Molecular origins of osmotic second virial coefficients of proteins

Competition between Self-Assembly and Phase Separation Governs High-Temperature Condensation of a DNA Liquid

In many biopolymer solutions, attractive interactions that stabilize finite-sized clusters at low concentrations also promote phase separation at high concentrations. Here we study a model biopolymer system that exhibits the opposite behavior, whereby self-assembly of DNA oligonucleotides into finite-sized, stoichiometric clusters tends to inhibit phase separation. We first use microfluidics-based experiments to map a novel phase transition in which the oligonucleotides condense as the temperature increases at high concentrations of divalent cations. We then show that a theoretical model of competition between self-assembly and phase separation quantitatively predicts changes in experimental phase diagrams arising from DNA sequence perturbations. Our results point to a general mechanism by which self-assembly shapes phase boundaries in complex biopolymer solutions.

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.

Optimization of therapeutic antibodies for reduced self-association and non-specific binding via interpretable machine learning

Antibody development, delivery, and efficacy are influenced by antibody-antigen affinity interactions, off-target interactions that reduce antibody bioavailability and pharmacokinetics, and repulsive self-interactions that increase the stability of concentrated antibody formulations and reduce their corresponding viscosity. Yet identifying antibody variants with optimal combinations of these three types of interactions is challenging. Here we show that interpretable machine-learning classifiers, leveraging antibody structural features descriptive of their variable regions and trained on experimental data for a panel of 80 clinical-stage monoclonal antibodies, can identify antibodies with optimal combinations of low off-target binding in a common physiological-solution condition and low self-association in a common antibody-formulation condition. For three clinical-stage antibodies with suboptimal combinations of off-target binding and self-association, the classifiers predicted variable-region mutations that optimized non-affinity interactions while maintaining high-affinity antibody-antigen interactions. Interpretable machine-learning models may facilitate the optimization of antibody candidates for therapeutic applications.

Membrane-Mediated Cooperative Interactions of CD47 and SIRPα

The specific binding of the ubiquitous 'marker of self' protein CD47 to the SIRPα protein anchored in the macrophage plasma membrane results in the inhibition of the engulfment of 'self' cells by macrophages and thus constitutes a key checkpoint of our innate immune system. Consequently, the CD47-SIRPα protein complex has been recognized as a potential therapeutic target in cancer and inflammation. Here, we introduce a lattice-based mesoscale model for the biomimetic system studied recently in fluorescence microscopy experiments where GFP-tagged CD47 proteins on giant plasma membrane vesicles bind to SIRPα proteins immobilized on a surface. Computer simulations of the lattice-based mesoscale model allow us to study the biomimetic system on multiple length scales, ranging from single nanometers to several micrometers and simultaneously keep track of single CD47-SIRPα binding and unbinding events. Our simulations not only reproduce data from the fluorescence microscopy experiments but also are consistent with results of several other experiments, which validates our numerical approach. In addition, our simulations yield quantitative predictions on the magnitude and range of effective, membrane-mediated attraction between CD47-SIRPα complexes. Such detailed information on CD47-SIRPα interactions cannot be obtained currently from experiments alone. Our simulation results thus extend the present understanding of cooperative effects in CD47-SIRPα interactions and may have an influence on the advancement of new cancer treatments.

The physical basis of osmosis

Osmosis is an important force in all living organisms, yet the molecular basis of osmosis is widely misunderstood as arising from diffusion of water across a membrane separating solutions of differing osmolarities, and hence different water concentrations. In 1923, Peter Debye proposed a physical model for a semipermeable membrane emphasizing the repulsive forces between solute molecules and membrane that prevent the solute from entering the membrane. His work was hardly noticed at the time and slipped out of view. We show that Debye's analysis of van 't Hoff's law for osmotic equilibrium also provides a consistent and plausible mechanism for osmotic flow. A difference in osmolyte concentrations in solutions separated by a semipermeable membrane leads to different pressures at the two water-membrane interfaces because the total repulsive force between solute molecules and the membrane is different at the two interfaces. Water is therefore driven through the membrane for exactly the same reason that pure water flows in response to an imposed hydrostatic pressure difference. In this paper, we present the Debye model in both equilibrium and flow conditions. We point out its applicability regardless of the nature of the membrane with examples ranging from the predominantly convective flow of water through synthetic membranes and capillary walls to the purely diffusive flow of independent water molecules through a lipid bilayer and the flow of a single-file column of water molecules in narrow protein channels.

A workflow for the development of template-assisted membrane crystallization downstream processing for monoclonal antibody purification

Monoclonal antibodies (mAbs) are commonly used biologic drugs for the treatment of diseases such as rheumatoid arthritis, multiple sclerosis, COVID-19 and various cancers. They are produced in Chinese hamster ovary cell lines and are purified via a number of complex and expensive chromatography-based steps, operated in batch mode, that rely heavily on protein A resin. The major drawback of conventional procedures is the high cost of the adsorption media and the extensive use of chemicals for the regeneration of the chromatographic columns, with an environmental cost. We have shown that conventional protein A chromatography can be replaced with a single crystallization step and gram-scale production can be achieved in continuous flow using the template-assisted membrane crystallization process. The templates are embedded in a membrane (e.g., porous polyvinylidene fluoride with a layer of polymerized polyvinyl alcohol) and serve as nucleants for crystallization. mAbs are flexible proteins that are difficult to crystallize, so it can be challenging to determine the optimal conditions for crystallization. The objective of this protocol is to establish a systematic and flexible approach for the design of a robust, economic and sustainable mAb purification platform to replace at least the protein A affinity stage in traditional chromatography-based purification platforms. The procedure provides details on how to establish the optimal parameters for separation (crystallization conditions, choice of templates, choice of membrane) and advice on analytical and characterization methods.

The ins and outs of membrane bending by intrinsically disordered proteins

Membrane curvature is essential to diverse cellular functions. While classically attributed to structured domains, recent work illustrates that intrinsically disordered proteins are also potent drivers of membrane bending. Specifically, repulsive interactions among disordered domains drive convex bending, while attractive interactions drive concave bending, creating membrane-bound, liquid-like condensates. How might disordered domains that contain both repulsive and attractive domains affect curvature? Here, we examined chimeras that combined attractive and repulsive interactions. When the attractive domain was closer to the membrane, its condensation amplified steric pressure among repulsive domains, leading to convex curvature. In contrast, when the repulsive domain was closer to the membrane, attractive interactions dominated, resulting in concave curvature. Further, a transition from convex to concave curvature occurred with increasing ionic strength, which reduced repulsion while enhancing condensation. In agreement with a simple mechanical model, these results illustrate a set of design rules for membrane bending by disordered proteins.

Phase Transitions of Associative Biomacromolecules

Multivalent proteins and nucleic acids, collectively referred to as multivalent associative biomacromolecules, provide the driving forces for the formation and compositional regulation of biomolecular condensates. Here, we review the key concepts of phase transitions of aqueous solutions of associative biomacromolecules, specifically proteins that include folded domains and intrinsically disordered regions. The phase transitions of these systems come under the rubric of coupled associative and segregative transitions. The concepts underlying these processes are presented, and their relevance to biomolecular condensates is discussed.

Phase separation and dynamical arrest of protein solutions dominated by short-range attractions

The interplay of liquid-liquid phase separation (LLPS) and dynamical arrest can lead to the formation of gels and glasses, which is relevant for such diverse fields as condensed matter physics, materials science, food engineering, and the pharmaceutical industry. In this context, protein solutions exhibit remarkable equilibrium and non-equilibrium behaviors. In the regime where attractive and repulsive forces compete, it has been demonstrated, for example, that the location of the dynamical arrest line seems to be independent of ionic strength, so that the arrest lines at different ionic screening lengths overlap, in contrast to the LLPS coexistence curves, which strongly depend on the salt concentration. In this work, we show that the same phenomenology can also be observed when the electrostatic repulsions are largely screened, and the range and strength of the attractions are varied. In particular, using lysozyme in brine as a model system, the metastable gas-liquid binodal and the dynamical arrest line as well as the second virial coefficient have been determined for various solution conditions by cloud-point measurements, optical microscopy, centrifugation experiments, and light scattering. With the aim of understanding this new experimental phenomenology, we apply the non-equilibrium self-consistent generalized Langevin equation theory to a simple model system with only excluded volume plus short-range attractions, to study the dependence of the predicted arrest lines on the range of the attractive interaction. The theoretical predictions find a good qualitative agreement with experiments when the range of the attraction is not too small compared with the size of the protein.

Predicting Experimental B22 Values and the Effects of Histidine Charge States for Monoclonal Antibodies Using Coarse-Grained Molecular Simulations

Static light scattering (SLS) was used to characterize five monoclonal antibodies (MAbs) as a function of total ionic strength (TIS) at pH values between 5.5 and 7.0. Second osmotic virial coefficient (B₂₂) values were determined experimentally for each MAb as a function of TIS using low protein concentration SLS data. Coarse-grained molecular simulations were performed to predict the B₂₂ values for each MAb at a given pH and TIS. To include the effect of charge fluctuations of titratable residues in the B₂₂ calculations, a statistical approach was introduced in the Monte Carlo algorithm based on the protonation probability based on a given pH value and the Henderson-Hasselbalch equation. The charged residues were allowed to fluctuate individually, based on the sampled microstates and the influence of electrostatic interactions on net protein-protein interactions during the simulations. Compared to static charge simulations, the new approach provided improved results compared to experimental B₂₂ values at pH conditions near the pK_a of titratable residues.

Determination of specific and non-specific protein-protein interactions for beta-lactoglobulin by analytical ultracentrifugation and membrane osmometry experiments

Protein-protein interactions are essential for the understanding of biological processes. Specific protein aggregation is an important aspect for many biological systems. In particular, electrostatic interactions play the key role for protein-protein interactions, as many amino acids have pH-dependent charge states. Moreover, protein dissociation is directly related to the solution pH, ionic strength, temperature and protein concentration. The subtle interplay between different specific and non-specific interactions is demonstrated for beta-lactoglobulin (BLG) with a focus on low salt concentrations, thus mimicking technically relevant processing conditions. BLG is a well-characterized model system, proven to attain its monomer-dimer equilibrium strongly dependent upon the pH of the solution. In this manuscript, we present a unique combination of analytical ultracentrifugation and membrane osmometry experiments, which quantifies specific and non-specific interactions, i.e. in terms of the dimer dissociation constants and the second osmotic virial coefficient, at pH 3 and 7 and sodium chloride concentrations of 10 mM and 100 mM. This provides direct insight to protein-protein interactions for a system with a concentration-dependent monomer-dimer equilibrium. Moreover, using a coarse-grained extended DLVO model in combination with molecular dynamics simulations, we quantify non-specific monomer-monomer, monomer-dimer and dimer-dimer interactions as well as the binding free energy of BLG dimerization from theoretical calculations. The experimentally determined interactions are shown to be mainly governed by electrostatic interactions and further agree with free energy calculations. Our experimental protocol aims to determine non-specific and specific interactions for a dynamically interacting system and provides an understanding of protein-protein interactions for BLG at low salt concentrations.

Use of Debye-Hückel-Henry charge measurements in early antibody development elucidates effects of non-specific association

The diffusion interaction parameter (kD) has been demonstrated to be a high-throughput technique for characterizing interactions between proteins in solution. kD reflects both attractive and repulsive interactions, including long-ranged electrostatic repulsions. Here, we plot the mutual diffusion coefficient (Dm) as a function of the experimentally determined Debye-Hückel-Henry surface charge (ZDHH) for seven human monoclonal antibodies (mAbs) in 15 mM histidine, pH 6. We find that graphs of Dm versus ZDHH intersect at ZDHH, ~ 2.6, independent of protein concentration. The same data plotted as kD vs. ZDHH shows a transition from net attractive to net repulsive interactions in the same region of the ZDHH intersection point. These data suggest that there is a minimum surface charge necessary on these mAbs needed to overcome attractive interactions.

Viscoelasticity, Like Forces, Plays a Role in Mechanotransduction

Viscoelasticity and its alteration in time and space has turned out to act as a key element in fundamental biological processes in living systems, such as morphogenesis and motility. Based on experimental and theoretical findings it can be proposed that viscoelasticity of cells, spheroids and tissues seems to be a collective characteristic that demands macromolecular, intracellular component and intercellular interactions. A major challenge is to couple the alterations in the macroscopic structural or material characteristics of cells, spheroids and tissues, such as cell and tissue phase transitions, to the microscopic interferences of their elements. Therefore, the biophysical technologies need to be improved, advanced and connected to classical biological assays. In this review, the viscoelastic nature of cytoskeletal, extracellular and cellular networks is presented and discussed. Viscoelasticity is conceptualized as a major contributor to cell migration and invasion and it is discussed whether it can serve as a biomarker for the cells’ migratory capacity in several biological contexts. It can be hypothesized that the statistical mechanics of intra- and extracellular networks may be applied in the future as a powerful tool to explore quantitatively the biomechanical foundation of viscoelasticity over a broad range of time and length scales. Finally, the importance of the cellular viscoelasticity is illustrated in identifying and characterizing multiple disorders, such as cancer, tissue injuries, acute or chronic inflammations or fibrotic diseases.

Measuring Self-Association of Antibody Lead Candidates with Dynamic Light Scattering

In this method chapter, we provide a brief overview of the key methods available to measure self-association of monoclonal antibodies (mAbs) and explain for which experimental throughputs they are usually applied. We then focus on dynamic light scattering (DLS) and describe experimental details on how to measure the diffusion interaction parameter (k_D) which is occasionally referred to as the gold standard for measuring self-association of proteins. The k_D is a well-established parameter to predict solution viscosity, which is one of the most critical developability parameters of mAbs. Finally, we present a pH and excipient screen that is designed to measure self-association with DLS under conditions that are relevant for bioprocessing and formulation of mAbs. The presented light scattering methods are well suited for lead candidate selections where it is essential to select mAbs with high developability potential for progression toward first human dose.

ATP and Tri-Polyphosphate (TPP) Suppress Protein Aggregate Growth by a Supercharging Mechanism

A common strategy to increase aggregation resistance is through rational mutagenesis to supercharge proteins, which leads to high colloidal stability, but often has the undesirable effect of lowering conformational stability. We show this trade-off can be overcome by using small multivalent polyphosphate ions, adenosine triphosphate (ATP) and tripolyphosphate (TPP) as excipients. These ions are equally effective at suppressing aggregation of ovalbumin and bovine serum albumin (BSA) upon thermal stress as monitored by dynamic and static light scattering. Monomer loss kinetic studies, combined with measurements of native state protein–protein interactions and ζ-potentials, indicate the ions reduce aggregate growth by increasing the protein colloidal stability through binding and overcharging the protein. Out of three additional proteins studied, ribonuclease A (RNaseA), α-chymotrypsinogen (α-Cgn), and lysozyme, we only observed a reduction in aggregate growth for RNaseA, although overcharging by the poly-phosphate ions still occurs for lysozyme and α-Cgn. Because the salts do not alter protein conformational stability, using them as excipients could be a promising strategy for stabilizing biopharmaceuticals once the protein structural factors that determine whether multivalent ion binding will increase colloidal stability are better elucidated. Our findings also have biological implications. Recently, it has been proposed that ATP also plays an important role in maintaining intracellular biological condensates and preventing protein aggregation in densely packed cellular environments. We expect electrostatic interactions are a significant factor in determining the stabilizing ability of ATP towards maintaining proteins in non-dispersed states in vivo.

Bayesian analysis of static light scattering data for globular proteins

Static light scattering is a popular physical chemistry technique that enables calculation of physical attributes such as the radius of gyration and the second virial coefficient for a macromolecule (e.g., a polymer or a protein) in solution. The second virial coefficient is a physical quantity that characterizes the magnitude and sign of pairwise interactions between particles, and hence is related to aggregation propensity, a property of considerable scientific and practical interest. Estimating the second virial coefficient from experimental data is challenging due both to the degree of precision required and the complexity of the error structure involved. In contrast to conventional approaches based on heuristic ordinary least squares estimates, Bayesian inference for the second virial coefficient allows explicit modeling of error processes, incorporation of prior information, and the ability to directly test competing physical models. Here, we introduce a fully Bayesian model for static light scattering experiments on small-particle systems, with joint inference for concentration, index of refraction, oligomer size, and the second virial coefficient. We apply our proposed model to study the aggregation behavior of hen egg-white lysozyme and human γS-crystallin using in-house experimental data. Based on these observations, we also perform a simulation study on the primary drivers of uncertainty in this family of experiments, showing in particular the potential for improved monitoring and control of concentration to aid inference.

The Protein Folding Problem: The Role of Theory

The protein folding problem was first articulated as question of how order arose from disorder in proteins: How did the various native structures of proteins arise from interatomic driving forces encoded within their amino acid sequences, and how did they fold so fast? These matters have now been largely resolved by theory and statistical mechanics combined with experiments. There are general principles. Chain randomness is overcome by solvation-based codes. And in the needle-in-a-haystack metaphor, native states are found efficiently because protein haystacks (conformational ensembles) are funnel-shaped. Order-disorder theory has now grown to encompass a large swath of protein physical science across biology.

Cluster Percolation Causes Shear Thinning Behavior in Concentrated Solutions of Monoclonal Antibodies

High-concentration (>100 g/L) solutions of monoclonal antibodies (mAbs) are typically characterized by anomalously large solution viscosity and shear thinning behavior for strain rates ≥10³ s^-1. Here, the link between protein-protein interactions (PPIs) and the rheology of concentrated solutions of COE-03 and COE-19 mAbs is studied by means of static and dynamic light scattering and microfluidic rheometry. By comparing the experimental data with predictions based on the Baxter sticky hard-sphere model, we surprisingly find a connection between the observed shear thinning and the predicted percolation threshold. The longest shear relaxation time of mAbs was much larger than that of model sticky hard spheres within the same region of the phase diagram, which is attributed to the anisotropy of the mAb PPIs. Our results suggest that not only the strength but also the patchiness of short-range attractive PPIs should be explicitly accounted for by theoretical approaches aimed at predicting the shear rate-dependent viscosity of dense mAb solutions.

A coarse-grained xDLVO model for colloidal protein-protein interactions

Colloidal protein-protein interactions (PPIs) of attractive and repulsive nature modulate the solubility of proteins, their aggregation, precipitation and crystallization. Such interactions are very important for many biotechnological processes, but are complex and hard to control, therefore, difficult to be understood in terms of measurements alone. In diluted protein solutions, PPIs can be estimated from the osmotic second virial coefficient, B22, which has been calculated using different methods and levels of theory. The most popular approach is based on the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory and its extended versions, i.e. xDLVO. Despite much efforts, these models are not fully quantitative and must be fitted to experiments, which limits their predictive value. Here, we report an extended xDLVO-CG model, which extends existing models by a coarse-grained representation of proteins and the inclusion of an additional ion-protein dispersion interaction term. We demonstrate for four proteins, i.e. lysozyme (LYZ), subtilisin (Subs), bovine serum albumin (BSA) and immunoglobulin (IgG1), that semi-quantitative agreement with experimental values without the need to fit to experimental B22 values. While most likely not the final step in the nearly hundred years of research in PPIs, xDLVO-CG is a step towards predictive PPIs calculations that are transferable to different proteins.

Chemical Properties Determine Solubility and Stability in βγ-Crystallins of the Eye Lens

βγ-Crystallins are the primary structural and refractive proteins found in the vertebrate eye lens. Because crystallins are not replaced after early eye development, their solubility and stability must be maintained for a lifetime, which is even more remarkable given the high protein concentration in the lens. Aggregation of crystallins caused by mutations or post-translational modifications can reduce crystallin protein stability and alter intermolecular interactions. Common post-translational modifications that can cause age-related cataracts include deamidation, oxidation, and tryptophan derivatization. Metal ion binding can also trigger reduced crystallin solubility through a variety of mechanisms. Interprotein interactions are critical to maintaining lens transparency: crystallins can undergo domain swapping, disulfide bonding, and liquid-liquid phase separation, all of which can cause opacity depending on the context. Important experimental techniques for assessing crystallin conformation in the absence of a high-resolution structure include dye-binding assays, circular dichroism, fluorescence, light scattering, and transition metal FRET.

Toward a Suite of Coarse-Grained Models for Molecular Simulation of Monoclonal Antibodies and Therapeutic Proteins

A series of coarse-grained models for molecular simulation of proteins are considered, with emphasis on the application of predicting protein-protein self-interactions for monoclonal antibodies (MAbs). As an illustrative example and for quantitative comparison, the models are used to predict osmotic virial coefficients over a broad range of attractive and repulsive self-interactions and solution conditions for a series of MAbs where the second osmotic virial coefficient has been experimentally determined in prior work. The models are compared based on how well they can predict experimental behavior, their computational burdens, and scalability. An intermediate-resolution model is also introduced that can capture specific electrostatic interactions with improved efficiency and similar or improved accuracy when compared to the previously published models. Guidance is included for the selection of coarse-grained models more generally for capturing a balance of electrostatic, steric, and short-ranged nonelectrostatic interactions for proteins from low to high concentrations.

Subcompartmentalization of polyampholyte species in organelle-like condensates is promoted by charge-pattern mismatch and strong excluded-volume interaction

Polyampholyte field theory and explicit-chain molecular dynamics models of sequence-specific phase separation of a system with two intrinsically disordered protein (IDP) species indicate consistently that a substantial polymer excluded volume and a significant mismatch of the IDP sequence charge patterns can act in concert, but not in isolation, to demix the two IDP species upon condensation. This finding reveals an energetic-geometric interplay in a stochastic, "fuzzy" molecular recognition mechanism that may facilitate subcompartmentalization of membraneless organelles.

High-Throughput Screening for Colloidal Stability of Peptide Formulations Using Dynamic and Static Light Scattering

Selection of an appropriate formulation to stabilize therapeutic proteins against aggregation is one of the most challenging tasks in early-stage drug product development. The amount of aggregates is more difficult to quantify in the case of peptides due to their small molecular size. Here, we investigated the suitability of diffusion self-interaction parameters (k_D) and osmotic second virial coefficients (B₂₂) for high-throughput (HT) screening of peptide formulations regarding their aggregation risk. These parameters were compared to the effect of thermal stress on colloidal stability. The formulation matrix comprised six buffering systems at two selected pH values, four tonicity agents, and a common preservative. The results revealed that electrostatic interactions are the main driver to control colloidal stability. Preferred formulations consisted of acetate and succinate buffer at pH 4.5 combined with glycerol or mannitol and optional m-cresol. k_D proved to be a suitable surrogate for B₂₂ as an indicator of high colloidal stability in the case of peptides as was previously described for globular proteins and antibodies. Formulation assessment solely based on k_D obtained by HT methods offers important insights into the optimization of colloidal stability during the early development of peptide-based liquid formulations and can be performed with a limited amount of peptide (∼360 mg).

Molecular forces governing protein-protein interaction: Structure-function relationship of complexes protein in the food industry

The application of protein-protein interaction (PPI) has been widely used in various industries, such as food, nutraceutical, and pharmaceutical. A deeper understanding of PPI is needed, and the molecular forces governing proteins and their interaction must be explained. The design of new structures with improved functional properties, e.g., solubility, emulsion, and gelation, has been fueled by the development of structural and colloidal building blocks. In this review, the molecular forces of protein structures are discussed, followed by the relationship between molecular force and structure, ways of a bind of proteins together in solution or at the interface, and functional properties. A more detailed look is thus taken at the relationship between the various influencing factors on molecular forces involved in PPI. These factors include protein properties, such as types, concentration, and mixing ratio, and solvent conditions, such as ionic strength and pH. This review also summarizes methods tha1t are capable of identifying molecular forces in protein and PPI, as well as characterizing protein structure.

Protein aggregation and immunogenicity of biotherapeutics

Recombinant proteins are the mainstay of biopharmaceuticals. A key challenge in the manufacturing and formulation of protein biologic products is the tendency for the active pharmaceutical ingredients to aggregate, resulting in irreversible drug loss, and an increase in immunogenicity risk. While the molecular mechanisms of protein aggregation have been discussed extensively in the literature, knowledge gaps remain in connecting the phenomenon in the context of immunogenicity of biotherapeutics. In this review, we discussed factors that drive aggregation of pharmaceutical recombinant proteins, and highlighted methods of prediction and mitigation that can be deployed through the development stages, from formulation to bioproduction. The purpose is to stimulate new dialogs that would bridge the interface between physical characterizations of protein aggregates in biotherapeutics and the functional attributes of the immune system.

Quantifying Protein-Protein Interactions in Molecular Simulations

Interactions among proteins, nucleic acids, and other macromolecules are essential for their biological functions and shape the physicochemcial properties of the crowded environments inside living cells. Binding interactions are commonly quantified by dissociation constants K_d, and both binding and nonbinding interactions are quantified by second osmotic virial coefficients B₂. As a measure of nonspecific binding and stickiness, B₂ is receiving renewed attention in the context of so-called liquid–liquid phase separation in protein and nucleic acid solutions. We show that K_d is fully determined by B₂ and the fraction of the dimer observed in molecular simulations of two proteins in a box. We derive two methods to calculate B₂. From molecular dynamics or Monte Carlo simulations using implicit solvents, we can determine B₂ from insertion and removal energies by applying Bennett’s acceptance ratio (BAR) method or the (binless) weighted histogram analysis method (WHAM). From simulations using implicit or explicit solvents, one can estimate B₂ from the probability that the two molecules are within a volume large enough to cover their range of interactions. We validate these methods for coarse-grained Monte Carlo simulations of three weakly binding proteins. Our estimates for K_d and B₂ allow us to separate out the contributions of nonbinding interactions to B₂. Comparison of calculated and measured values of K_d and B₂ can be used to (re-)parameterize and improve molecular force fields by calibrating specific affinities, overall stickiness, and nonbinding interactions. The accuracy and efficiency of K_d and B₂ calculations make them well suited for high-throughput studies of large interactomes.

On the Aggregation and Nucleation Mechanism of the Monoclonal Antibody Anti-CD20 Near Liquid-Liquid Phase Separation (LLPS)

The crystallization of Anti-CD20, a full-length monoclonal antibody, has been studied in the PEG400/Na2SO4/Water system near Liquid-Liquid Phase Separation (LLPS) conditions by both sitting-drop vapour diffusion and batch methods. In order to understand the Anti-CD20 crystallization propensity in the solvent system of different compositions, we investigated some measurable parameters, normally used to assess protein conformational and colloidal stability in solution, with the aim to understand the aggregation mechanism of this complex biomacromolecule. We propose that under crystallization conditions a minor population of specifically aggregated protein molecules are present. While this minor species hardly contributes to the measured average solution behaviour, it induces and promotes crystal formation. The existence of this minor species is the result of the LLPS occurring concomitantly under crystallization conditions.

Life in Phases: Intra- and Inter- Molecular Phase Transitions in Protein Solutions

Proteins, these evolutionarily-edited biological polymers, are able to undergo intramolecular and intermolecular phase transitions. Spontaneous intramolecular phase transitions define the folding of globular proteins, whereas binding-induced, intra- and inter- molecular phase transitions play a crucial role in the functionality of many intrinsically-disordered proteins. On the other hand, intermolecular phase transitions are the behind-the-scenes players in a diverse set of macrosystemic phenomena taking place in protein solutions, such as new phase nucleation in bulk, on the interface, and on the impurities, protein crystallization, protein aggregation, the formation of amyloid fibrils, and intermolecular liquid-liquid or liquid-gel phase transitions associated with the biogenesis of membraneless organelles in the cells. This review is dedicated to the systematic analysis of the phase behavior of protein molecules and their ensembles, and provides a description of the major physical principles governing intramolecular and intermolecular phase transitions in protein solutions.

Determination of Protein-Protein Interactions in a Mixture of Two Monoclonal Antibodies

The coformulation of monoclonal antibody (mAb) mixtures provides an attractive route to achieving therapeutic efficacy where the targeting of multiple epitopes is necessary. Controlling and predicting the behavior of such mixtures requires elucidating the molecular basis for the self- and cross-protein-protein interactions and how they depend on solution variables. While self-interactions are now beginning to be well understood, systematic studies of cross-interactions between mAbs in solution do not exist. Here, we have used static light scattering to measure the set of self- and cross-osmotic second virial coefficients in a solution containing a mixture of two mAbs, mAbA and mAbB, as a function of ionic strength and pH. mAbB exhibits strong association at a low ionic strength, which is attributed to an electrostatic attraction that is enhanced by the presence of a strong short-ranged attraction of nonelectrostatic origin. Under all solution conditions, the measured cross-interactions are intermediate self-interactions and follow similar patterns of behavior. There is a strong electrostatic attraction at higher pH values, reflecting the behavior of mAbB. Protein-protein interactions become more attractive with an increasing pH due to reducing the overall protein net charges, an effect that is attenuated with an increasing ionic strength due to the screening of electrostatic interactions. Under moderate ionic strength conditions, the reduced cross-virial coefficient, which reflects only the energetic contribution to protein-protein interactions, is given by a geometric average of the corresponding self-coefficients. We show the relationship can be rationalized using a patchy sphere model, where the interaction energy between sites i and j is given by the arithmetic mean of the i-i and j-j interactions. The geometric mean does not necessarily apply to all mAb mixtures and is expected to break down at a lower ionic strength due to the nonadditivity of electrostatic interactions.

Protein-protein interactions and water activity coefficients can be used to aid a first excipient choice in protein formulations

With respect to all biopharmaceuticals marketed to date, monoclonal antibodies represent the largest fraction with more than 48% market share (2012). However, the development of biopharmaceutical formulations is a challenging task, and time-consuming and cost-intensive high-throughput screenings are still state-of-the-art in formulation design. These screening techniques are almost exclusively based on heuristic decisions thus the benefit in terms of mechanistic understanding is often unclear. It requires novel, physical-sound methods to enhance/optimize future formulation development, ideally by understanding molecular interactions in these complex solutions. A suitable and evaluated measure-of-choice to characterize protein-protein interactions in aqueous protein solutions is the second osmotic virial coefficient B₂₂ which can be measured using static light scattering techniques. Furthermore B₂₂ can be modeled/predicted via the extended mxDLVO model for protein-protein interactions in the presence of single excipients and excipient-mixtures. Building up on this approach, giving an additional insight into water-water and water-excipient interactions, the thermodynamic equation-of-state ePC-SAFT is used to calculate water activity coefficients in the presence of excipient-mixtures. Immunoglobulin G (IgG) was chosen as a model protein to predict B₂₂-values for IgG in the presence of model excipient-mixtures (trehalose-NaCl, l-histidine-trehalose, l-histidine-NaCl). The combination of water activity coefficients and B₂₂ allows to quickly identify a first guess on suitable formulation conditions that then can be further evaluated with existing methods/knowledge.

Calculation of Second Virial Coefficients of Atomistic Proteins Using Fast Fourier Transform

The second virial coefficient, B₂, measures a protein solution's deviation from ideal behavior. It is widely used to predict or explain solubility, crystallization condition, aggregation propensity, and critical temperature for liquid-liquid phase separation. B₂ is determined by the interaction energy between two protein molecules and, specifically, by the integration of the Mayer f-function in the relative configurational space (translation and rotation) of the two molecules. Simple theoretical models, such as one attributed to Derjaguin, Landau, Verwey, and Overbeek (DLVO), can fit the dependence of B₂ on salt concentrations. However, model parameters derived often are physically unrealistic and hardly transferable from protein to protein. Previous B₂ calculations incorporating atomistic details were done with limited sampling in the configurational space, due to enormous computational cost. Our FMAP method, based on fast Fourier transform, can considerably accelerate such calculations, and here we adapt it to calculate B₂ values for proteins represented at the atomic level in implicit solvent. After tuning of a single parameter in the energy function, FMAPB2 predicts well the B₂ values for lysozyme and other proteins over wide ranges of solvent conditions (salt concentration, pH, and temperature). The method is available as a web server at http://pipe.rcc.fsu.edu/fmapb2 .

Measuring the effects of macromolecular crowding on antibody function with biolayer interferometry

Biotherapeutic proteins are commonly dosed at high concentrations into the blood, which is an inherently complex, crowded solution with substantial protein content. The effects of macromolecular crowding may lead to an appreciable level of non-specific hetero-association in this physiological environment. Therefore, developing a method to characterize the diverse consequences of non-specific interactions between proteins under such non-ideal, crowded conditions, which deviate substantially from those commonly employed for in vitro characterization, is vital to achieving a more complete picture of antibody function in a biological context. In this study, we investigated non-specific interactions between human serum albumin (HSA) and two monoclonal antibodies (mAbs) by static light scattering and determined these interactions are both ionic strength-dependent and mAb-dependent. Using biolayer interferometry (BLI), we assessed the effect of HSA on antigen binding by mAbs, demonstrating that these non-specific interactions have a functional impact on mAb:antigen interactions, particularly at low ionic strength. While this effect is mitigated at physiological ionic strength, our in vitro data support the notion that HSA in the blood may lead to non-specific interactions with mAbs in vivo, with a potential impact on their interactions with antigen. Furthermore, the BLI method offers a high-throughput advantage compared to orthogonal techniques such as analytical ultracentrifugation and is amenable to a greater variety of solution conditions compared to nuclear magnetic resonance spectroscopy. Our study demonstrates that BLI is a viable technology for examining the impact of non-specific interactions on specific biologically relevant interactions, providing a direct method to assess binding events in crowded conditions.

Development and applications of a concentrating membrane osmometer for colloid solutions

The membrane concentration osmometer coupled with multiple sample preparations has been used for over a century to determine a number of colloidal properties. At the dilute region, this method has been used to determine solute molecular mass. When the solution is proteinaceous, in the intermediate region, the osmotic pressure profile provides the second virial coefficient, useful for estimating protein crystallization and salting out. At the most crowded concentrations, it provides insight into protein hydration and protein-ion interaction. One of the most critical factors in generating the osmotic pressure profile is minimizing the quantity of protein used and reducing the error in preparing samples. Here, we introduce a membrane concentrating osmometer that allows one to measure osmotic pressure over a wide concentration range from a single sample. A test study was performed using the osmotic pressure profile of self-crowded bovine serum albumin solutions. The resulting profile was in good agreement with previous data in the literature obtained from multiple sample studies. The osmotic pressure profile was further used with a free solvent-based osmotic pressure model to determine protein hydration and ion binding. These results were in excellent agreement with literature values. This concentrating osmometer has several advantages over a conventional concentration osmometer for obtaining the osmotic pressure profile for proteinaceous solutions: (1) the amount of protein required is significantly decreased, (2) the potential for experimental error in sample preparation diminishes, and (3) the time for generating the osmotic pressure profile is substantially reduced.

Steric Repulsion Forces Contributed by PEGylation of Interleukin-1 Receptor Antagonist Reduce Gelation and Aggregation at the Silicone Oil-Water Interface

Silicone oil, used as a lubricating coating in pharmaceutical containers, has been implicated as a cause of therapeutic protein aggregation. After adsorbing to silicone oil-water interfaces, proteins may form interfacial gels, which can be transported into solution as insoluble aggregates if the interfaces are perturbed. Mechanical interfacial perturbation of both monomeric recombinant human interleukin-1 receptor antagonist (rhIL-1ra) and PEGylated rhIL-1ra (PEG rhIL-1ra) in siliconized syringes resulted in losses of soluble monomeric protein. However, the loss of rhIL-1ra was twice that for PEG rhIL-1ra; even though in solution, PEG rhIL-1ra had a lower ΔG_unf and exhibited a more perturbed tertiary structure at the interface. Net protein-protein interactions in solution for rhIL-1ra were attractive but increased steric repulsion because of PEGylation led to net repulsive interactions for PEG rhIL-1ra. Attractive interactions for rhIL-1ra were associated with increases in intermolecular β-sheet content at the interface, whereas no intermolecular β-sheet structures were observed for adsorbed PEG rhIL-1ra. rhIL-1ra formed interfacial gels that were 5 times stronger than those formed by PEG rhIL-1ra. Thus, the steric repulsion contributed by the PEGylation resulted in decreased interfacial gelation and in the reduction of aggregation, in spite of the destabilizing effects of PEGylation on the protein's conformational stability.

Relation between single-molecule properties and phase behavior of intrinsically disordered proteins

Proteins that undergo liquid-liquid phase separation (LLPS) have been shown to play a critical role in many physiological functions through formation of condensed liquid-like assemblies that function as membraneless organelles within biological systems. To understand how different proteins may contribute differently to these assemblies and their functions, it is important to understand the molecular driving forces of phase separation and characterize their phase boundaries and material properties. Experimental studies have shown that intrinsically disordered regions of these proteins are a major driving force, as many of them undergo LLPS in isolation. Previous work on polymer solution phase behavior suggests a potential correspondence between intramolecular and intermolecular interactions that can be leveraged to discover relationships between single-molecule properties and phase boundaries. Here, we take advantage of a recently developed coarse-grained framework to calculate the θ temperature [Formula: see text], the Boyle temperature [Formula: see text], and the critical temperature [Formula: see text] for 20 diverse protein sequences, and we show that these three properties are highly correlated. We also highlight that these correlations are not specific to our model or simulation methodology by comparing between different pairwise potentials and with data from other work. We, therefore, suggest that smaller simulations or experiments to determine [Formula: see text] or [Formula: see text] can provide useful insights into the corresponding phase behavior.

Spectroscopic methods for assessing the molecular origins of macroscopic solution properties of highly concentrated liquid protein solutions

In cases of subcutaneous injection of therapeutic monoclonal antibodies, high protein concentrations (>50 mg/ml) are often required. During the development of these high concentration liquid formulations (HCLF), challenges such as aggregation, gelation, opalescence, phase separation, and high solution viscosities are more prone compared to low concentrated protein formulations. These properties can impair manufacturing processes, as well as protein stability and shelf life. To avoid such unfavourable solution properties, a detailed understanding about the nature of these properties and their driving forces are required. However, the fundamental mechanisms that lead to macroscopic solution properties, as above mentioned, are complex and not fully understood, yet. Established analytical methods for assessing the colloidal stability, i.e. the ability of a native protein to remain dispersed in solution, are restricted to dilute conditions and provide parameters such as the second osmotic virial coefficient, B₂₂, and the diffusion interaction coefficient, k_D. These parameters are routinely applied for qualitative estimations and identifications of proteins with challenging solution behaviours, such as high viscosities and aggregation, although the assays are prepared for low protein concentration conditions, typically between 0.1 and 20 mg/ml ("ideal" solution conditions). Quantitative analysis of samples of high protein concentration is difficult and it is hard to obtain information about the driving forces of such solution properties and corresponding protein-protein self-interactions. An advantage of using specific spectroscopic methods is the potential of directly analysing highly concentrated protein solutions at different solution conditions. This allows for collecting/gaining valuable information about the fundamental mechanisms of solution properties of the high protein concentration regime. In addition, the derived parameters might be more predictive as compared to the parameters originating from assays which are optimized for the low protein concentration range. The provided information includes structural data, molecular dynamics at various timescales and protein-solvent interactions, which can be obtained at molecular resolution. Herein, we provide an overview about spectroscopic techniques for analysing the origins of macroscopic solution behaviours in general, with a specific focus on pharmaceutically relevant high protein concentration and formulation conditions.

Biophysical characterization and molecular simulation of electrostatically driven self-association of a single-chain antibody

Colloidal protein-protein interactions (PPI) are often expected to impact key behaviors of proteins in solution, such as aggregation rates and mechanisms, aggregate structure, protein solubility, and solution viscosity. PPI of an anti-fluorescein single chain antibody variable fragment (scFv) were characterized experimentally at low to intermediate ionic strength using a combination of static light scattering and sedimentation equilibrium ultracentrifugation. Surprisingly, the results indicated that interactions were strongly net-attractive and electrostatics promoted self-association. Only repulsive interactions were expected based on prior work and calculations based a homology model of a related scFv crystal structure. However, the crystal structure lacks the charged, net-neutral linker sequence. PyRosetta was used to generate a set of scFv structures with different linker conformations, and coarse-grained Monte Carlo simulations were used to evaluate the effect of different linker configurations via second osmotic virial coefficient (B₂₂ ) simulations. The results show that the configuration of the linker has a significant effect on the calculated B₂₂ values, and can result in strong electrostatic attractions between oppositely charged residues on the protein surface. This is particularly relevant for development of non-natural antibody products, where charged linkers and other loop regions may be prevalent. The results also provide a preliminary computational framework to evaluate the effect of unstructured linkers on experimental protein-protein interaction parameters such as B₂₂ .

Revisiting the colloidal fundamentals of water-dispersible polyesters: interactions and self-assembly of polymer nanoaggregates in water

Water-dispersible sulfopolyesters are a major class of film-forming and solution-modifying polymers, which are routinely used in applications such as inks, adhesives, coatings, and personal care products. Since these polyesters are designed to be used as waterborne dispersions, understanding their colloidal interactions in dispersions is critical for their application. By using a range of commercially available water-dispersible sulfopolyesters as a model system, we investigated the relationship between their molecular composition, colloidal interactions, and phase equilibria. We established how these polyesters undergo different molecular configurations and nanoaggregated states, depending on the nature of the liquid medium. For example, the polyesters are in a solvated molecular form in certain organic solvents, whereas they self-assemble into compact nanoaggregates in water. We found that the interactions of these nanoaggregates follow the classical DLVO theory of critical colloidal coagulation where the stability of these nanoparticles is extremely sensitive to multivalent electrolytes (i.e., C_crit ∝ z^-6). By using static, dynamic, and electrophoretic light scattering, we correlate their nanoscale intermolecular and interparticle interactions with corresponding macroscale phase behavior in both organic medium and water, based on the theoretical framework of second virial coefficients. We present a model for nanoaggregate formation in water based on the critical surface charge density of these nanoparticles. Such fundamental understanding of colloidal interactions could be used to efficiently control and improve the colloidal stability and film-formation ability of these polyesters and may enable the design of novel high-performance surfactant-free waterborne dispersion systems.

Protein-protein interactions controlling interfacial aggregation of rhIL-1ra are not described by simple colloid models

We investigated the effects of protein-protein interaction strength on interfacial viscoelastic properties and aggregation of recombinant human interleukin-1 receptor antagonist (rhIL-1ra) at silicone oil-water interfaces. Osmotic second virial coefficients determined by static light scattering were used to quantify protein-protein interactions in bulk solution. Attractive protein-protein interactions dominated at low ionic strengths and their magnitude decreased with increasing ionic strength, in contrast to repulsive interactions that would be expected based on uniformly charged sphere models. Interfacial shear rheometry was used to characterize rhIL-1ra interfacial layers. More attractive protein-protein interactions in bulk solution correlated with stronger interfacial gels. Thioflavin-T fluorescence measurements indicated that the intermolecular β-sheet content of rhIL-1ra incubated in the presence of silicone oil-water interfaces correlated with gel strength. Siliconized syringes were used to probe the effects of mechanical perturbation of the interfacial gel layers. When rhIL-1ra solutions in siliconized glass syringes were subjected to end-over-end rotation, monomeric rhIL-1ra was lost from solution, and particles containing aggregated protein were released into the bulk aqueous phase. The loss of monomeric rhIL-1ra in response to mechanical perturbation was highest under the conditions where the strongest gels were observed. Aggregation of rhIL-1ra was strictly interface-induced and growth of aggregates in the bulk solution was not observed, even in the presence of particles released from silicone oil-water interfaces.

A tetramer micelle: the smallest aggregation number corresponding to the vertex number of regular polyhedra in platonic micelles

In this paper, we describe the construction of tetramer micelles based on the idea of "Platonic micelles" whose aggregation number (N_agg) matches the vertex number of regular polyhedra and exhibits the monodispersity and discreteness in the N_agg.

Self-assembly pathways and polymorphism in peptide-based nanostructures

Dipeptide derivative molecules can self-assemble into space-filling nanofiber networks at low volume fractions (<1%), allowing the formation of molecular gels with tunable mechanical properties. The self-assembly of dipeptide-based molecules is reminiscent of pathological amyloid fibril formation by naturally occurring polypeptides. Fluorenylmethoxycarbonyl-diphenylalanine (Fmoc-FF) is the most widely studied such molecule, but the thermodynamic and kinetic phenomena giving rise to Fmoc-FF gel formation remain poorly understood. We have previously presented evidence that the gelation process is a first order phase transition characterized by low energy barriers to nucleation, short induction times, and rapid quasi-one-dimensional crystal growth, stemming from solvent-solute interactions and highly specific molecular packing. Here, we discuss the phase behavior of Fmoc-FF in different solvents. We find that Fmoc-FF gel formation can be induced in apolar solvents, in addition to previously established pathways in aqueous systems. We further show that in certain solvent systems anisotropic crystals (nanofibers) are an initial metastable state, after which macroscopic crystal aggregates with no preferred axis of growth are formed. The molecular conformation is sensitive to solvent composition during assembly, indicating that Fmoc-FF may be a simple model system to study complex thermodynamic and kinetic phenomena involved in peptide self-assembly.

Predicting Protein-Protein Interactions of Concentrated Antibody Solutions Using Dilute Solution Data and Coarse-Grained Molecular Models

Protein-protein interactions for solutions of an IgG1 molecule were quantified using static light scattering (SLS) measurements from low to high protein concentrations (c₂). SLS was used to determine second osmotic virial coefficients (B₂₂) at low c₂, and excess Rayleigh profiles (R^ex/K vs. c₂) and zero-q structure factors (S_q=0) as a function of c₂ at higher c₂ for a series of conditions (pH, sucrose concentration, and total ionic strength [TIS]). Repulsive (attractive) interactions were observed at low TIS (high TIS) for pH 5 and 6.5, with increasing repulsions when 5% w/w sucrose was also present. Previously developed and refined coarse-grained antibody models were used to fit model parameters from B₂₂ versus TIS data. The resulting parameters from low-c₂ conditions were used as the sole input to multiprotein Monte Carlo simulations to predict high-c₂R^ex/K and S_q=0 behavior up to 150 g/L. Experimental results at high-c₂ conditions were quantitatively predicted by the simulations for the coarse-grained models that treated antibody molecules as either 6 or 12 (sub) domains, which preserved the basic shape of a monoclonal antibody. Finally, preferential accumulation of sucrose around the protein surface was identified via high-precision density measurements, which self-consistently explained the simulation and experimental SLS results.

Thermodynamic stability of worm-like micelle solutions

Worm-like micelles (WLMs) are nano-scale self-assemblies widely used for viscosity enhancement, for drug delivery, and in personal care products. The stability of WLMs under variable ionic and surfactant concentrations is important to applications of these fascinating materials. In this work it is demonstrated that a virial approach can be used to understand and predict WLM stability. A mixed surfactant system consisting of sodium laureth sulfate and cocoamidopropyl betaine was examined using small-angle neutron scattering. A linear relationship between the second virial coefficient, A₂, and the salt to surfactant ratio, Θ_s-s, is derived and demonstrated. The Θ_s-s-dependent term is described via association/dissociation kinetics of salt ions between the bulk and an ion cloud surrounding the WLMs yielding, , where K_eq is the association/dissociation constant, n_surf is the molar surfactant concentration, b is the molar excluded volume, M the WLM molar mass, Θ_s-s is the salt-surfactant ratio and Θ is the salt-surfactant ratio where the interactions are solely determined by the excluded volume. The ratio b/M² is independent of WLM contour length. The exponent ϑ is found to be approximately 5/4 in agreement with polymer scaling laws for the semi-dilute regime in good solvents.

Intrinsically disordered sequences enable modulation of protein phase separation through distributed tyrosine motifs

Liquid–liquid phase separation (LLPS) is thought to contribute to the establishment of many biomolecular condensates, eukaryotic cell structures that concentrate diverse macromolecules but lack a bounding membrane. RNA granules control RNA metabolism and comprise a large class of condensates that are enriched in RNA-binding proteins and RNA molecules. Many RNA granule proteins are composed of both modular domains and intrinsically disordered regions (IDRs) having low amino acid sequence complexity. Phase separation of these molecules likely plays an important role in the generation and stability of RNA granules. To understand how folded domains and IDRs can cooperate to modulate LLPS, we generated a series of engineered proteins. These were based on fusions of an IDR derived from the RNA granule protein FUS (fused in sarcoma) to a multivalent poly-Src homology 3 (SH3) domain protein that phase-separates when mixed with a poly-proline–rich-motif (polyPRM) ligand. We found that the wild-type IDR promotes LLPS of the polySH3–polyPRM system, decreasing the phase separation threshold concentration by 8-fold. Systematic mutation of tyrosine residues in Gly/Ser-Tyr-Gly/Ser motifs of the IDR reduced this effect, depending on the number but not on the position of these substitutions. Mutating all tyrosines to non-aromatic residues or phosphorylating the IDR raised the phase separation threshold above that of the unmodified polySH3–polyPRM pair. These results show that low-complexity IDRs can modulate LLPS both positively and negatively, depending on the degree of aromaticity and phosphorylation status. Our findings provide plausible mechanisms by which these sequences could alter RNA granule properties on evolutionary and cellular timescales.