Computational methods for RNA structure prediction and analysis

RNA cannot be considered anymore as a simple transfer molecule. On the contrary, a plethora of noncoding RNA molecules are being discovered, which is transforming our thinking about how the cell is regulated. Large and small RNAs carry now a large repertory of diverse biological functions within cells. Altogether, RNA is now considered as a major player in the molecular regulation of essential cellular processes. Similar to proteins, RNAs adopt threedimensional (3D) structures that are necessary for performing their functional roles. Unfortunately, despite advances in understanding the folding and unfolding of RNA molecules, our knowledge of the atomic mechanism by which RNA molecules adopt their biologically active structures is still limited. Moreover, experimental determination of RNA structures either by X-ray crystallography or nuclear magnetic resonance is challenging, given the instability of RNA molecules. Therefore, computational approaches for predicting the 3D structure of RNAs are becoming essential in the study of the molecular mechanisms of RNA function. Here we start by outlining the general principles of the RNA structure, and then we describe the databases and algorithms for analyzing and predicting RNA secondary and 3D structures.