Investigation of the Structural Basis for Thermodynamic Stabilities of Tandem GU Wobble Pairs:  NMR Structures of (rGGAGUUCC)2 and (rGGAUGUCC)2,

McDowell, Jeffrey A.; He, Liyan; Chen, Xiaoying; Turner, Douglas H.

doi:10.1021/bi970122c

Cited by 53 publications

(66 citation statements)

References 31 publications

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“…Presumably these destabilizing mismatches are relatively unstructured. Symmetric tandem mismatches comprised of GU, GA, or UU pairs can be stabilizing, and NMR evidence indicates that there are significant hydrogen bonding interactions in the mismatches, as well as stacking between mismatches and stacking between mismatches and closing base pairs (30,(81)(82)(83)(84). For tandem GU, GA, and UU mismatches, stabilities are therefore more dependent on the identity and orientation of the closing base pairs and do not fit a simple model.…”

Section: Discussionmentioning

confidence: 99%

Thermodynamic Parameters for an Expanded Nearest-Neighbor Model for Formation of RNA Duplexes with Watson−Crick Base Pairs

et al. 1998

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Improved thermodynamic parameters for prediction of RNA duplex formation are derived from optical melting studies of 90 oligoribonucleotide duplexes containing only Watson-Crick base pairs. To test end or base composition effects, new sets of duplexes are included that have identical nearest neighbors, but different base compositions and therefore different ends. Duplexes with terminal GC pairs are more stable than duplexes with the same nearest neighbors but terminal AU pairs. Penalizing terminal AU base pairs by 0.45 kcal/mol relative to terminal GC base pairs significantly improves predictions of ∆G°3 7 from a nearest-neighbor model. A physical model is suggested in which the differential treatment of AU and GC ends accounts for the dependence of the total number of Watson-Crick hydrogen bonds on the base composition of a duplex. On average, the new parameters predict ∆G°3 7 , ∆H°, ∆S°, and T M within 3.2%, 6.0%, 6.8%, and 1.3°C, respectively. These predictions are within the limit of the model, based on experimental results for duplexes predicted to have identical thermodynamic parameters.The thermodynamics of secondary structure formation are important for unraveling structure-function relationships for RNA. For example, these thermodynamics provide a foundation for predicting secondary structure and stability, both of which can correlate with function. Moreover, predicting secondary structure is a crucial intermediate step toward predicting three-dimensional structure (1, 2). In addition, differences between the thermodynamics of secondary structure formation and of overall folding can provide insight into the thermodynamics of tertiary structure formation (3-7).Watson-Crick base pairs are one of the most important motifs in RNA secondary structures. The thermodynamics of Watson-Crick base pair formation have been studied in short RNA duplexes (8, 9). The results are well-represented by a nearest-neighbor model in which the thermodynamic stability of a base pair is dependent on the identity of the adjacent base pairs. This model has been termed an individual nearest-neighbor (INN) model (10, 11). The pioneering implementation by Borer et al. (8) employed 6 nearest-neighbor parameters and separate initiation parameters for duplexes with and without a GC base pair. Due to advances in oligoribonucleotide synthesis (12), Freier et al. (9) were able to determine all 10 nearest-neighbor parameters in the INN model and the initiation parameter for duplexes with at least one GC base pair. The initiation parameter for duplexes with only AU base pairs was not determined.It has been suggested that a nearest-neighbor model that treats terminal base pairs differently from internal base pairs (8) or treats terminal GC base pairs differently from terminal AU base pairs (10, 11, 13) may improve modeling of duplex stability. The model proposed by Gray (10) has been termed an independent short sequence (ISS) model because the 14 sequence-dependent parameters of the model must be combined into 12 "short sequence" p...

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Section: Discussionmentioning

confidence: 99%

Thermodynamic Parameters for an Expanded Nearest-Neighbor Model for Formation of RNA Duplexes with Watson−Crick Base Pairs

et al. 1998

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“…First, the antisense oligonucleotides asDIM and as that bind all or part of the palindrome were able to prevent as548-mediated tight dimerization of 1-561⌬SL1 or 1-561⌬NAR1⌬SL1 RNAs. Second, the nucleotide sequence within the palindrome, 5Ј-GAGUGCUC-3Ј is known to form an unusually stable duplex in vitro, and is statistically overrepresented in ribosomal RNA (Gautheret et al 1995;McDowell et al 1997;Chen et al 2000;Deng and Sundaralingam 2000). Furthermore, the unique conformational features of UG base pairs are important recognition motifs in RNA-RNA FIGURE 6. as548-Mediated tight dimerization of 1-561 RNA lacking SL1 and PBS dimerization sites.…”

Section: Discussionmentioning

confidence: 99%

A structural linkage between the dimerization and encapsidation signals in HIV-2 leader RNA

Lanchy

Ivanovitch

Lodmell

2003

RNA

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The 5 untranslated leader region of retroviral RNAs contains noncoding information that is essential for viral replication, including signals for transcriptional transactivation, splicing, primer binding for reverse transcription, dimerization of the genomic RNA, and encapsidation of the viral RNA into virions. These RNA motifs have considerable structural and functional overlap. In this study, we investigate the conformational dynamics associated with the use and silencing of a sequence in HIV-2 RNA that is involved in genomic RNA dimerization called stem-loop 1 (SL1) and its relationship with a flanking sequence that is known to be important for encapsidation of viral RNAs. We demonstrate that a long-distance intramolecular interaction between nucleotides located upstream of the primer-binding site domain and nucleotides encompassing the Gag translation start codon functionally silences SL1 as a dimerization element. This silencing can be relieved by mutation or by hybridization of an oligonucleotide that disrupts the long-distance interaction. Furthermore, we identify a palindrome within the packaging/ encapsidation signal (just 5 of SL1) that can either serve as an efficient dimerization signal itself, or can mediate SL1 silencing through base pairing with SL1. These results provide a tangible link between the functions of genomic RNA dimerization and encapsidation, which are known to be related, but whose physical relationship has been unclear. A model is proposed that accounts for observations of dimerization, packaging, and translation of viral RNAs during different phases of the viral replication cycle.

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“…Secondly, we collected a thermodynamic set denoted by T-Full that contains data from 1291 optical melting experiments, published in 53 research articles Sugimoto et al 1986Sugimoto et al , 1987Uhlenbeck 1988, 1989;Longfellow et al 1990;SantaLucia et al 1990SantaLucia et al , 1991aAntao et al 1991;He et al 1991;Peritz et al 1991;Antao and Tinoco 1992;Serra et al 1993Serra et al , 1994Serra et al , 1997Serra et al , 2004Walter et al 1994;Morse and Draper 1995;Wu et al 1995;Laing and Hall 1996;McDowell and Turner 1996;McDowell et al 1997;Schroeder et al 1996Schroeder et al , 2003Xia et al 1997Xia et al , 1998Giese et al 1998;Kierzek et al 1999;Meroueh and Chow 1999;Dale et al 2000;Turner 2000, 2001;Burkard et al 2001;Diamond et al 2001;Mathews and Turner 2002;Proctor et al 2002;Znosko et al 2002Znosko et al , 2004Chen et al 2004Chen et al , 2005Mathews et al 2004;Vecenie and Serra 2004;Bourdélat-Parks and Wartell 2005;…”

Section: Data Setsmentioning

confidence: 99%

Computational approaches for RNA energy parameter estimation

Andronescu

Condon²,

Hoos³

et al. 2010

RNA

122

156

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Methods for efficient and accurate prediction of RNA structure are increasingly valuable, given the current rapid advances in understanding the diverse functions of RNA molecules in the cell. To enhance the accuracy of secondary structure predictions, we developed and refined optimization techniques for the estimation of energy parameters. We build on two previous approaches to RNA free-energy parameter estimation: (1) the Constraint Generation (CG) method, which iteratively generates constraints that enforce known structures to have energies lower than other structures for the same molecule; and (2) the Boltzmann Likelihood (BL) method, which infers a set of RNA free-energy parameters that maximize the conditional likelihood of a set of reference RNA structures. Here, we extend these approaches in two main ways: We propose (1) a max-margin extension of CG, and (2) a novel linear Gaussian Bayesian network that models feature relationships, which effectively makes use of sparse data by sharing statistical strength between parameters. We obtain significant improvements in the accuracy of RNA minimum free-energy pseudoknot-free secondary structure prediction when measured on a comprehensive set of 2518 RNA molecules with reference structures. Our parameters can be used in conjunction with software that predicts RNA secondary structures, RNA hybridization, or ensembles of structures. Our data, software, results, and parameter sets in various formats are freely available at http://www.cs.ubc.ca/labs/beta/Projects/RNA-Params.

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Investigation of the Structural Basis for Thermodynamic Stabilities of Tandem GU Wobble Pairs: NMR Structures of (rGGAGUUCC)₂ and (rGGAUGUCC)₂^,

Cited by 53 publications

References 31 publications

Thermodynamic Parameters for an Expanded Nearest-Neighbor Model for Formation of RNA Duplexes with Watson−Crick Base Pairs

Thermodynamic Parameters for an Expanded Nearest-Neighbor Model for Formation of RNA Duplexes with Watson−Crick Base Pairs

A structural linkage between the dimerization and encapsidation signals in HIV-2 leader RNA

Computational approaches for RNA energy parameter estimation

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