Chapter 13 - RNA Secondary Structures: Combinatorial Models and Folding Algorithms

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Ribonucleic acid (RNA) is a long macromolecule built from nucleotides strung together along a sugar-phosphate backbone. Unlike its double-stranded cousin deoxyribonucleic acid, which twists into a double-helix structure, RNA folds and bonds to itself. Because the three-dimensional structure into which RNA folds determines its cellular function, scientists are very interested in understanding how it folds. The challenge is to predict an RNA’s three-dimensional structure given only its raw primary sequence. We begin this chapter by interpreting this problem in a combinatorial framework, using partial matchings and noncrossing arc diagrams called secondary structures. Next, we take an in-depth tour of two very different approaches to the secondary structure prediction problem. The first method attempts to minimize the free energy using a recursive technique called dynamic programming. The second method arises from the field of computational linguistics—RNA secondary structures are generated using a stochastic context-free grammar. Finally, the chapter concludes with a brief overview of how to extend the RNA combinatorial framework to more complicated structures called pseudoknots.