Computational RNA Structure Prediction
Marc A. Marti-Renom,
The view of RNA as simple information transfer molecule has been continuously challenged since the discovery of ribozymes, a class of RNA molecules with enzyme-like function. Moreover, the recent discovery of tiny RNA molecules such as μRNAs and small interfering RNA, is transforming our thinking about how gene expression is regulated. Thus, RNA molecules are now known to carry a large repertory of biological functions within cells including information transfer, enzymatic catalysis and regulation of cellular processes. Similar to proteins, functional RNA molecules fold into their native three-dimensional (3D) conformation, which is essential for performing their biological activity. Despite advances in understanding the folding and unfolding of RNA, our knowledge of the atomic mechanism by which RNA molecules adopt their biological active structure is still limited. In this review, we outline the general principles that govern RNA structure and describe the databases and algorithms for analyzing and predicting RNA secondary and tertiary structure. Finally, we assess the impact of the current coverage of the RNA structural space on comparative modeling RNA structures.
Keywords: RNA, secondary structure, tertiary structure, computational biology, structure prediction, comparative modeling
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