An energy model that predicts the correct folding of both the tRNA and the 5S RNA molecules

Papanicolaou, Catherine; Gouy, Manolo; Ninio, Jacques

doi:10.1093/nar/12.1part1.31

Cited by 112 publications

(59 citation statements)

References 38 publications

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“…For example, from published plots of Tm-1 vs. oligomer concentration, the measured difference in stabilities between A7CU7 and A7U7 is +4.3 kcal/mol (33). (34). These penalties are described in the legend to Table 1 and must be added to the AG0 values in Table 1.…”

Section: Methodsmentioning

confidence: 99%

Improved predictions of secondary structures for RNA.

Jaeger

Turner

Zuker

1989

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

774

538

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The accuracy of computer predictions of RNA secondary structure from sequence data and free energy parameters has been increased to roughly 70%. Performance is judged by comparison with structures known from phylogenetic analysis. The algorithm also generates suboptimal structures. On average, the best structure within 10% of the lowest free energy contains roughly 90% of phylogenetically known helixes. The algorithm does not include tertiary interactions or pseudoknots and employs a crude model for singlestranded regions. The only favorable interactions are base pairing and stacking of terminal unpaired nucleotides at the ends of helixes. The excellent performance is consistent with these interactions being the primary interactions determining RNA secondary structure.RNA is important for functions such as catalysis, RNA splicing, regulation of transcription and translation, and transport of proteins across membranes (1). Many RNA sequences are known. Determination of secondary structures, however, is difficult. Thermodynamics has been applied to predict RNA secondary structure from sequence (2, 3), but with modest success. Predictions of suboptimal structures make the method more useful (4). We report combining several recent advances to improve predictions of RNA secondary structures. Three advances are incorporated in this work. (i) New methods for synthesizing RNA make it possible to obtain model systems with a large variety of sequence (5, 6). This technique has led to measurements of improved parameters and the realization that non-base-paired nucleotides contribute sequence-dependent interactions that stabilize secondary structure (7, 8). (ii) A computer algorithm has been developed that allows incorporation of non-base-paired interactions in the prediction of optimal and suboptimal secondary structures (9). (iii) Several RNA secondary structures have been determined by phylogeny (10-15). Comparison of predicted and known structures allows optimization of parameters that have not been measured. Resultant predictions appear sufficiently reliable to aid planning and interpretation of experiments on RNA. MATERIALS AND METHODSThermodynamic Parameters. When possible, free energy increments at 370C, AG037, were taken from experiments in 1 M NaCl. For fully base-paired regions, experiments on dGCATGC indicate that 1 M NaCl mimics solutions containing 1-100 mM Mg2+ in the presence of 0.15-1 M NaCl (16).Relatively few experiments are available for loop structures, and, therefore, little is known about interactions determining loop stability. This situation forced approximations. (i) Jacobson-Stockmayer theory (17) was used to extrapolate the length dependence of AG37 for bulge, hairpin, and internal loops: AG0(n) = AG(nmax) + 1.75 RTln (n/nmax).For this equation n is the number of unpaired nucleotides in the loop, nma is the maximum-length loop for which experimental data is available, R is the gas constant (1.987 cal mol'lK-l; 1 cal = 4.184 J), and T is the temperature in K (310.15 K for 370C). (ii) When...

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Section: Methodsmentioning

confidence: 99%

Improved predictions of secondary structures for RNA.

Jaeger

Turner

Zuker

1989

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

774

538

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“…This is further evidence for the B conformation with the looped-out uridine at position 2. Calculation of the stacking energy of the two conformations according to Ninio's latest model (which is derived from an examination of 5 S rRNA sequences, [5]) gives AG = 258 -21.4 kcal for A and AG = 24.3 kcal for B, a slight 'advantage' for the looped-out-base version. This superiority is due particularly to the presence of two cytidines opposite the unpaired uridine, poor stacking of these pyrimidines is assumed to be responsible for increased flexibility allowing intercalation of the unpaired base [S].…”

Section: Heandximentioning

confidence: 99%

“…This approach has been accompanied by a refinement in the scoring values for base-pair stacking interactions made in [4,5] based on the thermodynamic measurements in [6,7].…”

Section: Introductionmentioning

confidence: 99%

The secondary and tertiary structure of the 5 S rRNA from the horsetail Equisetum arvense

1984

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The secondary and tertiary structures of the 5 S rRNA from Equisetum arvense were examined using doublestrand and single-strand specific nucleates, the bisulphite mediated deamination of unpaired cytidines and the ethylnitrosourea modification of accessible phosphodiesters. The results are evaluated in terms of the consensus eubaryotic 5 S rRNA structure, the occurrence of 'looped-out' nucleotides, structure of loops and a putative tertiary structure.Eukaryotic 5 S rRNA Single-strand spe& nuclease RNA structure

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“…(c) mRNA local secondary structure Predictions of mRNA secondary structure werc made with the help of a programrne kindly supplied by Papanicolaou et al ( 1984 ).…”

Section: Materialsand Methods (A) Bacterial Strains and Expression Vementioning

confidence: 99%

Enhancement of translational efficiency by the Escherichia coli atpE translational initiation region: its fusion with two human genes

McCarthy

Sebald

Groß

et al. 1986

Gene

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An energy model that predicts the correct folding of both the tRNA and the 5S RNA molecules

Cited by 112 publications

References 38 publications

Improved predictions of secondary structures for RNA.

Improved predictions of secondary structures for RNA.

The secondary and tertiary structure of the 5 S rRNA from the horsetail Equisetum arvense

Enhancement of translational efficiency by the Escherichia coli atpE translational initiation region: its fusion with two human genes

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