Protein structural transitions critically transform the network connectivity and viscoelasticity of RNA-binding protein condensates but RNA can prevent it

Viscoelastic mechanics of living cells

In cell mechanotransduction, cells respond to external forces or to perceive mechanical properties of their supporting substrates by remodeling themselves. This ability is endowed by modulating cells' viscoelastic properties, which dominates over various complex cellular processes. The viscoelasticity of living cells, a concept adapted from rheology, exhibits substantially spatial and temporal variability. This review aims not only to discuss the rheological properties of cells but also to clarify the complexity of cellular rheology, emphasizing its dependence on both the size scales and time scales of the measurements. Like typical viscoelastic materials, the storage and loss moduli of cells often exhibit robust power-law rheological characteristics with respect to loading frequency. This intrinsic feature is consistent across cell types and is attributed to internal structures, such as cytoskeleton, cortex, cytoplasm and nucleus, all of which contribute to the complexity of cellular rheology. Moreover, the rheological properties of cells are dynamic and play a crucial role in various cellular and tissue functions. In this review, we focus on elucidating time- and size-dependent aspects of cell rheology, the origins of intrinsic rheological properties and how these properties adapt to cellular functions, with the goal of interpretation of rheology into the language of cell biology.

Material properties of biomolecular condensates emerge from nanoscale dynamics

Biomolecular condensates form by phase separation of biological polymers and have important functions in the cell-functions that are inherently linked to their physical properties at different scales. A notable aspect of such membraneless organelles is that their viscoelastic properties can vary by orders of magnitude, but it has remained unclear how these pronounced differences are rooted in the nanoscale dynamics at the molecular level. Here, we investigate a series of condensates formed by complex coacervation of highly charged disordered proteins and polypeptides that span about two orders of magnitude in bulk viscosity. We find that their viscosity is highly correlated with protein translational diffusion and nano- to microsecond chain dynamics. Remarkably, analytical relations from polymer physics can predict condensate viscosity from diffusivity and chain dynamics, and vice versa, even for more hydrophobic disordered proteins and for synthetic polyelectrolytes, indicating a mechanistic link across several decades of length- and timescales. Atomistic simulations reveal that the observed differences in friction-a key quantity underlying these relations-reflect differences in interresidue contact lifetimes as a function of arginine content and salt concentration, leading to the vastly different dynamics among condensates. The rapid exchange of interresidue contacts we observe may be a general mechanism for preventing dynamic arrest in compartments densely packed with polyelectrolytes, such as the cell nucleus.

Molecular simulations of enzymatic phosphorylation of disordered proteins and their condensates

Condensation and aggregation of disordered proteins in cellular non-equilibrium environments are shaped decisively by enzymes. Enzymes called kinases phosphorylate proteins, consuming the chemical fuel ATP. Protein phosphorylation by kinases such as Casein kinase 1 delta (CK1δ) determines the interactions of neurodegeneration-linked proteins such as TDP-43. Hyperphosphorylation of TDP-43 by CK1δ may be a cytoprotective mechanism for neurons, but how CK1δ interacts with protein condensates is not known. Molecular dynamics simulations hold the promise to resolve how kinases interact with disordered proteins and their condensates, and how this shapes the phosphorylation dynamics. In practice, it is difficult to verify whether implementations of chemical-fuel driven coarse-grained simulations are thermodynamically consistent, which we address by a generally applicable and automatic Markov state modeling approach. In this work, we thus elucidate with coarse-grained simulations, drivers of how TDP-43 is phosphorylated by CK1δ and how this leads to the dissolution of TDP-43 condensates upon hyperphosphorylation.

Chemically Informed Coarse-Graining of Electrostatic Forces in Charge-Rich Biomolecular Condensates

Biomolecular condensates composed of highly charged biomolecules, such as DNA, RNA, chromatin, and nucleic-acid binding proteins, are ubiquitous in the cell nucleus. The biophysical properties of these charge-rich condensates are largely regulated by electrostatic interactions. Residue-resolution coarse-grained models that describe solvent and ions implicitly are widely used to gain mechanistic insights into the biophysical properties of condensates, offering transferability, computational efficiency, and accurate predictions for multiple systems. However, their predictive accuracy diminishes for charge-rich condensates due to the implicit treatment of solvent and ions. Here, we present Mpipi-Recharged, a residue-resolution coarse-grained model that improves the description of charge effects in biomolecular condensates containing disordered proteins, multidomain proteins, and/or disordered single-stranded RNAs. Mpipi-Recharged introduces a pair-specific asymmetric Yukawa electrostatic potential, informed by atomistic simulations. We show that this asymmetric coarse-graining of electrostatic forces captures intricate effects, such as charge blockiness, stoichiometry variations in complex coacervates, and modulation of salt concentration, without requiring explicit solvation. Mpipi-Recharged provides excellent agreement with experiments in predicting the phase behavior of highly charged condensates. Overall, Mpipi-Recharged improves the computational tools available to investigate the physicochemical mechanisms regulating biomolecular condensates, enhancing the scope of computer simulations in this field.

Quantification of Biomolecular Condensate Volume Reveals Network Swelling and Dissolution Regimes during Phase Transition

Accurate determination of biomolecular condensate volume reveals that destabilization of condensates can lead to either swelling or shrinking of condensates, giving fundamental insights into the regulation of the volume of cellular condensates. Determination of the volume of biomolecular condensates and coacervate protocells is essential to investigate their precise composition and impact on (bio)chemical reactions that are localized inside the condensates. It is not a straightforward task, as condensates have tiny volumes, are highly viscous, and are prone to wetting. Here, we examine different strategies to determine condensate volume and introduce two new methods, with which condensate volumes of 1 μL or less (volume fraction 0.4%) can be determined with a standard deviation of 0.03 μL. Using these methods, we show that the swelling or shrinking of condensates depends on the degree of physical cross-linking. These observations are supported by Flory-Huggins theory and can have profound effects on condensates in cell biology.

The molecular mechanism of temperature-dependent phase separation of heat shock factor 1

Heat shock factor 1 (HSF1) is the critical orchestrator of cell responses to heat shock, and its dysfunction is linked to various diseases. HSF1 undergoes phase separation upon heat shock, and its activity is regulated by post-translational modifications (PTMs). The molecular details underlying HSF1 phase separation, temperature sensing and PTM regulation remain poorly understood. Here, we discovered that HSF1 exhibits temperature-dependent phase separation with a lower critical solution temperature behavior, providing a new conceptual mechanism accounting for HSF1 activation. We revealed the residue-level molecular details of the interactions driving the phase separation of wild-type HSF1 and its distinct PTM patterns at various temperatures. The mapped interfaces were validated experimentally and accounted for the reported HSF1 functions. Importantly, the molecular grammar of temperature-dependent HSF1 phase separation is species specific and physiologically relevant. These findings delineate a chemical code that integrates accurate phase separation with physiological body temperature control in animals.

Mesoscale properties of biomolecular condensates emerging from protein chain dynamics

Biomolecular condensates form by phase separation of biological polymers and have important functions in the cell - functions that are inherently connected to their physical properties. A remarkable aspect of such condensates is that their viscoelastic properties can vary by orders of magnitude, but it has remained unclear how these pronounced differences are rooted in the nanoscale dynamics at the molecular level. Here we investigate a series of condensates formed by complex coacervation that span about two orders of magnitude in molecular dynamics, diffusivity, and viscosity. We find that the nanoscale chain dynamics on the nano- to microsecond timescale can be accurately related to both translational diffusion and mesoscale condensate viscosity by analytical relations from polymer physics. Atomistic simulations reveal that the observed differences in friction - a key quantity underlying these relations - are caused by differences in inter-residue contact lifetimes, leading to the vastly different dynamics among the condensates. The rapid exchange of inter-residue contacts we observe may be a general mechanism for preventing dynamic arrest in compartments densely packed with polyelectrolytes, such as the cell nucleus.

Formation of multicompartment structures through aging of protein-RNA condensates

Cells can dynamically organize reactions through the formation of biomolecular condensates. These viscoelastic networks exhibit complex material properties and mesoscale architectures, including the ability to form multiphase assemblies. It was shown previously that condensates with complex architectures may arise at equilibrium in multicomponent systems or in condensates that were driven out of equilibrium by changes in external parameters such as temperature. In this study, we demonstrate that the aging of initially homogeneous protein-RNA condensates can spontaneously lead to the formation of kinetically arrested double-emulsion and core-shell structures without changes in external variables such as temperature or solution conditions. By combining time-resolved fluorescence-based experimental techniques with simulations based on the Cahn-Hilliard theory, we show that, as the protein-RNA condensates age, the decrease of the relative strength of protein-RNA interactions induces the release of RNA molecules from the dense phase. In condensates exceeding a critical size, aging combined with slow diffusion of the macromolecules trigger nucleation of dilute phase inside the condensates, which leads to the formation of double-emulsion structures. These findings illustrate a new mechanism of formation of multicompartment condensates.

TIP 4 P 2005 Ice : Simulating water with two molecular states

Rigid, non-polarizable water models are very efficient from a computational point of view, and some of them have a great ability in predicting experimental properties. There is, however, little room for improvement in simulating water with this strategy, whose main shortcoming is that water molecules do not change their interaction parameters in response to the local molecular landscape. In this work, we propose a novel modeling strategy that involves using two rigid non-polarizable models as states that water molecules can adopt depending on their molecular environment. During the simulation, molecules dynamically transition from one state to another depending on a local order parameter that quantifies some local structural feature. In particular, molecules belonging to low- and high-tetrahedral order environments are represented with the TIP4P/2005 and TIP4P/Ice rigid models, respectively. In this way, the interaction between water molecules is strengthened when they acquire a tetrahedral coordination, which can be viewed as an effective way of introducing polarization effects. We call the resulting model TIP4P2005Ice and show that it outperforms either of the rigid models that build it. This multi-state strategy only slows down simulations by a factor of 1.5 compared to using a standard non-polarizable model and holds great promise for improving simulations of water and aqueous solutions.

Benchmarking residue-resolution protein coarse-grained models for simulations of biomolecular condensates

Intracellular liquid-liquid phase separation (LLPS) of proteins and nucleic acids is a fundamental mechanism by which cells compartmentalize their components and perform essential biological functions. Molecular simulations play a crucial role in providing microscopic insights into the physicochemical processes driving this phenomenon. In this study, we systematically compare six state-of-the-art sequence-dependent residue-resolution models to evaluate their performance in reproducing the phase behaviour and material properties of condensates formed by seven variants of the low-complexity domain (LCD) of the hnRNPA1 protein (A1-LCD)-a protein implicated in the pathological liquid-to-solid transition of stress granules. Specifically, we assess the HPS, HPS-cation-π, HPS-Urry, CALVADOS2, Mpipi, and Mpipi-Recharged models in their predictions of the condensate saturation concentration, critical solution temperature, and condensate viscosity of the A1-LCD variants. Our analyses demonstrate that, among the tested models, Mpipi, Mpipi-Recharged, and CALVADOS2 provide accurate descriptions of the critical solution temperatures and saturation concentrations for the multiple A1-LCD variants tested. Regarding the prediction of material properties for condensates of A1-LCD and its variants, Mpipi-Recharged stands out as the most reliable model. Overall, this study benchmarks a range of residue-resolution coarse-grained models for the study of the thermodynamic stability and material properties of condensates and establishes a direct link between their performance and the ranking of intermolecular interactions these models consider.

Sequence-Encoded Spatiotemporal Dependence of Viscoelasticity of Protein Condensates Using Computational Microrheology

Many biomolecular condensates act as viscoelastic complex fluids with distinct cellular functions. Deciphering the viscoelastic behavior of biomolecular condensates can provide insights into their spatiotemporal organization and physiological roles within cells. Although there is significant interest in defining the role of condensate dynamics and rheology in physiological functions, the quantification of their time-dependent viscoelastic properties is limited and is mostly done through experimental rheological methods. Here, we demonstrate that a computational passive probe microrheology technique, coupled with continuum mechanics, can accurately characterize the linear viscoelasticity of condensates formed by intrinsically disordered proteins (IDPs). Using a transferable coarse-grained protein model, we first provide a physical basis for choosing optimal values that define the attributes of the probe particle, namely, its size and interaction strength with the residues in an IDP chain. We show that the technique captures the sequence-dependent viscoelasticity of heteropolymeric IDPs that differ in either sequence charge patterning or sequence hydrophobicity. We also illustrate the technique's potential in quantifying the spatial dependence of viscoelasticity in heterogeneous IDP condensates. The computational microrheology technique has important implications for investigating the time-dependent rheology of complex biomolecular architectures, resulting in the sequence-rheology-function relationship for condensates.

The Effect of Dipeptide Repeat Proteins on FUS/TDP43-RNA Condensation in C9orf72 ALS/FTD

Condensation of RNA binding proteins (RBPs) with RNA is essential for cellular function. The most common familial cause of the diseases ALS and FTD is C9orf72 repeat expansion disorders that produce dipeptide repeat proteins (DPRs). We explore the hypothesis that DPRs disrupt the native condensation behavior of RBPs and RNA through molecular interactions resulting in toxicity. FUS and TDP43 are two RBPs known to be affected in ALS/FTD. We use our previously developed 1-bead-per-amino acid and a newly developed 3-bead-per-nucleotide molecular dynamics model to explore ternary phase diagrams of FUS/TDP43-RNA-DPR systems. We show that the most toxic arginine containing DPRs (R-DPRs) can disrupt the RBP condensates through cation-π interactions and can strongly sequester RNA through electrostatic interactions. The native droplet morphologies are already modified at small additions of R-DPRs leading to non-native FUS/TDP43-encapsulated condensates with a marbled RNA/DPR core.

Reduced dynamicity and increased high-order protein assemblies in dense fibrillar component of the nucleolus under cellular senescence

Cellular senescence, which is triggered by various stressors, manifests as irreversible cell cycle arrest, resulting in the disruption of multiple nuclear condensates. One of the affected structures is the nucleolus, whose tripartite layout, separated into distinct liquid phases, allows for the stepwise progression of ribosome biogenesis. The dynamic properties of dense fibrillar components, a sub-nucleolar phase, are crucial for mediating pre-rRNA processing. However, the mechanistic link between the material properties of dense fibrillar components and cellular senescence remains unclear. We established a significant association between cellular senescence and alterations in nucleolar materiality and characteristics, including the number, size, and sphericity of individual subphases of the nucleolus. Senescent cells exhibit reduced fibrillarin dynamics, aberrant accumulation of high-order protein assemblies, such as oligomers and fibrils, and increased dense fibrillar component density. Intriguingly, the addition of RNA-interacting entities mirrored the diminished diffusion of fibrillarin in the nucleolus during cellular senescence. Thus, our findings contribute to a broader understanding of the intricate changes in the materiality of the nucleolus associated with cellular senescence and shed light on nucleolar dynamics in the context of aging and cellular stress.

Sequence-encoded Spatiotemporal Dependence of Viscoelasticity of Protein Condensates Using Computational Microrheology

Many biomolecular condensates act as viscoelastic complex fluids with distinct cellular functions. Deciphering the viscoelastic behavior of biomolecular condensates can provide insights into their spatiotemporal organization and physiological roles within cells. Though there is significant interest in defining the role of condensate dynamics and rheology in physiological functions, the quantification of their time-dependent viscoelastic properties is limited and mostly done through experimental rheological methods. Here, we demonstrate that a computational passive probe microrheology technique, coupled with continuum mechanics, can accurately characterize the linear viscoelasticity of condensates formed by intrinsically disordered proteins (IDPs). Using a transferable coarse-grained protein model, we first provide a physical basis for choosing optimal values that define the attributes of the probe particle, namely its size and interaction strength with the residues in an IDP chain. We show that the technique captures the sequence-dependent viscoelasticity of heteropolymeric IDPs that differ either in sequence charge patterning or sequence hydrophobicity. We also illustrate the technique's potential in quantifying the spatial dependence of viscoelasticity in heterogeneous IDP condensates. The computational microrheology technique has important implications for investigating the time-dependent rheology of complex biomolecular architectures, resulting in the sequence-rheology-function relationship for condensates.

Wet Conformation of Prion-Like Domain and Intimate Correlation of Hydration and Conformational Fluctuations

Proteins with prion-like domains (PLDs) are involved in neurodegeneration-associated aggregation and are prevalent in liquid-like membrane-less organelles. These PLDs contain amyloidogenic stretches but can maintain dynamic disordered conformations, even in the condensed phase. However, the molecular mechanism underlying such intricate conformational properties of PLDs remains elusive. Here we employed molecular dynamics simulations to investigate the conformational properties of a prototypical PLD system (i.e., FUS PLD). According to our simulation results, PLD adopts a wet collapsed conformation, wherein most residues maintain sufficient hydration with the abundance of internal water. These internal water molecules can rapidly exchange between the protein interior and the bulk, enabling intensive coupling of the entire protein with its hydration environment. The dynamic exchange of water molecules is intimately correlated to the overall conformational fluctuations of PLD. Furthermore, the abundance of dynamic internal water suppresses the formation of aggregation-prone ordered structures. These results collectively elucidate the crucial role of internal water in sustaining the dynamic disordered conformation of the PLD and inhibiting its aggregation propensity.

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.

RNA modulates hnRNPA1A amyloid formation mediated by biomolecular condensates

Several RNA binding proteins involved in membraneless organelles can form pathological amyloids associated with neurodegenerative diseases, but the mechanisms of how this aggregation is modulated remain elusive. Here we investigate how heterotypic protein-RNA interactions modulate the condensation and the liquid to amyloid transition of hnRNPA1A, a protein involved in amyothropic lateral sclerosis. In the absence of RNA, formation of condensates promotes hnRNPA1A aggregation and fibrils are localized at the interface of the condensates. Addition of RNA modulates the soluble to amyloid transition of hnRNPA1A according to different pathways depending on RNA/protein stoichiometry. At low RNA concentrations, RNA promotes both condensation and amyloid formation, and the catalytic effect of RNA adds to the role of the interface between the dense and dilute phases. At higher RNA concentrations, condensation is suppressed according to re-entrant phase behaviour but formation of hnRNPA1A amyloids is observed over longer incubation times. Our findings show how heterotypic nucleic acid-protein interactions affect the kinetics and molecular pathways of amyloid formation.

The disordered N-terminal tail of SARS-CoV-2 Nucleocapsid protein forms a dynamic complex with RNA

The SARS-CoV-2 Nucleocapsid (N) protein is responsible for condensation of the viral genome. Characterizing the mechanisms controlling nucleic acid binding is a key step in understanding how condensation is realized. Here, we focus on the role of the RNA binding domain (RBD) and its flanking disordered N-terminal domain (NTD) tail, using single-molecule Förster Resonance Energy Transfer and coarse-grained simulations. We quantified contact site size and binding affinity for nucleic acids and concomitant conformational changes occurring in the disordered region. We found that the disordered NTD increases the affinity of the RBD for RNA by about 50-fold. Binding of both nonspecific and specific RNA results in a modulation of the tail configurations, which respond in an RNA length-dependent manner. Not only does the disordered NTD increase affinity for RNA, but mutations that occur in the Omicron variant modulate the interactions, indicating a functional role of the disordered tail. Finally, we found that the NTD-RBD preferentially interacts with single-stranded RNA and that the resulting protein:RNA complexes are flexible and dynamic. We speculate that this mechanism of interaction enables the Nucleocapsid protein to search the viral genome for and bind to high-affinity motifs.

Sequence-dependent material properties of biomolecular condensates and their relation to dilute phase conformations

Material properties of phase-separated biomolecular condensates, enriched with disordered proteins, dictate many cellular functions. Contrary to the progress made in understanding the sequence-dependent phase separation of proteins, little is known about the sequence determinants of condensate material properties. Using the hydropathy scale and Martini models, we computationally decipher these relationships for charge-rich disordered protein condensates. Our computations yield dynamical, rheological, and interfacial properties of condensates that are quantitatively comparable with experimentally characterized condensates. Interestingly, we find that the material properties of model and natural proteins respond similarly to charge segregation, despite different sequence compositions. Molecular interactions within the condensates closely resemble those within the single-chain ensembles. Consequently, the material properties strongly correlate with molecular contact dynamics and single-chain structural properties. We demonstrate the potential to harness the sequence characteristics of disordered proteins for predicting and engineering the material properties of functional condensates, with insights from the dilute phase properties.

More than a bystander: RNAs specify multifaceted behaviors of liquid-liquid phase-separated biomolecular condensates

Cells contain a myriad of membraneless ribonucleoprotein (RNP) condensates with distinct compositions of proteins and RNAs. RNP condensates participate in different cellular activities, including RNA storage, mRNA translation or decay, stress response, etc. RNP condensates are assembled via liquid-liquid phase separation (LLPS) driven by multivalent interactions. Transition of RNP condensates into bodies with abnormal material properties, such as solid-like amyloid structures, is associated with the pathogenesis of various diseases. In this review, we focus on how RNAs regulate multiple aspects of RNP condensates, such as dynamic assembly and/or disassembly and biophysical properties. RNA properties - including concentration, sequence, length and structure - also determine the phase behaviors of RNP condensates. RNA is also involved in specifying autophagic degradation of RNP condensates. Unraveling the role of RNA in RNPs provides novel insights into pathological accumulation of RNPs in various diseases. This new understanding can potentially be harnessed to develop therapeutic strategies.

Martini on the Rocks: Can a Coarse-Grained Force Field Model Crystals?

Computational chemistry is an important tool in numerous scientific disciplines, including drug discovery and structural biology. Coarse-grained models offer simple representations of molecular systems that enable simulations of large-scale systems. Because there has been an increase in the adoption of such models for simulations of biomolecular systems, critical evaluation is warranted. Here, the stability of the amyloid peptide and organic crystals is evaluated using the Martini 3 coarse-grained force field. The crystals change shape drastically during the simulations. Radial distribution functions show that the distance between backbone beads in β-sheets increases by ∼1 Å, breaking the crystals. The melting points of organic compounds are much too low in the Martini force field. This suggests that Martini 3 lacks the specific interactions needed to accurately simulate peptides or organic crystals without imposing artificial restraints. The problems may be exacerbated by the use of the 12-6 potential, suggesting that a softer potential could improve this model for crystal simulations.

Location and Concentration of Aromatic-Rich Segments Dictates the Percolating Inter-Molecular Network and Viscoelastic Properties of Ageing Condensates

Maturation of functional liquid-like biomolecular condensates into solid-like aggregates has been linked to the onset of several neurodegenerative disorders. Low-complexity aromatic-rich kinked segments (LARKS) contained in numerous RNA-binding proteins can promote aggregation by forming inter-protein β-sheet fibrils that accumulate over time and ultimately drive the liquid-to-solid transition of the condensates. Here, atomistic molecular dynamics simulations are combined with sequence-dependent coarse-grained models of various resolutions to investigate the role of LARKS abundance and position within the amino acid sequence in the maturation of condensates. Remarkably, proteins with tail-located LARKS display much higher viscosity over time than those in which the LARKS are placed toward the center. Yet, at very long timescales, proteins with a single LARKS-independently of its location-can still relax and form high viscous liquid condensates. However, phase-separated condensates of proteins containing two or more LARKS become kinetically trapped due to the formation of percolated β-sheet networks that display gel-like behavior. Furthermore, as a work case example, they demonstrate how shifting the location of the LARKS-containing low-complexity domain of FUS protein toward its center effectively precludes the accumulation of β-sheet fibrils in FUS-RNA condensates, maintaining functional liquid-like behavior without ageing.

Chaotic aging: intrinsically disordered proteins in aging-related processes

The development of aging is associated with the disruption of key cellular processes manifested as well-established hallmarks of aging. Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) have no stable tertiary structure that provide them a power to be configurable hubs in signaling cascades and regulate many processes, potentially including those related to aging. There is a need to clarify the roles of IDPs/IDRs in aging. The dataset of 1702 aging-related proteins was collected from established aging databases and experimental studies. There is a noticeable presence of IDPs/IDRs, accounting for about 36% of the aging-related dataset, which is however less than the disorder content of the whole human proteome (about 40%). A Gene Ontology analysis of the used here aging proteome reveals an abundance of IDPs/IDRs in one-third of aging-associated processes, especially in genome regulation. Signaling pathways associated with aging also contain IDPs/IDRs on different hierarchical levels, revealing the importance of "structure-function continuum" in aging. Protein-protein interaction network analysis showed that IDPs present in different clusters associated with different aging hallmarks. Protein cluster with IDPs enrichment has simultaneously high liquid-liquid phase separation (LLPS) probability, "nuclear" localization and DNA-associated functions, related to aging hallmarks: genomic instability, telomere attrition, epigenetic alterations, and stem cells exhaustion. Intrinsic disorder, LLPS, and aggregation propensity should be considered as features that could be markers of pathogenic proteins. Overall, our analyses indicate that IDPs/IDRs play significant roles in aging-associated processes, particularly in the regulation of DNA functioning. IDP aggregation, which can lead to loss of function and toxicity, could be critically harmful to the cell. A structure-based analysis of aging and the identification of proteins that are particularly susceptible to disturbances can enhance our understanding of the molecular mechanisms of aging and open up new avenues for slowing it down.

Challenges in studying the liquid-to-solid phase transitions of proteins using computer simulations

"Membraneless organelles," also referred to as biomolecular condensates, perform a variety of cellular functions and their dysregulation is implicated in cancer and neurodegeneration. In the last two decades, liquid-liquid phase separation (LLPS) of intrinsically disordered and multidomain proteins has emerged as a plausible mechanism underlying the formation of various biomolecular condensates. Further, the occurrence of liquid-to-solid transitions within liquid-like condensates may give rise to amyloid structures, implying a biophysical link between phase separation and protein aggregation. Despite significant advances, uncovering the microscopic details of liquid-to-solid phase transitions using experiments remains a considerable challenge and presents an exciting opportunity for the development of computational models which provide valuable, complementary insights into the underlying phenomenon. In this review, we first highlight recent biophysical studies which provide new insights into the molecular mechanisms underlying liquid-to-solid (fibril) phase transitions of folded, disordered and multi-domain proteins. Next, we summarize the range of computational models used to study protein aggregation and phase separation. Finally, we discuss recent computational approaches which attempt to capture the underlying physics of liquid-to-solid transitions along with their merits and shortcomings.

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.

Surfactants or scaffolds? RNAs of varying lengths control the thermodynamic stability of condensates differently

Biomolecular condensates, thought to form via liquid-liquid phase separation of intracellular mixtures, are multicomponent systems that can include diverse types of proteins and RNAs. RNA is a critical modulator of RNA-protein condensate stability, as it induces an RNA concentration-dependent reentrant phase transition-increasing stability at low RNA concentrations and decreasing it at high concentrations. Beyond concentration, RNAs inside condensates can be heterogeneous in length, sequence, and structure. Here, we use multiscale simulations to understand how different RNA parameters interact with one another to modulate the properties of RNA-protein condensates. To do so, we perform residue/nucleotide resolution coarse-grained molecular dynamics simulations of multicomponent RNA-protein condensates containing RNAs of different lengths and concentrations, and either FUS or PR25 proteins. Our simulations reveal that RNA length regulates the reentrant phase behavior of RNA-protein condensates: increasing RNA length sensitively rises the maximum value that the critical temperature of the mixture reaches, and the maximum concentration of RNA that the condensate can incorporate before beginning to become unstable. Strikingly, RNAs of different lengths are organized heterogeneously inside condensates, which allows them to enhance condensate stability via two distinct mechanisms: shorter RNA chains accumulate at the condensate's surface acting as natural biomolecular surfactants, while longer RNA chains concentrate inside the core to saturate their bonds and enhance the density of molecular connections in the condensate. Using a patchy particle model, we additionally demonstrate that the combined impact of RNA length and concentration on condensate properties is dictated by the valency, binding affinity, and polymer length of the various biomolecules involved. Our results postulate that diversity on RNA parameters within condensates allows RNAs to increase condensate stability by fulfilling two different criteria: maximizing enthalpic gain and minimizing interfacial free energy; hence, RNA diversity should be considered when assessing the impact of RNA on biomolecular condensates regulation.

Sequence- and structure-specific RNA oligonucleotide binding attenuates heterogeneous nuclear ribonucleoprotein A1 dysfunction

The RNA binding protein heterogeneous nuclear ribonucleoprotein A1 (A1) regulates RNA metabolism, which is crucial to maintaining cellular homeostasis. A1 dysfunction mechanistically contributes to reduced cell viability and loss, but molecular mechanisms of how A1 dysfunction affects cell viability and loss, and methodologies to attenuate its dysfunction, are lacking. Utilizing in silico molecular modeling and an in vitro optogenetic system, this study examined the consequences of RNA oligonucleotide (RNAO) treatment on attenuating A1 dysfunction and its downstream cellular effects. In silico and thermal shift experiments revealed that binding of RNAOs to the RNA Recognition Motif 1 of A1 is stabilized by sequence- and structure-specific RNAO-A1 interactions. Using optogenetics to model A1 cellular dysfunction, we show that sequence- and structure-specific RNAOs significantly attenuated abnormal cytoplasmic A1 self-association kinetics and A1 cytoplasmic clustering. Downstream of A1 dysfunction, we demonstrate that A1 clustering affects the formation of stress granules, activates cell stress, and inhibits protein translation. With RNAO treatment, we show that stress granule formation is attenuated, cell stress is inhibited, and protein translation is restored. This study provides evidence that sequence- and structure-specific RNAO treatment attenuates A1 dysfunction and its downstream effects, thus allowing for the development of A1-specific therapies that attenuate A1 dysfunction and restore cellular homeostasis.

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.

Highly Charged Proteins and Their Repulsive Interactions Antagonize Biomolecular Condensation

Biomolecular condensation is involved in various cellular processes; therefore, regulation of condensation is crucial to prevent deleterious protein aggregation and maintain a stable cellular environment. Recently, a class of highly charged proteins, known as heat-resistant obscure (Hero) proteins, was shown to protect other client proteins from pathological aggregation. However, the molecular mechanisms by which Hero proteins protect other proteins from aggregation remain unknown. In this study, we performed multiscale molecular dynamics (MD) simulations of Hero11, a Hero protein, and the C-terminal low-complexity domain (LCD) of the transactive response DNA-binding protein 43 (TDP-43), a client protein of Hero11, under various conditions to examine their interactions with each other. We found that Hero11 permeates into the condensate formed by the LCD of TDP-43 (TDP-43-LCD) and induces changes in conformation, intermolecular interactions, and dynamics of TDP-43-LCD. We also examined possible Hero11 structures in atomistic and coarse-grained MD simulations and found that Hero11 with a higher fraction of disordered region tends to assemble on the surface of the condensates. Based on the simulation results, we have proposed three possible mechanisms for Hero11's regulatory function: (i) In the dense phase, TDP-43-LCD reduces contact with each other and shows faster diffusion and decondensation due to the repulsive Hero11-Hero11 interactions. (ii) In the dilute phase, the saturation concentration of TDP-43-LCD is increased, and its conformation is relatively more extended and variant, induced by the attractive Hero11-TDP-43-LCD interactions. (iii) Hero11 on the surface of small TDP-43-LCD condensates can contribute to avoiding their fusion due to repulsive interactions. The proposed mechanisms provide new insights into the regulation of biomolecular condensation in cells under various conditions.

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.