Phase separation in amino acid mixtures is governed by composition

Balancing thermodynamic stability, dynamics, and kinetics in phase separation of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are prevalent participants in liquid-liquid phase separation due to their inherent potential for promoting multivalent binding. Understanding the underlying mechanisms of phase separation is challenging, as phase separation is a complex process, involving numerous molecules and various types of interactions. Here, we used a simplified coarse-grained model of IDPs to investigate the thermodynamic stability of the dense phase, conformational properties of IDPs, chain dynamics, and kinetic rates of forming condensates. We focused on the IDP system, in which the oppositely charged IDPs are maximally segregated, inherently possessing a high propensity for phase separation. By varying interaction strengths, salt concentrations, and temperatures, we observed that IDPs in the dense phase exhibited highly conserved conformational characteristics, which are more extended than those in the dilute phase. Although the chain motions and global conformational dynamics of IDPs in the condensates are slow due to the high viscosity, local chain flexibility at the short timescales is largely preserved with respect to that at the free state. Strikingly, we observed a non-monotonic relationship between interaction strengths and kinetic rates for forming condensates. As strong interactions of IDPs result in high stable condensates, our results suggest that the thermodynamics and kinetics of phase separation are decoupled and optimized by the speed-stability balance through underlying molecular interactions. Our findings contribute to the molecular-level understanding of phase separation and offer valuable insights into the developments of engineering strategies for precise regulation of biomolecular condensates.

Fundamental Aspects of Phase-Separated Biomolecular Condensates

Biomolecular condensates, formed through phase separation, are upending our understanding in much of molecular, cell, and developmental biology. There is an urgent need to elucidate the physicochemical foundations of the behaviors and properties of biomolecular condensates. Here we aim to fill this need by writing a comprehensive, critical, and accessible review on the fundamental aspects of phase-separated biomolecular condensates. We introduce the relevant theoretical background, present the theoretical basis for the computation and experimental measurement of condensate properties, and give mechanistic interpretations of condensate behaviors and properties in terms of interactions at the molecular and residue levels.

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.

Capturing chemical reactions inside biomolecular condensates with reactive Martini simulations

Biomolecular condensates are phase separated systems that play an important role in the spatio-temporal organisation of cells. Their distinct physico-chemical nature offers a unique environment for chemical reactions to occur. The compartmentalisation of chemical reactions is also believed to be central to the development of early life. To demonstrate how molecular dynamics may be used to capture chemical reactions in condensates, here we perform reactive molecular dynamics simulations using the coarse-grained Martini forcefield. We focus on the formation of rings of benzene-1,3-dithiol inside a synthetic peptide-based condensate, and find that the ring size distribution shifts to larger macrocycles compared to when the reaction takes place in an aqueous environment. Moreover, reaction rates are noticeably increased when the peptides simultaneously undergo phase separation, hinting that condensates may act as chaperones in recruiting molecules to reaction hubs.

Peptide diffusion in biomolecular condensates

Diffusion determines the turnover of biomolecules in liquid-liquid phase-separated condensates. We considered the mean square displacement and thus the diffusion constant for simple model systems of peptides GGGGG, GGQGG, and GGVGG in aqueous solutions after phase separation by simulating atomic-level models. These solutions readily separate into aqueous and peptide-rich droplet phases. We noted the effect of the peptides being in a solvated, surface, or droplet state on the peptide's diffusion coefficients. Both sequence and peptide conformational distribution were found to influence diffusion and condensate turnover in these systems, with sequence dominating the magnitude of the differences. We found that the most compact structures for each sequence diffused the fastest in the peptide-rich condensate phase. This model result may have implications for turnover dynamics in signaling systems.

Aromatic and arginine content drives multiphasic condensation of protein-RNA mixtures

Multiphasic architectures are found ubiquitously in biomolecular condensates and are thought to have important implications for the organization of multiple chemical reactions within the same compartment. Many of these multiphasic condensates contain RNA in addition to proteins. Here, we investigate the importance of different interactions in multiphasic condensates comprising two different proteins and RNA using computer simulations with a residue-resolution coarse-grained model of proteins and RNA. We find that in multilayered condensates containing RNA in both phases, protein-RNA interactions dominate, with aromatic residues and arginine forming the key stabilizing interactions. The total aromatic and arginine content of the two proteins must be appreciably different for distinct phases to form, and we show that this difference increases as the system is driven toward greater multiphasicity. Using the trends observed in the different interaction energies of this system, we demonstrate that we can also construct multilayered condensates with RNA preferentially concentrated in one phase. The "rules" identified can thus enable the design of synthetic multiphasic condensates to facilitate further study of their organization and function.

Elucidating the reversible and irreversible self-assembly mechanisms of low-complexity aromatic-rich kinked peptides and steric zipper peptides

Many RNA-binding proteins such as fused-in sarcoma (FUS) can self-assemble into reversible liquid droplets and fibrils through the self-association of their low-complexity (LC) domains. Recent experiments have revealed that SYG-rich segments in the FUS LC domains play critical roles in the reversible self-assembly behaviors of FUS. These FUS LC segments alone can self-assemble into reversible kinked fibrils, which are markedly different from the canonical irreversible steric zipper β-sheet fibrils. However, the molecular determinants underlying the reversible and irreversible self-assembly are poorly understood. Herein we conducted extensive all-atom and coarse-grained molecular dynamics simulations of four representative hexapeptides: two low-complexity aromatic-rich kinked peptides from the amyotrophic lateral sclerosis-related FUS protein, FUS37-42 (SYSGYS) and FUS54-59 (SYSSYG); and two steric zipper peptides from Alzheimer's-associated Aβ and Tau proteins, Aβ16-21 (KLVFFA) and Tau306-311 (VQIVYK). We dissected their reversible and irreversible self-assembly dynamics, predicted their phase separation behaviors, and elucidated the underpinning molecular interactions. Our simulations showed that alternating stickers (Tyr) and spacers (Gly and Ser) in FUS37-42 and FUS54-59 facilitate the formation of highly dynamic coil-rich oligomers and lead to reversible self-assembly, while consecutive hydrophobic residues of LVFF in Aβ16-21 and IVY in Tau306-311 act as hydrophobic patches, favoring the formation of stable β-sheet-rich oligomers and driving the irreversible self-assembly. Intriguingly, we found that FUS37-42 and FUS54-59 peptides, possessing the same amino acid composition and the same number of sticker and spacer residues, display differential self-assembly propensities. This finding suggests that the self-assembly behaviors of FUS peptides are fine-tuned by the site-specific patterning of spacer residues (Ser and Gly). This study provides significant mechanistic insights into reversible and irreversible peptide self-assembly, which would be helpful for understanding the molecular mechanisms underlying the formation of biological liquid condensates and pathological solid amyloid fibrils.

Phase separation of multicomponent peptide mixtures into dehydrated clusters with hydrophilic cores

Phase separation of biomolecules underlies the formation and regulation of various membraneless condensates in cells. How condensates function reliably while surrounded by heterogeneous and dynamic mixtures of biomolecular components with specific and nonspecific interactions is yet to be understood. Studying multicomponent biomolecular mixtures with designer peptides has recently become an attractive avenue for learning about physicochemical principles governing cellular condensates. In this work, we employed long-timescale atomistic simulations of multicomponent tripeptide mixtures with all residue substitutions to illuminate the nature of direct and water-mediated interactions in a prototypical cellular condensate environment. We find that peptide mixtures form clusters with inverse hydrophobic order. Most multivalent and charged residues are localized in the cluster's core, with a large fraction of nonaromatic hydrophobic residues remaining on the surface. This inverse hydrophobic order in peptide clusters is partly driven by the expulsion of nonspecifically bound water molecules following peptide cluster growth. The growth of clusters is also accompanied by the formation of increasing numbers of specific water-mediated interactions between polar and charged residues. While the present study focused on the condensation of short peptide motifs, the general findings and analysis techniques should be helpful for future studies on larger peptides and protein condensation.

Biomolecular Condensates: Structure, Functions, Methods of Research

The term "biomolecular condensates" is used to describe membraneless compartments in eukaryotic cells, accumulating proteins and nucleic acids. Biomolecular condensates are formed as a result of liquid-liquid phase separation (LLPS). Often, they demonstrate properties of liquid-like droplets or gel-like aggregates; however, some of them may appear to have a more complex structure and high-order organization. Membraneless microcompartments are involved in diverse processes both in cytoplasm and in nucleus, among them ribosome biogenesis, regulation of gene expression, cell signaling, and stress response. Condensates properties and structure could be highly dynamic and are affected by various internal and external factors, e.g., concentration and interactions of components, solution temperature, pH, osmolarity, etc. In this review, we discuss variety of biomolecular condensates and their functions in live cells, describe their structure variants, highlight domain and primary sequence organization of the constituent proteins and nucleic acids. Finally, we describe current advances in methods that characterize structure, properties, morphology, and dynamics of biomolecular condensates in vitro and in vivo.

Theoretical and Data-Driven Approaches for Biomolecular Condensates

Biomolecular condensation processes are increasingly recognized as a fundamental mechanism that living cells use to organize biomolecules in time and space. These processes can lead to the formation of membraneless organelles that enable cells to perform distinct biochemical processes in controlled local environments, thereby supplying them with an additional degree of spatial control relative to that achieved by membrane-bound organelles. This fundamental importance of biomolecular condensation has motivated a quest to discover and understand the molecular mechanisms and determinants that drive and control this process. Within this molecular viewpoint, computational methods can provide a unique angle to studying biomolecular condensation processes by contributing the resolution and scale that are challenging to reach with experimental techniques alone. In this Review, we focus on three types of dry-lab approaches: theoretical methods, physics-driven simulations and data-driven machine learning methods. We review recent progress in using these tools for probing biomolecular condensation across all three fields and outline the key advantages and limitations of each of the approaches. We further discuss some of the key outstanding challenges that we foresee the community addressing next in order to develop a more complete picture of the molecular driving forces behind biomolecular condensation processes and their biological roles in health and disease.

Theory and Simulation of Multiphase Coexistence in Biomolecular Mixtures

Biomolecular condensates constitute a newly recognized form of spatial organization in living cells. Although many condensates are believed to form as a result of phase separation, the physicochemical properties that determine the phase behavior of heterogeneous biomolecular mixtures are only beginning to be explored. Theory and simulation provide invaluable tools for probing the relationship between molecular determinants, such as protein and RNA sequences, and the emergence of phase-separated condensates in such complex environments. This review covers recent advances in the prediction and computational design of biomolecular mixtures that phase-separate into many coexisting phases. First, we review efforts to understand the phase behavior of mixtures with hundreds or thousands of species using theoretical models and statistical approaches. We then describe progress in developing analytical theories and coarse-grained simulation models to predict multiphase condensates with the molecular detail required to make contact with biophysical experiments. We conclude by summarizing the challenges ahead for modeling the inhomogeneous spatial organization of biomolecular mixtures in living cells.

Light, Water, and Melatonin: The Synergistic Regulation of Phase Separation in Dementia

The swift rise in acceptance of molecular principles defining phase separation by a broad array of scientific disciplines is shadowed by increasing discoveries linking phase separation to pathological aggregations associated with numerous neurodegenerative disorders, including Alzheimer’s disease, that contribute to dementia. Phase separation is powered by multivalent macromolecular interactions. Importantly, the release of water molecules from protein hydration shells into bulk creates entropic gains that promote phase separation and the subsequent generation of insoluble cytotoxic aggregates that drive healthy brain cells into diseased states. Higher viscosity in interfacial waters and limited hydration in interiors of biomolecular condensates facilitate phase separation. Light, water, and melatonin constitute an ancient synergy that ensures adequate protein hydration to prevent aberrant phase separation. The 670 nm visible red wavelength found in sunlight and employed in photobiomodulation reduces interfacial and mitochondrial matrix viscosity to enhance ATP production via increasing ATP synthase motor efficiency. Melatonin is a potent antioxidant that lowers viscosity to increase ATP by scavenging excess reactive oxygen species and free radicals. Reduced viscosity by light and melatonin elevates the availability of free water molecules that allow melatonin to adopt favorable conformations that enhance intrinsic features, including binding interactions with adenosine that reinforces the adenosine moiety effect of ATP responsible for preventing water removal that causes hydrophobic collapse and aggregation in phase separation. Precise recalibration of interspecies melatonin dosages that account for differences in metabolic rates and bioavailability will ensure the efficacious reinstatement of the once-powerful ancient synergy between light, water, and melatonin in a modern world.

Biophysics of biomolecular condensates

The formation of biomolecular condensates has emerged as a new biophysical principle for subcellular compartmentalization within cells to facilitate the spatiotemporal regulation of a multitude of complex biomolecular reactions. In this Research Highlight, we summarize the findings that were published in Biophysical Journal during the past two years (2021 and 2022). These papers provided biophysical insights into the formation of biomolecular condensates via phase separation of proteins with or without nucleic acids.

Structural and Dynamical Properties of Elastin-Like Peptides near Their Lower Critical Solution Temperature

Elastin-like peptides (ELPs) are artificially derived intrinsically disordered proteins (IDPs) mimicking the hydrophobic repeat unit in the protein elastin. ELPs are characterized by a lower critical solution temperature (LCST) in aqueous media. Here, we investigate the sequence GVG(VPGVG)₃ over a wide range of temperatures (below, around, and above the LCST) and peptide concentrations employing all-atom molecular dynamics simulations, where we focus on the role of intra- and interpeptide interactions. We begin by investigating the structural properties of a single peptide that demonstrates a hydrophobic collapse with temperature, albeit moderate, because the sequence length is short. We observe a change in the interaction between two peptides from repulsive to attractive with temperature by evaluating the potential of mean force, indicating an LCST-like behavior. Next, we explore dynamical and structural properties of peptides in multichain systems. We report the formation of dynamical aggregates with coil-like conformation, in which valine central residues play an important role. Moreover, the lifetime of contacts between chains strongly depends on the temperature and can be described by a power-law decay that is consistent with the LCST-like behavior. Finally, the peptide translational and internal motion are slowed by an increase in the peptide concentration and temperature.