2025-10-23 マサチューセッツ大学アマースト校
The phase separation of RNA induces many single strands to self-organize into condensates that resemble a self-enclosed droplet. Top: A 3D rendered illustration of an mRNA strand (Credit: Getty Images).
<関連情報>
- https://www.umass.edu/news/article/umass-amherst-chemists-develop-tool-providing-unrivaled-look-inside-cells
- https://www.pnas.org/doi/10.1073/pnas.2504583122
RNA凝縮の駆動力は、Mg 2+を明示的に用いた粗視化モデリングによって明らかにされた Driving forces of RNA condensation revealed through coarse-grained modeling with explicit Mg2+
Shanlong Li and Jianhan Chen
Proceedings of the National Academy of Sciences Published:October 23, 2025
DOI:https://doi.org/10.1073/pnas.2504583122
Significance
Dynamic RNAs and proteins are major drivers of biomolecular phase separation to form condensates that have been recently discovered to underlie numerous biological processes and be involved in many human diseases. Molecular simulation has an indispensable role to play in dissecting the driving forces and regulation of biomolecular phase separation. The current work describes an intermediate-resolution coarse-grained RNA model that is capable of describing the structure dynamics and complex sequence, concentration, temperature, and ion-dependent phase transitions of flexible RNAs. The study further reveals a central role of RNA folding in coordinating Mg2+–phosphate interactions, base stacking, and base pairing to drive phase separation, paving the road for studies of RNA-mediated phase separation in relevant biological contexts.
Abstract
RNAs are major drivers of phase separation in the formation of biomolecular condensates and can undergo protein-free phase separation in the presence of divalent ions or crowding agents. Much remains to be understood regarding how the complex interplay of base stacking, base pairing, electrostatics, ion interactions, and particularly structural propensities governs RNA phase behavior. Here, we develop an intermediate resolution model for condensates of RNAs (iConRNA) that can capture key local and long-range structural features of dynamic RNAs and simulate their spontaneous phase transitions with Mg2+. Representing each nucleotide using 6 to 7 beads, iConRNA accurately captures base stacking and pairing and includes explicit Mg2+. The model not only reproduces major conformational properties of poly(rA) and poly(rU) but also correctly folds small structured RNAs and predicts their melting temperatures. With an effective model of explicit Mg2+, iConRNA successfully recapitulates experimentally observed lower critical solution temperature phase separation of poly(rA) and triplet repeats, and critically, the nontrivial dependence of phase transitions on RNA sequence, length, concentration, and Mg2+ level. Further mechanistic analysis reveals a key role of RNA folding in modulating phase separation as well as its temperature and ion dependence, besides other driving forces such as Mg2+–phosphate interactions, base stacking, and base pairing. These studies also support iConRNA as a powerful tool for direct simulation of RNA-driven phase transitions, enabling molecular studies of how RNA conformational dynamics and its response to complex condensate environments control the phase behavior and condensate material properties.
