Intrinsically Disordered Proteins Research Articles

Intrinsically disordered regions and RNA binding domains contribute to protein enrichment in biomolecular condensates in Xenopus oocytes.

Proteins containing both intrinsically disordered regions (IDRs) and RNA binding domains (RBDs) can phase separate in vitro, forming bodies similar to cellular biomolecular condensates. However, how IDR and RBD domains contribute to in vivo recruitment of proteins to biomolecular condensates remains poorly understood. Here, we analyzed the roles of IDRs and RBDs in L-bodies, biomolecular condensates present in Xenopus oocytes. We show that a cytoplasmic isoform of hnRNPAB, which contains two RBDs and an IDR, is highly enriched in L-bodies. While both of these domains contribute to hnRNPAB self-association and phase separation in vitro and mediate enrichment into L-bodies in oocytes, neither the RBDs nor the IDR replicate the localization of full-length hnRNPAB. Our results suggest a model where the combined effects of the IDR and RBDs regulate hnRNPAB partitioning into L-bodies. This model likely has widespread applications as proteins containing RBD and IDR domains are common biomolecular condensate residents.

Likely Overstabilization of Charge-Charge Interactions in CHARMM36m(w): A Case for a99SB-disp Water.

Recent years have witnessed drastic improvements in general-purpose explicit solvent protein force fields, partially driven by the need to study intrinsically disordered proteins (IDPs), and yet the state-of-the-art force fields such as CHARMM36m (c36m) and a99SB-disp still provide different performances in simulating disordered protein states, where c36m has a bias toward overcompaction for large IDPs. Here, we examine the performance of c36m and a99SB-disp in describing the stabilities of a set of 46 amino acid backbone and side chain pairs in various configurations. The free energy results show that c36m systematically predicts stronger interactions compared to a99SB-disp by an average of 0.2 kcal/mol for nonpolar pairs, 0.6 kcal/mol for polar pairs, and 0.8 kcal/mol for salt bridges. The most severe overstabilization in c36m is observed for charged pairs involving the Arg and Glu side chains by up to 2.9 kcal/mol. Importantly, the systematic overstabilization of c36m is only marginally alleviated by c36mw, an ad hoc patch to c36m that increases the dispersion interactions between TIP3P hydrogens and protein atoms. Guided by free energy decomposition, we evaluated if revising the charges alone could alleviate the severe overstabilization of salt bridges of c36m(w) vs a99SB-disp. The results suggested that the direct modification of protein-water interactions is also necessary. Toward this end, we proposed a tentative modification to c36m, referred to as c36mrb-disp, which combines modified Arg side chain charges, retuned backbone hydrogen bonding strength, and the a99SB-disp water model. The modified force field successfully reproduces the secondary structures of several intrinsically disordered peptides and proteins including (AAQAA)3, GB1p, and p53 transactivation domain, while maintaining the stability of a set of folded proteins. This work provides a set of useful systems for benchmarking and optimizing protein force fields and highlights the importance of balancing protein-protein and protein-water electrostatic interactions for accurately describing both folded and disordered proteins.

Direct and indirect salt effects on homotypic phase separation

The low-complexity domain of hnRNPA1 (A1-LCD) phase separates in a salt-dependent manner. Unlike many intrinsically disordered proteins (IDPs) whose phase separation is suppressed by increasing salt concentrations, the phase separation of A1-LCD is promoted by >100 mM NaCl. To investigate the atypical salt effect on A1-LCD phase separation, we carried out all-atom molecular dynamics simulations of systems comprising multiple A1-LCD chains at NaCl concentrations from 50 to 1000 mM NaCl. The ions occupy first shell as well as more distant sites around the IDP chains, with Arg sidechains and backbone carbonyls the favored partners of Cl– and Na+, respectively. They play two direct roles in driving A1-LCD condensation. The first is to neutralize the high net charge of the protein (+9) by an excess of bound Cl– over Na+; the second is to bridge between A1-LCD chains, thereby fortifying the intermolecular interaction networks in the dense phase. At high concentrations, NaCl also indirectly strengthens π–π, cation–π, and amino–π interactions, by drawing water away from the interaction partners. Therefore, at low salt, A1-LCD is prevented from phase separation by net charge repulsion; at intermediate concentrations, NaCl neutralizes enough of the net charge while also bridging IDP chains to drive phase separation. This drive becomes even stronger at high salt due to strengthened π-type interactions. Based on this understanding, four classes of salt dependence of IDP phase separation can be predicted from amino-acid composition.

Direct and indirect salt effects on homotypic phase separation.

The low-complexity domain of hnRNPA1 (A1-LCD) phase separates in a salt-dependent manner. Unlike many intrinsically disordered proteins (IDPs) whose phase separation is suppressed by increasing salt concentrations, the phase separation of A1-LCD is promoted by >100 mM NaCl. To investigate the atypical salt effect on A1-LCD phase separation, we carried out all-atom molecular dynamics simulations of systems comprising multiple A1-LCD chains at NaCl concentrations from 50 to 1000 mM NaCl. The ions occupy first shell as well as more distant sites around the IDP chains, with Arg sidechains and backbone carbonyls the favored partners of Cl- and Na+, respectively. They play two direct roles in driving A1-LCD condensation. The first is to neutralize the high net charge of the protein (+9) by an excess of bound Cl- over Na+; the second is to bridge between A1-LCD chains, thereby fortifying the intermolecular interaction networks in the dense phase. At high concentrations, NaCl also indirectly strengthens π-π, cation-π, and amino-π interactions, by drawing water away from the interaction partners. Therefore, at low salt, A1-LCD is prevented from phase separation by net charge repulsion; at intermediate concentrations, NaCl neutralizes enough of the net charge while also bridging IDP chains to drive phase separation. This drive becomes even stronger at high salt due to strengthened π-type interactions. Based on this understanding, four classes of salt dependence of IDP phase separation can be predicted from amino-acid composition.

The kinase NEK6 positively regulates LSD1 activity and accumulation in local chromatin sub-compartments

LSD1 plays a crucial role in mammalian biology, regulated through interactions with coregulators and post-translational modifications. Here we show that the kinase NEK6 stimulates LSD1 activity in cells and observe a strong colocalization of NEK6 and LSD1 at distinct chromatin sub-compartments (CSCs). We demonstrate that LSD1 is a substrate for NEK6 phosphorylation at the N-terminal intrinsically disordered region (IDR) of LSD1, which shows phase separation behavior in vitro and in cells. The LSD1-IDR is important for LSD1 activity and functions to co-compartmentalize NEK6, histone peptides and DNA. The subsequent phosphorylation of LSD1 by NEK6 supports the concentration of LSD1 at these distinct CSCs, which is imperative for dynamic control of transcription. This suggest that phase separation is crucial for the regulatory function of LSD1 and our findings highlight the role of NEK6 in modulating LSD1 activity and phase separation, expanding our understanding of LSD1 regulation and its implications in cellular processes.

Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning.

Predicting protein-small molecule binding sites, the initial step in structure-guided drug design, remains challenging for proteins lacking experimentally derived ligand-bound structures. Here, we propose CLAPE-SMB, which integrates a pre-trained protein language model with contrastive learning to provide high accuracy predictions of small molecule binding sites that can accommodate proteins without a published crystal structure. We trained and tested CLAPE-SMB on the SJC dataset, a non-redundant dataset based on sc-PDB, JOINED, and COACH420, and achieved an MCC of 0.529. We also compiled the UniProtSMB dataset, which merges sites from similar proteins based on raw data from UniProtKB database, and achieved an MCC of 0.699 on the test set. In addition, CLAPE-SMB achieved an MCC of 0.815 on our intrinsically disordered protein (IDP) dataset that contains 336 non-redundant sequences. Case studies of DAPK1, RebH, and Nep1 support the potential of this binding site prediction tool to aid in drug design. The code and datasets are freely available at https://github.com/JueWangTHU/CLAPE-SMB . SCIENTIFIC CONTRIBUTION: CLAPE-SMB combines a pre-trained protein language model with contrastive learning to accurately predict protein-small molecule binding sites, especially for proteins without experimental structures, such as IDPs. Trained across various datasets, this model shows strong adaptability, making it a valuable tool for advancing drug design and understanding protein-small molecule interactions.

SOP-MULTI: A Self-Organized Polymer-Based Coarse-Grained Model for Multidomain and Intrinsically Disordered Proteins with Conformation Ensemble Consistent with Experimental Scattering Data.

Multidomain proteins with long flexible linkers and full-length intrinsically disordered proteins (IDPs) are best defined as an ensemble of conformations rather than a single structure. Determining high-resolution ensemble structures of such proteins poses various challenges by using tools from experimental structural biophysics. Integrative approaches combining available low-resolution ensemble-averaged experimental data and in silico biomolecular reconstructions are now often used for the purpose. However, extensive Boltzmann weighted conformation sampling for large proteins, especially for ones where both the folded and disordered domains exist in the same polypeptide chain, remains a challenge. In this work, we present a 2-site per amino-acid resolution SOP-MULTI force field for simulating coarse-grained models of multidomain proteins. SOP-MULTI combines two well-established self-organized polymer models─: (i) SOP-SC models for folded systems and (ii) SOP-IDP for IDPs. For the SOP-MULTI, we introduce cross-interaction terms between the beads belonging to the folded and disordered regions to generate conformation ensembles for full-length multidomain proteins such as hnRNP A1, TDP-43, G3BP1, hGHR-ECD, TIA1, HIV-1 Gag, polyubiquitin, and FUS. When back-mapped to all-atom resolution, SOP-MULTI trajectories faithfully recapitulate the scattering data over the range of the reciprocal space. We also show that individual folded domains preserve native contacts with respect to solved folded structures, and root-mean-square fluctuations of residues in folded domains match those obtained from all-atom molecular dynamics simulation trajectories of the same folded systems. SOP-MULTI force field is made available as a LAMMPS-compatible user package along with setup codes for generating the required files for any full-length protein with folded and disordered regions.

Genetically Engineered Liposwitch-Based Nanomaterials.

Fusion of intrinsically disordered and globular proteins is a powerful strategy to create functional nanomaterials. However, the immutable nature of genetic encoding restricts the dynamic adaptability of nanostructures postexpression. To address this, we envisioned using a myristoyl switch, a protein that combines allostery and post-translational modifications─two strategies that modify protein properties without altering their sequence─to regulate intrinsically disordered protein (IDP)-driven nanoassembly. A typical myristoyl switch, allosterically activated by a stimulus, reveals a sequestered lipid for membrane association. We hypothesize that this conditional exposure of lipids can regulate the assembly of fusion proteins, a concept we term "liposwitching". We tested this by fusing recoverin, a calcium-dependent myristoyl switch, with elastin-like polypeptide, a thermoresponsive model IDP. Biophysical analyses confirmed recoverin's myristoyl-switch functionality, while dynamic light scattering and cryo-transmission electron microscopy showed distinct calcium- and lipidation-dependent phase separation and assembly. This study highlights liposwitching as a viable strategy for controlling DP-driven nanoassembly, enabling applications in synthetic biology and cellular engineering.

The landscape of intrinsically disordered proteins in Leishmania parasite: Implications for drug discovery

Proteins that lack three-dimensional structures are known as Intrinsically disordered proteins (IDPs). In this study, we aimed to identify intrinsically disordered proteins in the Leishmania donovani proteome using various predictors that can identify IDPs based on amino acid residues and charge hydropathy. Top identified IDPs are analyzed using STRING, PSP-Hunter, Deep Loc-2.0, and Alpha fold to understand the protein-protein interaction, phase separation, localization, and structural assessment of those proteins. From this study, we found that >50 % of Leishmania donovani proteome has proteins or regions of proteins that are intrinsically disordered with VSL2 score >0.5; most proteins interact with many other proteins with PPI enrichment p-value <1.0e-16. Few proteins, such as Protein phosphatase inhibitor, UMSBP, and Zinc knuckle, have redox-sensitive regions. Functional disorder profiles of identified IDPs showed MoRFs and predicted protein domains. HASPB, UTP11, Nucleolar protein 12, and UMSBP have a high probability of undergoing phase separation. Localization studies showed that most of these proteins are in the cytoplasm and nucleus. Our present study of identifying IDPs in Leishmania proteome yields significant information on druggable targets and can serve as a basis for further studies to identify unexplored pathways.

The dual life of disordered lysine-rich domains of snoRNPs in rRNA modification and nucleolar compaction

Intrinsically disordered regions (IDRs) are highly enriched in the nucleolar proteome but their physiological role in ribosome assembly remains poorly understood. Our study reveals the functional plasticity of the extremely abundant lysine-rich IDRs of small nucleolar ribonucleoprotein particles (snoRNPs) from protists to mammalian cells. We show in Saccharomyces cerevisiae that the electrostatic properties of this lysine-rich IDR, the KKE/D domain, promote snoRNP accumulation in the vicinity of nascent rRNAs, facilitating their modification. Under stress conditions reducing the rate of ribosome assembly, they are essential for nucleolar compaction and sequestration of key early-acting ribosome biogenesis factors, including RNA polymerase I, owing to their self-interaction capacity in a latent, non-rRNA-associated state. We propose that such functional plasticity of these lysine-rich IDRs may represent an ancestral eukaryotic regulatory mechanism, explaining how nucleolar morphology is continuously adapted to rRNA production levels.

Predicting the sequence-dependent backbone dynamics of intrinsically disordered proteins.

How the sequences of intrinsically disordered proteins (IDPs) code for functions is still an enigma. Dynamics, in particular residue-specific dynamics, holds crucial clues. Enormous efforts have been spent to characterize residue-specific dynamics of IDPs, mainly through NMR spin relaxation experiments. Here, we present a sequence-based method, SeqDYN, for predicting residue-specific backbone dynamics of IDPs. SeqDYN employs a mathematical model with 21 parameters: one is a correlation length and 20 are the contributions of the amino acids to slow dynamics. Training on a set of 45 IDPs reveals aromatic, Arg, and long-branched aliphatic amino acids as the most active in slow dynamics whereas Gly and short polar amino acids as the least active. SeqDYN predictions not only provide an accurate and insightful characterization of sequence-dependent IDP dynamics but may also serve as indicators in a host of biophysical processes, including the propensities of IDP sequences to undergo phase separation.

Predicting the sequence-dependent backbone dynamics of intrinsically disordered proteins

How the sequences of intrinsically disordered proteins (IDPs) code for functions is still an enigma. Dynamics, in particular residue-specific dynamics, holds crucial clues. Enormous efforts have been spent to characterize residue-specific dynamics of IDPs, mainly through NMR spin relaxation experiments. Here, we present a sequence-based method, SeqDYN, for predicting residue-specific backbone dynamics of IDPs. SeqDYN employs a mathematical model with 21 parameters: one is a correlation length and 20 are the contributions of the amino acids to slow dynamics. Training on a set of 45 IDPs reveals aromatic, Arg, and long-branched aliphatic amino acids as the most active in slow dynamics whereas Gly and short polar amino acids as the least active. SeqDYN predictions not only provide an accurate and insightful characterization of sequence-dependent IDP dynamics but may also serve as indicators in a host of biophysical processes, including the propensities of IDP sequences to undergo phase separation.

Phosphorylation in the Plasmodium falciparum Proteome: A Meta-Analysis of Publicly Available Data Sets.

Malaria is a deadly disease caused by Apicomplexan parasites of the Plasmodium genus. Several species of the Plasmodium genus are known to be infectious to humans, of which P. falciparum is the most virulent. Post-translational modifications (PTMs) of proteins coordinate cell signaling and hence regulate many biological processes in P. falciparum homeostasis and host infection, of which the most highly studied is phosphorylation. Phosphosites on proteins can be identified by tandem mass spectrometry (MS) performed on enriched samples (phosphoproteomics), followed by downstream computational analyses. We have performed a large-scale meta-analysis of 11 publicly available phosphoproteomics data sets to build a comprehensive atlas of phosphosites in the P. falciparum proteome, using robust pipelines aimed at strict control of false identifications. We identified a total of 26,609 phosphorylated sites on P. falciparum proteins, split across three categories of data reliability (gold/silver/bronze). We identified significant sequence motifs, likely indicative of different groups of kinases responsible for different groups of phosphosites. Conservation analysis identified clusters of phosphoproteins that are highly conserved and others that are evolving faster within the Plasmodium genus, and implicated in different pathways. We were also able to identify over 180,000 phosphosites within Plasmodium species beyond falciparum, based on orthologue mapping. We also explored the structural context of phosphosites, identifying a strong enrichment for phosphosites on fast-evolving (low conservation) intrinsically disordered regions (IDRs) of proteins. In other species, IDRs have been shown to have an important role in modulating protein-protein interactions, particularly in signaling, and thus warranting further study for their roles in host-pathogen interactions. All data have been made available via UniProtKB, PRIDE, and PeptideAtlas, with visualization interfaces for exploring phosphosites in the context of other data on Plasmodium proteins.

Systematic Evaluation and Application of IDR Domain-Mediated Transcriptional Activation of NUP98 in Saccharomyces cerevisiae.

Implementing dynamic control over gene transcription to decouple cell growth is essential for regulating protein expression in microbial cells. However, the availability of efficient regulatory elements in Saccharomyces cerevisiae remains limited. In this study, we present a novel β-estradiol-inducible gene expression system, termed DEN. This system combines a DNA-binding domain with an estradiol-binding domain and an intrinsically disordered region (IDR) from NUP98. Comparative analysis shows that the DEN system outperforms IDRs from other proteins, achieving an approximately 60-fold increase in EGFP expression upon β-estradiol induction. Moreover, our system is tightly controlled; nontoxic gene expression makes it a powerful tool for rapid and precise modulation of target gene expression. This system holds great potential for unlocking new functionalities from existing proteins in future research.

MOBIDB in 2025: integrating ensemble properties and function annotations for intrinsically disordered proteins.

The MobiDB database (URL: https://mobidb.org/) aims to provide structural and functional information about intrinsic protein disorder, aggregating annotations from the literature, experimental data, and predictions for all known protein sequences. Here, we describe the improvements made to our resource to capture more information, simplify access to the aggregated data, and increase documentation of all MobiDB features. Compared to the previous release, all underlying pipeline modules were updated. The prediction module is ten times faster and can detect if a predicted disordered region is structurally extended or compact. The PDB component is now able to process large cryo-EM structures extending the number of processed entries. The entry page has been restyled to highlight functional aspects of disorder and all graphical modules have been completely reimplemented for better flexibility and faster rendering. The server has been improved to optimise bulk downloads. Annotation provenance has been standardised by adopting ECO terms. Finally, we propagated disorder function (IDPO and GO terms) from the DisProt database exploiting sequence similarity and protein embeddings. These improvements, along with the addition of comprehensive training material, offer a more intuitive interface and novel functional knowledge about intrinsic disorder.

Landscape of intrinsically disordered proteins in mental disorder diseases

Disrupted genes linked to mental disorders sometimes exhibit characteristics of Intrinsically Disordered Proteins (IDPs). However, few studies have comprehensively explored the functional associations between protein disorder properties and different psychiatric disorders. In this study, we collected disrupted proteins for seven mental diseases (MDD, SCZ, BP, ID, AD, ADHD, ASD) and a control dataset from normal brains. After calculating the disorder scores for each protein, we thoroughly compared the proportions and functions of IDPs between differentially expressed proteins in each disease and healthy controls.Our findings revealed that disrupted proteins, particularly in ASD and ADHD, contain more IDPs than controls from normal brains. Distinct patterns in disorder properties were observed among different mental disorders. Functional enrichment analysis indicated that IDPs in mental disorders were associated with neurodevelopment, synaptic signaling, and gene expression regulatory pathways. In addition, we analyzed the proportion and function of liquid-phase-separated proteins (LLPS) in psychiatric disorders, finding that LLPS proteins are mainly enriched in pathways related to neurodevelopment and inter-synaptic signaling. Furthermore, to validate our findings, we conducted an analysis of differentially expressed genes in an ASD cohort, revealing that the encoded proteins also exhibit a higher proportion of IDPs. Notably, these IDPs were particularly enriched in pathways related to neurodevelopment, including head development, a process known to be disrupted in ASD.Our study sheds light on the crucial role of IDPs in psychiatric disorders, enhancing our understanding of their molecular mechanisms.

Comparison of Methodologies for Absolute Binding Free Energy Calculations of Ligands to Intrinsically Disordered Proteins.

Modulating the function of Intrinsically Disordered Proteins (IDPs) with small molecules is of considerable importance given the crucial roles of IDPs in the pathophysiology of numerous diseases. Reported binding affinities for ligands to diverse IDPs vary broadly, and little is known about the detailed molecular mechanisms that underpin ligand efficacy. Molecular simulations of IDP ligand binding mechanisms can help us understand the mode of action of small molecule inhibitors of IDP function, but it is still unclear how binding energies can be modeled rigorously for such a flexible class of proteins. Here, we compare alchemical absolute binding free energy calculations (ABFE) and Markov-State Modeling (MSM) protocols to model the binding of the small molecule 10058-F4 to a disordered peptide extracted from a segment of the oncoprotein c-Myc. The ABFE results produce binding energy estimates that are sensitive to the choice of reference structure. In contrast, the MSM results produce more reproducible binding energy estimates consistent with weak mM binding affinities and transient intermolecular contacts reported in the literature.

How Salt and Temperature Drive Reentrant Condensation of Aβ40.

Within the framework of liquid-liquid phase separation (LLPS), biomolecular condensation orchestrates vital cellular processes, and its dysregulation is implicated in severe pathological conditions. Recent studies highlight the role of intrinsically disordered proteins (IDPs) in LLPS, yet the influence of microenvironmental factors has remained a puzzling factor. Here, via computational simulation of the impact of solution conditions on LLPS behavior of neurologically pathogenic IDP Aβ40, we chanced upon a salt-driven reentrant condensation phenomenon, wherein Aβ40 aggregation increases with low salt concentrations (25-50 mM), followed by a decline with further salt increments. An exploration of the thermodynamic and kinetic signatures of reentrant condensation unveils a nuanced interplay between protein electrostatics and ionic strength as potential drivers. Notably, the charged residues of the N-terminus exhibit a nonmonotonic response to salt screening, intricately linked to the recurrence of reentrant behavior in hydrophobic core-induced condensation. Intriguingly, our findings also unveil the reappearance of similar reentrant condensation phenomena under varying temperature conditions. Collectively, our study illuminates the profoundly context-dependent nature of Aβ40s liquid-liquid phase separation behavior, extending beyond its intrinsic molecular framework, where microenvironmental cues wield significant influence over its aberrant functionality.

Intrinsically disordered region amplifies membrane remodeling to augment selective ER-phagy

Intrinsically disordered regions (IDRs) play a pivotal role in organellar remodeling. They transduce signals across membranes, scaffold signaling complexes, and mediate vesicular traffic. Their functions are regulated by constraining conformational ensembles through specific intra- and intermolecular interactions, physical tethering, and posttranslational modifications. The endoplasmic reticulum (ER)-phagy receptor FAM134B/RETREG1, known for its reticulon homology domain (RHD), includes a substantial C-terminal IDR housing the LC3 interacting motif. Beyond engaging the autophagic machinery, the function of the FAM134B-IDR is unclear. Here, we investigate the characteristics of the FAM134B-IDR by extensive modeling and molecular dynamics simulations. We present detailed structural models for the IDR, mapping its conformational landscape in solution and membrane-anchored configurations. Our analysis reveals that depending on the membrane anchor, the IDRs collapse onto the membrane and induce positive membrane curvature to varying degrees. The charge patterns underlying this Janus-like behavior are conserved across other ER-phagy receptors. We found that IDRs alone are sufficient to sense curvature. When combined with RHDs, they intensify membrane remodeling and drive efficient protein clustering, leading to faster budding, thereby amplifying RHD remodeling functions. Our simulations provide a perspective on IDRs of FAM134B, their Janus-like membrane interactions, and the resulting modulatory functions during large-scale ER remodeling.

Synapsin condensation is governed by sequence-encoded molecular grammars.

Multiple biomolecular condensates coexist at the pre- and post- synapse to enable vesicle dynamics and controlled neurotransmitter release in the brain. In pre-synapses, intrinsically disordered regions (IDRs) of synaptic proteins are drivers of condensation that enable clustering of synaptic vesicles (SVs). Using computational analysis, we show that the IDRs of SV proteins feature evolutionarily conserved non-random compositional biases and sequence patterns. Synapsin-1 is essential for condensation of SVs, and its C-terminal IDR has been shown to be a key driver of condensation. Focusing on this IDR, we dissected the contributions of two conserved features namely the segregation of polar and proline residues along the linear sequence, and the compositional preference for arginine over lysine. Scrambling the blocks of polar and proline residues weakens the driving forces for forming micron-scale condensates. However, the extent of clustering in subsaturated solutions remains equivalent to that of the wild-type synapsin-1. In contrast, substituting arginine with lysine significantly weakens both the driving forces for condensation and the extent of clustering in subsaturated solutions. Co-expression of the scrambled variant of synapsin-1 with synaptophysin results in a gain-of-function phenotype in cells, whereas arginine to lysine substitutions eliminate condensation. We report an emergent consequence of synapsin-1 condensation, which is the generation of interphase pH gradients realized via differential partitioning of protons between coexisting phases. This pH gradient is likely to be directly relevant for vesicular ATPase functions and the loading of neurotransmitters. Our study highlights how conserved IDR grammars serve as drivers of synapsin-1 condensation.