Enzymatic metabolons dramatically enhance metabolic fluxes of low-efficiency biochemical reactions.

In this work, we investigate how spatial proximity of enzymes belonging to the same pathway (metabolon) affects metabolic flux. Using off-lattice Langevin dynamics simulations in tandem with a stochastic reaction-diffusion protocol and a semi-analytical reaction-diffusion model, we systematically explored how strength of protein-protein interactions, catalytic efficiency, and protein-ligand interactions affect metabolic flux through the metabolon. Formation of a metabolon leads to a greater speedup for longer pathways and especially for reaction-limited enzymes, whereas, for fully optimized diffusion-limited enzymes, the effect is negligible. Notably, specific cluster architectures are not a prerequisite for enhancing reaction flux. Simulations uncover the crucial role of optimal nonspecific protein-ligand interactions in enhancing catalytic efficiency of a metabolon. Our theory implies, and bioinformatics analysis confirms, that longer catalytic pathways are enriched in less optimal enzymes, whereas most diffusion-limited enzymes populate shorter pathways. Our findings point toward a plausible evolutionary strategy where enzymes compensate for less-than-optimal efficiency by increasing their local concentration in the clustered state.

Phosphorylation sites are evolutionary checkpoints against liquid-solid transition in protein condensates.

Assemblies of multivalent RNA-binding protein fused in sarcoma (FUS) can exist in the functional liquid-like state as well as less dynamic and potentially toxic amyloid- and hydrogel-like states. How could then cells form liquid-like condensates while avoiding their transformation to amyloids? Here, we show how posttranslational phosphorylation can provide a "handle" that prevents liquid-solid transition of intracellular condensates containing FUS. Using residue-specific coarse-grained simulations, for 85 different mammalian FUS sequences, we show how the number of phosphorylation sites and their spatial arrangement affect intracluster dynamics preventing conversion to amyloids. All atom simulations further confirm that phosphorylation can effectively reduce the ß-sheet propensity in amyloid-prone fragments of FUS. A detailed evolutionary analysis shows that mammalian FUS PLDs are enriched in amyloid-prone stretches compared to control neutrally evolved sequences, suggesting that mammalian FUS proteins evolved to self-assemble. However, in stark contrast to proteins that do not phase-separate for their function, mammalian sequences have phosphosites in close proximity to these amyloid-prone regions. These results suggest that evolution uses amyloid-prone sequences in prion-like domains to enhance phase separation of condensate proteins while enriching phosphorylation sites in close proximity to safeguard against liquid-solid transitions.

Different states and the associated fates of biomolecular condensates.

Biomolecular condensates are functional assemblies, which can enrich intrinsically disordered proteins (IDPs) and/or RNAs at concentrations that are orders of magnitude higher than the bulk. In their native functional state, these structures can exist in multiple physical states including liquid-droplet phase, hydrogels, and solid assemblies. On the other hand, an aberrant transition between these physical states can result in loss-of-function or a gain-of-toxic-function. A prime example of such an aberrant transition is droplet aging-a phenomenon where some condensates may progressively transition into less dynamic material states at biologically relevant timescales. In this essay, we review structural and viscoelastic roots of aberrant liquid-solid transitions. Also, we highlight the different checkpoints and experimentally tunable handles, both active (ATP-dependent enzymes, post-translational modifications) and passive (colocalization of RNA molecules), that could alter the material state of assemblies.

The physics of liquid-to-solid transitions in multi-domain protein condensates.

Many RNA-binding proteins (RBPs) that assemble into membraneless organelles have a common architecture including disordered prion-like domain (PLD) and folded RNA-binding domain (RBD). An enrichment of PLD within the condensed phase gives rise to formation, on longer time scales, of amyloid-like fibrils (aging). In this study, we employ coarse-grained Langevin dynamics simulations to explore the physical basis for the structural diversity in condensed phases of multi-domain RBPs. We discovered a highly cooperative first-order transition between disordered structures and an ordered phase whereby chains of PLD organize in fibrils with high nematic orientational order. An interplay between homodomain (PLD-PLD) and heterodomain (PLD-RBD) interactions results in variety of structures with distinct spatial architectures. Interestingly, the different structural phases also exhibit vastly different intracluster dynamics of proteins, with diffusion coefficients 5 times (disordered structures) to 50 times (ordered structures) lower than that of the dilute phase. Cooperativity of this liquid-solid transition makes fibril formation highly malleable to mutations or post-translational modifications. Our results provide a mechanistic understanding of how multi-domain RBPs could form assemblies with distinct structural and material properties.

Role of non-specific interactions in the phase-separation and maturation of macromolecules.

Phase separation of biomolecules could be mediated by both specific and non-specific interactions. How the interplay between non-specific and specific interactions along with polymer entropy influences phase separation is an open question. We address this question by simulating self-associating molecules as polymer chains with a short core stretch that forms the specifically interacting functional interface and longer non-core regions that participate in non-specific/promiscuous interactions. Our results show that the interplay of specific (strength, ϵsp) and non-specific interactions (strength, ϵns) could result in phase separation of polymers and its transition to solid-like aggregates (mature state). In the absence of ϵns, the polymer chains do not dwell long enough in the vicinity of each other to undergo phase separation and transition into a mature state. On the other hand, in the limit of strong ϵns, the assemblies cannot transition into the mature state and form a non-specific assembly, suggesting an optimal range of interactions favoring mature multimers. In the scenario where only a fraction (Nfrac) of the non-core regions participate in attractive interactions, we find that slight modifications to either ϵns or Nfrac can result in dramatically altered self-assembled states. Using a combination of heterogeneous and homogeneous mix of polymers, we establish how this interplay between interaction energies dictates the propensity of biomolecules to find the correct binding partner at dilute concentrations in crowded environments.

Effect of RNA on Morphology and Dynamics of Membraneless Organelles.

Membraneless organelles (MLOs) are spatiotemporally regulated structures that concentrate multivalent proteins or RNA, often in response to stress. The proteins enriched within MLOs are often classified as high-valency "scaffolds" or low-valency "clients", with the former being associated with a phase-separation promoting role. In this study, we employ a minimal model for P-body components, with a defined protein-protein interaction network, to study their phase separation at biologically realistic low protein concentrations. Without RNA, multivalent proteins can assemble into solid-like clusters only in the regime of high concentration and stable interactions. RNA molecules promote cluster formation in an RNA-length-dependent manner, even in the regime of weak interactions and low protein volume fraction. Our simulations reveal that long RNA chains act as superscaffolds that stabilize large RNA-protein clusters by recruiting low-valency proteins within them while also ensuring functional "liquid-like" turnover of components. Our results suggest that RNA-mediated phase separation could be a plausible mechanism for spatiotemporally regulated phase separation in the cell.

Dynamic metastable long-living droplets formed by sticker-spacer proteins.

Multivalent biopolymers phase separate into membrane-less organelles (MLOs) which exhibit liquid-like behavior. Here, we explore formation of prototypical MOs from multivalent proteins on various time and length scales and show that the kinetically arrested metastable multi-droplet state is a dynamic outcome of the interplay between two competing processes: a diffusion-limited encounter between proteins, and the exhaustion of available valencies within smaller clusters. Clusters with satisfied valencies cannot coalesce readily, resulting in metastable, long-living droplets. In the regime of dense clusters akin to phase-separation, we observe co-existing assemblies, in contrast to the single, large equilibrium-like cluster. A system-spanning network encompassing all multivalent proteins was only observed at high concentrations and large interaction valencies. In the regime favoring large clusters, we observe a slow-down in the dynamics of the condensed phase, potentially resulting in loss of function. Therefore, metastability could be a hallmark of dynamic functional droplets formed by sticker-spacer proteins.

Complexation of NAC-Derived Peptide Ligands with the C-Terminus of α-Synuclein Accelerates Its Aggregation.

Aggregation of α-synuclein (α-Syn) into neurotoxic oligomers and amyloid fibrils is suggested to be the pathogenic mechanism for Parkinson's disease (PD). Recent studies have indicated that oligomeric species of α-Syn are more cytotoxic than their mature fibrillar counterparts, which are responsible for dopaminergic neuronal cell death in PD. Therefore, the effective therapeutic strategies for tackling aggregation-associated diseases would be either to prevent aggregation or to modulate the aggregation process to minimize the formation of toxic oligomers during aggregation. In this work, we showed that arginine-substituted α-Syn ligands, based on the most aggregation-prone sequence of α-Syn, accelerate the protein aggregation in a concentration-dependent manner. To elucidate the mechanism by which Arg-substituted peptides could modulate α-Syn aggregation kinetics, we performed surface plasmon resonance (SPR) spectroscopy, nuclear magnetic resonance (NMR) studies, and all-atom molecular dynamics (MD) simulation. The SPR analysis showed a high binding potency of these peptides with α-Syn but one that was nonspecific in nature. The two-dimensional NMR studies suggest that a large stretch within the C-terminus of α-Syn displays a chemical shift perturbation upon interacting with Arg-substituted peptides, indicating C-terminal residues of α-Syn might be responsible for this class of peptide binding. This is further supported by MD simulation studies in which the Arg-substituted peptide showed the strongest interaction with the C-terminus of α-Syn. Overall, our results suggest that the binding of Arg-substituted ligands to the highly acidic C-terminus of α-Syn leads to reduced charge density and flexibility, resulting in accelerated aggregation kinetics. This may be a potentially useful strategy while designing peptides, which act as α-Syn aggregation modulators.

Defining a Physical Basis for Diversity in Protein Self-Assemblies Using a Minimal Model.

Self-assembly of proteins into ordered, fibrillar structures is a commonly observed theme in biology. It has been observed that diverse set of proteins (e.g., alpha-synuclein, insulin, TATA-box binding protein, Sup35, p53), independent of their sequence, native structure, or function could self-assemble into highly ordered structures known as amyloids. What are the crucial features underlying amyloidogenesis that make it so generic? Using coarse-grained simulations of peptide self-assembly, we argue that variation in two physical parameters-bending stiffness of the polypeptide and strength of intermolecular interactions-can give rise to many of the structural features typically associated with amyloid self-assembly. We show that the interplay between these two factors gives rise to a rich phase diagram displaying high diversity in aggregated states. For certain parameters, we find a bimodal distribution for the order parameter implying the coexistence of ordered and disordered aggregates. Our findings may explain the experimentally observed variability including the "off-pathway" aggregated structures. Further, we demonstrate that sequence-dependence and protein-specific signatures could be mapped to our coarse-grained framework to study self-assembly behavior of realistic systems such as the STVIIE peptide and Aß42. The work also provides certain guiding principles that could be used to design novel peptides with desired self-assembly properties, by tuning a few physical parameters.

A minimal conformational switching-dependent model for amyloid self-assembly.

Amyloid formation is associated with various pathophysiological conditions like Alzheimer's and Parkinson's diseases as well as many useful functions. The hallmark of amyloid assemblies is a conformational transition of the constituent proteins into a ß - sheet rich filament. Accounting for this conformational transition in amyloidogenic proteins, we develop an analytically solvable model that can probe the dynamics of an ensemble of single filaments. Using the theory and Monte Carlo simulations, we show the presence of two kinetic regimes for the growth of a self-assembling filament - switching-dependent and -independent growth regimes. We observe a saturation in fibril elongation velocities at higher concentrations in the first regime, providing a novel explanation to the concentration-independence of growth velocities observed experimentally. We also compute the length fluctuation of the filaments to characterize aggregate heterogeneity. From the early velocities and length fluctuation, we propose a novel way of estimating the conformational switching rate. Our theory predicts a kinetic phase diagram that has three distinct phases - short oligomers/monomers, disordered aggregates and ß-rich filaments. The model also predicts the force generation potential and the intermittent growth of amyloid fibrils evident from single molecular experiments. Our model could contribute significantly to the physical understanding of amyloid aggregation.

Investigating the intrinsic aggregation potential of evolutionarily conserved segments in p53.

Protein aggregation and amyloid formation are known to play a role both in diseases and in biological functions. Transcription factor p53 plays a major role in tumor suppression by maintaining genomic stability. Recent studies have suggested that amyloid formation of p53 could lead to its loss of physiological function as a tumor suppressor. Here, we investigated the intrinsic amyloidogenic nature of wild-type p53 using sequence analysis. We used bioinformatics and aggregation prediction algorithms to establish the evolutionarily conserved nature of aggregation-prone sequences in wild-type p53. Further, we analyzed the amyloid forming capacity of conserved and aggregation-prone p53-derived peptides PILTIITL and YFTLQI in vitro using various biophysical techniques, including all atom molecular dynamics simulation. Finally, we probed the seeding ability of the PILTIITL peptide on p53 aggregation in vitro and in cells. Our data demonstrate the intrinsic amyloid forming ability of a sequence stretch of the p53 DNA binding domain (DBD) and its aggregation templating behavior on full-length and p53 core domain. Therefore, p53 aggregation, instigated through an amyloidogenic segment in its DBD, could be a putative driving force for p53 aggregation in vivo.

Elucidating the role of disulfide bond on amyloid formation and fibril reversibility of somatostatin-14: relevance to its storage and secretion.

The storage of protein/peptide hormones within subcellular compartments and subsequent release are crucial for their native function, and hence these processes are intricately regulated in mammalian systems. Several peptide hormones were recently suggested to be stored as amyloids within endocrine secretory granules. This leads to an apparent paradox where storage requires formation of aggregates, and their function requires a supply of non-aggregated peptides on demand. The precise mechanism behind amyloid formation by these hormones and their subsequent release remain an open question. To address this, we examined aggregation and fibril reversibility of a cyclic peptide hormone somatostatin (SST)-14 using various techniques. After proving that SST gets stored as amyloid in vivo, we investigated the role of native structure in modulating its conformational dynamics and self-association by disrupting the disulfide bridge (Cys(3)-Cys(14)) in SST. Using two-dimensional NMR, we resolved the initial structure of somatostatin-14 leading to aggregation and further probed its conformational dynamics in silico. The perturbation in native structure (S-S cleavage) led to a significant increase in conformational flexibility and resulted in rapid amyloid formation. The fibrils formed by disulfide-reduced noncyclic SST possess greater resistance to denaturing conditions with decreased monomer releasing potency. MD simulations reveal marked differences in the intermolecular interactions in SST and noncyclic SST providing plausible explanation for differential aggregation and fibril reversibility observed experimentally in these structural variants. Our findings thus emphasize that subtle changes in the native structure of peptide hormone(s) could alter its conformational dynamics and amyloid formation, which might have significant implications on their reversible storage and secretion.

Characterization of amyloid formation by glucagon-like peptides: role of basic residues in heparin-mediated aggregation.

Glycosaminoglycans (GAGs) have been reported to play a significant role in amyloid formation of a wide range of proteins/peptides either associated with diseases or native biological functions. The exact mechanism by which GAGs influence amyloid formation is not clearly understood. Here, we studied two closely related peptides, glucagon-like peptide 1 (GLP1) and glucagon-like peptide 2 (GLP2), for their amyloid formation in the presence and absence of the representative GAG heparin using various biophysical and computational approaches. We show that the aggregation and amyloid formation by these peptides follow distinct mechanisms: GLP1 follows nucleation-dependent aggregation, whereas GLP2 forms amyloids without any significant lag time. Investigating the role of heparin, we also found that heparin interacts with GLP1, accelerates its aggregation, and gets incorporated within its amyloid fibrils. In contrast, heparin neither affects the aggregation kinetics of GLP2 nor gets embedded within its fibrils. Furthermore, we found that heparin preferentially influences the stability of the GLP1 fibrils over GLP2 fibrils. To understand the specific nature of the interaction of heparin with GLP1 and GLP2, we performed all-atom MD simulations. Our in silico results show that the basic-nonbasic-basic (B-X-B) motif of GLP1 (K28-G29-R30) facilitates the interaction between heparin and peptide monomers. However, the absence of such a motif in GLP2 could be the reason for a significantly lower strength of interaction between GLP2 and heparin. Our study not only helps to understand the role of heparin in inducing protein aggregation but also provides insight into the nature of heparin-protein interaction.

Molecular interpretation of ACTH-ß-endorphin coaggregation: relevance to secretory granule biogenesis.

Peptide/protein hormones could be stored as non-toxic amyloid-like structures in pituitary secretory granules. ACTH and ß-endorphin are two of the important peptide hormones that get co-stored in the pituitary secretory granules. Here, we study molecular interactions between ACTH and ß-endorphin and their colocalization in the form of amyloid aggregates. Although ACTH is known to be a part of ACTH-ß-endorphin aggregate, ACTH alone cannot aggregate into amyloid under various plausible conditions. Using all atom molecular dynamics simulation we investigate the early molecular interaction events in the ACTH-ß-endorphin system, ß-endorphin-only system and ACTH-only system. We find that ß-endorphin and ACTH formed an interacting unit, whereas negligible interactions were observed between ACTH molecules in ACTH-only system. Our data suggest that ACTH is not only involved in interaction with ß-endorphin but also enhances the stability of mixed oligomers of the entire system.