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Finding stable local optimal RNA secondary structures
Author(s) -
Yuan Li,
Shaojie Zhang
Publication year - 2011
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btr510
Subject(s) - nucleic acid secondary structure , protein secondary structure , benchmark (surveying) , rna , riboswitch , pseudoknot , computer science , nucleic acid structure , stability (learning theory) , algorithm , folding (dsp implementation) , software , heuristic , biological system , physics , biology , non coding rna , artificial intelligence , genetics , engineering , gene , machine learning , programming language , geodesy , nuclear magnetic resonance , electrical engineering , geography
Many RNAs, such as riboswitches, can fold into multiple alternate structures and perform different biological functions. These biologically functional structures usually have low free energies in their local energy landscapes and are very stable such that they cannot easily jump out of the current states and fold into other stable conformations. The conformational space of feasible RNA secondary structures is prohibitively large, and accurate prediction of functional structure conformations is challenging. Because the stability of an RNA secondary structure is determined predominantly by energetically favorable helical regions (stacks), we propose to use configurations of putative stacks to represent RNA secondary structures. By considering a reduced conformational space of local optimal stack configurations instead of all feasible RNA structures, we first present an algorithm for enumerating all possible local optimal stack configurations. In addition, we present a fast heuristic algorithm for approximating energy barriers encountered during folding pathways between each pair of local optimal stack configurations and finding all the stable local optimal structures.

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