title: Modeling nucleic acids.
abstract: Nucleic acids are an important class of biological macromolecules that carry out a variety of cellular roles. For many functions, naturally occurring DNA and RNA molecules need to fold into precise three-dimensional structures. Due to their self-assembling characteristics, nucleic acids have also been widely studied in the field of nanotechnology, and a diverse range of intricate three-dimensional nanostructures have been designed and synthesized. Different physical terms such as base-pairing and stacking interactions, tertiary contacts, electrostatic interactions and entropy all affect nucleic acid folding and structure. Here we review general computational approaches developed to model nucleic acid systems. We focus on four key areas of nucleic acid modeling: molecular representation, potential energy function, degrees of freedom and sampling algorithm. Appropriate choices in each of these key areas in nucleic acid modeling can effectively combine to aid interpretation of experimental data and facilitate prediction of nucleic acid structure.
authors.affiliation: Department of Applied Physics, Stanford University, Stanford, CA 94305, USA.
authors.forename: Adelene Y L
authors.initials: AY
authors.lastname: Sim
authors.forename: Peter
authors.initials: P
authors.lastname: Minary
authors.forename: Michael
authors.initials: M
authors.lastname: Levitt
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D008958:Models, Molecular; D009690:Nucleic Acid Conformation; D009696:Nucleic Acids / Q000737:chemistry*; D012984:Software
chemical_list: D009696:Nucleic Acids