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Nucleic acid secondary structure

About: Nucleic acid secondary structure is a research topic. Over the lifetime, 1950 publications have been published within this topic receiving 101125 citations.


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Journal ArticleDOI
TL;DR: In this article, a dynamic programming algorithm was proposed to fold an RNA molecule that finds a conformation of minimum free energy using published values of stacking and destabilizing energies, based on applied mathematics.
Abstract: This paper presents a new computer method for folding an RNA molecule that finds a conformation of minimum free energy using published values of stacking and destabilizing energies. It is based on a dynamic programming algorithm from applied mathematics, and is much more efficient, faster, and can fold larger molecules than procedures which have appeared up to now in the biological literature. Its power is demonstrated in the folding of a 459 nucleotide immunoglobulin gamma 1 heavy chain messenger RNA fragment. We go beyond the basic method to show how to incorporate additional information into the algorithm. This includes data on chemical reactivity and enzyme susceptibility. We illustrate this with the folding of two large fragments from the 16S ribosomal RNA of Escherichia coli.

3,202 citations

Journal ArticleDOI
TL;DR: The Vienna RNA secondary structure server provides a web interface to the most frequently used functions of the Vienna RNA software package for the analysis of RNA secondary structures.
Abstract: The Vienna RNA secondary structure server provides a web interface to the most frequently used functions of the Vienna RNA software package for the analysis of RNA secondary structures. It currently offers prediction of secondary structure from a single sequence, prediction of the consensus secondary structure for a set of aligned sequences and the design of sequences that will fold into a predefined structure. All three services can be accessed via the Vienna RNA web server at http://rna.tbi.univie.ac.at/.

2,236 citations

Journal ArticleDOI
TL;DR: The Vienna RNA package as mentioned in this paper is based on dynamic programming algorithms and aims at predictions of structures with minimum free energies as well as at computations of the equilibrium partition functions and base pairing probabilities.
Abstract: Computer codes for computation and comparison of RNA secondary structures, the Vienna RNA package, are presented, that are based on dynamic programming algorithms and aim at predictions of structures with minimum free energies as well as at computations of the equilibrium partition functions and base pairing probabilities. An efficient heuristic for the inverse folding problem of RNA is introduced. In addition we present compact and efficient programs for the comparison of RNA secondary structures based on tree editing and alignment. All computer codes are written in ANSI C. They include implementations of modified algorithms on parallel computers with distributed memory. Performance analysis carried out on an Intel Hypercube shows that parallel computing becomes gradually more and more efficient the longer the sequences are.

2,136 citations

Journal ArticleDOI
TL;DR: A comprehensive software package for the analysis, reconstruction and visualization of three-dimensional nucleic acid structures that can handle antiparallel and parallel double helices, single-stranded structures, triplexes, quadruplexes and other complex tertiary folding motifs found in both DNA and RNA structures is presented.
Abstract: We present a comprehensive software package, 3DNA, for the analysis, reconstruction and visualization of three-dimensional nucleic acid structures. Starting from a coordinate file in Protein Data Bank (PDB) format, 3DNA can handle antiparallel and parallel double helices, single-stranded structures, triplexes, quadruplexes and other complex tertiary folding motifs found in both DNA and RNA structures. The analysis routines identify and categorize all base interactions and classify the double helical character of appropriate base pair steps. The program makes use of a recently recommended reference frame for the description of nucleic acid base pair geometry and a rigorous matrix-based scheme to calculate local conformational parameters and rebuild the structure from these parameters. The rebuilding routines produce rectangular block representations of nucleic acids as well as full atomic models with the sugar-phosphate backbone and publication quality 'standardized' base stacking diagrams. Utilities are provided to locate the base pairs and helical regions in a structure and to reorient structures for effective visualization. Regular helical models based on X-ray diffraction measurements of various repeating sequences can also be generated within the program.

1,598 citations

Journal ArticleDOI
TL;DR: An in vitro selection procedure was used to develop a DNA enzyme that can be made to cleave almost any targeted RNA substrate under simulated physiological conditions, and its activity is dependent on the presence of Mg2+ ion.
Abstract: An in vitro selection procedure was used to develop a DNA enzyme that can be made to cleave almost any targeted RNA substrate under simulated physiological conditions. The enzyme is comprised of a catalytic domain of 15 deoxynucleotides, flanked by two substrate-recognition domains of seven to eight deoxynucleotides each. The RNA substrate is bound through Watson–Crick base pairing and is cleaved at a particular phosphodiester located between an unpaired purine and a paired pyrimidine residue. Despite its small size, the DNA enzyme has a catalytic efficiency (kcat/Km) of ≈109 M−1⋅min−1 under multiple turnover conditions, exceeding that of any other known nucleic acid enzyme. Its activity is dependent on the presence of Mg2+ ion. By changing the sequence of the substrate-recognition domains, the DNA enzyme can be made to target different RNA substrates. In this study, for example, it was directed to cleave synthetic RNAs corresponding to the start codon region of HIV-1 gag/pol, env, vpr, tat, and nef mRNAs.

1,411 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202326
202262
202185
202087
201980
201869