The abbreviated name,‘mfold web server’,describes a number of closely related software applications available on the World Wide Web (WWW) for the prediction of the secondary structure of single stranded nucleic acids. The objective of this web server is to provide easy access to RNA and DNA folding and hybridization software to the scientific community at large. By making use of universally available web GUIs (Graphical User Interfaces),the server circumvents the problem of portability of this software. Detailed output,in the form of structure plots with or without reliability information,single strand frequency plots and ‘energy dot plots’, are available for the folding of single sequences. A variety of ‘bulk’ servers give less information,but in a shorter time and for up to hundreds of sequences at once. The portal for the mfold web server is http://www.bioinfo.rpi.edu/applications/ mfold. This URL will be referred to as ‘MFOLDROOT’.

/pdf/mfold-web-server-for-nucleic-acid-folding-and-hybridization-3pzoe1h05m.pdf

Mfold web server for nucleic acid folding and hybridization prediction

https://njc.rockefeller.edu/pdf4/Class2-LeeAmbros1993.pdf

The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14

http://bio.gsnu.ac.kr/research/miRNA/RNAss/Mfold/miRNAss_JMB_1999_Mathews.pdf

Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure.

Background
Secondary structure forms an important intermediate level of description of nucleic acids that encapsulates the dominating part of the folding energy, is often well conserved in evolution, and is routinely used as a basis to explain experimental findings. Based on carefully measured thermodynamic parameters, exact dynamic programming algorithms can be used to compute ground states, base pairing probabilities, as well as thermodynamic properties.

/pdf/viennarna-package-2-0-4q9zpqix5v.pdf

ViennaRNA Package 2.0

Thirteen families have been described with an autosomal dominantly inherited dementia named frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17)(1-9), historically termed Pick's disease(10) Most FTDP-17 cases show neuronal and/or glial inclusions that stain positively with antibodies raised against the microtubule-associated protein Tau, although the Tau pathology varies considerably in both its quantity (or severity) and characteristics(1-8,12) Previous studies have mapped the FTDP-17 locus to a 2-centimorgan region on chromosome 17q2111; the tau gene also lies within this region We have now sequenced tau in FTDP-17 families and identified three missense mutations (G272V, P301L and R406W) and three mutations in the 5' splice site of exon in The splice-site mutations all destabilize a potential stem-loop structure which is probably involved in regulating the alternative splicing of exon10 (ref 13) This causes more frequent usage of the 5' splice site and an increased proportion of tan transcripts that include exon 10 The increase in exon 10(+) messenger RNA will increase the proportion of Tau containing four microtubule-binding repeats, which is consistent with the neuropathology described in several families with FTDP-17 (refs 12, 14)

Association of missense and 5′-splice-site mutations in tau with the inherited dementia FTDP-17

Thermodynamic parameters for prediction of RNA duplex stability are reported. One parameter for duplex initiation and 10 parameters for helix propagation are derived from enthalpy and free-energy changes for helix formation by 45 RNA oligonucleotide duplexes. The oligomer sequences were chosen to maximize reliability of secondary structure predictions. Each of the 10 nearest-neighbor sequences is well-represented among the 45 oligonucleotides, and the sequences were chosen to minimize experimental errors in delta GO at 37 degrees C. These parameters predict melting temperatures of most oligonucleotide duplexes within 5 degrees C. This is about as good as can be expected from the nearest-neighbor model. Free-energy changes for helix propagation at dangling ends, terminal mismatches, and internal G X U mismatches, and free-energy changes for helix initiation at hairpin loops, internal loops, or internal bulges are also tabulated.

https://www.pnas.org/content/pnas/83/24/9373.full.pdf

Improved free-energy parameters for predictions of RNA duplex stability

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 single-stranded 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.

https://www.pnas.org/content/pnas/86/20/7706.full.pdf

Improved predictions of secondary structures for RNA.

Publisher Summary There are two methods of predicting secondary structure: phylogeny and energy minimization. Phylogeny relies on alignment and subsequent folding of several sequences into similar structures for functionally analogous RNA. Energy minimization relies on thermodynamic parameters and computer. There are two versions of the program: LRNA folds linear sequences, and CRNA folds circular sequences. LRNA and CRNA have the same user interface. Information about the structure helps the program fold the sequence into a better secondary structure. The locations of single-stranded sites, double-stranded sites, or known helixes are easily entered in LRNA. In batch mode, a sequence of commands in a batch file is run non-interactively, usually in nonprime time. The user can type in the batch file using an editor or the interactive program BATGEN. BATGEN first asks for the batch file name and the header file name. The header file contains information placed at the top of the batch file, such as a system command to change directories.

Predicting optimal and suboptimal secondary structure for RNA

This article describes the latest version of an RNA folding algorithm that predicts both optimal and suboptimal solutions based on free energy minimization. A number of RNA's with known structures deduced from comparative sequence analysis are folded to test program performance. The group of solutions obtained for each molecule is analysed to determine how many of the known helixes occur in the optimal solution and in the best suboptimal solution. In most cases, a structure about 80% correct is found with a free energy within 2% of the predicted lowest free energy structure.

A comparison of optimal and suboptimal RNA secondary structures predicted by free energy minimization with structures determined by phylogenetic comparison

Little is known about the folding pathways of RNA. A particularly interesting RNA is L-21 Sca I, a linear form of the self-splicing intron from the precursor of the Tetrahymena thermophila large subunit (LSU) rRNA. Thermal unfolding of L-21 Sca I is studied by UV absorption and chemical mapping in 50 mM Na+ and 10 mM free Mg2+ at pH 7.5. UV melting experiments identify two major transitions with maxima at 65 and 73 degrees C. Chemical mapping at the beginning and middle of the first transition suggests it primarily involves disruption of tertiary structure. Phylogenetic comparisons suggest a potential tertiary interaction between loops L2.1 and L9.1a. Chemical mapping and melting experiments on a truncated form of the intron lacking P9.1a, L-21 Nhe I, are consistent with this hypothesis. The results indicate that increasing temperature disrupts tertiary interactions before disrupting secondary structure. This suggests tertiary interactions are weaker than secondary interactions in this case. These results support an important assumption for RNA structure prediction: that secondary structure dominates the free energy of folding.

John A. Jaeger

Papers

Improved free-energy parameters for predictions of RNA duplex stability

Improved predictions of secondary structures for RNA.

Predicting optimal and suboptimal secondary structure for RNA

A comparison of optimal and suboptimal RNA secondary structures predicted by free energy minimization with structures determined by phylogenetic comparison

Thermal unfolding of a group I ribozyme: the low-temperature transition is primarily disruption of tertiary structure.