Literature DB >> 25726466

Thermodynamic and kinetic folding of riboswitches.

Stefan Badelt1, Stefan Hammer2, Christoph Flamm3, Ivo L Hofacker2.   

Abstract

Riboswitches are structured RNA regulatory elements located in the 5'-UTRs of mRNAs. Ligand-binding induces a structural rearrangement in these RNA elements, effecting events in downstream located coding sequences. Since they do not require proteins for their functions, they are ideally suited for computational analysis using the toolbox of RNA structure prediction methods. By their very definition riboswitch function depends on structural change. Methods that consider only the thermodynamic equilibrium of an RNA are therefore of limited use. Instead, one needs to employ computationally more expensive methods that consider the energy landscape and the folding dynamics on that landscape. Moreover, for the important class of kinetic riboswitches, the mechanism of riboswitch function can only be understood in the context of co-transcriptional folding. We present a computational approach to simulate the dynamic behavior of riboswitches during co-transcriptional folding in the presence and absence of a ligand. Our investigations show that the abstraction level of RNA secondary structure in combination with a dynamic folding landscape approach is expressive enough to understand how riboswitches perform their function. We apply our approach to a experimentally validated theophylline-binding riboswitch.
© 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Co-transcriptional folding; Dynamic landscape; Kinetic folding; RNA secondary structure; Riboswitch; Theophylline aptamer

Mesh:

Substances:

Year:  2015        PMID: 25726466     DOI: 10.1016/bs.mie.2014.10.060

Source DB:  PubMed          Journal:  Methods Enzymol        ISSN: 0076-6879            Impact factor:   1.600


  3 in total

1.  Single-molecule FRET studies on the cotranscriptional folding of a thiamine pyrophosphate riboswitch.

Authors:  Heesoo Uhm; Wooyoung Kang; Kook Sun Ha; Changwon Kang; Sungchul Hohng
Journal:  Proc Natl Acad Sci U S A       Date:  2017-12-26       Impact factor: 11.205

Review 2.  Computational Methods for Modeling Aptamers and Designing Riboswitches.

Authors:  Sha Gong; Yanli Wang; Zhen Wang; Wenbing Zhang
Journal:  Int J Mol Sci       Date:  2017-11-17       Impact factor: 5.923

3.  Computational prediction of regulatory, premature transcription termination in bacteria.

Authors:  Adi Millman; Daniel Dar; Maya Shamir; Rotem Sorek
Journal:  Nucleic Acids Res       Date:  2016-08-29       Impact factor: 16.971

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.