Contributions of dangling end stacking and terminal base-pair formation to the stabilities of XGGCCp, XCCGGp, XGGCCYp, and XCCGGYp helixes

Freier, Susan M.; Alkema, Dirk; Sinclair, Alison; Neilson, Thomas; Turner, Douglas H.

doi:10.1021/bi00338a008

Cited by 130 publications

(178 citation statements)

References 36 publications

(50 reference statements)

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“…(3) Perhaps the most important obserVation is that the nature of the closing basepair plays a central role (29)(30)(31)(32)(33)(34). The same dangling nucleobase stacking on a G-C closing basepair with three hydrogen bonds always provides more stabilization than the A-U closing basepair with two hydrogen bonds.…”

Section: Resultsmentioning

confidence: 99%

A Uniform Mechanism Correlating Dangling-End Stabilization and Stacking Geometry

Isaksson

Chattopadhyaya

2005

Biochemistry

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The geometry of the dangling base in 105 published structures (from X-ray/NMR) containing single-stranded overhangs has been analyzed and correlated to the thermodynamic stabilization found (UV) for the corresponding dangling base/closing basepair combination in short oligonucleotides. The study considers most combinations of closing basepairs, sequence and dangling base residue type, attached in both the 3′-and 5′-ends of both DNA and RNA. Linear regression analysis showed a straightforward correlation (R ) 0.873) between the degree of screening for the hydrogen bonds of the closing basepair provided by the dangling base and the resulting thermodynamic stabilization in both DNA and RNA series with dangling ends either at the 3′-or at the 5′-terminus. Regression analysis of only the datasets from RNA gives an improved correlation, R ) 0.934, showing that dangling ends on RNA are more ordered than the dangling ends on DNA, R ) 0.376. This study highlights the gain in the free energy of stabilization owing to the favorable stacking between the dangling nucleobase and the neighboring basepair and the resulting strengthening of the hydrogen bond of the closing basepair. By acting as a hydrophobic cap on the terminal of the DNA or RNA duplex, the dangling-end residue restricts the bulk water access to the terminal basepair, thereby providing it with a microenvironment devoid of water, which consequently enhances its thermodynamic stability, making it energetically comparable to the corresponding internal basepair. Thus, one single structural model consisting of the interplay of the above electrostatic interactions can be used to explain the molecular basis of the observed thermodynamic effects for dangling-end attachment to the 3′-and 5′-ends of both DNA and RNA duplexes, which is a key step toward accurate dangling-end effect prediction.Unpaired terminal nucleotides naturally occur in various biologically important RNA structures: The acceptor stem in tRNA (1-3) has a characteristic 3′-NCCA nucleobase overhang that determines its structure, stability, and function. The dangling ends neighboring the codon-anticodon pair have also been found to stabilize the interaction between tRNA and mRNA (4, 5) for protein synthesis in the ribosomal machinery. The efficiency of down regulation of gene expression by RNA interference (RNAi) has been shown to be dependent on a two to three nucleotide overhang (6-9). Similarly, the structures of pseudoknots (10) are stabilized by a complicated interplay between single-stranded and double-stranded motifs. A multitude of literature on the stabilizing interactions of native single-stranded oligonucleotides is available (9,(11)(12)(13)(14).Accurate prediction of nucleic acid secondary structure and stability from its primary sequence is a key interest for probe binding optimization in biotechnological applications such as microarrays (15) and molecular beacons (16). To develop an accurate algorithm (14,(17)(18)(19)(20)(21)(22)(23)(24) for predicting the thermodynamics of hybridi...

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Section: Resultsmentioning

confidence: 99%

A Uniform Mechanism Correlating Dangling-End Stabilization and Stacking Geometry

Isaksson

Chattopadhyaya

2005

Biochemistry

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“…One hairpin closed with C * G had a 5' triphosphate at the 5' side of the stem since it was prepared with T7 RNA polymerase (13). This is expected to make the AG' for hairpin folding more favorable by about 0.3 kcal/mol (18). Six of the molecules share the same sequence except the base pair closing the loop; therefore, differences in stability of these hairpins are due to the effects of the closing base pair.…”

Section: Resultsmentioning

confidence: 99%

“…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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“…AU, GC, and GU pairs at the ends of helixes are allowed not to be hydrogen bonded because in some cases stacking without pairing gives a more favorable AG0. 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).…”

mentioning

confidence: 99%

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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Contributions of dangling end stacking and terminal base-pair formation to the stabilities of XGGCCp, XCCGGp, XGGCCYp, and XCCGGYp helixes

Cited by 130 publications

References 36 publications

A Uniform Mechanism Correlating Dangling-End Stabilization and Stacking Geometry

A Uniform Mechanism Correlating Dangling-End Stabilization and Stacking Geometry

RNA hairpin loop stability depends on closing base pair

Improved predictions of secondary structures for RNA.

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