Literature DB >> 20061789

Energy minimization methods applied to riboswitches: a perspective and challenges.

Danny Barash1, Idan Gabdank.   

Abstract

Energy minimization methods for RNA secondary structure prediction have been used extensively for studying a variety of biological systems. Here, we demonstrate their applicability in riboswitch studies, exemplified in both the expression platform and aptamer domains. In the expression platform domain, energy minimization methods can be used to predict in silico a unique point mutation positioned in the non-conserved region of the TPP riboswitch that will transform it from a termination to an anti-termination state, thus backing the prediction experimentally. Furthermore, a successive prediction can be made for a compensatory mutation that is positioned over half the sequence length of the riboswitch from the original mutation and that completely overturns the anti-termination effect of the original mutation. This approach can be used to computationally predict rational modifications in riboswitches for both research and practical applications. In the aptamer domain, energy minimization methods can be used when attempting to detect a novel purine riboswitch in eukaryotes based on the consensus sequence and structure of the bacterial guanine binding aptamer. In the process, some interesting candidates are identified, and although they are attractive enough to be tested experimentally, they are not detectable by sequence based methods alone. These brief examples represent the important lessons to be learned as to the strengths and limitations of energy minimization methods. In light of our growing knowledge in the energy minimization field, future challenges can be advanced for the rational design of known riboswitches and the detection of novel riboswitches. Unlike analyses of specific cases, it is stressed that all the results described here are predictive in scope with direct applicability and an attempt to validate the predictions experimentally.

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Year:  2010        PMID: 20061789     DOI: 10.4161/rna.7.1.10657

Source DB:  PubMed          Journal:  RNA Biol        ISSN: 1547-6286            Impact factor:   4.652


  7 in total

1.  The RNAmute web server for the mutational analysis of RNA secondary structures.

Authors:  Alexander Churkin; Idan Gabdank; Danny Barash
Journal:  Nucleic Acids Res       Date:  2011-04-07       Impact factor: 16.971

2.  RNAPattMatch: a web server for RNA sequence/structure motif detection based on pattern matching with flexible gaps.

Authors:  Matan Drory Retwitzer; Maya Polishchuk; Elena Churkin; Ilona Kifer; Zohar Yakhini; Danny Barash
Journal:  Nucleic Acids Res       Date:  2015-05-04       Impact factor: 16.971

Review 3.  Using RNA Sequence and Structure for the Prediction of Riboswitch Aptamer: A Comprehensive Review of Available Software and Tools.

Authors:  Deborah Antunes; Natasha A N Jorge; Ernesto R Caffarena; Fabio Passetti
Journal:  Front Genet       Date:  2018-01-19       Impact factor: 4.599

4.  Incipient Sympatric Speciation and Evolution of Soil Bacteria Revealed by Metagenomic and Structured Non-Coding RNAs Analysis.

Authors:  Sumit Mukherjee; Zhuoran Kuang; Samrat Ghosh; Rajesh Detroja; Gon Carmi; Sucheta Tripathy; Danny Barash; Milana Frenkel-Morgenstern; Eviatar Nevo; Kexin Li
Journal:  Biology (Basel)       Date:  2022-07-26

5.  RNAloops: a database of RNA multiloops.

Authors:  Jakub Wiedemann; Jacek Kaczor; Maciej Milostan; Tomasz Zok; Jacek Blazewicz; Marta Szachniuk; Maciej Antczak
Journal:  Bioinformatics       Date:  2022-07-09       Impact factor: 6.931

6.  An Efficient Minimum Free Energy Structure-Based Search Method for Riboswitch Identification Based on Inverse RNA Folding.

Authors:  Matan Drory Retwitzer; Ilona Kifer; Supratim Sengupta; Zohar Yakhini; Danny Barash
Journal:  PLoS One       Date:  2015-07-31       Impact factor: 3.240

7.  Phylogenomic and comparative analysis of the distribution and regulatory patterns of TPP riboswitches in fungi.

Authors:  Sumit Mukherjee; Matan Drory Retwitzer; Danny Barash; Supratim Sengupta
Journal:  Sci Rep       Date:  2018-04-03       Impact factor: 4.379

  7 in total

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