Pseudoknots: RNA Structures with Diverse Functions

Staple, David W.; Butcher, Samuel E.

doi:10.1371/journal.pbio.0030213

Cited by 310 publications

(238 citation statements)

References 35 publications

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“…The predicted helices, kink turn, and pseudoknot are all present in the structure. The pseudoknot is formed from nucleotides in the loops of the P3 and P1/P2 helices and is therefore an example of an H-H-type pseudoknot, also called an intramolecular kissing hairpin (27)(28)(29)(30). Helices P1 and P4 form a stack, with P2 at a right angle.…”

Section: Resultsmentioning

confidence: 99%

Structural basis of differential ligand recognition by two classes of bis-(3′-5′)-cyclic dimeric guanosine monophosphate-binding riboswitches

Smith

Shanahan

Moore

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

107

195

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The bis-(3′-5′)-cyclic dimeric guanosine monophosphate (c-di-GMP) signaling pathway regulates biofilm formation, virulence, and other processes in many bacterial species and is critical for their survival. Two classes of c-di-GMP-binding riboswitches have been discovered that bind this second messenger with high affinity and regulate diverse downstream genes, underscoring the importance of RNA receptors in this pathway. We have solved the structure of a c-di-GMP-II riboswitch, which reveals that the ligand is bound as part of a triplex formed with a pseudoknot. The structure also shows that the guanine bases of c-di-GMP are recognized through noncanonical pairings and that the phosphodiester backbone is not contacted by the RNA. Recognition is quite different from that observed in the c-di-GMP-I riboswitch, demonstrating that at least two independent solutions for RNA second messenger binding have evolved. We exploited these differences to design a c-di-GMP analog that selectively binds the c-di-GMP-II aptamer over the c-di-GMP-I RNA. There are several bacterial species that contain both types of riboswitches, and this approach holds promise as an important tool for targeting one riboswitch, and thus one gene, over another in a selective fashion.

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Section: Resultsmentioning

confidence: 99%

Structural basis of differential ligand recognition by two classes of bis-(3′-5′)-cyclic dimeric guanosine monophosphate-binding riboswitches

Smith

Shanahan

Moore

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

107

195

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show abstract

“…Pseudoknots are a situation where at least one pair of base pairs is such that neither base pair is completely between the other in sequence [19]. Covariance models use stochastic context-free grammars [20], which are incapable of describing a pseudoknot.…”

Section: Resultsmentioning

confidence: 99%

Joint Loop End Modeling Improves Covariance Model Based Non-coding RNA Gene Search

Smith

2010

Pattern Recognition in Bioinformatics

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Abstract. The effect of more detailed modeling of the interface between stem and loop in non-coding RNA hairpin structures on efficacy of covariance-model-based non-coding RNA gene search is examined. Currently, the prior probabilities of the two stem nucleotides and two loop-end nucleotides at the interface are treated the same as any other stem and loop nucleotides respectively. Laboratory thermodynamic studies show that hairpin stability is dependent on the identities of these four nucleotides, but this is not taken into account in current covariance models. It is shown that separate estimation of emission priors for these nucleotides and joint treatment of substitution probabilities for the two loop-end nucleotides leads to improved non-coding RNA gene search.Keywords: sequence analysis, RNA gene search, covariance models IntroductionCovariance models are an effective method of capturing the joint probability information inherent in the intramolecularly base-paired positions of a non-coding RNA molecule [1,2]. Unlike profile hidden Markov models [3,4], which have a set of four emission probabilities over the possible nucleotides at each consensus sequence position, covariance models allow consensus base pairs to be assigned sixteen joint probabilities over the possible ordered nucleotide pairs. Covariance models also allow the probability of insertion or deletion of a base pair to be different than the sum of the marginal probabilities of insertion or deletion of the individual nucleotides. The profile hidden Markov model can be viewed as a special form of a covariance model with no base pairs specified.

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“…The two stems are able to stack on top of each other to form a quasi-continuous helix with one continuous and one discontinuous strand. The single stranded loop regions often interact with the adjacent stems (loop 1, stem 2 or loop 2, stem 1) to form hydrogen bonds and to participate in the overall structure of the molecule [9]. Hence, this relatively simple fold can yield very complex and stable RNA structures.…”

Section: Pseudoknotsmentioning

confidence: 99%

compPknots: A Framework for Parallel Prediction and Comparison of RNA Secondary Structures with Pseudoknots

Estrada

Licon

Taufer

2006

Frontiers of High Performance Computing and Networking – ISPA 2006 Workshops

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Pseudoknots: RNA Structures with Diverse Functions

Abstract: Just as proteins form distinct structural motifs, certain structures are commonly adopted by RNA molecules. Amongst the most prevalent is the RNA pseudoknot.

Cited by 310 publications

References 35 publications

Structural basis of differential ligand recognition by two classes of bis-(3′-5′)-cyclic dimeric guanosine monophosphate-binding riboswitches

Structural basis of differential ligand recognition by two classes of bis-(3′-5′)-cyclic dimeric guanosine monophosphate-binding riboswitches

Joint Loop End Modeling Improves Covariance Model Based Non-coding RNA Gene Search

compPknots: A Framework for Parallel Prediction and Comparison of RNA Secondary Structures with Pseudoknots

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