Internal Normal Mode Analysis applied to RNA flexibility and conformational changes

Abstract

We investigated the capability of internal normal modes to reproduce RNA dynamics and predict observed RNA conformational changes, and, notably, those induced by the formation of RNA-protein and RNA-ligand complexes. Here, we extended our iNMA approach developed for proteins to study RNA molecules using a simplified representation of RNA structure and its potential energy. Three datasets were also created to investigate different aspects. Despite all the approximations, our study shows that iNMA is a suitable method to take into account RNA flexibility and describe its conformational changes opening the route to its applicability in any integrative approach where these properties are crucial.

Predicting RNA Structure and Dynamics with Deep Learning and Solution Scattering

“…There are several methods to sample the conformational ensemble from a starting RNA structure, including Molecular Dynamics simulations (18), Monte Carlo-based methods, such as SimRNA (20), Normal Modes (14, 21, 22), and robotics-inspired motion planning approach (KGSRNA (23)). However, there is only one predictor of metal ion positions in RNA, MetalionRNA (24), based on a statistical analysis of ions in the PDB.…”