Energy landscape analysis for regulatory RNA finding using scalable distributed cyberinfrastructure

Concurrency and Computation: Practice and Experience

Volumn 23, Issue 17, 2011, Pages 2292-2304

  Kim, Joohyun ^a   Huang, Wei ^a   Maddineni, Sharath ^a   Aboul Ela, Fareed ^a   Jha, Shantenu ^a  

^a LOUISIANA STATE UNIVERSITY   (United States)

Author keywords

concurrent programming and distributed computing; ncRNA gene finding; Pilot Job abstraction; RNA folding energy landscape; Simple API for Grid Applications (SAGA)

Indexed keywords

AMINO ACIDS; APPLICATION PROGRAMMING INTERFACES (API); COMPUTER PROGRAMMING; GENES; MAMMALS; SENSITIVITY ANALYSIS; VIRUSES;

CONCURRENT PROGRAMMING; ENERGY LANDSCAPE; GENE FINDING; GRID APPLICATIONS; PILOT-JOB ABSTRACTION;

RNA;

EID: 80052327009     PISSN: 15320626     EISSN: 15320634     Source Type: Journal    
DOI: 10.1002/cpe.1796     Document Type: Article

References (43)

1. Serganov A, Patel DJ,. Ribozymes, riboswitches and beyond: regulation of gene expression without proteins. Nature Review Genetics 2007; 8: 776-790. (Pubitemid 47429208)
2. Joyce GF, Orgel LE, (, Gesteland RF, Cech TR, Atkins JF, eds). Cold Spring Harbor Laboratory Press: New York, 1999.
3. Cruz JA, Westhof E,. The dynamic landscapes of RNA architecture. Cell 2009; 136: 604-609.
4. Amaral PP, Dinger ME, et al,. The eukaryotic genome as an RNA machine. Science 2008; 319: 1787-1789. (Pubitemid 351451554)
5. Shapiro BA, Yingling YG, et al,. Bridging the gap in RNA structure prediction. Current Opinion in Structural Biology 2007; 17: 157-165. (Pubitemid 46575248)
6. Berman HM, Olson WK, et al,. The nucleic acid database: a comprehensive relational database of three-dimensional structures of nucleic acids. Biophysical Journal 1992; 63: 751-759.
7. Kennedy SD, Mathews DH, et al,. NMR-assisted prediction of RNA secondary structure: identification of a probable pseudoknot in the coding region of an R2 retrotransposon. Journal of the American Chemical Society 2008; 130: 10233-10239.
8. Collier AJ, Gallego J, et al,. A conserved RNA structure within the HCV IRES elF3-binding site. Nature Structure and Molecular Biology 2002; 9 (5): 375-380. (Pubitemid 34462557)
9. Ogle JM, Carter AP, et al,. Insights into the decoding mechanism from recent ribosome structures. Trends in Biochemical Sciences 2005; 28: 259-266. (Pubitemid 36588668)
10. Clark BFC,. The crystal structure of tRNA. Journal of Biosciences 2006; 31 (4): 453-457. (Pubitemid 44747513)
11. Robertus JD, Ladner JE, et al,. Correlation between three-dimensional structure and chemical reactivity of transfer RNA. Nucleir Acids Research 1974; 1 (7): 927-932.
12. Schmeing TM, Ramakrishnan V,. What recent ribosome structures have revealed about the mechanism of translation. Nature 2009; 461: 1234-1242.
13. Hyeon C, Thirumalai D,. Multiple Probes are required to explore and control the rugged energy landscape of RNA hairpins. Journal of the American Chemical Society 2008; 130: 1538-1539. (Pubitemid 351214055)
14. Shcherbakova I, Mitra S, et al,. Energy barriers, pathways and dynamics during folding of large, multi-domain RNAs. Current Opinion in Chemical Biology 2008; 12 (6): 655-666.
15. Mattick JS,. Deconstructing the dogma: a new view of the evolution and genetic programming of complex organisms. Annals of the New York Academy of Sciences 2009; 1178: 29-46.
16. Dambach MD, Winkler WC,. Expanding roles for metabolite-sensing regulatory RNAs. Current Opinion in Microbiology 2009; 12: 161-169.
17. Montange RK, Batey RT,. Riboswitches: emerging themes in RNA structure and function. Annual Review of Biophysics 2008; 37: 117-133.
18. Onuchic JN, Wolynes PG,. Theory of protein folding: the energy landscape perspective. Annual Review of Physical Chemistry 1997; 48: 543-600.
19. Wolynes PG,. Landscape, funnels, glasses, and folding: from metaphor to software. Proceedings of American Philosophical Society 2001; 145 (4): 555-563.
20. Cupal J, Flamm C, et al,. Density of states, metastable states, and saddle points exploring the energy landscape of an RNA molecule. Proc Int Conf Intell Syst Mol Biol 1997; 5: 88-91.
21. Chen S, Dill KA,. RNA folding energy landscapes. Proceedings of the National Academy of Science, USA 2000; 97 (2): 646-651. (Pubitemid 30070363)
22. Solomatin S, Greenfeld M, et al,. Multiple native states reveal persistent ruggedness of an RNA folding landscape. Nature 2010; 463: 681-684.
23. Bonhoeffer S, McCaskill JS, et al,. RNA multi-structure landscapes: a study based on temperature partition functions. European Biophyics Journal 1993; 22: 13-24. (Pubitemid 23233150)
24. Nawrocki EP, Kolbe DL, et al,. Infernal 1.0: inference of RNA alignments. Bioinformatics 2009; 25: 1335-1337.
25. Huang W, Kim J, et al,. A mechanism for S-adenosyl methionine assisted formation of a riboswitch conformation: a small molecule with a strong arm. Nucleic Acids Research 2009; 37 (19): 6528-6539.
26. Tomsic J, McDaniel BA, et al,. Natural variability in S-adenosylmethionine (SAM)-dependent riboswitches: S-Box elements in Bacillus subtilis exhibit differential sensitivity to SAM in vivo and in vitro. Journal of Bacteriology 2008; 190: 823-833. (Pubitemid 351170925)
27. Chouljenko VN, Lin XQ, et al,. Comparison of genomic and predicted amino acid sequences of respiratory and enteric bovine coronaviruses isolated from the same animal with fatal shipping pneumonia. Journal of General Virology 2001; 82: 2927-2933. (Pubitemid 33107506)
28. Chouljenko VN, Kousoulas KG,. Private communication, 2010.
29. Luckow A, Jha S, et al.Adaptive distributed replica-exchange simulations. Philosophical Transactions of the Royal Society A: Mathematical,Physical and Engineering Sciences 2009; 367 (1897): 2595-2606.
30. Luckow A, Lacinski L, et al,. SAGA BigJob: an extensible and interoperable Pilot-Job abstraction for distributed applications and systems. In The 10th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, 2010.
31. Luckow A, Jha S,. Abstractions for Loosely-Coupled and Ensemble-based Simulations on Microsoft Azure. accepted for IEEE CloudCom (Dec 2010).
32. McCaskill JS,. The equilibrium partition function and base pair binding probabilities for RNA secondary structure. Biopolymers 1990; 29: 1105-1119. (Pubitemid 20145703)
33. Mathews DH, Turner DH,. Prediction of RNA secondary structure by free energy minimization. Current Opinion in Structural Biology 2006; 16 (3): 270-278. (Pubitemid 43831654)
34. Ding Y,. Statistical and Bayesian approaches to RNA secondary structure prediction. RNA 2006; 12 (3): 323-331. (Pubitemid 43290860)
35. Ding Y, Chan CY, et al,. Sfold web server for statistical folding and rational design of nucleic acids. Nucleic Acids Research 2004; 32: W135-W141. (Pubitemid 38997315)
36. Montange RK, Batey RT,. Structure of the S-adenosylmethionine riboswitch regulatory mRNA element. Nature 2006; 441: 1172-1175. (Pubitemid 43990740)
37. Montange RK, Mondragõn E, et al,. Discrimination between closely related cellular metabolites by the SAM-I riboswitch. Journal of Molecular Biology 2009. available online.
38. Ding Y, Lawrence CE,. A statistical sampling algorithm for RNA secondary structure prediction. Nucleic Acids Res. 2003; 31: 7280-7301. (Pubitemid 38008457)
39. Kim J, Huang W, et al,. Exploring the RNA Folding Energy Landscape Using Scalable Distributed Cyberinfrastructure. In ACM International Symposium on High Performance Distributed Computing (HPDC2010), June 2010.
40. Ko S, Kim N, et al,. Efficient Runtime Environment for Coupled Multi-Physics Simulations: Dynamic Resource Allocation and Load-Balancing. accepted in IEEE CCGrid 2010.
41. Stoddard CD, Montange RK, et al,. Free state conformational sampling of the SAM-I riboswitch aptamer domain. Structure 2010; 18: 787-797.
42. Reuter JS, Mathews DH,. RNAstructure: software for RNA secondary structure prediction and analysis. BMC Bioinformatics 2010; 11: 129.
43. Gruber AR, Lorenz R, et al,. The Vienna RNA websuite. Nucleir Acids Research 2008; 36: W70-W74.