Biology subjects

Joseph, J. A.

Publications and source records attributed to Joseph, J. A..

At least 19 recordsLinked to original sources

bioRxiv2026

Non-equilibrium modeling of directed flux through biomolecular condensates

Cellular biomolecular condensates function far from equilibrium, sustained by continuous influx and efflux of molecular components. Notable examples include the nucleolus, nuclear pore complex, P-bodies, and stress granules, in which regulated molecular transport is essential for their function. Experimental characterization of molecular flux remains challenging due to limitations in spatiotemporal resolution, making computational approaches a powerful alternative for systematic investigation. Here, we present a computational approach (TRACE) to model molecular transport through biomolecular condensates under non-equilibrium steady-state conditions at near-atomistic resolution. Using TRACE, we systematically probe physicochemical factors that govern molecular flux through condensates. We find that protein sequence composition and patterning determine the internal structure of the condensates, which strongly influences molecular transport efficiency. Our work also suggests that molecular flux through condensates exhibits reptation dynamics. Moreover, interactions between fluxing molecules and condensates play a critical role in regulating transport. In particular, associative interactions enable a handoff mechanism, in which successive transient interactions facilitate directed transport through condensates. Together, these results help advance our understanding on how molecular flux is regulated in biomolecular condensates and provide a basis for rationally tuning condensate-mediated molecular flux, with potential applications in therapeutics and active soft material design.

biophysics↗

bioRxiv2026

Biomolecular Condensates Dictate the Folding Landscape of Proteins

Protein structure is exquisitely sensitive to the surrounding chemical environment, and many proteins encounter complex environments within cells. Importantly, numerous proteins organize into biomolecular condensates--dense macromolecular assemblies with distinct physicochemical properties. This raises a fundamental question: how does condensation reshape protein structure and dynamics? Here, we investigate how protein folding landscapes are altered inside condensates, using the protein -helix as a model folded domain. Atomistic simulations show that free energy surfaces within condensates differ markedly from those in dilute solution or in the presence of inert crowders. We then use Bayesian optimization to develop a chemically specific, near-atomistic model for quantification of -helical folding and apply it to characterize diverse helices, including -helical domains from the disease-associated proteins TDP43, Annexin A11, and the Androgen Receptor, within condensates of varying physicochemical properties. Our results support a framework in which multivalent interactions drive unfolding while crowding promotes folding, and protein conformational ensembles inside condensates emerge from this balance. Additionally, we show that folding transitions are kinetically frustrated inside condensates because they are coupled to the timescale of contact rearrangement with co-condensate proteins. As such, folding landscapes within condensates are dually sequence-dependent, informed by both the sequence of the folded domain and co-condensate proteins. Together, our work has implications for understanding condensate-mediated proteinopathies, targeting aberrant condensates, and designing condensates to program protein function across scales.

biophysics↗

bioRxiv2025

Molecular basis for thermoresponsive protein condensation in plants

Plants continuously experience temperature fluctuations that shape their physiology, development, and survival. Yet, how plants sense and adapt to elevated temperatures at the molecular level remains only partially understood. Here, we uncover a sequence-encoded mechanism by which plant proteins directly sense temperature through phase separation. Focusing on prion-like low-complexity domains (PLCDs) in Arabidopsis thaliana, we combine cellular imaging, quantitative biophysics, and coarse-grained molecular dynamics simulations to show that numerous PLCDs undergo reversible lower critical solution temperature (LCST)-type transitions. We find that PLCDs that are sufficient and necessary for phase separation confer thermoresponsive variability to full-length proteins. Sequence analysis and simulations reveal that thermoresponsiveness is encoded in compositional heuristics, with sufficient PLCDs enriched in aliphatic and aromatic residues, enabling accurate prediction and rational tuning of condensation thresholds. Engineered variants with altered sequence composition exhibit predictable shifts in thermoresponsive behavior, confirming a direct, sequence-level encoding of temperature sensitivity. Our findings establish LCST-driven phase separation as a fundamental mechanism of thermoresponsiveness in plants and provide a molecular framework for designing synthetic biomolecules with programmable temperature responses.

biophysics↗

bioRxiv2025

Structural insights into xyloglucan recognition by an ABC transporter from a Gram-positive, thermophilic bacterium

Xyloglucan (an -1,6-xylosyl-substituted {beta}-1,4-glucan) is a major hemicellulose of the primary cell wall of many plants and an important growth substrate for biomass-degrading bacteria in diverse ecological niches, including the gut microbiome and hot springs. In Gram-positive bacteria, xyloglucan is deconstructed into soluble oligosaccharides in the extracytoplasmic space before import by ATP-Binding Cassette (ABC) transporters, but the structural basis for this process remains poorly understood. Here, we identified an ABC transporter for xyloglucan uptake (Athe_2052-2054) in the Gram-positive, plant biomass-degrading thermophile Anaerocellum bescii, which is conserved across the Anaerocellum genus. We solved the apo crystal structure of its extracellular substrate-binding protein (SBP), Athe_2052, revealing a unique tertiary fold found only in a small subset of SBPs that bind complex oligosaccharides. This structure represents the first ABC SBP known to bind xyloglucan oligosaccharides. Biophysical analysis showed that while Athe_2052 binds unsubstituted {beta}-glucan chains, recognition of xyloglucan side chains in the binding pocket markedly increases affinity (Kd = 14 nM) for xyloglucan heptasaccharide (XXXG), the principal oligosaccharide released during xyloglucan deconstruction. Molecular modeling revealed that xyloglucan heptasaccharide, owing to its branched substitutions, is bound in a distinct conformation compared to unsubstituted {beta}-glucans. This represents a unique mode of xyloglucan recognition driven by -linked side-chain interactions rather than {beta}-glucan backbone recognition alone. Together, these findings provide the first structural basis for xyloglucan oligosaccharide recognition by an ABC transporter in Gram-positive bacteria.

molecular biology↗

bioRxiv2025

Biomolecular condensate viscoelasticity is dictated by the interplay between single-molecule shape memory and mesh reconfigurability

Biomolecular condensates are membraneless organelles that compartmentalize biological functions in living cells. Formed by the phase separation of biomolecules, condensates possess a wide range of mechanical responses. However, how condensate viscoelastic responses are encoded in the chemistries of their constituents--such as intrinsically disordered proteins (IDPs)--are not well understood. Here, we employ molecular dynamics simulations to connect measurable condensate viscoelasticity to the architectural heterogeneity and dynamic reconfigurability of associative networks formed by IDPs. Using a residue-resolution coarse-grained model, we characterize biologically relevant and synthetic condensates, demonstrating that their temperature sensitivity of elasticity is sequence dependent and modeled by exponential scaling laws. We interrogate condensate mesh heterogeneity via entanglement spacing, finding that entropy-driven structural heterogeneity and reduced IDP hydrophobicity favor condensate elasticity. Furthermore, we construct graph-theoretical representations of condensates and find that interaction network topologies with an abundance of redundant node pathways translates to more load-bearing paths for mechanical stress storage. Strikingly, we discover that elastic coupling of IDPs within condensates emerges when single-molecule shape memory timescales approach meshwork reconfiguration timescales. Akin to a condensate Deborah number, this interplay of timescales for molecular and microstructural processes dictates how restoring elastic forces propagate and are stored across IDP networks; linking condensate microstructure dynamics directly to mechanical responses. Taken together, our work provides a conceptual framework of how condensates act as stress-responsive biomaterials; helping illuminate how cells exploit condensate mechanics to sense and regulate their internal environment and opening avenues for the design of condensates with programmable material properties. SIGNIFICANCEBiomolecular condensates are soft materials that exhibit diverse viscoelastic responses. We show how microstructure dynamics dictate condensate mechanics by probing the heterogeneity of local structures and how their connectivity and persistence store elastic stress. Strikingly, we discover that the ratio of timescales of single-protein shape memory to that of the underlying network rearrangement is a robust indicator of whether a condensate is dominantly viscous or elastic. This finding makes condensate mechanics predictable from sequence-dependent "Deborah numbers," which are experimentally accessible. Our work therefore provides a tangible framework for understanding condensate stress dissipation mechanisms and opens opportunities for designing condensates with programmable material properties.

biophysics↗

bioRxiv2025

Interaction networks within biomolecular condensates feature topological cliques near the interface

Biomolecular condensates, including those formed by prion-like low complexity domains (LCDs) of proteins, are typically maintained by networks of molecular interactions. Such collective interactions give rise to the rich array of material behaviors underlying condensate function. Previous work has uncovered distinct LCD conformations in condensates versus dilute phases, and recently, single-component LCD condensates have been predicted to exhibit microstructures with "small-world" networks--where molecular nodes are highly clustered and connected via short pathlengths. However, a framework linking single-molecule properties, condensate microstructure, and macroscopic material properties remains elusive. Here, we combine molecular simulation and graph-theoretic analysis to reveal how molecular features encode condensate microstructure, which impacts molecule-scale conformations and droplet-scale material properties. Using a residue-resolution coarse-grained model, we probe condensates comprising natural LCD sequences and generalize our findings by varying composition and patterning in binary sequences of hydrophobic and polar residues. We show that non-blocky sequences form condensates with small-world internal networks featuring "hubs"--molecules responsible for global connectivity--and "cliques", molecular clusters bound by persistent short-ranged associations. Cliques localize near interfaces without a secondary phase transition, suggesting a role in mediating molecular partitioning and condensate aging by tuning interfacial material properties. Moreover, we demonstrate that network smallworldness predicts droplet surface tension. We also track single-molecule structure and dynamics inside condensates, revealing that internal heterogeneity at the single-molecule level is systematically encoded by network topology. Collectively, our work establishes multiscale structure-property relationships in LCD condensates, providing general principles for designing and interpreting condensates with complex internal organization and material properties.

biophysics↗

bioRxiv2025

Prediction of small-molecule partitioning into biomolecular condensates from simulation

Predicting small-molecule partitioning into biomolecular condensates is key to developing drugs that selectively target aberrant condensates. However, the molecular mechanisms underlying small-molecule partitioning remain largely unknown. Here, we first exploit atomistic molecular dynamics simulations of model condensates to elucidate physicochemical rules governing small-molecule partitioning. We find that while hydrophobicity is a major determinant, solubility becomes a stronger regulator of partitioning in more polar condensates. Additionally, more polar condensates exhibit selectivity toward certain compounds, suggesting that condensate-specific therapeutics can be engineered. Building on these insights, we develop minimal models (MAPPS) for efficient prediction of small-molecule partitioning into biologically relevant condensates. We demonstrate that this approach reproduces atomistic partition co-efficients in both model systems and condensates composed of the low complexity domain (LCD) of FUS. Applying MAPPS to various LCD-based condensates shows that protein sequence can exert a selective pressure, thereby influencing small-molecule partitioning. Collectively, our findings reveal that partitioning is driven by both small-molecule-protein affinity and the complex interplay between the compounds and the condensate chemical environment.

biophysics↗

bioRxiv2025

Accurate prediction of thermoresponsive phase behavior of disordered proteins

Protein responses to environmental stress, particularly temperature fluctuations, have long been a subject of investigation, with a focus on how proteins maintain homeostasis and exhibit thermoresponsive properties. While UCST-type (upper critical solution temperature) phase behavior has been studied extensively and can now be predicted reliably using computational models, LCST-type (lower critical solution temperature) phase transitions remain less explored, with a lack of computational models capable of accurate prediction. This gap limits our ability to probe fully how proteins undergo phase transitions in response to temperature changes. Here, we introduce Mpipi-T, a residue-level coarse-grained model designed to predict LCST-type phase behavior of proteins. Parametrized using both atomistic simulations and experimental data, Mpipi-T accounts for entropically driven protein phase separation that occurs upon heating. Accordingly, Mpipi-T predicts temperature-driven protein behavior quantitatively in both single- and multi-chain systems. Beyond its predictive capabilities, we demonstrate that Mpipi-T provides a framework for uncovering the molecular mechanisms underlying heat stress responses, offering new insights into how proteins sense and adapt to thermal changes in biological systems.

biophysics↗

bioRxiv2025

The Critical Role of the 2'-OH group in Phase Separation and Percolation Transitions of RNA

Mg2+ ion-dependent RNA liquid-liquid phase separation with lower critical solution temperatures is driven by the phosphate backbone and modulated by the solvation property of nucleobases. Here, we report a key role of the 2-OH group of the ribose sugar in RNA condensation in the presence of divalent cations. We show that 2-deoxyribose inhibits nucleic acid phase separation and suppresses the intra-condensate networking transition, known as percolation, that underlies condensate dynamical arrest. All-atom simulations reveal increased solvation and compaction of single-stranded DNA compared to RNA, suggesting an unintuitive role of chain flexibility in modulating heat-induced nucleic acid phase separation and percolation transitions. Further, 2-O-methylation (2-O-Me) of RNA, a common sugar modification, lowers the driving force of RNA phase transitions. These results highlight the diverse physicochemical parameters governing nucleic acid phase behavior and suggest how sugar modifications may have evolved to robustly tune the formation and dynamical arrest of RNA condensates.

biophysics↗

bioRxiv2025

A Highly Conserved ABC Transporter Mediates Cello-Oligosaccharide Uptake in the Extremely Thermophilic, Lignocellulolytic Bacterium Anaerocellum (f. Caldicellulosiruptor) bescii

Cellulose deconstruction and utilization are key to unlocking renewable fuel and chemical production. Anaerocellum bescii (formerly Caldicellulosiruptor bescii) is an extremely thermophilic cellulolytic bacterium, among the most effective at degrading lignocellulosic biomass due to its arsenal of multi-domain cellulases and hemicellulases. However, little is known about how it transports the assorted sugars released from lignocellulose degradation into the cell for catabolism. Among its twenty-three ATP-Binding Cassette (ABC) sugar transporters, the mechanism for uptake of cello-oligosaccharides released from cellulose degradation remains unclear. Here, we identify an ABC transporter locus (Athe_0595 -- 0598), highly conserved in the genus with two extracellular binding proteins, Athe_0597 and Athe_0598. Biophysical analyses, including Differential Scanning Calorimetry (DSC) and Isothermal Titration Calorimetry (ITC), reveal that Athe_0597, binds cello-oligosaccharides of varying lengths (G2-5), while Athe_0598 is specific to cellobiose (G2). Computational modeling of ligand docking supports these findings and sheds light on the subsite configuration of the substrate binding proteins. To assess its physiological importance, we genetically deleted this transporter locus in A. bescii strain HTAB187, which does not grow on cellulose and grows poorly on cellobiose. Comparison of growth with a msmK deletion strain that cannot consume oligosaccharides shows that HTAB187 can grow on non-cello-oligosaccharides (e.g. maltose) or monosaccharides. Taken together, this study integrates biophysical characterization, structural modeling, and genetic perturbation to elucidate how A. bescii transports cello-oligosaccharides release from cellulose, opening doors for its future use in applied bioprocessing contexts. ImportanceAnaerocellum bescii is the most thermophilic cellulolytic bacterium known, and holds potential for bioprocessing lignocellulosic biomass into renewable fuels. Its diverse ATP-Binding Cassette (ABC) sugar transporters make it a valuable model for studying thermophilic sugar uptake. Here, we identify a single ABC transporter with two substrate binding proteins (Athe_0597 and Athe_0598) responsible for cello-oligosaccharide uptake. Genetic deletion of this transporter impaired growth on cellobiose and eliminated growth on cellulose. This is the first genetic manipulation in A. bescii to modulate transport of a specific sugar. We also characterize the substrate specificity of the substrate binding proteins associated with the locus; one binds various cellodextrins (G2-5), while the other specifically binds cellobiose (G2). Computational modeling reveals how each sugar docks within the binding pocket of these proteins. Understanding the mechanism of cello-oligosaccharide uptake by A. bescii expands opportunities for its metabolic engineering and furthers our understanding of thermophilic sugar transport.

microbiology↗

bioRxiv2024

Maltodextrin Transport in the Extremely Thermophilic, Lignocellulose Degrading Bacterium Anaerocellum bescii (f. Caldicellulosiruptor bescii)

Sugar transport into microbial cells is a critical, yet understudied step in the conversion of lignocellulosic biomass to metabolic products. Anaerocellum bescii (formerly Caldicellulosiruptor bescii) is an extremely thermophilic, anaerobic bacterium that readily degrades the cellulose and hemicellulose components of lignocellulosic biomass into a diversity of oligosaccharide substrates. Despite significant understanding of how this microorganism degrades lignocellulose, the mechanisms underlying its highly efficient transport of the resulting oligosaccharides into the cell are comparatively underexplored. Here, we identify and characterize the ATP-Binding Cassette (ABC) transporters in A. bescii governing maltodextrin transport. Utilizing past transcriptomic studies on Anaerocellum and Caldicellulosiruptor species, we identify two maltodextrin transporters in A. bescii and express and purify their substrate-binding proteins (Athe_2310 and Athe_2574) for characterization. Using differential scanning calorimetry and isothermal titration calorimetry, we show that Athe_2310 strongly interacts with shorter maltodextrins such as maltose and trehalose with dissociation constants in the micromolar range, while Athe_2574 binds longer maltodextrins, with dissociation constants in the sub-micro molar range. Using a sequence-structure-function comparison approach combined with molecular modeling we provide context for the specificity of each of these substrate-binding proteins. We propose that A. bescii utilizes orthogonal ABC transporters to uptake malto-oligosaccharides of different lengths to maximize transport efficiency. ImportanceHere, we reveal the biophysical and structural basis for oligosaccharide transport by two maltodextrin ABC transporters in A. bescii. This is the first biophysical characterization of carbohydrate uptake in this organism and establishes a workflow for characterizing other oligosaccharide transporters in A. bescii and similar lignocellulosic thermophiles of interest for lignocellulosic bioprocessing. By deciphering the mechanisms underlying high affinity sugar uptake in A. bescii, we shed light on an underexplored step between extracellular lignocellulose degradation and intracellular conversion of sugars to metabolic products. This understanding will expand opportunities for harnessing sugar transport in thermophiles to reshape lignocellulose bioprocessing as part of a renewable bioeconomy.

biophysics↗

bioRxiv2024

Tandem-repeat proteins introduce tuneable properties to engineered biomolecular condensates

The cells ability to rapidly partition biomolecules into biomolecular condensates is linked to a diverse range of cellular functions. Understanding how the structural attributes of biomolecular condensates are linked with their biological roles can be facilitated by the development synthetic condensate systems that can be manipulated in a controllable and predictable way. Here, we design and characterise a tuneable synthetic biomolecular condensate platform fusing modular consensus-designed tetratricopeptide repeat (CTPR) proteins to intrinsically-disordered domains. Trends between the CTPR structural attributes and condensate propensity were recapitulated across different experimental conditions and by in silico modelling, demonstrating that the CTPR domain can systematically affect the condensates in a predictable manner. Moreover, we show that incorporating short binding motifs into the CTPR domain results in specific target-protein recruitment into the condensates. Our model system can be rationally designed in a versatile manner to both tune condensate propensity and endow the condensates with new functions.

biophysics↗

bioRxiv2023

Accelerated simulations of RNA phase separation:a systematic study of non-redundant tandem repeats

Under certain conditions, RNA repeat sequences phase separate yielding protein-free biomolecular condensates. Importantly, RNA repeat sequences have also been implicated in neurological disorders, such as Huntingtons Disease. Thus, mapping repeat sequences to their phase behavior, functions, and dysfunctions is an active area of research. However, despite several advances, it remains challenging to characterize the RNA phase behavior at submolecular resolution. Here, we have implemented a residue-resolution coarse-grained model in LAMMPS - that incorporates both RNA sequence and structure - to study the clustering propensities of protein-free RNA systems. Importantly, we achieve multifold speedup in the simulation time compared to previous work. Leveraging this efficiency, we study the clustering propensity of all 20 non-redundant trinucleotide repeat sequences. Our results align with findings from experiments, emphasizing that canonical base pairing and G-U wobble pairs play a dominant role in regulating cluster formation of RNA repeat sequences. Strikingly, we find strong entropic contributions to the stability and composition of RNA clusters, which is demonstrated for single-component RNA systems, as well as binary mixtures of trinucleotide repeats. Additionally, we investigate clustering behaviors of trinucleotide (odd) repeats and their quadranucleotide (even) counterparts. We observe that odd repeats exhibit stronger clustering tendencies, attributed to the presence of consecutive base pairs in their sequences that are disrupted in even repeat sequences. Altogether, our work extends the set of computational tools for probing RNA cluster formation at submolecular resolution and uncovers physicochemical principles that govern the stability and composition of resulting clusters.

biophysics↗

bioRxiv2023

Universal predictive scaling laws of phase separation of prion-like low complexity domains

Proteins containing prion-like low complexity domains (PLDs) are common drivers of the formation of biomolecular condensates and are prone to misregulation due to amino acid mutations. Here, we exploit the accuracy of our residue-resolution coarse-grained model, Mpipi, to quantify the impact of amino acid mutations on the stability of 140 PLD mutants from six proteins (hnRNPA1, TDP43, FUS, EWSR1, RBM14, and TIA1). Our simulations reveal the existence of scaling laws that quantify the range of change in the critical solution temperature of PLDs as a function of the number and type of amino acid sequence mutations. These rules are consistent with the physicochemical properties of the mutations and extend across the entire family tested, suggesting that scaling laws can be used as tools to predict changes in the stability of PLD condensates. Our work offers a quantitative lens into how the emergent behavior of PLD solutions varies in response to physicochemical changes of single PLD molecules.

biophysics↗

bioRxiv2023

Energy landscapes and heat capacity signatures for peptides correlate with phase separation propensity

Phase separation plays an important role in the formation of membraneless compartments within the cell, and intrinsically disordered proteins with low-complexity sequences can drive this compartmentalisation. Various intermolecular forces, such as aromatic-aromatic and cation-aromatic interactions, promote phase separation. However, little is known about how the ability of proteins to phase separate under physiological conditions is encoded in their energy landscapes, and this is the focus of the present investigation. Our results provide a first glimpse into how the energy landscapes of minimal peptides that contain{pi} -{pi} and cation-{pi} interactions differ from the peptides that lack amino acids with such interactions. The peaks in the heat capacity (CV) as a function of temperature report on alternative low-lying conformations that differ significantly in terms of their enthalpic and entropic contributions. The CV analysis and subsequent quantification of frustration of the energy landscape suggest that the interactions that promote phase separation leads to features (peaks or inflection points) at low temperatures in CV, more features may occur for peptides containing residues with better phase separation propensity and the energy landscape is more frustrated for such peptides. Overall, this work links the features in the underlying single-molecule potential energy landscapes to their collective phase separation behaviour, and identifies quantities (CV and frustration metric) that can be utilised in soft material design.

biophysics↗

bioRxiv2023

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

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

biophysics↗

bioRxiv2022

A 2D Fragment-Assisted Protein Mimetic Approach to Rescue α-Synuclein Aggregation Mediated Early and Post-Disease Parkinsons Phenotypes

We have developed a Oligopyridylamide (OP) based 2-Dimensional Fragment-Assisted Structure-based Technique (2D-FAST) to identify potent antagonists of -Synuclein (S) aggregation, a process central to Parkinsons disease (PD). The 2D-FAST utilizes a fragment-based screening of large chemical space in OPs, which led to the identification of NS132 as an antagonist of the multiple facets of S aggregation. We also identified a better cell permeability analog (NS163) without sacrificing activity. OPs rescue S aggregation mediated PD phenotypes in muscle cells and dopaminergic (DA) neurons in C. elegans models. OPs prevent the progression of PD phenotypes in a novel post-disease onset PD model. This is one of the first examples of a synthetic mimetic-based 2D-FAST to identify antagonists of toxic S self-assembly. We envision that 2D-FAST will have tremendous potential as it is expandable for other oligoamide scaffolds and for a much larger chemical space to identify lead therapeutics for various diseases.

biochemistry↗

bioRxiv2022

Designing multiphase biomolecular condensates by coevolution of protein mixtures

Control of biomolecular condensates may hold considerable therapeutic potential. Intracellular condensates are highly multi-component systems in which complex phase behaviour can ensue, including the formation of architectures comprising multiple immiscible condensed phases. Conceivable avenues for manipulating condensates to bypass pathologies thus extend beyond merely controlling their stability and material properties, and relying solely on physical intuition to manipulate them is difficult because of the complexity of their composition. We address this challenge by developing an efficient computational approach to design pairs of protein sequences that result in well-separated multilayered condensates. Our method couples a genetic algorithm to a residue-resolution coarse-grained protein model. We demonstrate that we can design protein partners to form multiphase condensates containing naturally occurring proteins, such as the low-complexity domain of hnRNPA1 and its mutants, and show how homo- and heterotypic interactions must differ between proteins to result in multiphasicity.

biophysics↗