Multiscale modeling of RNA 3D structures

Abstract

Balancing accuracy and computational efficiency while studying biomolecular structures and dynamics necessitates scalable modeling techniques. We have been developing a coarse-grained model for RNA that uses pseudoatoms in place of all-atom representation. By reducing the number of interactions and mean-field representation of environmental effects, significant improvement in computational efficiency is achieved in a comparison to all-atom based physical modeling approaches. A five bead coarse-grained model utilized for RNA 3D structure prediction is presented. Unique features of this framework include the direct mapping between all atom and coarse-grained models, incorporation of electrostatic interactions, continuous and analytical energy function that can be used in molecular dynamics simulations, and statistical derived parameters. Here we present the basic framework of our model and recent applications to RNA folding.