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Folding and Finding RNA Secondary Structure

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Date 2010 Aug 6
PMID 20685845
Citations 84
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Abstract

Optimal exploitation of the expanding database of sequences requires rapid finding and folding of RNAs. Methods are reviewed that automate folding and discovery of RNAs with algorithms that couple thermodynamics with chemical mapping, NMR, and/or sequence comparison. New functional noncoding RNAs in genome sequences can be found by combining sequence comparison with the assumption that functional noncoding RNAs will have more favorable folding free energies than other RNAs. When a new RNA is discovered, experiments and sequence comparison can restrict folding space so that secondary structure can be rapidly determined with the help of predicted free energies. In turn, secondary structure restricts folding in three dimensions, which allows modeling of three-dimensional structure. An example from a domain of a retrotransposon is described. Discovery of new RNAs and their structures will provide insights into evolution, biology, and design of therapeutics. Applications to studies of evolution are also reviewed.

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References
1.
Harmanci A, Sharma G, Mathews D . Stochastic sampling of the RNA structural alignment space. Nucleic Acids Res. 2009; 37(12):4063-75. PMC: 2709569. DOI: 10.1093/nar/gkp276. View

2.
Disney M, Childs-Disney J . Using selection to identify and chemical microarray to study the RNA internal loops recognized by 6'-N-acylated kanamycin A. Chembiochem. 2007; 8(6):649-56. DOI: 10.1002/cbic.200600569. View

3.
Moore P, Steitz T . The roles of RNA in the synthesis of protein. Cold Spring Harb Perspect Biol. 2010; 3(11):a003780. PMC: 3220363. DOI: 10.1101/cshperspect.a003780. View

4.
Caetano-Anolles G . Tracing the evolution of RNA structure in ribosomes. Nucleic Acids Res. 2002; 30(11):2575-87. PMC: 117177. DOI: 10.1093/nar/30.11.2575. View

5.
Krek A, Grun D, Poy M, Wolf R, Rosenberg L, Epstein E . Combinatorial microRNA target predictions. Nat Genet. 2005; 37(5):495-500. DOI: 10.1038/ng1536. View