Energy landscapes of homopolymeric RNAs revealed by deep unsupervised learning

Biophys J. 2024 Apr 2:S0006-3495(24)00247-9. doi: 10.1016/j.bpj.2024.04.003. Online ahead of print.ABSTRACTConformational dynamics of RNA plays crucial for variety of cellular functions including acting as regulators of gene expression to being molecular scaffolds and sensors. The liquid-liquid phase separation of RNAs and the formation of stress granules partly relies on RNA's conformational plasticity and its ability to engage in multivalent interactions. Recent experiments with homopolymeric and low-complexity RNAs have revealed significant differences in phase separations due to differences in base chemistry of RNA units. We hypothesize that differences in RNA phase-transition dynamics stem from the differences in conformational dynamics of single RNA chains. To test this hypothesis we have employed atomistic simulations and deep dimensionality reduction techniques to map temperature dependent conformational free energy landscapes for homopolymeric RNA. Temperature dependent conformational energy landscapes of RNAs reveal a plethora of metastable states, populations of which are highly base dependent. Through detailed analysis base, phosphate and sugar interactions we show that experimentally observed temperature-driven shifts in metastable state populations align with experimental phase diagrams for homopolymer RNAs. Specifically, we finding that thermodynamics of folding of homopolymeric RNA follows the Poly(G) > Poly(A) > Poly(C) > Poly(U) order of stability w...
Source: Biophysical Journal - Category: Physics Authors: Source Type: research