Free energy contributions of G.cntdot.U and other terminal mismatches to helix stability

Freier, Susan M.; Kierzek, Ryszard; Caruthers, Marvin H.; Neilson, Thomas; Turner, Douglas H.

doi:10.1021/bi00359a019

Cited by 91 publications

(92 citation statements)

References 36 publications

(67 reference statements)

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“…All internal loops, including those containing 2 nt (single mismatches) have two such free energy increments. This assumption is consistent with the observation that the favorable free energy of a terminal mismatch in oligonucleotide duplexes comes primarily from 3'-terminal stacking (19). With these assumptions, AG037 values for internal loops were calculated from data on A4GC0U4 (32), A7CU7 (33), and CGCAnGCG and CGCAnCGC plus GCGAmGCG (N. Sugimoto, R. Kierzek, C. E. Longfellow, and D.H.T., unpublished experiments).…”

Section: Methodssupporting

confidence: 64%

“…Free energy increments for hydrogen-bonded AU, GC, and GU pairs are based on the nearest-neighbor model (5,7,8,18). Measured free energy increments for terminal hydrogen-bonded GU pairs are an average of 0.2 kcal/mol more favorable than internal GU mismatches (19). This information has not been included in the model.…”

Section: Methodsmentioning

confidence: 99%

“…Increments for terminal nonhydrogen-bonded AU, GC, and GU pairs are approximated by the corresponding 3'-dangling end made more favorable by 0.2 kcal/mol to approximate the effect of the opposing 5'-dangling end (20). Only one measurement is available for AG"37 associated with a dangling end adjacent to a terminal GU mismatch (19). For a 3'-dangling adenosine phosphate in the sequence GA, the free energy increment was roughly the average of increments measured for 3'-dangling ends adjacent to the corresponding AU and GC Hairpin Loops.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Improved predictions of secondary structures for RNA.

Jaeger

Turner

Zuker

1989

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

774

541

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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: Methodssupporting

confidence: 64%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Improved predictions of secondary structures for RNA.

Jaeger

Turner

Zuker

1989

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

774

541

View full text Add to dashboard Cite

show abstract

“…The results in Table I support the dependence of loop closure on base pair, although the difference between GC and AU closure is only about 1 kcal/mol. The difference between loop closure by GC and AU could be due to the extra hydrogen bond in a GC pair (18,27,28). The loop closed by G -U, however, is more stable than the loops closed by G-C or C *G. Since G U pairs have only 2 hydrogen bonds, the effect of closing base pair probably depends on more than the number of hydrogen bonds between the bases closing the loop.…”

Section: Resultsmentioning

confidence: 99%

RNA hairpin loop stability depends on closing base pair

Serra¹,

Lyttle²,

Axenson³

et al. 1993

Nucl Acids Res

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“…OligoWalk was used to calculate overall binding affinity for RNA hexamers+ The 626-nt secondary structure for the whole target was predicted by free-energy minimization (Mathews et al+, 1999)+ OligoWalk calculations were made with an oligomer concentration of 1 mM (an upper bound on the intracellular ribozyme concentration), considering local structure only, and considering the set of suboptimal target structures (Form II from Fig+ 2)+ There are 16 Us in the 70-nt region 59 to the sickle mutation, and, therefore, the 16 oligomers with 59 As were considered as potential IGS mimics+ This is reasonable because the free-energy increments for terminal G-U and A-U pairs are similar (Freier et al+, 1986)+ The oligomer with the second lowest ⌬G8 overall is the oligomer that binds to U61, the target found most often by screening (see Table 1; Lan et al+, 1998)+ The oligomer with the lowest ⌬G8 overall also binds to a region that was accessible to splicing+ These two hexamers predicted to be most favorable account for 11 of the 15 clones that showed splicing to the region 59 to the sickle mutation+ The range of overall free energies of binding for oligomers with a 59 A was Ϫ3+9 to ϩ5+0 kcal/mol+ The five target regions of mRNA, 59 to position 70, identified by either cell-free or cellular screening by at least one clone each ranged between Ϫ3+9 and ϩ0+6 kcal/mol in ⌬G8 overall +…”

Section: Rnase-h Cleavagementioning

confidence: 99%