Nucleoprotein phase-separation affinities revealed via atomistic simulations of short peptide and RNA fragments.

Liquid-liquid phase separation of proteins and nucleic acids into condensate phases is a versatile mechanism for ensuring compartmentalization of cellular biochemistry. RNA molecules play critical roles in these condensates, particularly in transcriptional regulation and stress responses, exhibiting a wide range of thermodynamic and dynamic behaviors. However, deciphering the molecular grammar that governs the stability and dynamics of protein-RNA condensates remains challenging due to the multicomponent and heterogeneous nature of these biomolecular mixtures. In this study, we employ atomistic simulations of twenty distinct mixtures containing minimal RNA and peptide fragments to dissect the phase-separating affinities of all twenty amino acids in the presence of RNA. Our findings elucidate chemically specific interactions, hydration profiles, and ionic effects that synergistically promote or suppress protein-RNA phase separation. We map a ternary phase diagram of interactions, identifying four distinct groups of residues that promote, maintain, suppress, or disrupt protein-RNA clusters.

Nucleoprotein Phase-Separation Affinities Revealed via Atomistic Simulations of Short Peptide and RNA Fragments.

Liquid-liquid phase separation of proteins and nucleic acids into condensate phases is a versatile mechanism for ensuring the compartmentalization of cellular biochemistry. RNA molecules play critical roles in these condensates, particularly in transcriptional regulation and stress responses, exhibiting a wide range of thermodynamic and dynamic behaviors. However, deciphering the molecular grammar that governs the stability and dynamics of protein-RNA condensates remains challenging due to the multicomponent and heterogeneous nature of condensates. In this study, we employ atomistic simulations of 20 distinct mixtures containing minimal RNA and peptide fragments which allows us to dissect the phase-separating affinities of all 20 amino acids in the presence of RNA. Our findings elucidate chemically specific interactions, hydration profiles, and ionic effects that synergistically promote or suppress protein-RNA phase separation. We map a ternary phase diagram of interactions, identifying four distinct groups of residues that promote, maintain, suppress, and disrupt protein-RNA clusters.

Atomistic insights into the reentrant phase-transitions in polyuracil and polylysine mixtures.

The phase separation of protein and RNA mixtures underpins the assembly and regulation of numerous membraneless organelles in cells. The ubiquity of protein-RNA condensates in cellular regulatory processes is in part due to their sensitivity to RNA concentration, which affects their physical properties and stability. Recent experiments with poly-cationic peptide-RNA mixtures have revealed closed-loop phase diagrams featuring lower and upper critical solution temperatures. These diagrams indicate reentrant phase transitions shaped by biomolecular interactions and entropic forces such as solvent and ion reorganization. We employed atomistic simulations to study mixtures with various RNA-polylysine stoichiometries and temperatures to elucidate the microscopic driving forces behind reentrant phase transitions in protein-RNA mixtures. Our findings reveal an intricate interplay between hydration, ion condensation, and specific RNA-polylysine hydrogen bonding, resulting in distinct stoichiometry-dependent phase equilibria governing stabilities and structures of the condensate phase. Our simulations show that reentrant transitions are accompanied by desolvation around the phosphate groups of RNA, with increased contacts between phosphate and lysine side chains. In RNA-rich systems at lower temperatures, RNA molecules can form an extensive pi-stacking and hydrogen bond network, leading to percolation. In protein-rich systems, no such percolation-induced transitions are observed. Furthermore, we assessed the performance of three prominent water force fields-Optimal Point Charge (OPC), TIP4P-2005, and TIP4P-D-in capturing reentrant phase transitions. OPC provided a superior balance of interactions, enabling effective capture of reentrant transitions and accurate characterization of changes in solvent reorganization. This study offers atomistic insights into the nature of reentrant phase transitions using simple model peptide and nucleotide mixtures. We believe that our results are broadly applicable to larger classes of peptide-RNA mixtures exhibiting reentrant phase transitions.

Energy landscapes of homopolymeric RNAs revealed by deep unsupervised learning.

Conformational dynamics of RNA plays important roles in a variety of cellular functions such as transcriptional regulation, catalysis, scaffolding, and sensing. Recently, RNAs with low-complexity sequences have been shown to phase separate and form condensate phases similar to lowcomplexity protein domains. The affinity for phase separation and the material characteristics of RNA condensates are strongly dependent on sequence composition and patterning. We hypothesize that differences in the affinities for RNA phase separation can be uncovered by studying sequence-dependent conformational dynamics of single RNA chains. To this end, we have employed atomistic simulations and deep dimensionality reduction techniques to map temperature-dependent conformational free energy landscapes for 20 base-long homopolymeric RNA sequences: poly(U), poly(G), poly(C), and poly(A). The energy landscapes of homopolymeric RNAs reveal a plethora of metastable states with qualitatively different populations stemming from differences in base chemistry. Through detailed analysis of base, phosphate, and sugar interactions, we show that experimentally observed temperature-driven shifts in metastable state populations align with experiments on RNA phase transitions. Specifically, we find that the thermodynamics of unfolding of homopolymeric RNA follows the poly(G) > poly(A) > poly(C) > poly(U) order of stability, mirroring the propensity of RNA to form condensates. To conclude, this work shows that at least for homopolymeric RNA sequences the single-chain conformational dynamics contains sufficient information for predicting and quantifying condensate forming affinities of RNAs. Thus, we anticipate that atomically detailed studies of temeprature -dependent energy landscapes of RNAs will be a useful guide for understanding the propensity of various RNA molecules to form condensates.

Determinants of viscoelasticity and flow activation energy in biomolecular condensates.

The form and function of biomolecular condensates are intimately linked to their material properties. Here, we integrate microrheology with molecular simulations to dissect the physical determinants of condensate fluid phase dynamics. By quantifying the timescales and energetics of network relaxation in a series of heterotypic viscoelastic condensates, we uncover distinctive roles of sticker motifs, binding energy, and chain length in dictating condensate dynamical properties. We find that the mechanical relaxation times of condensate-spanning networks are determined by both intermolecular interactions and chain length. We demonstrate, however, that the energy barrier for network reconfiguration, termed flow activation energy, is independent of chain length and only varies with the strengths of intermolecular interactions. Biomolecular diffusion in the dense phase depends on a complex interplay between viscoelasticity and flow activation energy. Our results illuminate distinctive roles of chain length and sequence-specific multivalent interactions underlying the complex material and transport properties of biomolecular condensates.

Dynamic effects of the spine of hydrated magnesium on viral RNA pseudoknot structure.

In the cellular environment, a viral RNA Pseudoknot (PK) structure is responsive to its prevailing ion atmosphere created by a mixture of monovalent and divalent cations. We investigate the influence of such a mixed-salt environment on RNA-PK structure at an atomic resolution through three sets of 1.5 µs explicit solvent molecular dynamics (MD) simulations and also by building a dynamic counterion-condensation (DCC) model at varying divalent Mg2+ concentrations. The DCC model includes explicit interaction of the ligand and adjacent chelated Mg2+ by extending the recently developed generalized Manning condensation model. Its implementation within an all-atom structure-based molecular dynamics framework bolsters its opportunity to explore large-length scale and long-timescale phenomena associated with complex RNA systems immersed in its dynamic ion environment. In the present case of RNA-PK, both explicit MD and DCC simulations reveal a spine of hydrated-Mg2+ to induce stem-I and stem-II closure where the minor groove between these stems is akin to breathing. Mg2+ mediated minor-groove narrowing is coupled with local base-flipping dynamics of a base triple and quadruple, changing the stem structure of such RNA. Contrary to the conversational view of the indispensable need for Mg2+ for the tertiary structure of RNA, the study warns about the plausible detrimental effect of specific Mg2+-phosphate interactions on the RNA-PK structure beyond a certain concentration of Mg2+.