Valence and patterning of aromatic residues determine the phase behavior of prion-like domains

MolPhase, an advanced prediction algorithm for protein phase separation

We introduce MolPhase, an advanced algorithm for predicting protein phase separation (PS) behavior that improves accuracy and reliability by utilizing diverse physicochemical features and extensive experimental datasets. MolPhase applies a user-friendly interface to compare distinct biophysical features side-by-side along protein sequences. By additional comparison with structural predictions, MolPhase enables efficient predictions of new phase-separating proteins and guides hypothesis generation and experimental design. Key contributing factors underlying MolPhase include electrostatic pi-interactions, disorder, and prion-like domains. As an example, MolPhase finds that phytobacterial type III effectors (T3Es) are highly prone to homotypic PS, which was experimentally validated in vitro biochemically and in vivo in plants, mimicking their injection and accumulation in the host during microbial infection. The physicochemical characteristics of T3Es dictate their patterns of association for multivalent interactions, influencing the material properties of phase-separating droplets based on the surrounding microenvironment in vivo or in vitro. Robust integration of MolPhase's effective prediction and experimental validation exhibit the potential to evaluate and explore how biomolecule PS functions in biological systems.

HYPK: A marginally disordered protein sensitive to charge decoration

Intrinsically disordered proteins (IDPs) that lie close to the empirical boundary separating IDPs and folded proteins in Uversky's charge-hydropathy plot may behave as "marginal IDPs" and sensitively switch conformation upon changes in environment (temperature, crowding, and charge screening), sequence, or both. In our search for such a marginal IDP, we selected Huntingtin-interacting protein K (HYPK) near that boundary as a candidate; PKIα, also near that boundary, has lower secondary structure propensity; and Crk1, just across the boundary on the folded side, has higher secondary structure propensity. We used a qualitative Förster resonance energy transfer-based assay together with circular dichroism to simultaneously probe global and local conformation. HYPK shows several unique features indicating marginality: a cooperative transition in end-to-end distance with temperature, like Crk1 and folded proteins, but unlike PKIα; enhanced secondary structure upon crowding, in contrast to Crk1 and PKIα; and a cross-over from salt-induced expansion to compaction at high temperature, likely due to a structure-to-disorder transition not seen in Crk1 and PKIα. We then tested HYPK's sensitivity to charge patterning by designing charge-flipped variants including two specific sequences with identical amino acid composition that markedly differ in their predicted size and response to salt. The experimentally observed trends, also including mutants of PKIα, verify the predictions from sequence charge decoration metrics. Marginal proteins like HYPK show features of both folded and disordered proteins that make them sensitive to physicochemical perturbations and structural control by charge patterning.

Disordered clock protein interactions and charge blocks turn an hourglass into a persistent circadian oscillator

Organismal physiology is widely regulated by the molecular circadian clock, a feedback loop composed of protein complexes whose members are enriched in intrinsically disordered regions. These regions can mediate protein-protein interactions via SLiMs, but the contribution of these disordered regions to clock protein interactions had not been elucidated. To determine the functionality of these disordered regions, we applied a synthetic peptide microarray approach to the disordered clock protein FRQ in Neurospora crassa. We identified residues required for FRQ's interaction with its partner protein FRH, the mutation of which demonstrated FRH is necessary for persistent clock oscillations but not repression of transcriptional activity. Additionally, the microarray demonstrated an enrichment of FRH binding to FRQ peptides with a net positive charge. We found that positively charged residues occurred in significant "blocks" within the amino acid sequence of FRQ and that ablation of one of these blocks affected both core clock timing and physiological clock output. Finally, we found positive charge clusters were a commonly shared molecular feature in repressive circadian clock proteins. Overall, our study suggests a mechanistic purpose for positive charge blocks and yielded insights into repressive arm protein roles in clock function.

Biomolecular condensates form spatially inhomogeneous network fluids

The functions of biomolecular condensates are thought to be influenced by their material properties, and these will be determined by the internal organization of molecules within condensates. However, structural characterizations of condensates are challenging, and rarely reported. Here, we deploy a combination of small angle neutron scattering, fluorescence recovery after photobleaching, and coarse-grained molecular dynamics simulations to provide structural descriptions of model condensates that are formed by macromolecules from nucleolar granular components (GCs). We show that these minimal facsimiles of GCs form condensates that are network fluids featuring spatial inhomogeneities across different length scales that reflect the contributions of distinct protein and peptide domains. The network-like inhomogeneous organization is characterized by a coexistence of liquid- and gas-like macromolecular densities that engenders bimodality of internal molecular dynamics. These insights suggest that condensates formed by multivalent proteins share features with network fluids formed by systems such as patchy or hairy colloids.

GENESIS CGDYN: large-scale coarse-grained MD simulation with dynamic load balancing for heterogeneous biomolecular systems

Residue-level coarse-grained (CG) molecular dynamics (MD) simulation is widely used to investigate slow biological processes that involve multiple proteins, nucleic acids, and their complexes. Biomolecules in a large simulation system are distributed non-uniformly, limiting computational efficiency with conventional methods. Here, we develop a hierarchical domain decomposition scheme with dynamic load balancing for heterogeneous biomolecular systems to keep computational efficiency even after drastic changes in particle distribution. These schemes are applied to the dynamics of intrinsically disordered protein (IDP) droplets. During the fusion of two droplets, we find that the changes in droplet shape correlate with the mixing of IDP chains. Additionally, we simulate large systems with multiple IDP droplets, achieving simulation sizes comparable to those observed in microscopy. In our MD simulations, we directly observe Ostwald ripening, a phenomenon where small droplets dissolve and their molecules redeposit into larger droplets. These methods have been implemented in CGDYN of the GENESIS software, offering a tool for investigating mesoscopic biological processes using the residue-level CG models.

Molecular determinants and signaling effects of PKA RIα phase separation

Spatiotemporal regulation of intracellular signaling molecules, such as the 3',5'-cyclic adenosine monophosphate (cAMP)-dependent protein kinase (PKA), ensures proper cellular function. Liquid-liquid phase separation (LLPS) of the ubiquitous PKA regulatory subunit RIα promotes cAMP compartmentation and signaling specificity. However, the molecular determinants of RIα LLPS remain unclear. Here, we reveal that two separate dimerization interfaces, combined with the cAMP-induced unleashing of the PKA catalytic subunit (PKA-C) from the pseudosubstrate inhibitory sequence, drive RIα condensate formation in the cytosol of mammalian cells, which is antagonized by docking to A-kinase anchoring proteins. Strikingly, we find that the RIα pseudosubstrate region is critically involved in forming a non-canonical R:C complex, which recruits active PKA-C to RIα condensates to maintain low basal PKA activity in the cytosol. Our results suggest that RIα LLPS not only facilitates cAMP compartmentation but also spatially restrains active PKA-C, thus highlighting the functional versatility of biomolecular condensates in driving signaling specificity.

Lipid Membrane Topographies Are Regulators for the Spatial Distribution of Liquid Protein Condensates

Liquid protein condensates play important roles in orchestrating subcellular organization and as biochemical reaction hubs. Recent studies have linked lipid membranes to proteins capable of forming liquid condensates, and shown that biophysical parameters, like protein enrichment and restricted diffusion at membranes, regulate condensate formation and size. However, the impact of membrane topography on liquid condensates remains poorly understood. Here, we devised a cell-free system to reconstitute liquid condensates on lipid membranes with microstructured topographies and demonstrated that lipid membrane topography is a significant biophysical regulator. Using membrane surfaces designed with microwells, we observed ordered condensate patterns. Furthermore, we demonstrate that membrane topographies influence the shape of liquid condensates. Finally, we show that capillary forces, mediated by membrane topographies, lead to the directed fusion of liquid condensates. Our results demonstrate that membrane topography is a potent biophysical regulator for the localization and shape of mesoscale liquid protein condensates.

Macromolecular condensation organizes nucleolar sub-phases to set up a pH gradient

Nucleoli are multicomponent condensates defined by coexisting sub-phases. We identified distinct intrinsically disordered regions (IDRs), including acidic (D/E) tracts and K-blocks interspersed by E-rich regions, as defining features of nucleolar proteins. We show that the localization preferences of nucleolar proteins are determined by their IDRs and the types of RNA or DNA binding domains they encompass. In vitro reconstitutions and studies in cells showed how condensation, which combines binding and complex coacervation of nucleolar components, contributes to nucleolar organization. D/E tracts of nucleolar proteins contribute to lowering the pH of co-condensates formed with nucleolar RNAs in vitro. In cells, this sets up a pH gradient between nucleoli and the nucleoplasm. By contrast, juxta-nucleolar bodies, which have different macromolecular compositions, featuring protein IDRs with very different charge profiles, have pH values that are equivalent to or higher than the nucleoplasm. Our findings show that distinct compositional specificities generate distinct physicochemical properties for condensates.

Fuzzy recognition by the prokaryotic transcription factor HigA2 from Vibrio cholerae

Disordered protein sequences can exhibit different binding modes, ranging from well-ordered folding-upon-binding to highly dynamic fuzzy binding. The primary function of the intrinsically disordered region of the antitoxin HigA2 from Vibrio cholerae is to neutralize HigB2 toxin through ultra-high-affinity folding-upon-binding interaction. Here, we show that the same intrinsically disordered region can also mediate fuzzy interactions with its operator DNA and, through interplay with the folded helix-turn-helix domain, regulates transcription from the higBA2 operon. NMR, SAXS, ITC and in vivo experiments converge towards a consistent picture where a specific set of residues in the intrinsically disordered region mediate electrostatic and hydrophobic interactions while "hovering" over the DNA operator. Sensitivity of the intrinsically disordered region to scrambling the sequence, position-specific contacts and absence of redundant, multivalent interactions, point towards a more specific type of fuzzy binding. Our work demonstrates how a bacterial regulator achieves dual functionality by utilizing two distinct interaction modes within the same disordered sequence.

Labile assembly of a tardigrade protein induces biostasis

Tardigrades are microscopic animals that survive desiccation by inducing biostasis. To survive drying tardigrades rely on intrinsically disordered CAHS proteins, which also function to prevent perturbations induced by drying in vitro and in heterologous systems. CAHS proteins have been shown to form gels both in vitro and in vivo, which has been speculated to be linked to their protective capacity. However, the sequence features and mechanisms underlying gel formation and the necessity of gelation for protection have not been demonstrated. Here we report a mechanism of fibrillization and gelation for CAHS D similar to that of intermediate filament assembly. We show that in vitro, gelation restricts molecular motion, immobilizing and protecting labile material from the harmful effects of drying. In vivo, we observe that CAHS D forms fibrillar networks during osmotic stress. Fibrillar networking of CAHS D improves survival of osmotically shocked cells. We observe two emergent properties associated with fibrillization; (i) prevention of cell volume change and (ii) reduction of metabolic activity during osmotic shock. We find that there is no significant correlation between maintenance of cell volume and survival, while there is a significant correlation between reduced metabolism and survival. Importantly, CAHS D's fibrillar network formation is reversible and metabolic rates return to control levels after CAHS fibers are resolved. This work provides insights into how tardigrades induce reversible biostasis through the self-assembly of labile CAHS gels.

A Hollow TFG Condensate Spatially Compartmentalizes the Early Secretory Pathway

In the early secretory pathway, endoplasmic reticulum (ER) and Golgi membranes form a nearly spherical interface. In this ribosome-excluding zone, bidirectional transport of cargo coincides with a spatial segregation of anterograde and retrograde carriers by an unknown mechanism. We show that at physiological conditions, Trk-fused gene (TFG) self-organizes to form a hollow, anisotropic condensate that matches the dimensions of the ER-Golgi interface. Regularly spaced hydrophobic residues in TFG control the condensation mechanism and result in a porous condensate surface. We find that TFG condensates act as a molecular sieve, enabling molecules corresponding to the size of anterograde coats (COPII) to access the condensate interior while restricting retrograde coats (COPI). We propose that a hollow TFG condensate structures the ER-Golgi interface to create a diffusion-limited space for bidirectional transport. We further propose that TFG condensates optimize membrane flux by insulating secretory carriers in their lumen from retrograde carriers outside TFG cages.

Mutational scanning of CRX classifies clinical variants and reveals biochemical properties of the transcriptional effector domain

Cone-Rod Homeobox, encoded by CRX, is a transcription factor (TF) essential for the terminal differentiation and maintenance of mammalian photoreceptors. Structurally, CRX comprises an ordered DNA-binding homeodomain and an intrinsically disordered transcriptional effector domain. Although a handful of human variants in CRX have been shown to cause several different degenerative retinopathies with varying cone and rod predominance, as with most human disease genes the vast majority of observed CRX genetic variants are uncharacterized variants of uncertain significance (VUS). We performed a deep mutational scan (DMS) of nearly all possible single amino acid substitution variants in CRX, using an engineered cell-based transcriptional reporter assay. We measured the ability of each CRX missense variant to transactivate a synthetic fluorescent reporter construct in a pooled fluorescence-activated cell sorting assay and compared the activation strength of each variant to that of wild-type CRX to compute an activity score, identifying thousands of variants with altered transcriptional activity. We calculated a statistical confidence for each activity score derived from multiple independent measurements of each variant marked by unique sequence barcodes, curating a high-confidence list of nearly 2,000 variants with significantly altered transcriptional activity compared to wild-type CRX. We evaluated the performance of the DMS assay as a clinical variant classification tool using gold-standard classified human variants from ClinVar, and determined that activity scores could be used to identify pathogenic variants with high specificity. That this performance could be achieved using a synthetic reporter assay in a foreign cell type, even for a highly cell type-specific TF like CRX, suggests that this approach shows promise for DMS of other TFs that function in cell types that are not easily accessible. Per-position average activity scores closely aligned to a predicted structure of the ordered homeodomain and demonstrated position-specific residue requirements. The intrinsically disordered transcriptional effector domain, by contrast, displayed a qualitatively different pattern of substitution effects, following compositional constraints without specific residue position requirements in the peptide chain. The observed compositional constraints of the effector domain were consistent with the acidic exposure model of transcriptional activation. Together, the results of the CRX DMS identify molecular features of the CRX effector domain and demonstrate clinical utility for variant classification.

Insights into Molecular Diversity within the FUS/EWS/TAF15 Protein Family: Unraveling Phase Separation of the N-Terminal Low-Complexity Domain from RNA-Binding Protein EWS

The FET protein family, comprising FUS, EWS, and TAF15, plays crucial roles in mRNA maturation, transcriptional regulation, and DNA damage response. Clinically, they are linked to Ewing family tumors and neurodegenerative diseases such as amyotrophic lateral sclerosis. The fusion protein EWS::FLI1, the causative mutation of Ewing sarcoma, arises from a genomic translocation that fuses a portion of the low-complexity domain (LCD) of EWS (EWSLCD) with the DNA binding domain of the ETS transcription factor FLI1. This fusion protein modifies transcriptional programs and disrupts native EWS functions, such as splicing. The exact role of the intrinsically disordered EWSLCD remains a topic of active investigation, but its ability to phase separate and form biomolecular condensates is believed to be central to EWS::FLI1's oncogenic properties. Here, we used paramagnetic relaxation enhancement NMR, microscopy, and all-atom molecular dynamics (MD) simulations to better understand the self-association and phase separation tendencies of the EWSLCD. Our NMR data and mutational analysis suggest that a higher density and proximity of tyrosine residues amplify the likelihood of condensate formation. MD simulations revealed that the tyrosine-rich termini exhibit compact conformations with unique contact networks and provided critical input on the relationship between contacts formed within a single molecule (intramolecular) and inside the condensed phase (intermolecular). These findings enhance our understanding of FET proteins' condensate-forming capabilities and underline differences between EWS, FUS, and TAF15.

Precise prediction of phase-separation key residues by machine learning

Understanding intracellular phase separation is crucial for deciphering transcriptional control, cell fate transitions, and disease mechanisms. However, the key residues, which impact phase separation the most for protein phase separation function have remained elusive. We develop PSPHunter, which can precisely predict these key residues based on machine learning scheme. In vivo and in vitro validations demonstrate that truncating just 6 key residues in GATA3 disrupts phase separation, enhancing tumor cell migration and inhibiting growth. Glycine and its motifs are enriched in spacer and key residues, as revealed by our comprehensive analysis. PSPHunter identifies nearly 80% of disease-associated phase-separating proteins, with frequent mutated pathological residues like glycine and proline often residing in these key residues. PSPHunter thus emerges as a crucial tool to uncover key residues, facilitating insights into phase separation mechanisms governing transcriptional control, cell fate transitions, and disease development.

Phosphorylation, disorder, and phase separation govern the behavior of Frequency in the fungal circadian clock

Circadian clocks are composed of transcription-translation negative feedback loops that pace rhythms of gene expression to the diurnal cycle. In the filamentous fungus Neurospora crassa, the proteins Frequency (FRQ), the FRQ-interacting RNA helicase (FRH), and Casein-Kinase I (CK1) form the FFC complex that represses expression of genes activated by the white-collar complex (WCC). FRQ orchestrates key molecular interactions of the clock despite containing little predicted tertiary structure. Spin labeling and pulse-dipolar electron spin resonance spectroscopy provide domain-specific structural insights into the 989-residue intrinsically disordered FRQ and the FFC. FRQ contains a compact core that associates and organizes FRH and CK1 to coordinate their roles in WCC repression. FRQ phosphorylation increases conformational flexibility and alters oligomeric state, but the changes in structure and dynamics are non-uniform. Full-length FRQ undergoes liquid-liquid phase separation (LLPS) to sequester FRH and CK1 and influence CK1 enzymatic activity. Although FRQ phosphorylation favors LLPS, LLPS feeds back to reduce FRQ phosphorylation by CK1 at higher temperatures. Live imaging of Neurospora hyphae reveals FRQ foci characteristic of condensates near the nuclear periphery. Analogous clock repressor proteins in higher organisms share little position-specific sequence identity with FRQ; yet, they contain amino acid compositions that promote LLPS. Hence, condensate formation may be a conserved feature of eukaryotic clocks.

Coiled-coil domains are sufficient to drive liquid-liquid phase separation in protein models

Liquid-liquid phase separation (LLPS) is thought to be a main driving force in the formation of membraneless organelles. Examples of such organelles include the centrosome, central spindle, and stress granules. Recently, it has been shown that coiled-coil (CC) proteins, such as the centrosomal proteins pericentrin, spd-5, and centrosomin, might be capable of LLPS. CC domains have physical features that could make them the drivers of LLPS, but it is unknown if they play a direct role in the process. We developed a coarse-grained simulation framework for investigating the LLPS propensity of CC proteins, in which interactions that support LLPS arise solely from CC domains. We show, using this framework, that the physical features of CC domains are sufficient to drive LLPS of proteins. The framework is specifically designed to investigate how the number of CC domains, as well as the multimerization state of CC domains, can affect LLPS. We show that small model proteins with as few as two CC domains can phase separate. Increasing the number of CC domains up to four per protein can somewhat increase LLPS propensity. We demonstrate that trimer-forming and tetramer-forming CC domains have a dramatically higher LLPS propensity than dimer-forming coils, which shows that multimerization state has a greater effect on LLPS than the number of CC domains per protein. These data support the hypothesis of CC domains as drivers of protein LLPS, and have implications in future studies to identify the LLPS-driving regions of centrosomal and central spindle proteins.

Galectin-3 does not interact with RNA directly

Galectin-3, well characterized as a glycan binding protein, has been identified as a putative RNA binding protein, possibly through participation in pre-mRNA maturation through interactions with splicosomes. Given recent developments with cell surface RNA biology, the putative dual-function nature of galectin-3 evokes a possible non-classical connection between glycobiology and RNA biology. However, with limited functional evidence of a direct RNA interaction, many molecular-level observations rely on affinity reagents and lack appropriate genetic controls. Thus, evidence of a direct interaction remains elusive. We demonstrate that antibodies raised to endogenous human galectin-3 can isolate RNA-protein crosslinks, but this activity remains insensitive to LGALS3 knock-out. Proteomic characterization of anti-galectin-3 IPs revealed enrichment of galectin-3, but high abundance of hnRNPA2B1, an abundant, well-characterized RNA-binding protein with weak homology to the N-terminal domain of galectin-3, in the isolate. Genetic ablation of HNRNPA2B1, but not LGALS3, eliminates the ability of the anti-galectin-3 antibodies to isolate RNA-protein crosslinks, implying either an indirect interaction or cross-reactivity. To address this, we introduced an epitope tag to the endogenous C-terminal locus of LGALS3. Isolation of the tagged galectin-3 failed to reveal any RNA-protein crosslinks. This result suggests that the galectin-3 does not directly interact with RNA and may be misidentified as an RNA-binding protein, at least in HeLa where the putative RNA associations were first identified. We encourage further investigation of this phenomenon employ gene deletions and, when possible, endogenous epitope tags to achieve the specificity required to evaluate potential interactions.

Thermodynamic modulation of gephyrin condensation by inhibitory synapse components

Phase separation drives compartmentalization of intracellular contents into various biomolecular condensates. Individual condensate components are thought to differentially contribute to the organization and function of condensates. However, how intermolecular interactions among constituent biomolecules modulate the phase behaviors of multicomponent condensates remains unclear. Here, we used core components of the inhibitory postsynaptic density (iPSD) as a model system to quantitatively probe how the network of intra- and intermolecular interactions defines the composition and cellular distribution of biomolecular condensates. We found that oligomerization-driven phase separation of gephyrin, an iPSD-specific scaffold, is critically modulated by an intrinsically disordered linker region exhibiting minimal homotypic attractions. Other iPSD components, such as neurotransmitter receptors, differentially promote gephyrin condensation through distinct binding modes and affinities. We further demonstrated that the local accumulation of scaffold-binding proteins at the cell membrane promotes the nucleation of gephyrin condensates in neurons. These results suggest that in multicomponent systems, the extent of scaffold condensation can be fine-tuned by scaffold-binding factors, a potential regulatory mechanism for self-organized compartmentalization in cells.

PABPC1 mediates degradation of C9orf72-FTLD/ALS GGGGCC repeat RNA

GGGGCC hexanucleotide repeat expansion in C9orf72 causes frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Expanded GGGGCC repeat RNA accumulates within RNA foci and is translated into toxic dipeptide repeat proteins; thus, efficient repeat RNA degradation may alleviate diseases. hnRNPA3, one of the repeat RNA-binding proteins, has been implicated in the destabilization of repeat RNA. Using APEX2-mediated proximity biotinylation, here, we demonstrate PABPC1, a cytoplasmic poly (A)-binding protein, interacts with hnRNPA3. Knockdown of PABPC1 increased the accumulation of repeat RNA and RNA foci to the same extent as the knockdown of hnRNPA3. Proximity ligation assays indicated PABPC1-hnRNPA3 and PABPC1-RNA exosomes, a complex that degrades repeat RNA, preferentially co-localized when repeat RNA was present. Our results suggest that PABPC1 functions as a mediator of polyadenylated GGGGCC repeat RNA degradation through interactions with hnRNPA3 and RNA exosome complex.

Coactivator condensation drives cardiovascular cell lineage specification

During development, cells make switch-like decisions to activate new gene programs specifying cell lineage. The mechanisms underlying these decisive choices remain unclear. Here, we show that the cardiovascular transcriptional coactivator myocardin (MYOCD) activates cell identity genes by concentration-dependent and switch-like formation of transcriptional condensates. MYOCD forms such condensates and activates cell identity genes at critical concentration thresholds achieved during smooth muscle cell and cardiomyocyte differentiation. The carboxyl-terminal disordered region of MYOCD is necessary and sufficient for condensate formation. Disrupting this region's ability to form condensates disrupts gene activation and smooth muscle cell reprogramming. Rescuing condensate formation by replacing this region with disordered regions from functionally unrelated proteins rescues gene activation and smooth muscle cell reprogramming. Our findings demonstrate that MYOCD condensate formation is required for gene activation during cardiovascular differentiation. We propose that the formation of transcriptional condensates at critical concentrations of cell type-specific regulators provides a molecular switch underlying the activation of key cell identity genes during development.

Specific protein-RNA interactions are mostly preserved in biomolecular condensates

Many biomolecular condensates are enriched in and depend on RNAs and RNA binding proteins (RBPs). So far, only a few studies have addressed the characterization of the intermolecular interactions responsible for liquid-liquid phase separation (LLPS) and the impact of condensation on RBPs and RNAs. Here, we present an approach to study protein-RNA interactions inside biomolecular condensates by applying cross-linking of isotope labeled RNA and tandem mass spectrometry to phase-separating systems (LLPS-CLIR-MS). LLPS-CLIR-MS enables the characterization of intermolecular interactions present within biomolecular condensates at residue-specific resolution and allows a comparison with the same complexes in the dispersed phase. We observe that sequence-specific RBP-RNA interactions present in the dispersed phase are generally maintained inside condensates. In addition, LLPS-CLIR-MS identifies structural alterations at the protein-RNA interfaces, including additional unspecific contacts in the condensed phase. Our approach offers a procedure to derive structural information of protein-RNA complexes within biomolecular condensates that could be critical for integrative structural modeling of ribonucleoproteins (RNPs) in this form.

Emerging experimental methods to study the thermodynamics of biomolecular condensate formation

The formation of biomolecular condensates in vivo is increasingly recognized to underlie a multitude of crucial cellular functions. Furthermore, the evolution of highly dynamic protein condensates into progressively less reversible assemblies is thought to be involved in a variety of disorders, from cancer over neurodegeneration to rare genetic disorders. There is an increasing need for efficient experimental methods to characterize the thermodynamics of condensate formation and that can be used in screening campaigns to identify and rationally design condensate modifying compounds. Theoretical advances in the field are also identifying the key parameters that need to be measured in order to obtain a comprehensive understanding of the underlying interactions and driving forces. Here, we review recent progress in the development of efficient and quantitative experimental methods to study the driving forces behind and the temporal evolution of biomolecular condensates.

Metastable condensates suppress conversion to amyloid fibrils

Stress granules form via co-condensation of RNA binding proteins with prion-like low complexity domains (PLCDs) and RNA molecules released by stress-induced polysomal runoff. Homotypic interactions among PLCDs can drive amyloid fibril formation and this is enhanced by ALS-associated mutations. We find that homotypic interactions that drive condensation versus fibril formation are separable for A1-LCD, the PLCD of hnRNPA1. These separable interactions lead to condensates that are metastable versus fibrils that are globally stable. Metastable condensates suppress fibril formation, and ALS-associated mutations enhance fibril formation by weakening condensate metastability. Mutations designed to enhance A1-LCD condensate metastability restore wild-type behaviors of stress granules in cells even when ALS-associated mutations are present. This suggests that fibril formation can be suppressed by enhancing condensate metastability through condensate-driving interactions.

Biomolecular condensation orchestrates clathrin-mediated endocytosis in plants

Clathrin-mediated endocytosis is an essential cellular internalization pathway involving the dynamic assembly of clathrin and accessory proteins to form membrane-bound vesicles. The evolutionarily ancient TSET-TPLATE complex (TPC) plays an essential, but ill-defined role in endocytosis in plants. Here we show that two highly disordered TPC subunits, AtEH1 and AtEH2, function as scaffolds to drive biomolecular condensation of the complex. These condensates specifically nucleate on the plasma membrane through interactions with anionic phospholipids, and facilitate the dynamic recruitment and assembly of clathrin, as well as early- and late-stage endocytic accessory proteins. Importantly, condensation promotes ordered clathrin assemblies. TPC-driven biomolecular condensation thereby facilitates dynamic protein assemblies throughout clathrin-mediated endocytosis. Furthermore, we show that a disordered region of AtEH1 controls the material properties of endocytic condensates in vivo. Alteration of these material properties disturbs the recruitment of accessory proteins, influences endocytosis dynamics and impairs plant responsiveness. Our findings reveal how collective interactions shape endocytosis.

Conformational fluctuations and phases in fused in sarcoma (FUS) low-complexity domain

The well-known phenomenon of phase separation in synthetic polymers and proteins has become a major topic in biophysics because it has been invoked as a mechanism of compartment formation in cells, without the need for membranes. Most of the coacervates (or condensates) are composed of Intrinsically Disordered Proteins (IDPs) or regions that are structureless, often in interaction with RNA and DNA. One of the more intriguing IDPs is the 526-residue RNA-binding protein, Fused in Sarcoma (FUS), whose monomer conformations and condensates exhibit unusual behavior that are sensitive to solution conditions. By focussing principally on the N-terminus low-complexity domain (FUS-LC comprising residues 1-214) and other truncations, we rationalize the findings of solid-state NMR experiments, which show that FUS-LC adopts a non-polymorphic fibril structure (core-1) involving residues 39-95, flanked by fuzzy coats on both the N- and C-terminal ends. An alternate structure (core-2), whose free energy is comparable to core-1, emerges only in the truncated construct (residues 110-214). Both core-1 and core-2 fibrils are stabilized by a Tyrosine ladder as well as hydrophilic interactions. The morphologies (gels, fibrils, and glass-like) adopted by FUS seem to vary greatly, depending on the experimental conditions. The effect of phosphorylation is site-specific. Simulations show that phosphorylation of residues within the fibril has a greater destabilization effect than residues that are outside the fibril region, which accords well with experiments. Many of the peculiarities associated with FUS may also be shared by other IDPs, such as TDP43 and hnRNPA2. We outline a number of problems for which there is no clear molecular explanation.

Quantitative description of the phase-separation behavior of the multivalent SLP65-CIN85 complex

Biomolecular condensates play a major role in cell compartmentalization, besides membrane-enclosed organelles. The multivalent SLP65 and CIN85 proteins are proximal B-cell antigen receptor (BCR) signal effectors and critical for proper immune responses. In association with intracellular vesicles, the two effector proteins form phase separated condensates prior to antigen stimulation, thereby preparing B lymphocytes for rapid and effective activation upon BCR ligation. Within this tripartite system, 6 proline-rich motifs (PRMs) of SLP65 interact promiscuously with 3 SH3 domains of the CIN85 monomer, establishing 18 individual SH3-PRM interactions whose individual dissociation constants we determined. Based on these 18 dissociation constants, we measured the phase-separation properties of the natural SLP65/CIN85 system as well as designer constructs that emphasize the strongest SH3/PRM interactions. By modeling these various SLP65/CIN85 constructs with the program LASSI (LAttice simulation engine for Sticker and Spacer Interactions), we reproduced the observed phase-separation properties. In addition, LASSI revealed a deviation in the experimental measurement, which was independently identified as a previously unknown intramolecular interaction. Thus, thermodynamic properties of the individual PRM/SH3 interactions allow us to model the phase-separation behavior of the SLP65/CIN85 system faithfully.

Direct prediction of intrinsically disordered protein conformational properties from sequence

Intrinsically disordered regions (IDRs) are ubiquitous across all domains of life and play a range of functional roles. While folded domains are generally well described by a stable three-dimensional structure, IDRs exist in a collection of interconverting states known as an ensemble. This structural heterogeneity means that IDRs are largely absent from the Protein Data Bank, contributing to a lack of computational approaches to predict ensemble conformational properties from sequence. Here we combine rational sequence design, large-scale molecular simulations and deep learning to develop ALBATROSS, a deep-learning model for predicting ensemble dimensions of IDRs, including the radius of gyration, end-to-end distance, polymer-scaling exponent and ensemble asphericity, directly from sequences at a proteome-wide scale. ALBATROSS is lightweight, easy to use and accessible as both a locally installable software package and a point-and-click-style interface via Google Colab notebooks. We first demonstrate the applicability of our predictors by examining the generalizability of sequence-ensemble relationships in IDRs. Then, we leverage the high-throughput nature of ALBATROSS to characterize the sequence-specific biophysical behavior of IDRs within and between proteomes.

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.

The molecular basis for cellular function of intrinsically disordered protein regions

Intrinsically disordered protein regions exist in a collection of dynamic interconverting conformations that lack a stable 3D structure. These regions are structurally heterogeneous, ubiquitous and found across all kingdoms of life. Despite the absence of a defined 3D structure, disordered regions are essential for cellular processes ranging from transcriptional control and cell signalling to subcellular organization. Through their conformational malleability and adaptability, disordered regions extend the repertoire of macromolecular interactions and are readily tunable by their structural and chemical context, making them ideal responders to regulatory cues. Recent work has led to major advances in understanding the link between protein sequence and conformational behaviour in disordered regions, yet the link between sequence and molecular function is less well defined. Here we consider the biochemical and biophysical foundations that underlie how and why disordered regions can engage in productive cellular functions, provide examples of emerging concepts and discuss how protein disorder contributes to intracellular information processing and regulation of cellular function.

A sequence-based model for identifying proteins undergoing liquid-liquid phase separation/forming fibril aggregates via machine learning

Liquid-liquid phase separation (LLPS) and the solid aggregate (also referred to as amyloid aggregates) formation of proteins, have gained significant attention in recent years due to their associations with various physiological and pathological processes in living organisms. The systematic investigation of the differences and connections between proteins undergoing LLPS and those forming amyloid fibrils at the sequence level has not yet been explored. In this research, we aim to address this gap by comparing the two types of proteins across 36 features using collected data available currently. The statistical comparison results indicate that, 24 of the selected 36 features exhibit significant difference between the two protein groups. A LLPS-Fibrils binary classification model built on these 24 features using random forest reveals that the fraction of intrinsically disordered residues (FIDR ) is identified as the most crucial feature. While, in the further three-class LLPS-Fibrils-Background classification model built on the same screened features, the composition of cysteine and that of leucine show more significant contributions than others. Through feature ablation analysis, we finally constructed a model FLFB (Feature-based LLPS-Fibrils-Background protein predictor) using six refined features, with an average area under the receiver operating characteristics of 0.83. This work indicates using sequence features and a machine learning model, proteins undergoing LLPS or forming amyloid fibrils can be identified.

Distinct chemical environments in biomolecular condensates

Diverse mechanisms have been described for selective enrichment of biomolecules in membrane-bound organelles, but less is known about mechanisms by which molecules are selectively incorporated into biomolecular assemblies such as condensates that lack surrounding membranes. The chemical environments within condensates may differ from those outside these bodies, and if these differed among various types of condensate, then the different solvation environments would provide a mechanism for selective distribution among these intracellular bodies. Here we use small molecule probes to show that different condensates have distinct chemical solvating properties and that selective partitioning of probes in condensates can be predicted with deep learning approaches. Our results demonstrate that different condensates harbor distinct chemical environments that influence the distribution of molecules, show that clues to condensate chemical grammar can be ascertained by machine learning and suggest approaches to facilitate development of small molecule therapeutics with optimal subcellular distribution and therapeutic benefit.

A Unified Description of Salt Effects on the Liquid-Liquid Phase Separation of Proteins

Protein aggregation via liquid-liquid phase separation (LLPS) is ubiquitous in nature and is intimately connected to many human diseases. Although it is widely known that the addition of salt has crucial impacts on the LLPS of proteins, full understanding of the salt effects remains an outstanding challenge. Here, we develop a molecular theory that systematically incorporates the self-consistent field theory for charged macromolecules into the solution thermodynamics. The electrostatic interaction, hydrophobicity, ion solvation, and translational entropy are included in a unified framework. Our theory fully captures the long-standing puzzles of the nonmonotonic salt concentration dependence and the specific ion effect. We find that proteins show salting-out at low salt concentrations due to ionic screening. The solubility follows the inverse Hofmeister series. In the high salt concentration regime, protein continues salting-out for small ions but turns to salting-in for larger ions, accompanied by the reversal of the Hofmeister series. We reveal that the solubility at high salt concentrations is determined by the competition between the solvation energy and translational entropy of the ion. Furthermore, we derive an analytical criterion for determining the boundary between the salting-in and salting-out regimes, which is in good agreement with experimental results for various proteins and salt ions.

Checkpoint activation by Spd1: a competition-based system relying on tandem disordered PCNA binding motifs

DNA regulation, replication and repair are processes fundamental to all known organisms and the sliding clamp proliferating cell nuclear antigen (PCNA) is central to all these processes. S-phase delaying protein 1 (Spd1) from S. pombe, an intrinsically disordered protein that causes checkpoint activation by inhibiting the enzyme ribonucleotide reductase, has one of the most divergent PCNA binding motifs known. Using NMR spectroscopy, in vivo assays, X-ray crystallography, calorimetry, and Monte Carlo simulations, an additional PCNA binding motif in Spd1, a PIP-box, is revealed. The two tandemly positioned, low affinity sites exchange rapidly on PCNA exploiting the same binding sites. Increasing or decreasing the binding affinity between Spd1 and PCNA through mutations of either motif compromised the ability of Spd1 to cause checkpoint activation in yeast. These results pinpoint a role for PCNA in Spd1-mediated checkpoint activation and suggest that its tandemly positioned short linear motifs create a neatly balanced competition-based system, involving PCNA, Spd1 and the small ribonucleotide reductase subunit, Suc22R2. Similar mechanisms may be relevant in other PCNA binding ligands where divergent binding motifs so far have gone under the PIP-box radar.

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.

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.

Expanding the molecular grammar of polar residues and arginine in FUS prion-like domain phase separation and aggregation

A molecular grammar governing low-complexity prion-like domains phase separation (PS) has been proposed based on mutagenesis experiments that identified tyrosine and arginine as primary drivers of phase separation via aromatic-aromatic and aromatic-arginine interactions. Here we show that additional residues make direct favorable contacts that contribute to phase separation, highlighting the need to account for these contributions in PS theories and models. We find that tyrosine and arginine make important contacts beyond only tyrosine-tyrosine and tyrosine-arginine, including arginine-arginine contacts. Among polar residues, glutamine in particular contributes to phase separation with sequence/position-specificity, making contacts with both tyrosine and arginine as well as other residues, both before phase separation and in condensed phases. For glycine, its flexibility, not its small solvation volume, favors phase separation by allowing favorable contacts between other residues and inhibits the liquid-to-solid (LST) transition. Polar residue types also make sequence-specific contributions to aggregation that go beyond simple rules, which for serine positions is linked to formation of an amyloid-core structure by the FUS low-complexity domain. Hence, here we propose a revised molecular grammar expanding the role of arginine and polar residues in prion-like domain protein phase separation and aggregation.

Molecular Crowding: Physiologic Sensing and Control

The cytoplasm is densely packed with molecules that contribute to its nonideal behavior. Cytosolic crowding influences chemical reaction rates, intracellular water mobility, and macromolecular complex formation. Overcrowding is potentially catastrophic; to counteract this problem, cells have evolved acute and chronic homeostatic mechanisms that optimize cellular crowdedness. Here, we provide a physiology-focused overview of molecular crowding, highlighting contemporary advances in our understanding of its sensing and control. Long hypothesized as a form of crowding-induced microcompartmentation, phase separation allows cells to detect and respond to intracellular crowding through the action of biomolecular condensates, as indicated by recent studies. Growing evidence indicates that crowding is closely tied to cell size and fluid volume, homeostatic responses to physical compression and desiccation, tissue architecture, circadian rhythm, aging, transepithelial transport, and total body electrolyte and water balance. Thus, molecular crowding is a fundamental physiologic parameter that impacts diverse functions extending from molecule to organism.

Biomolecular condensates form spatially inhomogeneous network fluids

The functions of biomolecular condensates are thought to be influenced by their material properties, and these will be determined by the internal organization of molecules within condensates. However, structural characterizations of condensates are challenging, and rarely reported. Here, we deploy a combination of small angle neutron scattering, fluorescence recovery after photobleaching, and coarse-grained molecular dynamics simulations to provide structural descriptions of model condensates that are formed by macromolecules from nucleolar granular components (GCs). We show that these minimal facsimiles of GCs form condensates that are network fluids featuring spatial inhomogeneities across different length scales that reflect the contributions of distinct protein and peptide domains. The network-like inhomogeneous organization is characterized by a coexistence of liquid- and gas-like macromolecular densities that engenders bimodality of internal molecular dynamics. These insights suggest that condensates formed by multivalent proteins share features with network fluids formed by systems such as patchy or hairy colloids.

Enolase of Streptococcus suis serotype 2 promotes biomolecular condensation of ribosomal protein SA for HBMECs apoptosis

BACKGROUND

Ribosomal protein SA (RPSA) of human brain microvascular endothelial cells (HBMECs) can transfer from the cytosol to the cell surface and act as a receptor for some pathogens, including Streptococcus suis serotype 2 (SS2), a zoonotic pathogen causing meningitis in pigs and humans. We previously reported that SS2 virulence factor enolase (ENO) binds to RPSA on the cell surface of HBMECs and induces apoptosis. However, the mechanism that activates RPSA translocation to the cell surface and induces ENO-mediated HBMEC apoptosis is unclear.

RESULTS

Here, we show that RPSA localization and condensation on the host cell surface depend on its internally disordered region (IDR). ENO binds to the IDR of RPSA and promotes its interaction with RPSA and vimentin (VIM), which is significantly suppressed after 1,6-Hexanediol (1,6-Hex, a widely used tool to disrupt phase separation) treatment, indicating that ENO incorporation and thus the concentration of RPSA/VIM complexes via co-condensation. Furthermore, increasing intracellular calcium ions (Ca2+) in response to SS2 infection further facilitates the liquid-like condensation of RPSA and aggravates ENO-induced HBMEC cell apoptosis.

CONCLUSIONS

Together, our study provides a previously underappreciated molecular mechanism illuminating that ENO-induced RPSA condensation activates the migration of RPSA to the bacterial cell surface and stimulates SS2-infected HBMEC death and, potentially, disease progression. This study offers a fresh avenue for investigation into the mechanism by which other harmful bacteria infect hosts via cell surfaces' RPSA.

Heterotypic interactions can drive selective co-condensation of prion-like low-complexity domains of FET proteins and mammalian SWI/SNF complex

Prion-like domains (PLDs) are low-complexity protein sequences enriched within nucleic acid-binding proteins including those involved in transcription and RNA processing. PLDs of FUS and EWSR1 play key roles in recruiting chromatin remodeler mammalian SWI/SNF (mSWI/SNF) complex to oncogenic FET fusion protein condensates. Here, we show that disordered low-complexity domains of multiple SWI/SNF subunits are prion-like with a strong propensity to undergo intracellular phase separation. These PLDs engage in sequence-specific heterotypic interactions with the PLD of FUS in the dilute phase at sub-saturation conditions, leading to the formation of PLD co-condensates. In the dense phase, homotypic and heterotypic PLD interactions are highly cooperative, resulting in the co-mixing of individual PLD phases and forming spatially homogeneous condensates. Heterotypic PLD-mediated positive cooperativity in protein-protein interaction networks is likely to play key roles in the co-phase separation of mSWI/SNF complex with transcription factors containing homologous low-complexity domains.

Surface Charge Can Modulate Phase Separation of Multidomain Proteins

Phase separation has emerged as an important mechanism explaining the formation of certain biomolecular condensates. Biological phase separation is often driven by the multivalent interactions of modular protein domains. Beyond valency, the physical features of folded domains that promote phase separation are poorly understood. We used a model system─the small ubiquitin modifier (SUMO) and its peptide ligand, the SUMO interaction motif (SIM)─to examine how domain surface charge influences multivalency-driven phase separation. Phase separation of polySUMO and polySIM was altered by pH via a change in the protonation state of SUMO surface histidines. These effects were recapitulated by histidine mutations, which modulated SUMO solubility and polySUMO-polySIM phase separation in parallel and were quantitatively explained by atomistic modeling of weak interactions among proteins in the system. Thus, surface charge can tune the phase separation of multivalent proteins, suggesting a means of controlling phase separation biologically, evolutionarily, and therapeutically.

Defining the mechanisms and properties of post-transcriptional regulatory disordered regions by high-throughput functional profiling

Disordered regions within RNA binding proteins are required to control mRNA decay and protein synthesis. To understand how these disordered regions modulate gene expression, we surveyed regulatory activity across the entire disordered proteome using a high-throughput functional assay. We identified hundreds of regulatory sequences within intrinsically disordered regions and demonstrate how these elements cooperate with core mRNA decay machinery to promote transcript turnover. Coupling high-throughput functional profiling with mutational scanning revealed diverse molecular features, ranging from defined motifs to overall sequence composition, underlying the regulatory effects of disordered peptides. Machine learning analysis implicated aromatic residues in particular contexts as critical determinants of repressor activity, consistent with their roles in forming protein-protein interactions with downstream effectors. Our results define the molecular principles and biochemical mechanisms that govern post-transcriptional gene regulation by disordered regions and exemplify the encoding of diverse yet specific functions in the absence of well-defined structure.

Commonly asked questions about transcriptional activation domains

Eukaryotic transcription factors activate gene expression with their DNA-binding domains and activation domains. DNA-binding domains bind the genome by recognizing structurally related DNA sequences; they are structured, conserved, and predictable from protein sequences. Activation domains recruit chromatin modifiers, coactivator complexes, or basal transcriptional machinery via structurally diverse protein-protein interactions. Activation domains and DNA-binding domains have been called independent, modular units, but there are many departures from modularity, including interactions between these regions and overlap in function. Compared to DNA-binding domains, activation domains are poorly understood because they are poorly conserved, intrinsically disordered, and difficult to predict from protein sequences. This review, organized around commonly asked questions, describes recent progress that the field has made in understanding the sequence features that control activation domains and predicting them from sequence.

A complex network of interdomain interactions underlies the conformational ensemble of monomeric TDP-43 and modulates its phase behavior

TAR DNA-binding protein 43 (TDP-43) is a multidomain protein involved in the regulation of RNA metabolism, and its aggregates have been observed in neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Numerous studies indicate TDP-43 can undergo liquid-liquid phase separation (LLPS) in vitro and is a component of biological condensates. Homo-oligomerization via the folded N-terminal domain (aa:1-77) and the conserved helical region (aa:319-341) of the disordered, C-terminal domain is found to be an important driver of TDP-43 phase separation. However, a comprehensive molecular view of TDP-43 phase separation, particularly regarding the nature of heterodomain interactions, is lacking due to the challenges associated with its stability and purification. Here, we utilize all-atom and coarse-grained (CG) molecular dynamics (MD) simulations to uncover the network of interdomain interactions implicated in TDP-43 phase separation. All-atom simulations uncovered the presence of transient, interdomain interactions involving flexible linkers, RNA-recognition motif (RRM) domains and a charged segment of disordered C-terminal domain (CTD). CG simulations indicate these inter-domain interactions which affect the conformational landscape of TDP-43 in the dilute phase are also prevalent in the condensed phase. Finally, sequence and surface charge distribution analysis coupled with all-atom simulations (at high salt) confirmed that the transient interdomain contacts are predominantly electrostatic in nature. Overall, our findings from multiscale simulations lead to a greater appreciation of the complex interaction network underlying the structural landscape and phase separation of TDP-43.

BioXTAS RAW 2: new developments for a free open-source program for small-angle scattering data reduction and analysis

BioXTAS RAW is a free open-source program for reduction, analysis and modelling of biological small-angle scattering data. Here, the new developments in RAW version 2 are described. These include improved data reduction using pyFAI; updated automated Guinier fitting and D max finding algorithms; automated series (e.g. size-exclusion chromatography coupled small-angle X-ray scattering or SEC-SAXS) buffer- and sample-region finding algorithms; linear and integral baseline correction for series; deconvolution of series data using regularized alternating least squares (REGALS); creation of electron-density reconstructions using electron density via solution scattering (DENSS); a comparison window showing residuals, ratios and statistical comparisons between profiles; and generation of PDF reports with summary plots and tables for all analysis. Furthermore, there is now a RAW API, which can be used without the graphical user interface (GUI), providing full access to all of the functionality found in the GUI. In addition to these new capabilities, RAW has undergone significant technical updates, such as adding Python 3 compatibility, and has entirely new documentation available both online and in the program.

Recent advances in de novo computational design and redesign of intrinsically disordered proteins and intrinsically disordered protein regions

In the early 2000s, the concept of "unstructured biology" has emerged to be an important field in protein science by generating various new research directions. Many novel strategies and methods have been developed that are focused on effectively identifying/predicting intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs), identifying their potential functions, disorder based drug design etc. Due to the range of functions of IDPs/IDPRs and their involvement in various debilitating diseases they are of contemporary interest to the scientific community. Recent researches are focused on designing/redesigning specific IDPs/IDPRs de novo. These de novo design/redesigns of IDPs/IDPRs are carried out by altering compositional biases and specific sequence patterning parameters. The main focus of these researches is to influence specific molecular functions, phase behavior, cellular phenotypes etc. In this review, we first provide the differences of natively folded and natively unfolded or IDPs with respect to their potential energy landscapes. Here, we provide current understandings on the different computational design strategies and methods that have been utilized in de novo design and redesigns of IDPs and IDPRs. Finally, we conclude the review by discussing the challenges that have been faced during the computational design/design attempts of IDPs/IDPRs.

Helicity of a tardigrade disordered protein contributes to its protective function during desiccation

To survive extreme drying (anhydrobiosis), many organisms, spanning every kingdom of life, accumulate intrinsically disordered proteins (IDPs). For decades, the ability of anhydrobiosis-related IDPs to form transient amphipathic helices has been suggested to be important for promoting desiccation tolerance. However, evidence empirically supporting the necessity and/or sufficiency of helicity in mediating anhydrobiosis is lacking. Here, we demonstrate that the linker region of CAHS D, a desiccation-related IDP from the tardigrade Hypsibius exemplaris, that contains significant helical structure, is the protective portion of this protein. Perturbing the sequence composition and grammar of the linker region of CAHS D, through the insertion of helix-breaking prolines, modulating the identity of charged residues, or replacement of hydrophobic amino acids with serine or glycine residues results in variants with different degrees of helical structure. Importantly, correlation of protective capacity and helical content in variants generated through different helix perturbing modalities does not show as strong a trend, suggesting that while helicity is important, it is not the only property that makes a protein protective during desiccation. These results provide direct evidence for the decades-old theory that helicity of desiccation-related IDPs is linked to their anhydrobiotic capacity.

Conformational ensembles of the human intrinsically disordered proteome

Intrinsically disordered proteins and regions (collectively, IDRs) are pervasive across proteomes in all kingdoms of life, help to shape biological functions and are involved in numerous diseases. IDRs populate a diverse set of transiently formed structures and defy conventional sequence-structure-function relationships1. Developments in protein science have made it possible to predict the three-dimensional structures of folded proteins at the proteome scale2. By contrast, there is a lack of knowledge about the conformational properties of IDRs, partly because the sequences of disordered proteins are poorly conserved and also because only a few of these proteins have been characterized experimentally. The inability to predict structural properties of IDRs across the proteome has limited our understanding of the functional roles of IDRs and how evolution shapes them. As a supplement to previous structural studies of individual IDRs3, we developed an efficient molecular model to generate conformational ensembles of IDRs and thereby to predict their conformational properties from sequences4,5. Here we use this model to simulate nearly all of the IDRs in the human proteome. Examining conformational ensembles of 28,058 IDRs, we show how chain compaction is correlated with cellular function and localization. We provide insights into how sequence features relate to chain compaction and, using a machine-learning model trained on our simulation data, show the conservation of conformational properties across orthologues. Our results recapitulate observations from previous studies of individual protein systems and exemplify how to link-at the proteome scale-conformational ensembles with cellular function and localization, amino acid sequence, evolutionary conservation and disease variants. Our freely available database of conformational properties will encourage further experimental investigation and enable the generation of hypotheses about the biological roles and evolution of IDRs.

Design of functional intrinsically disordered proteins

Many proteins do not fold into a fixed three-dimensional structure, but rather function in a highly disordered state. These intrinsically disordered proteins pose a unique challenge to protein engineering and design: How can proteins be designed de novo if not by tailoring their structure? Here, we will review the nascent field of design of intrinsically disordered proteins with focus on applications in biotechnology and medicine. The design goals should not necessarily be the same as for de novo design of folded proteins as disordered proteins have unique functional strengths and limitations. We focus on functions where intrinsically disordered proteins are uniquely suited including disordered linkers, desiccation chaperones, sensors of the chemical environment, delivery of pharmaceuticals, and constituents of biomolecular condensates. Design of functional intrinsically disordered proteins relies on a combination of computational tools and heuristics gleaned from sequence-function studies. There are few cases where intrinsically disordered proteins have made it into industrial applications. However, we argue that disordered proteins can perform many roles currently performed by organic polymers, and that these proteins might be more designable due to their modularity.

Measurement of solubility product in a model condensate reveals the interplay of small oligomerization and self-association

Cellular condensates often consist of 10s to 100s of distinct interacting molecular species. Because of the complexity of these interactions, predicting the point at which they will undergo phase separation into discrete compartments is daunting. Using experiments and computation, we therefore studied a simple model system consisting of 2 proteins, polySH3 and polyPRM, designed for pentavalent heterotypic binding. We tested whether the peak solubility product, the product of dilute phase monomer concentrations, is a predictive parameter for the onset of phase separation. Titrating up equal total concentrations of each component showed that the maximum solubility product does approximately coincide with the threshold for phase separation in both the experiments and models. However, we found that measurements of dilute phase concentration include contributions from small oligomers, not just monomers; therefore, a quantitative comparison of the experiments and models required inclusion of small oligomers in the model analysis. We also examined full phase diagrams where the model results were almost symmetric along the diagonal, but the experimental results were highly asymmetric. This led us to perform dynamic light scattering experiments, where we discovered a weak homotypic interaction for polyPRM; when this was added to the computational model, it was able to recapitulate the experimentally observed asymmetry. Thus, comparing experiments to simulation reveals that the solubility product can be predictive of phase separation, even if small oligomers and low affinity homotypic interactions preclude experimental measurement of monomer concentration.