ABSTRACT
This chapter reviews some of the most employed methodologies to model the three-dimensional (3D) structure of ribonucleic acid (RNA) molecules, in particular those based on knowledge-based energy potentials. It summarizes the most common coarse-grained models used to predict RNA 3D structure and provides a qualitative description of their energy functions. Coarse-grained methods are the common choice in RNA modeling because they provide reasonably accurate results as compared to all-atom models at a lower computational expense. The chapter illustrates how experimental information can be used to improve sampling and hence the final quality of the models. It discusses the comparison of the state-of-the-art RNA structure prediction methods as reported in the international blind contest RNA-Puzzles. The increasing importance of RNA in biology raised the "RNA world" hypothesis, which advances the view that RNA is the precursor molecule to life because of its ability to self-replicate, catalyze reactions, and store genetic information.
