Modeling conformational transitions in DNA, RNA, and protein–nucleic acid complexes

Abstract

Abstract The flexibility of nucleic acids plays a central role in numerous biological processes, including chromatin organization, gene regulation, and ribosome assembly. While elastic network models (ENMs) have successfully captured conformational changes in proteins through harmonic normal modes (NMs), analogous approaches for nucleic acids remain limited. Here, we introduce a generalized essential dynamics-refined ENM (edENM) for both DNA, RNA, and protein–nucleic acid complexes, parametrized against a diverse set of molecular dynamics simulations and validated using experimental ensembles from nuclear magnetic resonance, X-ray crystallography, and cryogenic electron microscopy. edENM achieves high agreement with experimental conformational changes across a curated benchmark of ∼60 DNA, RNA, and protein–nucleic acid systems. Compared to uniform-spring parametrizations, it produces significantly more collective NMs and suppresses unphysical backbone ruptures. We further integrate edENM into eBDIMS2, an efficient Brownian Dynamics path-sampling framework, extending its applicability to nucleic acid-containing systems at the megadalton scale. This enables the exploration of complex conformational transitions, including rearrangements of RNA folds in coronaviruses, large-scale remodeling in Argonaute–RNA complexes, multi-nucleosome assemblies in chromatin, as well as ribosomal particles. Together, these results establish an accessible and scalable elastic network framework for modeling conformational changes across the full spectrum of nucleic acid-containing biological systems.