Coarse-grained modeling of RNA 3D structure

被引:38
作者
Dawson, Wayne K. [1 ]
Maciejczyk, Maciej [1 ,2 ]
Jankowska, Elzbieta J. [1 ]
Bujnicki, Janusz M. [1 ,3 ]
机构
[1] Int Inst Mol & Cell Biol Warsaw, Lab Bioinformat & Prot Engn, Ul Ks Trojdena 4, PL-02109 Warsaw, Poland
[2] Univ Warmia & Mazury, Dept Phys & Biophys, Ul Oczapowskiego 4, PL-10719 Olsztyn, Poland
[3] Adam Mickiewicz Univ, Fac Biol, Inst Mol Biol & Biotechnol, Lab Struct Bioinformat, Ul Umultowska 89, PL-61614 Poznan, Poland
基金
欧洲研究理事会;
关键词
RNA; Structure; Modeling; Bioinformatics; Simulation; Molecular dynamics; Monte Carlo dynamics; MOLECULAR-DYNAMICS SIMULATIONS; KNOWLEDGE-BASED POTENTIALS; FREE-ENERGY CALCULATIONS; IMPLICIT SOLVENT MODELS; DE-NOVO PREDICTION; ATOM FORCE-FIELD; MONTE-CARLO; POLYNUCLEOTIDE CHAINS; CONFIGURATIONAL STATISTICS; THERMODYNAMIC PARAMETERS;
D O I
10.1016/j.ymeth.2016.04.026
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Functional RNA molecules depend on three-dimensional (3D) structures to carry out their tasks within the cell. Understanding how these molecules interact to carry out their biological roles requires a detailed knowledge of RNA 3D structure and dynamics as well as thermodynamics, which strongly governs the folding of RNA and RNA-RNA interactions as well as a host of other interactions within the cellular environment. Experimental determination of these properties is difficult, and various computational methods have been developed to model the folding of RNA 3D structures and their interactions with other molecules. However, computational methods also have their limitations, especially when the biological effects demand computation of the dynamics beyond a few hundred nanoseconds. For the researcher confronted with such challenges, a more amenable approach is to resort to coarse-grained modeling to reduce the number of data points and computational demand to a more tractable size, while sacrificing as little critical information as possible. This review presents an introduction to the topic of coarse-grained modeling of RNA 3D structures and dynamics, covering both high- and low-resolution strategies. We discuss how physics-based approaches compare with knowledge based methods that rely on databases of information. In the course of this review, we discuss important aspects in the reasoning process behind building different models and the goals and pitfalls that can result. (C) 2016 The Authors. Published by Elsevier Inc.
引用
收藏
页码:138 / 156
页数:19
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