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231225s2020 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.26195
|2 doi
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|a pubmed24n1026.xml
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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| 100 |
1 |
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|a Alaidi, Osama
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Statistical mechanical prediction of ligand perturbation to RNA secondary structure and application to riboswitches
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|c 2020
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
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|a Date Completed 14.06.2021
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|a Date Revised 14.06.2021
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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| 520 |
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|a © 2020 Wiley Periodicals, Inc.
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|a The realization that noncoding RNA is implicated in numerous cellular processes, makes it imperative to understand and predict RNA-folding. RNA secondary structure prediction is more tractable than tertiary structure or protein structure. Yet insights into RNA structure-function relationships are complicated by coupling between RNA-folding and ligand-binding. Here, perturbations to equilibrium secondary structure conformational distributions for two riboswitches are calculated in the presence of bound cognate ligands. This work incorporates a key factor coupling ligand binding to RNA conformation but not considered in most previous calculations: the differential affinity of the ligand for a range of RNA-folding intermediates. Significant shifts in the free energy landscape (FEL) due to the ligand occur for transcripts of lengths corresponding to the "decision window," following transcription of the so-called anti-terminator helix. The results suggest how ligand perturbation can stabilize the formation of an intermediate conformation, readily facilitating terminator hairpin formation in the full-length riboswitch
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|a Journal Article
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4 |
|a Research Support, Non-U.S. Gov't
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| 650 |
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4 |
|a RNA-ligand interaction
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| 650 |
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4 |
|a S-adenosyl methionine
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| 650 |
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4 |
|a regulation of gene expression
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| 650 |
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4 |
|a riboswitch RNA secondary structure
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| 650 |
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4 |
|a riboswitch design
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| 650 |
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|a statistical thermodynamics
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| 650 |
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|a Ligands
|2 NLM
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| 650 |
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|a Riboswitch
|2 NLM
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| 650 |
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|a RNA
|2 NLM
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| 650 |
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|a 63231-63-0
|2 NLM
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| 700 |
1 |
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|a Aboul-Ela, Fareed
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 41(2020), 16 vom: 15. Juni, Seite 1521-1537
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
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| 773 |
1 |
8 |
|g volume:41
|g year:2020
|g number:16
|g day:15
|g month:06
|g pages:1521-1537
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| 856 |
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|u http://dx.doi.org/10.1002/jcc.26195
|3 Volltext
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