Secondary
and 3D structure of large RNA fragments -- a summary of algorithms (6)
RNA integrity (1) RNA integrity (2) RNA integrity (3) RNA integrity & DNA integrity (4) RNA integrity -- latest papers (5) RNA structure
Secondary and 3D structure of large RNA fragments -- a summary of algorithms The mFOLD Web Server http://mfold.rna.albany.edu/?q=mfold Mfold web server for nucleic acid folding and hybridization prediction. Zuker M Nucleic Acids Res. 2003 Jul 1;31(13):3406-15. 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'.
RNAML: a standard syntax for exchanging RNA information. Waugh A, Gendron P, Altman R, Brown JW, Case D, Gautheret D, Harvey SC, Leontis N, Westbrook J, Westhof E, Zuker M, Major F. RNA. 2002 8(6): 707-717 Analyzing a single data
set using multiple RNA informatics programs
often requires a file format conversion between each pair of programs,
significantly hampering productivity. To facilitate the interoperation
of these programs, we propose a syntax to exchange basic RNA molecular
information. This RNAML syntax allows for the storage and the exchange
of information about RNA sequence and secondary and tertiary
structures. The syntax permits the description of higher level
information about the data including, but not restricted to, base
pairs, base triples, and pseudoknots. A class-oriented approach allows
us to represent data common to a given set of RNA molecules, such as a
sequence alignment and a consensus secondary structure. Documentation
about experiments and computations, as well as references to journals
and external databases, are included in the syntax. The chief challenge
in creating such a syntax was to determine the appropriate scope of
usage and to ensure extensibility as new needs will arise. The syntax
complies with the eXtensible Markup Language (XML) recommendations, a
widely accepted standard for syntax specifications. In addition to the
various generic packages that exist to read and interpret XML formats,
an XML processor was developed and put in the open-source MC-Core
library for nucleic acid and protein structure computer manipulation.
Using reliability information to annotate RNA secondary structures. Zuker M and Jacobson AB. RNA. 1998 4(6): 669-679. A number of heuristic
descriptors have been developed previously in
conjunction with the mfold package that describe the propensity of
individual bases to participate in base pairs and whether or not a
predicted helix is "well-determined." They were developed for the
"energy dot plot" output of mfold. Two descriptors, P-num and H-num,
are used to measure the level of promiscuity in the association of any
given nucleotide or helix with alternative complementary pairs. The
third descriptor, S-num, measures the propensity of bases to be
single-stranded. In the current work, we describe a series of programs
that were developed in order to annotate individual structures with
"well-definedness" information. We use color annotation to present the
information. The programs can annotate PostScript files that are
created by the mfold package or the PostScript secondary structure
plots produced by the Weiser and Noller program XRNA (Weiser B, Noller
HF, 1995, XRNA: Auto-interactive program for modeling RNA, The Center
for Molecular Biology of RNA, Santa Cruz, California: University of
California; Internet: ftp://fangio.ucsc.edu/pub/XRNA).
In addition,
these programs can annotate ss files that serve as input to XRNA. The
annotation package can also handle structure comparison with a
reference structure. This feature can be used to compare predicted
structure with a phylogenetically deduced model, to compare two
different predicted foldings, and to identify conformational changes
that are predicted between wild-type and mutant RNAs. We provide
several examples of application. Predicted structures of two RNase P
RNAs were colored with P-num information and further annotated with
comparative information. The comparative model of a 16S rRNA was
annotated with P-num information from mfold and with base pair
probabilities obtained from the Vienna RNA folding package. Further
annotation adds comparisons with the optimal foldings obtained from
mfold and the Vienna package, respectively. The results of all of these
analyses are discussed in the context of the reliability of structure
prediction.
Sfold web server for statistical folding
and rational design of nucleic
acids.Folding and Finding RNA Secondary Structure. David H. Mathews, Walter N. Moss, and Douglas H. Turner Cold Spring Harb Perspect Biol. 2010 Dec; 2(12): a003665. Optimal exploitation of the expanding database of sequences requires rapid finding and folding of RNAs. Methods are reviewed that automate folding and discovery of RNAs with algorithms that couple thermodynamics with chemical mapping, NMR, and/or sequence comparison. New functional noncoding RNAs in genome sequences can be found by combining sequence comparison with the assumption that functional noncoding RNAs will have more favorable folding free energies than other RNAs. When a new RNA is discovered, experiments and sequence comparison can restrict folding space so that secondary structure can be rapidly determined with the help of predicted free energies. In turn, secondary structure restricts folding in three dimensions, which allows modeling of three-dimensional structure. An example from a domain of a retrotransposon is described. Discovery of new RNAs and their structures will provide insights into evolution, biology, and design of therapeutics. Applications to studies of evolution are also reviewed. Ding Y, Chan CY, Lawrence CE. Nucleic Acids Res. 2004 Jul 1;32(Web Server issue):W135-41. The Sfold web server
provides user-friendly access to Sfold, a recently
developed nucleic acid folding software package, via the World Wide Web
(WWW). The software is based on a new statistical sampling paradigm for
the prediction of RNA secondary structure. One of the main objectives
of this software is to offer computational tools for the rational
design of RNA-targeting nucleic acids, which include small interfering
RNAs (siRNAs), antisense oligonucleotides and trans-cleaving ribozymes
for gene knock-down studies. The methodology for siRNA design is based
on a combination of RNA target accessibility prediction, siRNA duplex
thermodynamic properties and empirical design rules. Our approach to
target accessibility evaluation is an original extension of the
underlying RNA folding algorithm to account for the likely existence of
a population of structures for the target mRNA. In addition to the
application modules Sirna, Soligo and Sribo for siRNAs, antisense
oligos and ribozymes, respectively, the module Srna offers
comprehensive features for statistical representation of sampled
structures. Detailed output in both graphical and text formats is
available for all modules. The Sfold server is available at http://sfold.wadsworth.org
RNAssess -- a web server for quality assessment of RNA 3D structures. Lukasiak P, Antczak M, Ratajczak T, Szachniuk M, Popenda M, Adamiak RW, Blazewicz J Nucleic Acids Res. 2015 Jun 11 Nowadays, various
methodologies can be applied to model RNA 3D structure. Thus, the
plausible quality assessment of 3D models has a fundamental impact on
the progress of structural bioinformatics. Here, we present RNAssess
server, a novel tool dedicated to visual evaluation of RNA 3D models in
the context of the known reference structure for a wide range of
accuracy levels (from atomic to the whole molecule perspective). The
proposed server is based on the concept of local neighborhood, defined
as a set of atoms observed within a sphere localized around a central
atom of a particular residue. A distinctive feature of our server is
the ability to perform simultaneous visual analysis of the
model-reference structure coherence. RNAssess supports the quality
assessment through delivering both static and interactive
visualizations that allows an easy identification of native-like models
and/or chosen structural regions of the analyzed molecule. A
combination of results provided by RNAssess allows us to rank analyzed
models. RNAssess offers new route to a fast and efficient 3D model
evaluation suitable for the RNA-Puzzles challenge. The proposed
automated tool is implemented as a free and open to all users web
server with an user-friendly interface and can be accessed at: http://rnassess.cs.put.poznan.pl/
Automated 3D structure composition for
large RNAs.Popenda M, Szachniuk M, Antczak M, Purzycka KJ, Lukasiak P, Bartol N, Blazewicz J, Adamiak RW. Nucleic Acids Res. 2012 40(14): e112 Understanding the
numerous functions that RNAs play in living cells depends critically on
knowledge of their three-dimensional structure. Due to the difficulties
in experimentally assessing structures of large RNAs, there is
currently great demand for new high-resolution structure prediction
methods. We present the novel method for the fully automated prediction
of RNA 3D structures from a user-defined secondary structure. The
concept is founded on the machine translation system. The translation
engine operates on the RNA FRABASE database tailored to the dictionary
relating the RNA secondary structure and tertiary structure elements.
The translation algorithm is very fast. Initial 3D structure is
composed in a range of seconds on a single processor. The method
assures the prediction of large RNA 3D structures of high quality. Our
approach needs neither structural templates nor RNA sequence alignment,
required for comparative methods. This enables the building of
unresolved yet native and artificial RNA structures. The method is
implemented in a publicly available, user-friendly server RNAComposer.
It works in an interactive mode and a batch mode. The batch mode is
designed for large-scale modelling and accepts atomic distance
restraints. Presently, the server is set to build RNA structures of up
to 500 residues.
RNA FRABASE 2.0 -- an advanced
web-accessible database with the capacity to search the
three-dimensional fragments within RNA structures.Popenda M, Szachniuk M, Blazewicz M, Wasik S, Burke EK, Blazewicz J, Adamiak RW. BMC Bioinformatics. 2010 11: 231 BACKGROUND: Recent discoveries
concerning novel functions of RNA, such as RNA interference, have
contributed towards the growing importance of the field. In this
respect, a deeper knowledge of complex three-dimensional RNA structures
is essential to understand their new biological functions. A number of
bioinformatic tools have been proposed to explore two major structural
databases (PDB, NDB) in order to analyze various aspects of RNA
tertiary structures. One of these tools is RNA FRABASE 1.0, the first
web-accessible database with an engine for automatic search of 3D
fragments within PDB-derived RNA structures. This search is based upon
the user-defined RNA secondary structure pattern. In this paper, we
present and discuss RNA FRABASE 2.0. This second version of the system
represents a major extension of this tool in terms of providing new
data and a wide spectrum of novel functionalities. An intuitionally
operated web server platform enables very fast user-tailored search of
three-dimensional RNA fragments, their multi-parameter conformational
analysis and visualization.
DESCRIPTION: RNA FRABASE 2.0
has stored information on 1565 PDB-deposited RNA structures, including
all NMR models. The RNA FRABASE 2.0 search engine algorithms operate on
the database of the RNA sequences and the new library of RNA secondary
structures, coded in the dot-bracket format extended to hold
multi-stranded structures and to cover residues whose coordinates are
missing in the PDB files. The library of RNA secondary structures (and
their graphics) is made available. A high level of efficiency of the 3D
search has been achieved by introducing novel tools to formulate
advanced searching patterns and to screen highly populated tertiary
structure elements. RNA FRABASE 2.0 also stores data and conformational
parameters in order to provide "on the spot" structural filters to
explore the three-dimensional RNA structures. An instant visualization
of the 3D RNA structures is provided. RNA FRABASE 2.0 is freely
available at http://rnafrabase.cs.put.poznan.pl
CONCLUSIONS: RNA FRABASE 2.0
provides a novel database and powerful search engine which is equipped
with new data and functionalities that are unavailable elsewhere. Our
intention is that this advanced version of the RNA FRABASE will be of
interest to all researchers working in the RNA field.
Towards 3D structure prediction of large
RNA molecules: an integer programming framework to insert local 3D
motifs in RNA secondary structure.Reinharz V, Major F, Waldispühl J Bioinformatics. 2012 Jun 15;28(12): i207-214 MOTIVATION: The prediction of
RNA 3D structures from its sequence only is a milestone to RNA function
analysis and prediction. In recent years, many methods addressed this
challenge, ranging from cycle decomposition and fragment assembly to
molecular dynamics simulations. However, their predictions remain
fragile and limited to small RNAs. To expand the range and accuracy of
these techniques, we need to develop algorithms that will enable to use
all the structural information available. In particular, the energetic
contribution of secondary structure interactions is now well
documented, but the quantification of non-canonical interactions-those
shaping the tertiary structure-is poorly understood. Nonetheless, even
if a complete RNA tertiary structure energy model is currently
unavailable, we now have catalogues of local 3D structural motifs
including non-canonical base pairings. A practical objective is thus to
develop techniques enabling us to use this knowledge for robust RNA
tertiary structure predictors.
RESULTS: In this work, we
introduce RNA-MoIP, a program that benefits from the progresses made
over the last 30 years in the field of RNA secondary structure
prediction and expands these methods to incorporate the novel local
motif information available in databases. Using an integer programming
framework, our method refines predicted secondary structures (i.e.
removes incorrect canonical base pairs) to accommodate the insertion of
RNA 3D motifs (i.e. hairpins, internal loops and k-way junctions).
Then, we use predictions as templates to generate complete 3D
structures with the MC-Sym program. We benchmarked RNA-MoIP on a set of
9 RNAs with sizes varying from 53 to 128 nucleotides. We show that our
approach (i) improves the accuracy of canonical base pair predictions;
(ii) identifies the best secondary structures in a pool of suboptimal
structures; and (iii) predicts accurate 3D structures of large RNA
molecules.
AVAILABILITY:
RNA-MoIP is publicly available at: http://csb.cs.mcgill.ca/RNAMoIPWeb 3DNA -- a web server for the analysis, reconstruction, and visualization of three-dimensional nucleic-acid structures. Zheng G, Lu XJ, Olson WK. Nucleic Acids Res. 2009 Jul;37(Web Server issue): W240-246 The w3DNA (web 3DNA)
server is a user-friendly web-based interface to the 3DNA suite of
programs for the analysis, reconstruction, and visualization of
three-dimensional (3D) nucleic-acid-containing structures, including
their complexes with proteins and other ligands. The server allows the
user to determine a wide variety of conformational parameters in a
given structure--such as the identities and rigid-body parameters of
interacting nucleic-acid bases and base-pair steps, the nucleotides
comprising helical fragments, etc. It is also possible to build 3D
models of arbitrary nucleotide sequences and helical types, customized
single-stranded and double-helical structures with user-defined
base-pair parameters and sequences, and models of DNA 'decorated' at
user-defined sites with proteins and other molecules. The visualization
component offers unique, publication-quality representations of
nucleic-acid structures, such as 'block' images of bases and base pairs
and stacking diagrams of interacting nucleotides. The w3DNA web server,
located at http://w3dna.rutgers.edu, is free and open to all users with
no login requirement.
Computational Methods for RNA Structure
Validation and Improvement.Jain S, Richardson DC, Richardson JS Methods Enzymol. 2015; 558: 181-212 With increasing
recognition of the roles RNA molecules and RNA/protein complexes play
in an unexpected variety of biological processes, understanding of RNA
structure-function relationships is of high current importance. To make
clean biological interpretations from three-dimensional structures, it
is imperative to have high-quality, accurate RNA crystal structures
available, and the community has thoroughly embraced that goal.
However, due to the many degrees of freedom inherent in RNA structure
(especially for the backbone), it is a significant challenge to succeed
in building accurate experimental models for RNA structures. This
chapter describes the tools and techniques our research group and our
collaborators have developed over the years to help RNA structural
biologists both evaluate and achieve better accuracy. Expert analysis
of large, high-resolution, quality-conscious RNA datasets provides the
fundamental information that enables automated methods for robust and
efficient error diagnosis in validating RNA structures at all
resolutions. The even more crucial goal of correcting the diagnosed
outliers has steadily developed toward highly effective,
computationally based techniques. Automation enables solving complex
issues in large RNA structures, but cannot circumvent the need for
thoughtful examination of local details, and so we also provide some
guidance for interpreting and acting on the results of current
structure validation for RNA.
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