ProbKnot: Fast prediction of RNA secondary structure including pseudoknots

Bellaousov, Stanislav; Mathews, David H.

doi:10.1261/rna.2125310

Cited by 190 publications

(188 citation statements)

References 76 publications

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“…As a prerequisite, these methods need to be capable of handling conformations of genus different from zero. A number of such methods based on free-energy minimization (50,51,(66)(67)(68)(69) or kinetic folding approaches (70) have been developed in recent years. Their predicted fold is typically encoded by a graph representation, which carries information about the succession of RNA strands contacts but is oblivious to associated sequence of strands over-and underpasses.…”

Section: Resultsmentioning

confidence: 99%

Absence of knots in known RNA structures

Micheletti

Stefano

Orland

2015

Proc. Natl. Acad. Sci. U.S.A.

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The ongoing effort to detect and characterize physical entanglement in biopolymers has so far established that knots are present in many globular proteins and also, abound in viral DNA packaged inside bacteriophages. RNA molecules, however, have not yet been systematically screened for the occurrence of physical knots. We have accordingly undertaken the systematic profiling of the several thousand RNA structures present in the Protein Data Bank (PDB). The search identified no more than three deeply knotted RNA molecules. These entries are rRNAs of about 3,000 nt solved by cryo-EM. Their genuine knotted state is, however, doubtful based on the detailed structural comparison with homologs of higher resolution, which are all unknotted. Compared with the case of proteins and viral DNA, the observed incidence of knots in available RNA structures is, therefore, practically negligible. This fact suggests that either evolutionary selection or thermodynamic and kinetic folding mechanisms act toward minimizing the entanglement of RNA to an extent that is unparalleled by other types of biomolecules. A possible general strategy for designing synthetic RNA sequences capable of self-tying in a twist-knot fold is finally proposed.RNA structure | RNA knots | physical knots | PDB-wide topological profiling T he notion that biomolecules should be minimally entangled to fold efficiently and reproducibly and sustain functionally oriented structural arrangements seems so intuitive that viable biological molecules have long been thought to be practically free of physical knots (1, 2).Indeed, it was only relatively recently that the occurrence of deeply knotted proteins was shown (3). Several other instances of knotted and slipknotted proteins have been discovered more recently (4), and it is now established that a sizeable fraction of the protein chains deposited in the Protein Data Bank (PDB) (5) host physical knots (1, 6). The latter range in complexity from the simplest trefoil knot to the six-crossing Stevedore's knot (7). The functional implications of these knots are still unclear. Nevertheless, several hypotheses have been formulated to rationalize the functional advantage that arguably leads specific knotted proteins to evolve from unknotted ones (6, 8). For instance, knots have been argued to enhance the mechanical stability of active sites and prevent proteolytic degradation (8, 9).Although empirical evidence shows de facto that knotted proteins do exist, it also confirms the expectations that physical knots can significantly hinder and slow down the spontaneous folding process (10). This occurs because the various folding steps need to be well-coordinated to ensure the formation of the correct knot type in the correct protein location (11-13). This limited kinetic accessibility is likely responsible for the much lower incidence of knots in proteins compared with generic equilibrated polymers (14), where entanglement inevitably arises with increasing chain length and compactness (15-18).Physical knots have also been shown t...

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Section: Resultsmentioning

confidence: 99%

Absence of knots in known RNA structures

Micheletti

Stefano

Orland

2015

Proc. Natl. Acad. Sci. U.S.A.

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“…The latter encompasses 1 of 2 nonrepeat associated "pyknons," putative regulatory motifs that are nonrandomly distributed throughout the genome (40). In addition, 3 putative pseudoknots (i.e., nested helices) are predicted by ProbKnot, which provides high sensitivity and positive prediction rates (41). Consistent with the absence of expression of SPRY4-IT1 outside of primates, no compatible structures appear to be significantly conserved throughout a multiple alignment of orthologous sequences from 31 eutherian mammals (see Materials and Methods).…”

Section: Structural Prediction Of Spry4-it1mentioning

confidence: 99%

The Melanoma-Upregulated Long Noncoding RNA SPRY4-IT1 Modulates Apoptosis and Invasion

et al. 2011

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The identification of cancer-associated long noncoding RNAs (lncRNAs) and the investigation of their molecular and biological functions are important to understand the molecular biology of cancer and its progression. Although the functions of lncRNAs and the mechanisms regulating their expression are largely unknown, recent studies are beginning to unravel their importance in human health and disease. Here, we report that a number of lncRNAs are differentially expressed in melanoma cell lines in comparison to melanocytes and keratinocyte controls. One of these lncRNAs, SPRY4-IT1 (GenBank accession ID AK024556), is derived from an intron of the SPRY4 gene and is predicted to contain several long hairpins in its secondary structure. RNA-FISH analysis showed that SPRY4-IT1 is predominantly localized in the cytoplasm of melanoma cells, and SPRY4-IT1 RNAi knockdown results in defects in cell growth, differentiation, and higher rates of apoptosis in melanoma cell lines. Differential expression of both SPRY4 and SPRY4-IT1 was also detected in vivo, in 30 distinct patient samples, classified as primary in situ, regional metastatic, distant metastatic, and nodal metastatic melanoma. The elevated expression of SPRY4-IT1 in melanoma cells compared to melanocytes, its accumulation in cell cytoplasm, and effects on cell dynamics, including increased rate of wound closure on SPRY4-IT1 overexpression, suggest that the higher expression of SPRY4-IT1 may have an important role in the molecular etiology of human melanoma. Cancer Res; 71(11); 3852-62. Ó2011 AACR.

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“…For RNA secondary structure prediction (Section 3.3.1), ProbKnot (Bellaousov and Mathews, 2010) uses a kind of posterior decoding method to predict secondary structure with pseudo-knots. It seems difficult to…”

Section: Posterior Decoding Methods (Pdms)mentioning

confidence: 99%

A Classification of Bioinformatics Algorithms from the Viewpoint of Maximizing Expected Accuracy (MEA)

Hamada

Asai

2012

Journal of Computational Biology

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Many estimation problems in bioinformatics are formulated as point estimation problems in a high-dimensional discrete space. In general, it is difficult to design reliable estimators for this type of problem, because the number of possible solutions is immense, which leads to an extremely low probability for every solution-even for the one with the highest probability. Therefore, maximum score and maximum likelihood estimators do not work well in this situation although they are widely employed in a number of applications. Maximizing expected accuracy (MEA) estimation, in which accuracy measures of the target problem and the entire distribution of solutions are considered, is a more successful approach. In this review, we provide an extensive discussion of algorithms and software based on MEA. We describe how a number of algorithms used in previous studies can be classified from the viewpoint of MEA. We believe that this review will be useful not only for users wishing to utilize software to solve the estimation problems appearing in this article, but also for developers wishing to design algorithms on the basis of MEA.

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ProbKnot: Fast prediction of RNA secondary structure including pseudoknots

Cited by 190 publications

References 76 publications

Absence of knots in known RNA structures

Absence of knots in known RNA structures

The Melanoma-Upregulated Long Noncoding RNA SPRY4-IT1 Modulates Apoptosis and Invasion

A Classification of Bioinformatics Algorithms from the Viewpoint of Maximizing Expected Accuracy (MEA)

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