Li Shanlong, Chen Jianhan
Department of Chemistry, University of Massachusetts, Amherst, MA 01003, USA.
bioRxiv. 2025 Feb 28:2024.11.17.624048. doi: 10.1101/2024.11.17.624048.
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 ntermediate resolution model for densates of s (iConRNA) that can capture key local and long-range structure features of dynamic RNAs and simulate their spontaneous phase transitions with Mg. Representing each nucleotide using 6-7 beads, iConRNA accurately captures base stacking and pairing and includes explicit Mg. The model does not only reproduce 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 Mg, 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 Mg 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 Mg-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 environment control the phase behavior and condensate material properties.
Dynamic RNAs and proteins are major drivers of biomolecular phase separation that has 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 a high-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 Mg-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.
RNA是生物分子凝聚物形成过程中相分离的主要驱动因素，并且在二价离子或拥挤剂存在的情况下可发生无蛋白质的相分离。关于碱基堆积、碱基配对、静电作用、离子相互作用，特别是结构倾向之间复杂的相互作用如何控制RNA的相行为，仍有许多有待了解的地方。在此，我们开发了一种用于RNA凝聚物的中等分辨率模型（iConRNA），它能够捕捉动态RNA的关键局部和长程结构特征，并模拟其与镁离子的自发相变。iConRNA使用6 - 7个珠子来表示每个核苷酸，能够准确捕捉碱基堆积和配对，并包含明确的镁离子。该模型不仅再现了聚（rA）和聚（rU）的主要构象特性，还能正确折叠小的结构化RNA并预测其解链温度。通过一个明确的镁离子有效模型，iConRNA成功重现了实验观察到的聚（rA）和三联体重复序列的较低临界溶液温度相分离，并且至关重要的是，相变对RNA序列、长度、浓度和镁离子水平的非平凡依赖性。进一步的机理分析揭示了RNA折叠在调节相分离及其温度和离子依赖性方面的关键作用，此外还有其他驱动力，如镁离子 - 磷酸相互作用、碱基堆积和碱基配对。这些研究还支持iConRNA作为直接模拟RNA驱动相变的强大工具，能够进行分子研究，以了解RNA构象动力学及其对复杂凝聚物环境的响应如何控制相行为和凝聚物材料特性。
动态RNA和蛋白质是生物分子相分离的主要驱动因素，最近发现生物分子相分离是众多生物过程的基础，并涉及许多人类疾病。分子模拟在剖析生物分子相分离的驱动力和调控方面具有不可或缺的作用。当前的工作描述了一种高分辨率粗粒度RNA模型，该模型能够描述柔性RNA的结构动力学以及复杂的序列、浓度、温度和离子依赖性相变。该研究进一步揭示了RNA折叠在协调镁离子 - 磷酸相互作用、碱基堆积和碱基配对以驱动相分离方面的核心作用，为在相关生物学背景下研究RNA介导的相分离铺平了道路。
