Using Simulations and Kinetic Network Models to Reveal the Dynamics and Functions of Riboswitches

被引:9
|
作者
Lin, Jong-Chin [1 ,2 ]
Yoon, Jeseong [3 ]
Hyeon, Changbong [3 ]
Thirumalai, D. [1 ,2 ]
机构
[1] Univ Maryland, Inst Phys Sci & Technol, College Pk, MD 20742 USA
[2] Univ Maryland, Dept Chem & Biochem, College Pk, MD 20742 USA
[3] Korea Inst Adv Study, Sch Computat Sci, Seoul, South Korea
基金
美国国家科学基金会;
关键词
ADENINE RIBOSWITCH; FOLDING LANDSCAPES; RNA HAIRPINS; BASE-PAIR; APTAMERS; TRANSCRIPTION; ADAPTATION; PATHWAYS; PROTEINS; BACTERIA;
D O I
10.1016/bs.mie.2014.10.062
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Riboswitches, RNA elements found in the untranslated region, regulate gene expression by binding to target metaboloites with exquisite specificity. Binding of metabolites to the conserved aptamer domain allosterically alters the conformation in the downstream expression platform. The fate of gene expression is determined by the changes in the downstream RNA sequence. As the metabolite-dependent cotranscriptional folding and unfolding dynamics of riboswitches are the key determinant of gene expression, it is important to investigate both the thermodynamics and kinetics of riboswitches both in the presence and absence of metabolite. Single molecule force experiments that decipher the free energy landscape of riboswitches from their mechanical responses, theoretical and computational studies have recently shed light on the distinct mechanism of folding dynamics in different classes of riboswitches. Here, we first discuss the dynamics of water around riboswitch, highlighting that water dynamics can enhance the fluctuation of nucleic acid structure. To go beyond native state fluctuations, we used the Self-Organized Polymer model to predict the dynamics of add adenine riboswitch under mechanical forces. In addition to quantitatively predicting the folding landscape of add-riboswitch, our simulations also explain the difference in the dynamics between pbuE adenine- and add adenine-riboswitches. In order to probe the function in vivo, we use the folding landscape to propose a system level kinetic network model to quantitatively predict how gene expression is regulated for riboswitches that are under kinetic control.
引用
收藏
页码:235 / 258
页数:24
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