The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots
Open accessAbstract
A pseudoknot forms in an RNA when nucleotides in a loop pair with a region outside the helices that close the loop. Pseudoknots occur relatively rarely in RNA but are highly overrepresented in functionally critical motifs in large catalytic RNAs, in riboswitches, and in regulatory elements of viruses. Pseudoknots are usually excluded from RNA structure prediction algorithms. When included, these pairings are difficult to model accurately, especially in large RNAs, because allowing this structure dramatically increases the number of possible incorrect folds and because it is difficult to search the fold space for an optimal structure. We have developed a concise secondary structure modeling approach that combines SHAPE (selective 2′-hydroxyl acylation analyzed by primer extension) experimental chemical probing information and a simple, but robust, energy model for the entropic cost of single pseudoknot formation. Structures are predicted with iterative refinement, using a dynamic programming algorithm. This melded experimental and thermodynamic energy function predicted the secondary structures and the pseudoknots for a set of 21 challenging RNAs of known structure ranging in size from 34 to 530 nt. On average, 93% of known base pairs were predicted, and all pseudoknots in well-folded RNAs were identified.
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Self-citationAccurate SHAPE-directed RNA structure determination
Deigan, K. E., Li, T. W., Mathews, D. H., & Weeks, K. M. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0806929106 · Cited by 696
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Self-citationThe Structural and Functional Diversity of Metabolite-Binding Riboswitches
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Self-citationStructure of the S-adenosylmethionine riboswitch regulatory mRNA element
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Structure and Mechanism of a Metal-Sensing Regulatory RNA
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Cited by
In vivo genome-wide profiling of RNA secondary structure reveals novel regulatory features
Ding, Y., Tang, Y., Kwok, C. K., Zhang, Y., Bevilacqua, P. C., & Assmann, S. M. (2014) · Nature · doi:10.1038/nature12756 · Cited by 775
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Self-citationGenome-wide mapping of SARS-CoV-2 RNA structures identifies therapeutically-relevant elements
Manfredonia, I., Nithin, C., Ponce-Salvatierra, A., Ghosh, P., Wirecki, T. K., Marinus, T., Ogando, N. S., Snijder, E. J., van Hemert, M. J., Bujnicki, J. M., et al. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa1053 · Cited by 282
Linnstaedt, S. D., Riker, K. D., Rueckeis, C. A., Kutchko, K. M., Lackey, L., McCarthy, K. R., Tsai, Y.-H., Parker, J. S., Kurz, M. C., Hendry, P. L., et al. (2018) · The Journal of Neuroscience · doi:10.1523/jneurosci.3458-17.2018 · Cited by 66
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Metadata
- Authors
- Hajdin, C. E., Bellaousov, S., Huggins, W., Leonard, C. W., Mathews, D. H., & Weeks, K. M.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2013-03-15
- Volume
- 110
- Issue
- 14
- Pages
- 5498-5503
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2148725278
- Cited by
- 331
- References
- 27
- FWCI
- 13.58
- Type
- journal article
- Language
- en
- Open access
- bronze
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