A computational approach to modeling nucleic acid hairpin structures.

Hairpin is a structural motif frequently observed in both RNA and DNA molecules. This motif is involved specifically in various biological functions (e.g., gene expression and regulation). To understand how these hairpin motifs perform their functions, it is important to study their structures. Compared to protein structural motifs, structures of nucleic acid hairpins are less known. Based on a set of reduced coordinates for describing nucleic acid structures and a sampling algorithm that equilibrates structures using Metropolis Monte Carlo simulation, we developed a method to model nucleic acid hairpin structures. This method was used to predict the structure of a DNA hairpin with a single-guanosine loop. The lowest energy structure from the ensemble of 200 sampled structures has a RMSD of < 1.5 A, from the structure determined using NMR. Additional constraints for the loop bases were introduced for modeling an RNA hairpin with two nucleotides in the loop. The modeled structure of this RNA hairpin has extensive base stacking and an extra hydrogen bond (between the CYT in the loop and a phosphate oxygen), as observed in the NMR structure.