A dynamic programming algorithm for finding alternative RNA secondary structure

Williams, Arthur L.; Tinoco, Ignacio

doi:10.1093/nar/14.1.299

Cited by 80 publications

(43 citation statements)

References 28 publications

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“…The corresponding mRNA hairpin loop predicted by size fractionation, indicates that the enzyme of C. glufrom this sequence has a AG' (25°C) of -25.4 kcal/mol (ca. tamicum is a tetramer with a calculated mass of 186,396 -106.3 kJ/mol) (50). The total structure is similar to those of daltons.…”

Section: Resultsmentioning

confidence: 86%

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Functional and structural analyses of threonine dehydratase from Corynebacterium glutamicum

1992

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Threonine dehydratase activity is an important element in the flux control of isoleucine biosynthesis. The enzyme of Corynebacterium gluamicum demonstrates a marked sigmoidal dependence of initial velocity on the threonine concentration, a dependence that is consistent with substrate-promoted conversion of the enzyme from a low-activity to a high-activity conformation. In the presence of the negative aliosteric effector isoleucine, the K.45 increased from 21 to 78 mM and the cooperativity, as expressed by the Hill coefficient increased from 2.4 to 3.7. Valine promoted opposite effects: the K0.5 was reduced to 12 mM, and the enzyme exhibited almost no cooperativity. Sequence determination of the C. ghutamicum gene for this enzyme revealed an open reading frame coding for a polypeptide of 436 amino acids. From this information and the molecular weight determination of the native enzyme, it follows that the dehydratase is a tetramer with a total mass of 186,396 daltons. Comparison of the deduced polypeptide sequence with the sequences of known threonine dehydratases revealed surprising differences from the C. glutamicum enzyme in the carboxy-terminal portion. This portion is greatly reduced in size, and a large gap of 95 amino acids must be introduced to achieve homology.

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Section: Resultsmentioning

confidence: 86%

“…E. coli and C. glutamicum were grown on complex medium as described previously (43). When appropriate, kanamycin (25 ,ug/ml) or ampicillin (50 ,ug/ml) was added.…”

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confidence: 99%

Functional and structural analyses of threonine dehydratase from Corynebacterium glutamicum

1992

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“…Two main methods are currently employed to predict RNA secondary structure; comparative sequence analysis (1-3) and free energy minimization (4)(5)(6)(7)(8)(9)(10).The former method proceeds from the assumption that structure is much more highly conserved than sequence during evolution. Base pairs are inferred by finding positions in aligned sequences that co-vary so as to conserve base pairing potential.…”

Section: Introductionmentioning

confidence: 99%

‘Well-determined’ regions in RNA secondary structure prediction: analysis of small subunit ribosomal RNA

Zuker

Jacobson

1995

Nucl Acids Res

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Recent structural analyses of genomic RNAs from RNA coliphages suggest that both well-determined base paired helices and well-determined structural domains that are identified by 'energy dot plot' analysis using the RNA folding package mfold, are likely to be predicted correctly. To test these observations with another group of large RNAs, we have analyzed 15 ribosomal RNAs. Published secondary structure models that were derived by comparative sequence analysis were used to evaluate the predicted structures. Both the optimal predicted fold and the predicted 'energy dot plot' of each sequence were examined. Each prediction was obtained from a single computer run on an entire ribosomal RNA sequence. All predicted base pairs in optimal foldings were examined for agreement with proven base pairs in the comparative models. Our analyses show that the overall correspondence between the predicted and comparative models varies for different RNAs and ranges from a low of 27% to a high of 70%, with a mean value of 49%. The correspondence improves to a mean value of 81% when the analysis is limited to welldetermined helices. In addition to well-determined helices, large well-determined structural domains can be observed in 'energy dot plots' of some 16S ribosomal RNAs. The predicted domains correspond closely with structural domains that are found by the comparative method in the same RNAs. Our analyses also show that measuring the agreement between predicted and comparative secondary structure models underestimates the reliability of structural prediction by mfold.

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“…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.…”

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confidence: 99%

Improved predictions of secondary structures for RNA.

Jaeger

Turner

Zuker

1989

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

777

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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A dynamic programming algorithm for finding alternative RNA secondary structure

Cited by 80 publications

References 28 publications

Functional and structural analyses of threonine dehydratase from Corynebacterium glutamicum

Functional and structural analyses of threonine dehydratase from Corynebacterium glutamicum

‘Well-determined’ regions in RNA secondary structure prediction: analysis of small subunit ribosomal RNA

Improved predictions of secondary structures for RNA.

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