期刊
METHODS
卷 103, 期 -, 页码 138-156出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ymeth.2016.04.026
关键词
RNA; Structure; Modeling; Bioinformatics; Simulation; Molecular dynamics; Monte Carlo dynamics
资金
- European Research Council (ERC, StG Grant) [261351, RNA+P=123D]
- European Commission (E.C., REGPOT Grant FishMed) [316125]
- Polish National Science Centre (NCN) [2012/04/A/NZ2/00455]
- Polish Ministry of Science and Higher Education (MNiSW) [POIG.02.03.00-00-003/09]
- IIMCB
- Ideas for Poland fellowship from the Foundation for Polish Science
- European Research Council (ERC) [261351] Funding Source: European Research Council (ERC)
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.
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