar
- M. Gerstein, A. M. Lesk, and C. Chothia. Structural mechanisms for domain movements in proteins. Biochemistry, 33:6739--6749, 1994.Google ScholarCross Ref
- N. Haspel, M. Moll, M. Baker, W. Chiu, and L. E. Kavraki. Tracing conformational changes in proteins. BMC Structural Biology, Suppl1:S1, 2010.Google ScholarCross Ref
- A. P. Heath, L. E. Kavraki, and C. Clementi. From coarse-grain to all-atom: Toward multiscale analysis of protein landscapes. Proteins: Structure, Function and Bioinformatics, 68(3):646--661, August 2007.Google ScholarCross Ref
- L. J. Heyer, S. Kruglyak, and S. Yooseph. Exploring expression data: Identification and analysis of coexpressed genes. Genome Research, 9(11):1106--1115, 1999.Google ScholarCross Ref
- W. Humphrey, A. Dalke, and K. Schulten. VMD - Visual Molecular Dynamics. 14(1):33--38, 1996. http://www.ks.uiuc.edu/Research/vmd/.Google Scholar
- D. Jacobs and B. Hendrickson. An algorithms for two-dimensional rigidity percolation: the pebble game. Journal of Computational Physics, 137:346--365, 1997. Google ScholarDigital Library
- D. Jacobs and M. Thorpe. Generic rigidity percolation: the pebble game. Physics Review Letters, 75:4051--4054, 1995.Google ScholarCross Ref
- F. Jagodzinski, J. Hardy, and I. Streinu. Using rigidity analysis to probe mutation-induced structural changes in proteins. Journal of Bioinformatics and Computational Biology, 10(3), 2012.Google ScholarCross Ref
- H. Jónsson, G. Mills, and K. W. Jacobsen. Nudged elastic band method for finding minimum energy paths of transitions. In B. J. Berne, G. Ciccoti, and D. F. Coker, editors, Classical and Quantum Dynamics in Condensed Phase Simulations, pages 385--404. World Scientific, Singapore, 1998.Google ScholarCross Ref
- G. G. Krivov, M. V. Shapovalov, and R. L. Dunbrack. Improved prediction of protein side-chain conformations with scwrl4. Proteins: Structure, Function, and Bioinformatics, 77(4):778--795, 2009.Google Scholar
- D. Luo and N. Haspel. Efficient coarse-grained geometry-based sampling of protein conformational paths. In Proc. of the 5th international conference on Bioinformatics and Computational Biology (BiCOB), Honolulu, HI, March 2013.Google Scholar
- K. Molloy and A. Shehu. A robotics-inspired method to sample conformational paths connecting known functionally-relevant structures in protein systems. In proc. of Comput Struct Bioinf. Workshop (CSBW), pages 56--63, Philadelphia, PA, October 2012. Google ScholarDigital Library
- H. N. Tracing conformational changes in proteins represented at a coarse level. In Proc. of the 5th international conference on Bio-Inspired Models of Network, Information, and Computing Systems (BIONETICS), pages 343--356, Boston MA, USA, December 2010. Springer.Google Scholar
- G. A. Papoian, J. Ulander, M. P. Eastwood, Z. Luthey-Schulten, and P. G. Wolynes. Water in protein structure prediction. Proc. Natl. Acad. Sci. USA, 101(10):3352--3357, 2004.Google ScholarCross Ref
- B. Raveh, A. Enosh, O. Furman-Schueler, and D. Halperin. Rapid sampling of molecular motions with prior information constraints. Plos Comp. Biol., 5(2):e1000295, 2009.Google ScholarCross Ref
- G. Schroeder, A. T. Brunger, and M. Levitt. Combining efficient conformational sampling with a deformable elastic network model facilitates structure refinement at low resolution. Structure, 15:1630--1641, 2007.Google ScholarCross Ref
- A. Shehu, L. Kavraki, and C. Clementi. Multiscale characterization of protein conformational ensembles. Proteins: Structure, Function and Bioinformatics, 2009.Google Scholar
- E. Yap, N. Fawzi, and T. Head-Gordon. A coarse-grained alpha-carbon protein model with anisotropic hydrogen-bonding. Proteins: Structure, function and bioinformatics, 70:626--638, 2008.Google Scholar
- W. Zheng and B. Brooks. Identification of dynamical correlations within the myosin motor domain by the normal mode analysis of an elastic network model. J. Mol. Biol., 346(3):745--759, 2005.Google ScholarCross Ref
- Multi-Resolution Rigidity-Based Sampling of Protein Conformational Paths
Recommendations
An Evolutionary Conservation & Rigidity Analysis Machine Learning Approach for Detecting Critical Protein Residues
BCB'13: Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical InformaticsIn proteins, certain amino acids may play a critical role in determining their structure and function. Examples include flexible regions which allow domain motions, and highly conserved residues on functional interfaces which play a role in binding and ...
An analysis of conformational changes upon RNA-protein binding
BCB '14: Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health InformaticsRNA-binding proteins (RBPs) have myriad functions in transcription, translation, and post-transcriptional gene regulation, with central roles in normal development as well as in both genetic and infectious diseases. When a protein binds RNA, a ...
Off-lattice protein structure prediction with homologous crossover
GECCO '13: Proceedings of the 15th annual conference on Genetic and evolutionary computationAb-initio structure prediction refers to the problem of using only knowledge of the sequence of amino acids in a protein molecule to find spatial arrangements, or conformations, of the amino-acid chain capturing the protein in its biologically-active or ...
Comments