Dataset Information

Thermodynamic Features of Structural Motifs Formed by ?-L-RNA.

ABSTRACT: This is the first report to provide comprehensive thermodynamic and structural data concerning duplex, hairpin, quadruplex and i-motif structures in ?-L-RNA series. Herein we confirm that, within the limits of experimental error, the thermodynamic stability of enantiomeric structural motifs is the same as that of naturally occurring D-RNA counterparts. In addition, formation of D-RNA/L-RNA heterochiral duplexes is also observed; however, their thermodynamic stability is significantly reduced in reference to homochiral D-RNA duplexes. The presence of three locked nucleic acid (LNA) residues within the D-RNA strand diminishes the negative effect of the enantiomeric, complementary L-RNA strand in the formation of heterochiral RNA duplexes. Similar behavior is also observed for heterochiral LNA-2'-O-methyl-D-RNA/L-RNA duplexes. The formation of heterochiral duplexes was confirmed by 1H NMR spectroscopy. The CD curves of homochiral L-RNA structural motifs are always reversed, whereas CD curves of heterochiral duplexes present individual features dependent on the composition of chiral strands.

SUBMITTER: Szabat M

PROVIDER: S-EPMC4801053 | biostudies-other | 2016

REPOSITORIES: biostudies-other

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Thermodynamic Features of Structural Motifs Formed by β-L-RNA.

Szabat Marta M Gudanis Dorota D Kotkowiak Weronika W Gdaniec Zofia Z Kierzek Ryszard R Pasternak Anna A

PloS one 20160223 2

This is the first report to provide comprehensive thermodynamic and structural data concerning duplex, hairpin, quadruplex and i-motif structures in β-L-RNA series. Herein we confirm that, within the limits of experimental error, the thermodynamic stability of enantiomeric structural motifs is the same as that of naturally occurring D-RNA counterparts. In addition, formation of D-RNA/L-RNA heterochiral duplexes is also observed; however, their thermodynamic stability is significantly reduced in ...[more]

PMID: 26908023

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Project description:Conformational entropy for atomic-level, three dimensional biomolecules is known experimentally to play an important role in protein-ligand discrimination, yet reliable computation of entropy remains a difficult problem. Here we describe the first two accurate and efficient algorithms to compute the conformational entropy for RNA secondary structures, with respect to the Turner energy model, where free energy parameters are determined from UV absorption experiments. An algorithm to compute the derivational entropy for RNA secondary structures had previously been introduced, using stochastic context free grammars (SCFGs). However, the numerical value of derivational entropy depends heavily on the chosen context free grammar and on the training set used to estimate rule probabilities. Using data from the Rfam database, we determine that both of our thermodynamic methods, which agree in numerical value, are substantially faster than the SCFG method. Thermodynamic structural entropy is much smaller than derivational entropy, and the correlation between length-normalized thermodynamic entropy and derivational entropy is moderately weak to poor. In applications, we plot the structural entropy as a function of temperature for known thermoswitches, such as the repression of heat shock gene expression (ROSE) element, we determine that the correlation between hammerhead ribozyme cleavage activity and total free energy is improved by including an additional free energy term arising from conformational entropy, and we plot the structural entropy of windows of the HIV-1 genome. Our software RNAentropy can compute structural entropy for any user-specified temperature, and supports both the Turner'99 and Turner'04 energy parameters. It follows that RNAentropy is state-of-the-art software to compute RNA secondary structure conformational entropy. Source code is available at https://github.com/clotelab/RNAentropy/; a full web server is available at http://bioinformatics.bc.edu/clotelab/RNAentropy, including source code and ancillary programs.

Dataset Information

Thermodynamic Features of Structural Motifs Formed by ?-L-RNA.

Publications

Thermodynamic Features of Structural Motifs Formed by β-L-RNA.

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