A reduced-coordinate approach to modeling RNA 3-D structures

With the realization of RNA molecules capable of performing very specific functions (e.g., catalytic RNAs and RNAs that bind ligand with affinity and specificity of an anti-body) and contrary to the traditional view that structure of RNA molecules being functionally passive, it has become clear that studying the 3-dimensional (3-D) folding of RNA molecules is a very important task. In the absence of sufficient number of experimentally determined RNA structures available up-to-date, folding of RNA structures computationally provides an alternative approach in studying the 3-D structure of RNA molecules. We have developed a computational approach for folding RNA 3-D structures. The method is conceptually simple and general. It consists of two major components. The first being the arrangement of all helices in space. Once the helices are positioned and oriented in space, structures of the connecting loops are modeled and inserted between the helices. Any number of structural constraints derived either experimentally or theoretically can be used to guide the folding processes. A conformational sampling approach is developed with structural equilibration using the Metropolis Monte Carlo simulation. The lengths of various loop sizes (ranging from 1 base to 7 bases) are calculated based on a set of RNA structures deposited in PDB as well as a set of loop structures constructed using our method. The validity of using the averaged loop lengths of the connecting loops as distance constraints for arranging the helices in space is studied