Literature DB >> 28730429

A New Method to Predict Ion Effects in RNA Folding.

Li-Zhen Sun1, Shi-Jie Chen2.   

Abstract

The strong interaction between metal ions in solution and highly charged RNA molecules is critical for RNA structure formation and stabilization. Metal ions binding to RNA can induce RNA structural changes that are important for RNA cellular functions. Therefore, quantitative modeling of the ion effects is essential for RNA structure prediction and RNA-based molecular design. Recently, inspired by the increasing experimental evidence that supports the importance of ion correlation and fluctuation in ion-RNA interactions, we developed a new computational model, Monte Carlo Tightly Bound Ion (MCTBI) model. The validity of the model is shown by the improved accuracy in the predictions for ion binding properties and ion-dependent free energies for RNA structures. In this chapter, using homodimeric tetraloop-receptor docking as an illustrative example, we showcase the MCTBI method for the computational prediction of the ion effects in RNA folding.

Entities:  

Keywords:  Ion–RNA interactions; Metal ion effects; RNA folding; Tightly Bound Ion model

Mesh:

Substances:

Year:  2017        PMID: 28730429      PMCID: PMC5749638          DOI: 10.1007/978-1-4939-7138-1_1

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  55 in total

1.  Electrostatics of nanosystems: application to microtubules and the ribosome.

Authors:  N A Baker; D Sept; S Joseph; M J Holst; J A McCammon
Journal:  Proc Natl Acad Sci U S A       Date:  2001-08-21       Impact factor: 11.205

2.  Predicting ion binding properties for RNA tertiary structures.

Authors:  Zhi-Jie Tan; Shi-Jie Chen
Journal:  Biophys J       Date:  2010-09-08       Impact factor: 4.033

3.  Ions and RNAs: Free Energies of Counterion-Mediated RNA Fold Stabilities.

Authors:  C H Mak; Paul S Henke
Journal:  J Chem Theory Comput       Date:  2012-11-01       Impact factor: 6.006

Review 4.  RNA folding: thermodynamic and molecular descriptions of the roles of ions.

Authors:  David E Draper
Journal:  Biophys J       Date:  2008-10-03       Impact factor: 4.033

Review 5.  RNA folding: conformational statistics, folding kinetics, and ion electrostatics.

Authors:  Shi-Jie Chen
Journal:  Annu Rev Biophys       Date:  2008       Impact factor: 12.981

6.  Computational methods toward accurate RNA structure prediction using coarse-grained and all-atom models.

Authors:  Andrey Krokhotin; Nikolay V Dokholyan
Journal:  Methods Enzymol       Date:  2015-02-03       Impact factor: 1.600

7.  Reduced model captures Mg(2+)-RNA interaction free energy of riboswitches.

Authors:  Ryan L Hayes; Jeffrey K Noel; Paul C Whitford; Udayan Mohanty; Karissa Y Sanbonmatsu; José N Onuchic
Journal:  Biophys J       Date:  2014-04-01       Impact factor: 4.033

8.  Ion-mediated nucleic acid helix-helix interactions.

Authors:  Zhi-Jie Tan; Shi-Jie Chen
Journal:  Biophys J       Date:  2006-04-28       Impact factor: 4.033

9.  Magnesium fluctuations modulate RNA dynamics in the SAM-I riboswitch.

Authors:  Ryan L Hayes; Jeffrey K Noel; Udayan Mohanty; Paul C Whitford; Scott P Hennelly; José N Onuchic; Karissa Y Sanbonmatsu
Journal:  J Am Chem Soc       Date:  2012-07-16       Impact factor: 15.419

10.  Predicting ion-nucleic acid interactions by energy landscape-guided sampling.

Authors:  Zhaojian He; Shi-Jie Chen
Journal:  J Chem Theory Comput       Date:  2012-04-30       Impact factor: 6.006

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  1 in total

1.  Modeling Loop Composition and Ion Concentration Effects in RNA Hairpin Folding Stability.

Authors:  Chenhan Zhao; Dong Zhang; Yangwei Jiang; Shi-Jie Chen
Journal:  Biophys J       Date:  2020-09-02       Impact factor: 4.033

  1 in total

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