Computational prediction of nucleic acid secondary structure: Methods, applications, and challenges

Abstract

RNA molecules are crucial in different levels of cellular function, ranging from translation and regulating genes to coding for proteins. Additionally, nucleic acids (RNA and DNA molecules) are designed for novel applications in biotechnology. Understanding the structure of a molecule is important in inferring its function, and computational methods for structure prediction have captured the interest of many researchers. Some functions of RNA molecules in cells, such as gene regulation, result from the binding of one RNA molecule to another, so-called target RNA molecule. This has led to recent interest in prediction of the secondary structure formed from interacting molecules. In this paper, we provide a brief overview of methods, applications, and challenges in computational prediction of nucleic acid secondary structure, both for single strands and for interacting strands.