1,717 research outputs found
Force-induced misfolding in RNA
RNA folding is a kinetic process governed by the competition of a large
number of structures stabilized by the transient formation of base pairs that
may induce complex folding pathways and the formation of misfolded structures.
Despite of its importance in modern biophysics, the current understanding of
RNA folding kinetics is limited by the complex interplay between the weak
base-pair interactions that stabilize the native structure and the disordering
effect of thermal forces. The possibility of mechanically pulling individual
molecules offers a new perspective to understand the folding of nucleic acids.
Here we investigate the folding and misfolding mechanism in RNA secondary
structures pulled by mechanical forces. We introduce a model based on the
identification of the minimal set of structures that reproduce the patterns of
force-extension curves obtained in single molecule experiments. The model
requires only two fitting parameters: the attempt frequency at the level of
individual base pairs and a parameter associated to a free energy correction
that accounts for the configurational entropy of an exponentially large number
of neglected secondary structures. We apply the model to interpret results
recently obtained in pulling experiments in the three-helix junction S15 RNA
molecule (RNAS15). We show that RNAS15 undergoes force-induced misfolding where
force favors the formation of a stable non-native hairpin. The model reproduces
the pattern of unfolding and refolding force-extension curves, the distribution
of breakage forces and the misfolding probability obtained in the experiments.Comment: 28 pages, 11 figure
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Three-dimensional modeling of single stranded DNA hairpins for aptamer-based biosensors.
Aptamers consist of short oligonucleotides that bind specific targets. They provide advantages over antibodies, including robustness, low cost, and reusability. Their chemical structure allows the insertion of reporter molecules and surface-binding agents in specific locations, which have been recently exploited for the development of aptamer-based biosensors and direct detection strategies. Mainstream use of these devices, however, still requires significant improvements in optimization for consistency and reproducibility. DNA aptamers are more stable than their RNA counterparts for biomedical applications but have the disadvantage of lacking the wide array of computational tools for RNA structural prediction. Here, we present the first approach to predict from sequence the three-dimensional structures of single stranded (ss) DNA required for aptamer applications, focusing explicitly on ssDNA hairpins. The approach consists of a pipeline that integrates sequentially building ssDNA secondary structure from sequence, constructing equivalent 3D ssRNA models, transforming the 3D ssRNA models into ssDNA 3D structures, and refining the resulting ssDNA 3D structures. Through this pipeline, our approach faithfully predicts the representative structures available in the Nucleic Acid Database and Protein Data Bank databases. Our results, thus, open up a much-needed avenue for integrating DNA in the computational analysis and design of aptamer-based biosensors
Monovalent ions modulate the flux through multiple folding pathways of an RNA pseudoknot
The functions of RNA pseudoknots (PKs), which are minimal tertiary structural
motifs and an integral part of several ribozymes and ribonucleoprotein
complexes, are determined by their structure, stability and dynamics.
Therefore, it is important to elucidate the general principles governing their
thermodynamics/folding mechanisms. Here, we combine experiments and simulations
to examine the folding/unfolding pathways of the VPK pseudoknot, a variant of
the Mouse Mammary Tumor Virus (MMTV) PK involved in ribosomal frameshifting.
Fluorescent nucleotide analogs (2-aminopurine and pyrrolocytidine) placed at
different stem/loop positions in the PK, and laser temperature-jump approaches
serve as local probes allowing us to monitor the order of assembly of VPK with
two helices with different intrinsic stabilities. The experiments and molecular
simulations show that at 50 mM KCl the dominant folding pathway populates only
the more stable partially folded hairpin. As the salt concentration is
increased a parallel folding pathway emerges, involving the less stable hairpin
structure as an alternate intermediate. Notably, the flux between the pathways
is modulated by the ionic strength. The findings support the principle that the
order of PK structure formation is determined by the relative stabilities of
the hairpins, which can be altered by sequence variations or salt
concentrations. Our study not only unambiguously demonstrates that PK folds by
parallel pathways, but also establishes that quantitative description of RNA
self-assembly requires a synergistic combination of experiments and
simulations.Comment: Supporting Information include
Autism-associated SNPs in the clock genes _npas2_, _per1_ and the homeobox gene _en2_ alter DNA sequences that show characteristics of microRNA genes.
Intronic single nucleotide polymorphisms (SNPs) in the clock genes _npas2_ and _per1_ and the homeobox gene _en2_ are reported to be associated with autism. This bioinformatics analysis of the intronic regions which contain the autism-associated SNPs rs1861972 and rs1861973 in _en2_, rs1811399 in _npas2_, and rs885747 in _per1_, shows that these regions encode RNA transcripts with predicted structural characteristics of microRNAs. These microRNA-like structures are disrupted _in silico_ by the presence of the autism enriched alleles of rs1861972, rs1861973, rs1811399 and rs885747 specifically, as compared with the minor alleles of these SNPs. The predicted gene targets of these microRNA-like structures include genes reported to be implicated in autism (_gabrb3_, _shank3_) and genes causative of diseases co-morbid with autism (_mecp2_ and _rai1_). The inheritance of the AC haplotype of rs1861972 - rs1861973 in _en2_, the C allele of rs1811399 in _npas2_, and the C allele of rs1234747 in _per1_ may contribute to the causes of autism by affecting microRNA genes that are co-expressed along with the homeobox gene _en2_ and the circadian genes _npas2_ and _per1_
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PATTERNA: transcriptome-wide search for functional RNA elements via structural data signatures.
Establishing a link between RNA structure and function remains a great challenge in RNA biology. The emergence of high-throughput structure profiling experiments is revolutionizing our ability to decipher structure, yet principled approaches for extracting information on structural elements directly from these data sets are lacking. We present PATTERNA, an unsupervised pattern recognition algorithm that rapidly mines RNA structure motifs from profiling data. We demonstrate that PATTERNA detects motifs with an accuracy comparable to commonly used thermodynamic models and highlight its utility in automating data-directed structure modeling from large data sets. PATTERNA is versatile and compatible with diverse profiling techniques and experimental conditions
Ab initio RNA folding
RNA molecules are essential cellular machines performing a wide variety of
functions for which a specific three-dimensional structure is required. Over
the last several years, experimental determination of RNA structures through
X-ray crystallography and NMR seems to have reached a plateau in the number of
structures resolved each year, but as more and more RNA sequences are being
discovered, need for structure prediction tools to complement experimental data
is strong. Theoretical approaches to RNA folding have been developed since the
late nineties when the first algorithms for secondary structure prediction
appeared. Over the last 10 years a number of prediction methods for 3D
structures have been developed, first based on bioinformatics and data-mining,
and more recently based on a coarse-grained physical representation of the
systems. In this review we are going to present the challenges of RNA structure
prediction and the main ideas behind bioinformatic approaches and physics-based
approaches. We will focus on the description of the more recent physics-based
phenomenological models and on how they are built to include the specificity of
the interactions of RNA bases, whose role is critical in folding. Through
examples from different models, we will point out the strengths of
physics-based approaches, which are able not only to predict equilibrium
structures, but also to investigate dynamical and thermodynamical behavior, and
the open challenges to include more key interactions ruling RNA folding.Comment: 28 pages, 18 figure
Experimental Progress in Computation by Self-Assembly of DNA Tilings
Approaches to DNA-based computing by self-assembly require the
use of D. T A nanostructures, called tiles, that have efficient chemistries, expressive
computational power: and convenient input and output (I/O) mechanisms.
We have designed two new classes of DNA tiles: TAO and TAE, both
of which contain three double-helices linked by strand exchange. Structural
analysis of a TAO molecule has shown that the molecule assembles efficiently
from its four component strands. Here we demonstrate a novel method for
I/O whereby multiple tiles assemble around a single-stranded (input) scaffold
strand. Computation by tiling theoretically results in the formation of structures
that contain single-stranded (output) reported strands, which can then
be isolated for subsequent steps of computation if necessary. We illustrate the
advantages of TAO and TAE designs by detailing two examples of massively
parallel arithmetic: construction of complete XOR and addition tables by linear
assemblies of DNA tiles. The three helix structures provide flexibility for
topological routing of strands in the computation: allowing the implementation
of string tile models
A model for the force stretching double-stranded chain molecules
We modify and extend the recently developed statistical mechanical model for
predicting the thermodynamic properties of chain molecules having noncovalent
double-stranded conformations, as in RNA or ssDNA, and sheets in
protein, by including the constant force stretching at one end of molecules as
in a typical single-molecule experiment. The conformations of double-stranded
regions of the chain are calculated based on polymer graph-theoretic approach
[S-J. Chen and K. A. Dill, J. Chem. Phys. {\bf109}, 4602(1998)], while the
unpaired single-stranded regions are treated as self-avoiding walks. Sequence
dependence and excluded volume interaction are taken into account explicitly.
Two classes of conformations, hairpin and RNA secondary structure are explored.
For the hairpin conformations, all possible end-to-end distances corresponding
to the different types of double-stranded regions are enumerated exactly. For
the RNA secondary structure conformations, a new recursive formula
incorporating the secondary structure and end-to-end distribution has been
derived. Using the model, we investigate the extension-force curves, contact
and population distributions and re-entering phenomena, respectively. we find
that the force stretching homogeneous chains of hairpin and secondary structure
conformations are very different: the unfolding of hairpins is two-state, while
unfolding the latter is one-state. In addition, re-entering transitions only
present in hairpin conformations, but are not observed in secondary structure
conformations.Comment: 19 pages, 28 figure
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