Mfold web server for nucleic acid folding and hydrization prediction,

Mfold web server for nucleic acid folding and hydrization prediction, (2003)

by M Zuker

Venue:

Nucleic Acids Research,

Results 1 - 10 of 1,992

Molecular basis for the recognition of primary microRNAs by the Drosha-DGCR8 complex

by Jinju Han, Yoontae Lee, Kyu-hyeon Yeom, Jin-wu Nam, Inha Heo, Je-keun Rhee, Sun Young Sohn, Yunje Cho, Byoung-tak Zhang, V. Narry Kim - Cell , 2006

"... The Drosha-DGCR8 complex initiates micro-RNA maturation by precise cleavage of the stem loops that are embedded in primary transcripts (pri-miRNAs). Here we propose a model for this process that is based upon evidence from both computational and biochemical analyses. A typical metazoan pri-miRNA con ..."

Abstract - Cited by 133 (1 self) - Add to MetaCart

The Drosha-DGCR8 complex initiates micro-RNA maturation by precise cleavage of the stem loops that are embedded in primary transcripts (pri-miRNAs). Here we propose a model for this process that is based upon evidence from both computational and biochemical analyses. A typical metazoan pri-miRNA consists of a stem of 33 bp, with a terminal loop and flanking segments. The terminal loop is unessential, whereas the flanking ssRNA segments are critical for processing. The cleavage site is determined mainly by the distance ( 11 bp) from the stem-ssRNA junction. Purified DGCR8, but not Drosha, interacts with pri-miRNAs both directly and specifically, and the flanking ssRNA segments are vital for this binding to occur. Thus, DGCR8 may function as the molecular anchor that measures the distance from the dsRNA-ssRNA junction. Our current study thus facilitates the prediction of novel micro-RNAs and will assist in the rational design of small hairpin RNAs for RNA interference.

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CONTRAfold: RNA secondary structure prediction without physics-based models

by Chuong B. Do, Daniel A. Woods, Serafim Batzoglou - Bioinformatics , 2006

"... doi:10.1093/bioinformatics/btl246 ..."

Abstract - Cited by 122 (8 self) - Add to MetaCart

doi:10.1093/bioinformatics/btl246

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Sfold web server for statistical folding and rational design of nucleic acids

by Ye Ding, Chi Yu Chan, Charles E. Lawrence - Nucleic Acids Res , 2004

"... nucleic acids ..."

Abstract - Cited by 108 (10 self) - Add to MetaCart

nucleic acids

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Engineered riboregulators enable posttranscriptional control of gene expression.

by Farren J Isaacs , Daniel J Dwyer , Chunming Ding , Dmitri D Pervouchine , Charles R Cantor , James J Collins - Nat. Biotechnol. , 2004

"... RNA molecules are most often thought of as messengers of information from genes to the proteins they encode 1,2 . RNAs can also assume various structural, regulatory and enzymatic roles 3 . These noncoding RNAs (ncRNA) have diverse functions including synthesizing proteins, splicing and editing RNA ..."

Abstract - Cited by 77 (5 self) - Add to MetaCart

RNA molecules are most often thought of as messengers of information from genes to the proteins they encode 1,2 . RNAs can also assume various structural, regulatory and enzymatic roles 3 . These noncoding RNAs (ncRNA) have diverse functions including synthesizing proteins, splicing and editing RNA, modifying rRNA 1-3 and catalyzing biochemical reactions A number of approaches that exploit RNA's structural dynamics and sequence-specific binding abilities are used in RNA-mediated control of gene expression 20 . Antisense strategies for gene silencing, in which an antisense RNA binds and inhibits a target RNA, are actively being pursued RESULTS Artificial riboregulation design In contrast to previous engineered schemes for prokaryotic posttranscriptional regulation, in which repression is achieved through antisense RNA or trans-acting ribozymes 24,25 , our approach obtains effective repression by formation of an RNA secondary structure that sequesters the ribosome binding site (RBS). A short nucleotide sequence complementary to the RBS is introduced in the DNA directly upstream of the RBS such that the 5′-untranslated region (UTR) of the mRNA sequence naturally folds to form a stem-loop structure encompassing the RBS We aimed to construct a modular post-transcriptional system able to function with numerous transcriptional and regulatory components. In this regard, because the cis element is located in the 5′-UTR, the crRNA and taRNA sequences that we designed do not target genespecific sequences or require specific promoters. Several aspects of Recent studies have demonstrated the important enzymatic, structural and regulatory roles of RNA in the cell. Here we present a post-transcriptional regulation system in Escherichia coli that uses RNA to both silence and activate gene expression. We inserted a complementary cis sequence directly upstream of the ribosome binding site in a target gene. Upon transcription, this cis-repressive sequence causes a stem-loop structure to form at the 5′-untranslated region of the mRNA. The stem-loop structure interferes with ribosome binding, silencing gene expression. A small noncoding RNA that is expressed in trans targets the cis-repressed RNA with high specificity, causing an alteration in the stem-loop structure that activates expression. Such engineered riboregulators may lend insight into mechanistic actions of endogenous RNA-based processes and could serve as scalable components of biological networks, able to function with any promoter or gene to directly control gene expression.

Pure multiple RNA secondary structure alignments: a progressive profile approach

by Matthias Höchsmann, Björn Voss, Robert Giegerich - IEEE/ACM Trans. Comput. Biol. Bioinform

"... Abstract—In functional, noncoding RNA, structure is often essential to function. While the full 3D structure is very difficult to determine, the 2D structure of an RNA molecule gives good clues to its 3D structure, and for molecules of moderate length, it can be predicted with good reliability. Stru ..."

Abstract - Cited by 73 (3 self) - Add to MetaCart

Abstract—In functional, noncoding RNA, structure is often essential to function. While the full 3D structure is very difficult to determine, the 2D structure of an RNA molecule gives good clues to its 3D structure, and for molecules of moderate length, it can be predicted with good reliability. Structure comparison is, in analogy to sequence comparison, the essential technique to infer related function. We provide a method for computing multiple alignments of RNA secondary structures under the tree alignment model, which is suitable to cluster RNA molecules purely on the structural level, i.e., sequence similarity is not required. We give a systematic generalization of the profile alignment method from strings to trees and forests. We introduce a tree profile representation of RNA secondary structure alignments which allows reasonable scoring in structure comparison. Besides the technical aspects, an RNA profile is a useful data structure to represent multiple structures of RNA sequences. Moreover, we propose a visualization of RNA consensus structures that is enriched by the full sequence information. Index Terms—Alignment of trees, RNA secondary structures, noncoding RNAs.

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Molecular basis for target RNA recognition and cleavage by human RISC. Cell 130:101–112

by Stefan Ludwig Ameres, Javier Martinez, Renée Schroeder , 2007

"... a ribonucleoprotein particle composed of a single-stranded short interfering RNA (siRNA) and an endonucleolytically active Argonaute protein, capable of cleaving mRNAs complementary to the siRNA. The mechanism by which RISC cleaves a target RNA is well understood, however it remains enigmatic how RI ..."

Abstract - Cited by 70 (0 self) - Add to MetaCart

a ribonucleoprotein particle composed of a single-stranded short interfering RNA (siRNA) and an endonucleolytically active Argonaute protein, capable of cleaving mRNAs complementary to the siRNA. The mechanism by which RISC cleaves a target RNA is well understood, however it remains enigmatic how RISC finds its target RNA. Here, we show, both in vitro and in vivo, that the accessibility of the target site correlates directly with the efficiency of cleavage, demonstrating that RISC is unable to unfold structured RNA. In the course of target recognition, RISC transiently contacts singlestranded RNA nonspecifically and promotes siRNA-target RNA annealing. Furthermore, the 5 0 part of the siRNA within RISC creates a thermodynamic threshold that determines the stable association of RISC and the target RNA. We therefore provide mechanistic insights by revealing features of RISC and target RNAs that are crucial to achieve efficiency and specificity in RNA interference.

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Thermodynamics of RNA-RNA Binding

by Ulrike Mückstein , Hakim Tafer , Jörg Hackermüller , Stephan H. Bernhart , Peter F. Stadler , Ivo L. Hofacker , 2005

"... Background: Reliable predictions of RNA-RNA binding energies is crucial e.g. for the understanding on RNAi, microRNA-mRNA binding, and antisense interactions. The thermodynamics of such RNA-RNA interactions can be understood as the sum of two energy contributions: (1) the energy necessary to “open ” ..."

Abstract - Cited by 63 (13 self) - Add to MetaCart

Background: Reliable predictions of RNA-RNA binding energies is crucial e.g. for the understanding on RNAi, microRNA-mRNA binding, and antisense interactions. The thermodynamics of such RNA-RNA interactions can be understood as the sum of two energy contributions: (1) the energy necessary to “open ” the binding site, and (2) the energy gained from hybridization. Methods: We present an extension of the standard partition function approach to RNA secondary structures that computes the probabilities Pu[i, j] that a sequence interval [i, j] is unpaired. Results: Comparison with experimental data shows that Pu[i, j] can be applied as a significant determinant of local target site accessibility for RNA interference (RNAi). Furthermore, these quantities can be used to rigorously determine binding free energies of short oligomers to large mRNA targets. The resource consumption is comparable to a single partition function computation for the large target molecule. We can show that RNAi efficiency correlates well with the binding energies of siRNAs to their respective mRNA target.

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