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MOTIVATION: Sidechain rotamer libraries of the common amino acids of a protein are useful for folded protein structure determination and for generating ensembles of intrinsically disordered proteins (IDPs). However, much of protein function is modulated beyond the translated sequence through the introduction of post-translational modifications (PTMs). RESULTS: In this work, we have provided a curated set of side chain rotamers for the most common PTMs derived from the RCSB PDB database, including phosphorylated, methylated, and acetylated sidechains. Our rotamer libraries improve upon existing methods such as SIDEpro, Rosetta, and AlphaFold3 in predicting the experimental structures for PTMs in folded proteins. In addition, we showcase our PTM libraries in full use by generating ensembles with the Monte Carlo Side Chain Entropy (MCSCE) for folded proteins, and combining MCSCE with the Local Disordered Region Sampling algorithms within IDPConformerGenerator for proteins with intrinsically disordered regions. AVAILABILITY AND IMPLEMENTATION: The codes for dihedral angle computations and library creation are available at https://github.com/THGLab/ptm_sc.git.

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

Numerous biological systems contain vesicle-like biomolecular compartments without membranes, which contribute to diverse functions including gene regulation, stress response, signaling, and skin barrier formation. Coacervation, as a form of liquid-liquid phase separation (LLPS), is recognized as a representative precursor to the formation and assembly of membrane-less vesicle-like structures, although their formation mechanism remains unclear. In this study, a coacervation-driven membrane-less vesicle-like structure is constructed using two proteins, GG1234 (an anionic intrinsically disordered protein) and bhBMP-2 (a bioengineered human bone morphogenetic protein 2). GG1234 formed both simple coacervates by itself and complex coacervates with the relatively cationic bhBMP-2 under acidic conditions. Upon addition of dissolved bhBMP-2 to the simple coacervates of GG1234, a phase transition from spherical simple coacervates to vesicular condensates occurred via the interactions between GG1234 and bhBMP-2 on the surface of the highly viscoelastic GG1234 simple coacervates. Furthermore, the shell structure in the outer region of the GG1234/bhBMP-2 vesicular condensates exhibited gel-like properties, leading to the formation of multiphasic vesicle-like compartments. A potential mechanism is proposed for the formation of the membrane-less GG1234/bhBMP-2 vesicle-like compartments. This study provides a dynamic process underlying the formation of biomolecular multiphasic condensates, thereby enhancing the understanding of these biomolecular structures.

Intrinsically disordered proteins and protein regions (IDPs) are prevalent in all proteomes and are essential to cellular function. Unlike folded proteins, IDPs exist in an ensemble of dissimilar conformations. Despite this structural plasticity, intramolecular interactions create sequence-specific structural biases that determine an IDP ensemble's three-dimensional shape. Such structural biases can be key to IDP function and are often measured in vitro, but whether those biases are preserved inside the cell is unclear. Here we show that structural biases in IDP ensembles found in vitro are recapitulated inside human-derived cells. We further reveal that structural biases can change in a sequence-dependent manner due to changes in the intracellular milieu, subcellular localization, and intramolecular interactions with tethered well-folded domains. We propose that the structural sensitivity of IDP ensembles can be leveraged for biological function, can be the underlying cause of IDP-driven pathology or can be used to design disorder-based biosensors and actuators.

The Protein Ensemble Database (PED) (URL: https://proteinensemble.org) is the primary resource for depositing structural ensembles of intrinsically disordered proteins. This updated version of PED reflects advancements in the field, denoting a continual expansion with a total of 461 entries and 538 ensembles, including those generated without explicit experimental data through novel machine learning (ML) techniques. With this significant increment in the number of ensembles, a few yet-unprecedented new entries entered the database, including those also determined or refined by electron paramagnetic resonance or circular dichroism data. In addition, PED was enriched with several new features, including a novel deposition service, improved user interface, new database cross-referencing options and integration with the 3D-Beacons network-all representing efforts to improve the FAIRness of the database. Foreseeably, PED will keep growing in size and expanding with new types of ensembles generated by accurate and fast ML-based generative models and coarse-grained simulations. Therefore, among future efforts, priority will be given to further develop the database to be compatible with ensembles modeled at a coarse-grained level.

SUMMARY: The Local Disordered Region Sampling (LDRS, pronounced loaders) tool is a new module developed for IDPConformerGenerator, a previously validated approach to model intrinsically disordered proteins (IDPs). The IDPConformerGenerator LDRS module provides a method for generating all-atom conformations of intrinsically disordered protein regions at N- and C-termini of and in loops or linkers between folded regions of an existing protein structure. These disordered elements often lead to missing coordinates in experimental structures or low confidence in predicted structures. Requiring only a pre-existing PDB or mmCIF formatted structural template of the protein with missing coordinates or with predicted confidence scores and its full-length primary sequence, LDRS will automatically generate physically meaningful conformational ensembles of the missing flexible regions to complete the full-length protein. The capabilities of the LDRS tool of IDPConformerGenerator include modeling phosphorylation sites using enhanced Monte Carlo-Side Chain Entropy, transmembrane proteins within an all-atom bilayer, and multi-chain complexes. The modeling capacity of LDRS capitalizes on the modularity, the ability to be used as a library and via command-line, and the computational speed of the IDPConformerGenerator platform. AVAILABILITY AND IMPLEMENTATION: The LDRS module is part of the IDPConformerGenerator modeling suite, which can be downloaded from GitHub at https://github.com/julie-forman-kay-lab/IDPConformerGenerator. IDPConformerGenerator is written in Python3 and works on Linux, Microsoft Windows, and Mac OS versions that support DSSP. Users can utilize LDRSs Python API for scripting the same way they can use any part of IDPConformerGenerators API, by importing functions from the idpconfgen.ldrs_helper library. Otherwise, LDRS can be used as a command line interface application within IDPConformerGenerator. Full documentation is available within the command-line interface as well as on IDPConformerGenerators official documentation pages (https://idpconformergenerator.readthedocs.io/en/latest/).

Aggregated and hyperphosphorylated Tau is one of the pathological hallmarks of Alzheimer's disease. Tau is a polyampholytic and intrinsically disordered protein (IDP). In this paper, we present for the first time experimental results on the ionic strength dependence of the radius of gyration (Rg) of human Tau 4RS and 4RL isoforms. Synchrotron X-ray scattering revealed that 4RS Rg is regulated from 65.4 to 58.5 Å and 4RL Rg is regulated from 70.9 to 57.9 Å by varying ionic strength from 0.01 to 0.592 M. The Rg of 4RL Tau is larger than 4RS at lower ionic strength. This result provides an insight into the ion-responsive nature of intrinsically disordered and polyampholytic Tau, and can be implicated to the further study of Tau-Tau and Tau-tubulin intermolecular structure in ionic environments.

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.

Intrinsically disordered protein regions (IDRs) make up over 30% of the human proteome and exist in a dynamic conformational ensemble instead of a native, well-folded structure. Tethering IDRs to a surface (for example, the surface of a well-folded region of the same protein) can reduce the number of accessible conformations in these ensembles. This reduces the ensemble's conformational entropy, generating an effective entropic force that pulls away from the point of tethering. Recent experimental work has shown that this entropic force causes measurable, physiologically relevant changes to protein function. But how the magnitude of this force depends on IDR sequence remains unexplored. Here, we use all-atom simulations to analyze how structural preferences in IDR ensembles contribute to the entropic force they exert upon tethering. We show that sequence-encoded structural preferences play an important role in determining the magnitude of this force: compact, spherical ensembles generate an entropic force that can be several times higher than more extended ensembles. We further show that changes in the surrounding solution's chemistry can modulate the IDR entropic force strength. We propose that the entropic force is a sequence-dependent, environmentally tunable property of terminal IDR sequences.

The structural characterization of proteins with a disorder requires a computational approach backed by experiments to model their diverse and dynamic structural ensembles. The selection of conformational ensembles consistent with solution experiments of disordered proteins highly depends on the initial pool of conformers, with currently available tools limited by conformational sampling. We have developed a Generative Recurrent Neural Network (GRNN) that uses supervised learning to bias the probability distributions of torsions to take advantage of experimental data types such as nuclear magnetic resonance J-couplings, nuclear Overhauser effects, and paramagnetic resonance enhancements. We show that updating the generative model parameters according to the reward feedback on the basis of the agreement between experimental data and probabilistic selection of torsions from learned distributions provides an alternative to existing approaches that simply reweight conformers of a static structural pool for disordered proteins. Instead, the biased GRNN, DynamICE, learns to physically change the conformations of the underlying pool of the disordered protein to those that better agree with experiments.

Toxoplasma gondii oocysts, which are shed in large quantities in the feces from infected felines, are very stable in the environment, resistant to most inactivation procedures, and highly infectious. The oocyst wall provides an important physical barrier for sporozoites contained inside oocysts, protecting them from many chemical and physical stressors, including most inactivation procedures. Furthermore, sporozoites can withstand large temperature changes, even freeze-thawing, as well as desiccation, high salinity, and other environmental insults; however, the genetic basis for this environmental resistance is unknown. Here, we show that a cluster of four genes encoding Late Embryogenesis Abundant (LEA)-related proteins are required to provide Toxoplasma sporozoites resistance to environmental stresses. Toxoplasma LEA-like genes (TgLEAs) exhibit the characteristic features of intrinsically disordered proteins, explaining some of their properties. Our in vitro biochemical experiments using recombinant TgLEA proteins show that they have cryoprotective effects on the oocyst-resident lactate dehydrogenase enzyme and that induced expression in E. coli of two of them leads to better survival after cold stress. Oocysts from a strain in which the four LEA genes were knocked out en bloc were significantly more susceptible to high salinity, freezing, and desiccation compared to wild-type oocysts. We discuss the evolutionary acquisition of LEA-like genes in Toxoplasma and other oocyst-producing apicomplexan parasites of the Sarcocystidae family and discuss how this has likely contributed to the ability of sporozoites within oocysts to survive outside the host for extended periods. Collectively, our data provide a first molecular detailed view on a mechanism that contributes to the remarkable resilience of oocysts against environmental stresses. IMPORTANCE Toxoplasma gondii oocysts are highly infectious and may survive in the environment for years. Their resistance against disinfectants and irradiation has been attributed to the oocyst and sporocyst walls by acting as physical and permeability barriers. However, the genetic basis for their resistance against stressors like changes in temperature, salinity, or humidity, is unknown. We show that a cluster of four genes encoding Toxoplasma Late Embryogenesis Abundant (TgLEA)-related proteins are important for this resistance to environmental stresses. TgLEAs have features of intrinsically disordered proteins, explaining some of their properties. Recombinant TgLEA proteins show cryoprotective effects on the parasite's lactate dehydrogenase, an abundant enzyme in oocysts, and expression in E. coli of two TgLEAs has a beneficial effect on growth after cold stress. Moreover, oocysts from a strain lacking all four TgLEA genes were more susceptible to high salinity, freezing, and desiccation compared to wild-type oocysts, highlighting the importance of the four TgLEAs for oocyst resilience.

Network Hamiltonian models (NHMs) are a framework for topological coarse-graining of protein-protein interactions, in which each node corresponds to a protein, and edges are drawn between nodes representing proteins that are noncovalently bound. Here, this framework is applied to aggregates of γD-crystallin, a structural protein of the eye lens implicated in cataract disease. The NHMs in this study are generated from atomistic simulations of equilibrium distributions of wild-type and the cataract-causing variant W42R in solution, performed by Wong, E. K.; Prytkova, V.; Freites, J. A.; Butts, C. T.; Tobias, D. J. Molecular Mechanism of Aggregation of the Cataract-Related γD-Crystallin W42R Variant from Multiscale Atomistic Simulations. Biochemistry2019, 58 (35), 3691-3699. Network models are shown to successfully reproduce the aggregate size and structure observed in the atomistic simulation, and provide information about the transient protein-protein interactions therein. The system size is scaled from the original 375 monomers to a system of 10000 monomers, revealing a lowering of the upper tail of the aggregate size distribution of the W42R variant. Extrapolation to higher and lower concentrations is also performed. These results provide an example of the utility of NHMs for coarse-grained simulation of protein systems, as well as their ability to scale to large system sizes and high concentrations, reducing computational costs while retaining topological information about the system.

The power of structural information for informing biological mechanisms is clear for stable folded macromolecules, but similar structure-function insight is more difficult to obtain for highly dynamic systems such as intrinsically disordered proteins (IDPs) which must be described as structural ensembles. Here, we present IDPConformerGenerator, a flexible, modular open-source software platform for generating large and diverse ensembles of disordered protein states that builds conformers that obey geometric, steric, and other physical restraints on the input sequence. IDPConformerGenerator samples backbone phi (φ), psi (ψ), and omega (ω) torsion angles of relevant sequence fragments from loops and secondary structure elements extracted from folded protein structures in the RCSB Protein Data Bank and builds side chains from robust Monte Carlo algorithms using expanded rotamer libraries. IDPConformerGenerator has many user-defined options enabling variable fractional sampling of secondary structures, supports Bayesian models for assessing the agreement of IDP ensembles for consistency with experimental data, and introduces a machine learning approach to transform between internal and Cartesian coordinates with reduced error. IDPConformerGenerator will facilitate the characterization of disordered proteins to ultimately provide structural insights into these states that have key biological functions.

Intrinsically disordered proteins (IDPs) fold upon binding to select/recruit multiple partners, morph around the partner's structure, and exhibit allostery. However, we do not know whether these properties emerge passively from disorder, or rather are encoded into the IDP's folding mechanisms. A main reason for this gap is the lack of suitable methods to dissect the energetics of IDP conformational landscapes without partners. Here we introduce such an approach that we term molecular LEGO, and apply it to NCBD, a helical, molten globule–like IDP, as proof of concept. The approach entails the experimental and computational characterization of the protein, its separate secondary structure elements (LEGO building blocks), and their supersecondary combinations. Comparative analysis uncovers specific, yet inconspicuous, energetic biases in the conformational/folding landscape of NCBD, including 1) strong local signals that define the three native helices, 2) stabilization of helix–helix interfaces via soft pairwise tertiary interactions, 3) cooperative stabilization of a heterogeneous three-helix bundle fold, and 4) a dynamic exchange between sets of tertiary interactions (native and nonnative) that recapitulate the different structures NCBD adopts in complex with various partners. Crucially, a tug of war between sets of interactions makes NCBD gradually shift between structural subensembles as a conformational rheostat. Such conformational rheostatic behavior provides a built-in mechanism to modulate binding and switch/recruit partners that is likely at the core of NCBD's function as transcriptional coactivator. Hence, the molecular LEGO approach emerges as a powerful tool to dissect the conformational landscapes of unbound IDPs and rationalize their functional mechanisms.

Intrinsically disordered proteins and unfolded proteins have fluctuating conformational ensembles that are fundamental to their biological function and impact protein folding, stability, and misfolding. Despite the importance of protein dynamics and conformational sampling, time-dependent data types are not fully exploited when defining and refining disordered protein ensembles. Here we introduce a computational framework using an elastic network model and normal-mode displacements to generate a dynamic disordered ensemble consistent with NMR-derived dynamics parameters, including transverse R2 relaxation rates and Lipari-Szabo order parameters (S2 values). We illustrate our approach using the unfolded state of the drkN SH3 domain to show that the dynamical ensembles give better agreement than a static ensemble for a wide range of experimental validation data including NMR chemical shifts, J-couplings, nuclear Overhauser effects, paramagnetic relaxation enhancements, residual dipolar couplings, hydrodynamic radii, single-molecule fluorescence Förster resonance energy transfer, and small-angle X-ray scattering.

Intrinsically disordered proteins rich in cationic amino acid groups can undergo Liquid-Liquid Phase Separation (LLPS) in the presence of charge-balancing anionic counterparts. Arginine and Lysine are the two most prevalent cationic amino acids in proteins that undergo LLPS, with arginine-rich proteins observed to undergo LLPS more readily than lysine-rich proteins, a feature commonly attributed to arginine's ability to form stronger cation-π interactions with aromatic groups. Here, we show that arginine's ability to promote LLPS is independent of the presence of aromatic partners, and that arginine-rich peptides, but not lysine-rich peptides, display re-entrant phase behavior at high salt concentrations. We further demonstrate that the hydrophobicity of arginine is the determining factor giving rise to the reentrant phase behavior and tunable viscoelastic properties of the dense LLPS phase. Controlling arginine-induced reentrant LLPS behavior using temperature and salt concentration opens avenues for the bioengineering of stress-triggered biological phenomena and drug delivery systems.

Intrinsically disordered proteins (IDPs) have recently become systems of great interest due to their involvement in modulating many biological processes and their aggregation being implicated in many diseases. Since IDPs do not have a stable, folded structure, however, they cannot be easily studied with experimental techniques. Hence, conducting a computational study of these systems can be helpful and be complementary with experimental work to elucidate their mechanisms. Thus, we have implemented the coarse-grained force field for proteins (COFFDROP) in Browndye 2.0 to study IDPs using Brownian dynamics (BD) simulations, which are often used to study large-scale motions with longer time scales and diffusion-limited molecular associations. Specifically, we have checked our COFFDROP implementation with eight naturally occurring IDPs and have investigated five (Glu-Lys)25 IDP sequence variants. From measuring the hydrodynamic radii of eight naturally occurring IDPs, we found the ideal scaling factor of 0.786 for non-bonded interactions. We have also measured the entanglement indices (average C α distances to the other chain) between two (Glu-Lys)25 IDP sequence variants, a property related to molecular association. We found that entanglement indices decrease for all possible pairs at excess salt concentration, which is consistent with long-range interactions of these IDP sequence variants getting weaker at increasing salt concentration.

Intracellular phase separation is emerging as a universal principle for organizing biochemical reactions in time and space. It remains incompletely resolved how biological function is encoded in these assemblies and whether this depends on their material state. The conserved intrinsically disordered protein PopZ forms condensates at the poles of the bacterium Caulobacter crescentus, which in turn orchestrate cell-cycle regulating signaling cascades. Here we show that the material properties of these condensates are determined by a balance between attractive and repulsive forces mediated by a helical oligomerization domain and an expanded disordered region, respectively. A series of PopZ mutants disrupting this balance results in condensates that span the material properties spectrum, from liquid to solid. A narrow range of condensate material properties supports proper cell division, linking emergent properties to organismal fitness. We use these insights to repurpose PopZ as a modular platform for generating tunable synthetic condensates in human cells.

Cell signaling is a complex process. The faithful transduction of information into specific cellular actions depends on the synergistic effects of many regulatory molecules, nurtured by their strict spatiotemporal regulation. Over the years, we have gained copious insights into the subcellular architecture supporting this spatiotemporal control, including the roles of membrane-bound organelles and various signaling nanodomains. Recently, liquid-liquid phase separation (LLPS) has been recognized as another potentially ubiquitous framework for organizing signaling molecules with high specificity and precise spatiotemporal control in cells. Here, we review the pervasive role of LLPS in signal transduction, highlighting several key pathways that intersect with LLPS, including examples in which LLPS is controlled by signaling events. We also examine how LLPS orchestrates signaling by compartmentalizing signaling molecules, amplifying signals non-linearly, and moderating signaling dynamics. We focus on the specific molecules that drive LLPS and highlight the known functional and pathological consequences of LLPS in each pathway.

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.

UTX (also known as KDM6A) encodes a histone H3K27 demethylase and is an important tumour suppressor that is frequently mutated in human cancers1. However, as the demethylase activity of UTX is often dispensable for mediating tumour suppression and developmental regulation2-8, the underlying molecular activity of UTX remains unknown. Here we show that phase separation of UTX underlies its chromatin-regulatory activity in tumour suppression. A core intrinsically disordered region (cIDR) of UTX forms phase-separated liquid condensates, and cIDR loss caused by the most frequent cancer mutation of UTX is mainly responsible for abolishing tumour suppression. Deletion, mutagenesis and replacement assays of the intrinsically disordered region demonstrate a critical role of UTX condensation in tumour suppression and embryonic stem cell differentiation. As shown by reconstitution in vitro and engineered systems in cells, UTX recruits the histone methyltransferase MLL4 (also known as KMT2D) to the same condensates and enriches the H3K4 methylation activity of MLL4. Moreover, UTX regulates genome-wide histone modifications and high-order chromatin interactions in a condensation-dependent manner. We also found that UTY, the Y chromosome homologue of UTX with weaker tumour-suppressive activity, forms condensates with reduced molecular dynamics. These studies demonstrate a crucial biological function of liquid condensates with proper material states in enabling the tumour-suppressive activity of a chromatin regulator.

Cell homeostasis is perturbed when dramatic shifts in the external environment cause the physical-chemical properties inside the cell to change. Experimental approaches for dynamically monitoring these intracellular effects are currently lacking. Here, we leverage the environmental sensitivity and structural plasticity of intrinsically disordered protein regions (IDRs) to develop a FRET biosensor capable of monitoring rapid intracellular changes caused by osmotic stress. The biosensor, named SED1, utilizes the Arabidopsis intrinsically disordered AtLEA4-5 protein expressed in plants under water deficit. Computational modeling and in vitro studies reveal that SED1 is highly sensitive to macromolecular crowding. SED1 exhibits large and near-linear osmolarity-dependent changes in FRET inside living bacteria, yeast, plant, and human cells, demonstrating the broad utility of this tool for studying water-associated stress. This study demonstrates the remarkable ability of IDRs to sense the cellular environment across the tree of life and provides a blueprint for their use as environmentally-responsive molecular tools.

Many pairwise additive force fields are in active use for intrinsically disordered proteins (IDPs) and regions (IDRs), some of which modify energetic terms to improve the description of IDPs/IDRs but are largely in disagreement with solution experiments for the disordered states. This work considers a new direction-the connection to configurational entropy-and how it might change the nature of our understanding of protein force field development to equally well encompass globular proteins, IDRs/IDPs, and disorder-to-order transitions. We have evaluated representative pairwise and many-body protein and water force fields against experimental data on representative IDPs and IDRs, a peptide that undergoes a disorder-to-order transition, for seven globular proteins ranging in size from 130 to 266 amino acids. We find that force fields with the largest statistical fluctuations consistent with the radius of gyration and universal Lindemann values for folded states simultaneously better describe IDPs and IDRs and disorder-to-order transitions. Hence, the crux of what a force field should exhibit to well describe IDRs/IDPs is not just the balance between protein and water energetics but the balance between energetic effects and configurational entropy of folded states of globular proteins.

Intrinsically disordered proteins (IDPs) are widely distributed across eukaryotic cells, playing important roles in molecular recognition, molecular assembly, post-translational modification, and other biological processes. IDPs are also associated with many diseases such as cancers, cardiovascular diseases, and neurodegenerative diseases. Due to their structural flexibility, conventional experimental methods cannot reliably capture their heterogeneous structures. Molecular dynamics simulation becomes an important complementary tool to quantify IDP structures. This review covers recent force field strategies proposed for more accurate molecular dynamics simulations of IDPs. The strategies include adjusting dihedral parameters, adding grid-based energy correction map (CMAP) parameters, refining protein-water interactions, and others. Different force fields were found to perform well on specific observables of specific IDPs but also are limited in reproducing all available experimental observables consistently for all tested IDPs. We conclude the review with perspective areas for improvements for future force fields for IDPs.

Low complexity (LC) head domains 92 and 108 residues in length are, respectively, required for assembly of neurofilament light (NFL) and desmin intermediate filaments (IFs). As studied in isolation, these IF head domains interconvert between states of conformational disorder and labile, β-strand-enriched polymers. Solid-state NMR (ss-NMR) spectroscopic studies of NFL and desmin head domain polymers reveal spectral patterns consistent with structural order. A combination of intein chemistry and segmental isotope labeling allowed preparation of fully assembled NFL and desmin IFs that could also be studied by ss-NMR. Assembled IFs revealed spectra overlapping with those observed for β-strand-enriched polymers formed from the isolated NFL and desmin head domains. Phosphorylation and disease-causing mutations reciprocally alter NFL and desmin head domain self-association yet commonly impede IF assembly. These observations show how facultative structural assembly of LC domains via labile, β-strand-enriched self-interactions may broadly influence cell morphology.

The Protein Ensemble Database (PED) (https://proteinensemble.org), which holds structural ensembles of intrinsically disordered proteins (IDPs), has been significantly updated and upgraded since its last release in 2016. The new version, PED 4.0, has been completely redesigned and reimplemented with cutting-edge technology and now holds about six times more data (162 versus 24 entries and 242 versus 60 structural ensembles) and a broader representation of state of the art ensemble generation methods than the previous version. The database has a completely renewed graphical interface with an interactive feature viewer for region-based annotations, and provides a series of descriptors of the qualitative and quantitative properties of the ensembles. High quality of the data is guaranteed by a new submission process, which combines both automatic and manual evaluation steps. A team of biocurators integrate structured metadata describing the ensemble generation methodology, experimental constraints and conditions. A new search engine allows the user to build advanced queries and search all entry fields including cross-references to IDP-related resources such as DisProt, MobiDB, BMRB and SASBDB. We expect that the renewed PED will be useful for researchers interested in the atomic-level understanding of IDP function, and promote the rational, structure-based design of IDP-targeting drugs.

Screening ligands directly binding to an ensemble of intrinsically disordered proteins (IDP) to discover potential hits or leads for new drugs is an emerging but challenging area as IDPs lack well-defined and ordered 3D-protein structures. To explore a new IDP-based rational drug discovery strategy, a differential binding score (DIBS) is defined. The basis of DIBS is to quantitatively determine the binding preference of a ligand to an ensemble of conformations specified by IDP versus such preferences to an ensemble of random coil conformations of the same protein. Ensemble docking procedures performed on repeated sampling of conformations, and the results tested for statistical significance determine the preferential ligand binding sites of the IDP. The results of this approach closely reproduce the experimental data from recent literature on the binding of the ligand epigallocatechin gallate (EGCG) to the intrinsically disordered N-terminal domain of the tumor suppressor p53. Combining established approaches in developing a new method to screen ligands against IDPs could be valuable as a screening tool for IDP-based drug discovery.

Many pairwise additive force fields are in active use for intrinsically disordered proteins (IDPs) and regions (IDRs), some of which modify energetic terms to improve the description of IDPs/IDRs but are largely in disagreement with solution experiments for the disordered states. This work considers a new direction-the connection to configurational entropy-and how it might change the nature of our understanding of protein force field development to equally well encompass globular proteins, IDRs/IDPs, and disorder-to-order transitions. We have evaluated representative pairwise and many-body protein and water force fields against experimental data on representative IDPs and IDRs, a peptide that undergoes a disorder-to-order transition, for seven globular proteins ranging in size from 130 to 266 amino acids. We find that force fields with the largest statistical fluctuations consistent with the radius of gyration and universal Lindemann values for folded states simultaneously better describe IDPs and IDRs and disorder-to-order transitions. Hence, the crux of what a force field should exhibit to well describe IDRs/IDPs is not just the balance between protein and water energetics but the balance between energetic effects and configurational entropy of folded states of globular proteins.

Cell homeostasis is perturbed when dramatic shifts in the external environment cause the physical-chemical properties inside the cell to change. Experimental approaches for dynamically monitoring these intracellular effects are currently lacking. Here, we leverage the environmental sensitivity and structural plasticity of intrinsically disordered protein regions (IDRs) to develop a FRET biosensor capable of monitoring rapid intracellular changes caused by osmotic stress. The biosensor, named SED1, utilizes the Arabidopsis intrinsically disordered AtLEA4-5 protein expressed in plants under water deficit. Computational modeling and in vitro studies reveal that SED1 is highly sensitive to macromolecular crowding. SED1 exhibits large and near-linear osmolarity-dependent changes in FRET inside living bacteria, yeast, plant, and human cells, demonstrating the broad utility of this tool for studying water-associated stress. This study demonstrates the remarkable ability of IDRs to sense the cellular environment across the tree of life and provides a blueprint for their use as environmentally-responsive molecular tools.

Cryptochrome (CRY) proteins play an essential role in regulating mammalian circadian rhythms. CRY is composed of a structured N-terminal domain known as the photolyase homology region (PHR), which is tethered to an intrinsically disordered C-terminal tail. The PHR domain is a critical hub for binding other circadian clock components such as CLOCK, BMAL1, PERIOD, or the ubiquitin ligases FBXL3 and FBXL21. While the isolated PHR domain is necessary and sufficient to generate circadian rhythms, removing or modifying the cryptochrome tails modulates the amplitude and/or periodicity of circadian rhythms, suggesting that they play important regulatory roles in the molecular circadian clock. In this commentary, we will discuss how recent studies of these intrinsically disordered tails are helping to establish a general and evolutionarily conserved model for CRY function, where the function of PHR domains is modulated by reversible interactions with their intrinsically disordered tails. Video abstract.

Cryptochrome (CRY) proteins play an essential role in regulating mammalian circadian rhythms. CRY is composed of a structured N-terminal domain known as the photolyase homology region (PHR), which is tethered to an intrinsically disordered C-terminal tail. The PHR domain is a critical hub for binding other circadian clock components such as CLOCK, BMAL1, PERIOD, or the ubiquitin ligases FBXL3 and FBXL21. While the isolated PHR domain is necessary and sufficient to generate circadian rhythms, removing or modifying the cryptochrome tails modulates the amplitude and/or periodicity of circadian rhythms, suggesting that they play important regulatory roles in the molecular circadian clock. In this commentary, we will discuss how recent studies of these intrinsically disordered tails are helping to establish a general and evolutionarily conserved model for CRY function, where the function of PHR domains is modulated by reversible interactions with their intrinsically disordered tails. Video abstract.

Intrinsically disordered proteins (IDPs) have fluctuating heterogeneous conformations, which makes their structural characterization challenging. Although challenging, characterization of the conformational ensembles of IDPs is of great interest, since their conformational ensembles are the link between their sequences and functions. An accurate description of IDP conformational ensembles depends crucially on the amount and quality of the experimental data, how it is integrated, and if it supports a consistent structural picture. We used integrative modeling and validation to apply conformational restraints and assess agreement with the most common structural techniques for IDPs: Nuclear Magnetic Resonance (NMR) spectroscopy, Small-angle X-ray Scattering (SAXS), and single-molecule Förster Resonance Energy Transfer (smFRET). Agreement with such a diverse set of experimental data suggests that details of the generated ensembles can now be examined with a high degree of confidence. Using the disordered N-terminal region of the Sic1 protein as a test case, we examined relationships between average global polymeric descriptions and higher-moments of their distributions. To resolve apparent discrepancies between smFRET and SAXS inferences, we integrated SAXS data with NMR data and reserved the smFRET data for independent validation. Consistency with smFRET, which was not guaranteed a priori, indicates that, globally, the perturbative effects of NMR or smFRET labels on the Sic1 ensemble are minimal. Analysis of the ensembles revealed distinguishing features of Sic1, such as overall compactness and large end-to-end distance fluctuations, which are consistent with biophysical models of Sic1's ultrasensitive binding to its partner Cdc4. Our results underscore the importance of integrative modeling and validation in generating and drawing conclusions from IDP conformational ensembles.

The need for accurate and efficient force fields for modeling 3D structures of macrobiomolecules and in particular intrinsically disordered proteins (IDPs) has increased with recent findings to associate IDPs and human diseases. However, most conventional protein force fields and recent IDP-specific force fields are limited in reproducing accurate structural features of IDPs. Here, we present an environmental specific precise force field (ESFF1) based on CMAP corrections of 71 different sequence environments to improve the accuracy and efficiency of MD simulation for both IDPs and folded proteins. MD simulations of 84 different short peptides, IDPs, and structured proteins show that ESFF1 can accurately reproduce spectroscopic properties for different peptides and proteins whether they are disordered or ordered. The successful ab initio folding of five fast-folding proteins further supports the reliability of ESFF1. The extensive analysis documented here shows that ESFF1 is able to achieve a reasonable balance between ordered and disordered states in protein simulations.

Intrinsically disordered proteins (IDPs) play important roles in biology, but little is known about the energetics of their inter-residue interactions. Methods that have been successfully applied to analyze the energetics of globular proteins are not applicable to the fluctuating partially ordered ensembles populated by IDPs. A combined computational experimental strategy is introduced for analyzing the energetic role of individual residues in the free state of IDPs. The approach combines experimental measurements of the binding of wild-type and mutant IDPs to their partners with alchemical free energy calculations of the structured complexes. These data allow quantitative information to be deduced about the free state via a thermodynamic cycle. The approach is validated by the analysis of the effects of mutations upon the binding free energy of the ovomucoid inhibitor third binding domain to its partners and is applied to the C-terminal domain of the measles virus nucleoprotein, a 125-residue IDP involved in the RNA transcription and replication of measles virus. The analysis reveals significant inter-residue interactions in the unbound IDP and suggests a biological role for them. The work demonstrates that advances in force fields and computational hardware have now led to the point where it is possible to develop methods, which integrate experimental and computational techniques to reveal insights that cannot be studied using either technique alone.

Molecular dynamics simulation as an important complement of experiment is widely used to study protein structures and functions. However, previous studies indicate that the current force fields cannot, simultaneously, provide accurate descriptions of folded proteins and intrinsically disordered proteins (IDPs). Therefore, a correction maps (CMAP)-optimized force field based on the Amber ff03 force field (termed ff03CMAP herein) was developed for a balanced sampling of folded proteins and IDPs. Extensive validations of short peptides, folded proteins, disordered proteins, and fast-folding proteins show that simulated chemical shifts, J-coupling constants, order parameters, and residual dipolar couplings (RDCs) with the ff03CMAP force field are in very good agreement with nuclear magnetic resonance measurements and are more accurate than other ff03-series force fields. The influence of solvent models was also investigated. It was found that the combination of ff03CMAP/TIP4P-Ew is suitable for folded proteins, and that of ff03CMAP/TIP4PD is better for disordered proteins. These findings confirm that the newly developed force field ff03CMAP can improve the balance of conformer sampling between folded proteins and IDPs.

In this minireview, which is part of a special issue in honor of Jacob N. Israelachvilis remarkable research career on intermolecular forces and interfacial science, we present studies of structures, phase behavior, and forces in reaction mixtures of microtubules (MTs) and tubulin oligomers with either intrinsically disordered protein (IDP) Tau, cationic vesicles, or the polyamine spermine (4+). Bare MTs consist of 13 protofilaments (PFs), on average, where each PF is made of a linear stack of αβ-tubulin dimers (i.e., tubulin oligomers). We begin with a series of experiments which demonstrate the flexibility of PFs toward shape changes in response to local environmental cues. First, studies show that MT-associated protein (MAP) Tau controls the diameter of microtubules upon binding to the outer surface, implying a shape change in the cross-sectional area of PFs forming the MT perimeter. The diameter of a MT may also be controlled by the charge density of a lipid bilayer membrane that coats the outer surface. We further describe an experimental study where it is unexpectedly found that the biologically relevant polyamine spermine (+4e) is able to depolymerize taxol-stabilized microtubules with efficiency that increases with decreasing temperature. This MT destabilization drives a dynamical structural transition where inside-out curving of PFs, during the depolymerization peeling process, is followed by reassembly of ring-like curved PF building blocks into an array of helical inverted tubulin tubules. We finally turn to a very recent study on pressure-distance measurements in bundles of MTs employing the small-angle X-ray scattering (SAXS)-osmotic pressure technique, which complements the surface-forces-apparatus technique developed by Jacob N. Israelachvili. These latter studies are among the very few which are beginning to shed light on the precise nature of the interactions between MTs mediated by MAP Tau in 37 °C reaction mixtures containing GTP and lacking taxol.

In this minireview, which is part of a special issue in honor of Jacob N. Israelachvili's remarkable research career on intermolecular forces and interfacial science, we present studies of structures, phase behavior, and forces in reaction mixtures of microtubules (MTs) and tubulin oligomers with either intrinsically disordered protein (IDP) Tau, cationic vesicles, or the polyamine spermine (4+). Bare MTs consist of 13 protofilaments (PFs), on average, where each PF is made of a linear stack of αβ-tubulin dimers (i.e., tubulin oligomers). We begin with a series of experiments which demonstrate the flexibility of PFs toward shape changes in response to local environmental cues. First, studies show that MT-associated protein (MAP) Tau controls the diameter of microtubules upon binding to the outer surface, implying a shape change in the cross-sectional area of PFs forming the MT perimeter. The diameter of a MT may also be controlled by the charge density of a lipid bilayer membrane that coats the outer surface. We further describe an experimental study where it is unexpectedly found that the biologically relevant polyamine spermine (+4e) is able to depolymerize taxol-stabilized microtubules with efficiency that increases with decreasing temperature. This MT destabilization drives a dynamical structural transition where inside-out curving of PFs, during the depolymerization peeling process, is followed by reassembly of ring-like curved PF building blocks into an array of helical inverted tubulin tubules. We finally turn to a very recent study on pressure-distance measurements in bundles of MTs employing the small-angle X-ray scattering (SAXS)-osmotic pressure technique, which complements the surface-forces-apparatus technique developed by Jacob N. Israelachvili. These latter studies are among the very few which are beginning to shed light on the precise nature of the interactions between MTs mediated by MAP Tau in 37 °C reaction mixtures containing GTP and lacking taxol.

Reflectin proteins are widely distributed in reflective structures in cephalopods. However, only in loliginid squids are they and the subwavelength photonic structures they control dynamically tunable, driving changes in skin color for camouflage and communication. The reflectins are block copolymers with repeated canonical domains interspersed with cationic linkers. Neurotransmitter-activated signal transduction culminates in catalytic phosphorylation of the tunable reflectins' cationic linkers; the resulting charge neutralization overcomes coulombic repulsion to progressively allow condensation, folding, and assembly into multimeric spheres of tunable well-defined size and low polydispersity. Here, we used dynamic light scattering, transmission EM, CD, atomic force microscopy, and fluorimetry to analyze the structural transitions of reflectins A1 and A2. We also analyzed the assembly behavior of phosphomimetic, deletion, and other mutants in conjunction with pH titration as an in vitro surrogate of phosphorylation. Our experiments uncovered a previously unsuspected, precisely predictive relationship between the extent of neutralization of a reflectin's net charge density and the size of resulting multimeric protein assemblies of narrow polydispersity. Comparisons of mutants revealed that this sensitivity to neutralization resides in the linkers and is spatially distributed along the protein. Imaging of large particles and analysis of sequence composition suggested that assembly may proceed through a dynamically arrested liquid-liquid phase-separated intermediate. Intriguingly, it is this dynamic arrest that enables the observed fine-tuning by charge and the resulting calibration between neuronal trigger and color in the squid. These results offer insights into the basis of reflectin-based biophotonics, opening paths for the design of new materials with tunable properties.

The phase separation behavior of intrinsically disordered proteins (IDPs) is thought of as analogous to that of polymers that undergo equilibrium lower or upper critical solution temperature (LCST and UCST, respectively) phase transition. This view, however, ignores possible nonequilibrium properties of protein assemblies. Here, by studying IDP polymers (IDPPs) composed of repeat motifs that encode LCST or UCST phase behavior, we discovered that IDPs can access a wide spectrum of nonequilibrium, hysteretic phase behaviors. Experimentally and through simulations, we show that hysteresis in IDPPs is tunable and that it emerges through increasingly stable interchain interactions in the insoluble phase. To explore the utility of hysteretic IDPPs, we engineer self-assembling nanostructures with tunable stability. These findings shine light on the rich phase separation behavior of IDPs and illustrate hysteresis as a design parameter to program nonequilibrium phase behavior in self-assembling materials.

The phase separation behavior of intrinsically disordered proteins (IDPs) is thought of as analogous to that of polymers that undergo equilibrium lower or upper critical solution temperature (LCST and UCST, respectively) phase transition. This view, however, ignores possible nonequilibrium properties of protein assemblies. Here, by studying IDP polymers (IDPPs) composed of repeat motifs that encode LCST or UCST phase behavior, we discovered that IDPs can access a wide spectrum of nonequilibrium, hysteretic phase behaviors. Experimentally and through simulations, we show that hysteresis in IDPPs is tunable and that it emerges through increasingly stable interchain interactions in the insoluble phase. To explore the utility of hysteretic IDPPs, we engineer self-assembling nanostructures with tunable stability. These findings shine light on the rich phase separation behavior of IDPs and illustrate hysteresis as a design parameter to program nonequilibrium phase behavior in self-assembling materials.

Intrinsically disordered proteins (IDPs) have received increasing attention in recent studies due to their structural heterogeneity and critical biological functions. To fully understand the structural properties and determine accurate ensembles of IDPs, molecular dynamics (MD) simulation was widely used to sample diverse conformations and reveal the structural dynamics. However, the classical state-of-the-art force fields perform well for folded proteins while being unsatisfactory for the simulations of disordered proteins reported in many previous studies. Thus, improved force fields were developed to precisely describe both folded proteins and disordered proteins. Preliminary tests show that our newly developed CHARMM36IDPSFF (C36IDPSFF) force field can well reproduce the experimental observables of several disordered proteins, but more tests on different types of proteins are needed to further evaluate the performance of C36IDPSFF. Here, we extensively simulate short peptides, disordered proteins, and fast-folding proteins as well as folded proteins, and compare the simulated results with the experimental observables. The simulation results show that C36IDPSFF could substantially reproduce the experimental observables for most of the tested proteins but some limitations are also found in the radius of gyration of large disordered proteins and the stability of fast-folding proteins. This force field will facilitate large scale studies of protein structural dynamics and functions using MD simulations.

Stress granules (SGs) form during cellular stress and are implicated in neurodegenerative diseases such as amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD). To yield insights into the role of SGs in pathophysiology, we performed a high-content screen to identify small molecules that alter SG properties in proliferative cells and human iPSC-derived motor neurons (iPS-MNs). One major class of active molecules contained extended planar aromatic moieties, suggesting a potential to intercalate in nucleic acids. Accordingly, we show that several hit compounds can prevent the RNA-dependent recruitment of the ALS-associated RNA-binding proteins (RBPs) TDP-43, FUS, and HNRNPA2B1 into SGs. We further demonstrate that transient SG formation contributes to persistent accumulation of TDP-43 into cytoplasmic puncta and that our hit compounds can reduce this accumulation in iPS-MNs from ALS patients. We propose that compounds with planar moieties represent a promising starting point to develop small-molecule therapeutics for treating ALS/FTD.

A number of intrinsically disordered proteins have been shown to self-assemble via liquid-liquid phase separation into protein-rich and dilute phases. The resulting coacervates can have important biological functions, and the ability to form these assemblies is dictated by the protein's primary amino acid sequence as well as by the solution conditions. We present a complete phase diagram for the simple coacervation of a polyampholyte intrinsically disordered protein using a field-theoretic simulation approach. We show that differences in the primary amino acid sequence and in the distribution of charged amino acids along the sequence lead to differences in the phase window for coacervation, with block-charged sequences having a larger coacervation window than sequences with a random patterning of charges. The model also captures how changing solution conditions modifies the phase diagram and can serve to guide experimental studies.

Phase separation of multivalent protein and RNA molecules underlies the biogenesis of biomolecular condensates such as membraneless organelles. In vivo, these condensates encompass hundreds of distinct types of molecules that typically organize into multilayered structures supporting the differential partitioning of molecules into distinct regions with distinct material properties. The interplay between driven (active) versus spontaneous (passive) processes that are required for enabling the formation of condensates with coexisting layers of distinct material properties remains unclear. Here, we deploy systematic experiments and simulations based on coarse-grained models to show that the collective interactions among the simplest, biologically relevant proteins and archetypal RNA molecules are sufficient for driving the spontaneous emergence of multilayered condensates with distinct material properties. These studies yield a set of rules regarding homotypic and heterotypic interactions that are likely to be relevant for understanding the interplay between active and passive processes that control the formation of functional biomolecular condensates.

Since publication of the crystal structure of protein kinase (PK)A three decades ago, a structural portrait of the conserved kinase core has been drawn. The next challenge is to elucidate structures of full-length kinases and to address the intrinsically disordered regions (IDRs) that typically flank the core as well as the small linear motifs (SLiMs) that are embedded within the IDRs. It is increasingly apparent that unstructured regions integrate the kinase catalytic chassis into multienzyme-based regulatory networks. The extracellular signal-regulated kinase-ribosomal S6 PK-phosphoinositide-dependent kinase (ERK-RSK-PDK) complex is an excellent example to demonstrate how IDRs and SLiMs govern communication between four different kinase catalytic cores to mediate activation and how in molecular terms these promote the formation of kinase heterodimers in a context dependent fashion.

Phase separation of multivalent protein and RNA molecules underlies the biogenesis of biomolecular condensates such as membraneless organelles. In vivo, these condensates encompass hundreds of distinct types of molecules that typically organize into multilayered structures supporting the differential partitioning of molecules into distinct regions with distinct material properties. The interplay between driven (active) versus spontaneous (passive) processes that are required for enabling the formation of condensates with coexisting layers of distinct material properties remains unclear. Here, we deploy systematic experiments and simulations based on coarse-grained models to show that the collective interactions among the simplest, biologically relevant proteins and archetypal RNA molecules are sufficient for driving the spontaneous emergence of multilayered condensates with distinct material properties. These studies yield a set of rules regarding homotypic and heterotypic interactions that are likely to be relevant for understanding the interplay between active and passive processes that control the formation of functional biomolecular condensates.

Molecular dynamics simulations of intrinsically disordered proteins (IDPs) can provide high resolution structural ensembles if the force field is accurate enough and if the simulation sufficiently samples the conformational space of the IDP with the correct weighting of sub-populations. Here, we investigate the combined force field-sampling problem by testing a standard force field as well as newer fixed charge force fields, the latter specifically motivated for better description of unfolded states and IDPs, and comparing them with a standard temperature replica exchange (TREx) protocol and a non-equilibrium Temperature Cool Walking (TCW) sampling algorithm. The force field and sampling combinations are used to characterize the structural ensembles of the amyloid-beta peptides Aβ42 and Aβ43, which both should be random coils as shown recently by experimental nuclear magnetic resonance (NMR) and 2D Förster resonance energy transfer (FRET) experiments. The results illustrate the key importance of the sampling algorithm: while the standard force field using TREx is in poor agreement with the NMR J-coupling and nuclear Overhauser effect and 2D FRET data, when using the TCW method, the standard and optimized protein-water force field combinations are in very good agreement with the same experimental data since the TCW sampling method produces qualitatively different ensembles than TREx. We also discuss the relative merit of the 2D FRET data when validating structural ensembles using the different force fields and sampling protocols investigated in this work for small IDPs such as the Aβ42 and Aβ43 peptides.

Folded proteins show a high degree of structural order and undergo (fairly constrained) collective motions related to their functions. On the other hand, intrinsically disordered proteins (IDPs), while lacking a well-defined three-dimensional structure, do exhibit some structural and dynamical ordering, but are less constrained in their motions than folded proteins. The larger structural plasticity of IDPs emphasizes the importance of entropically driven motions. Many IDPs undergo function-related disorder-to-order transitions driven by their interaction with specific binding partners. As experimental techniques become more sensitive and become better integrated with computational simulations, we are beginning to see how the modest structural ordering and large amplitude collective motions of IDPs endow them with an ability to mediate multiple interactions with different partners in the cell. To illustrate these points, here, we use Prostate-associated gene 4 (PAGE4), an IDP implicated in prostate cancer (PCa) as an example. We first review our previous efforts using molecular dynamics simulations based on atomistic AWSEM to study the conformational dynamics of PAGE4 and how its motions change in its different physiologically relevant phosphorylated forms. Our simulations quantitatively reproduced experimental observations and revealed how structural and dynamical ordering are encoded in the sequence of PAGE4 and can be modulated by different extents of phosphorylation by the kinases HIPK1 and CLK2. This ordering is reflected in changing populations of certain secondary structural elements as well as in the regularity of its collective motions. These ordered features are directly correlated with the functional interactions of WT-PAGE4, HIPK1-PAGE4 and CLK2-PAGE4 with the AP-1 signaling axis. These interactions give rise to repeated transitions between (high HIPK1-PAGE4, low CLK2-PAGE4) and (low HIPK1-PAGE4, high CLK2-PAGE4) cell phenotypes, which possess differing sensitivities to the standard PCa therapies, such as androgen deprivation therapy (ADT). We argue that, although the structural plasticity of an IDP is important in promoting promiscuous interactions, the modulation of the structural ordering is important for sculpting its interactions so as to rewire with agility biomolecular interaction networks with significant functional consequences.

The over-expression and aggregation of α-synuclein (αSyn) are linked to the onset and pathology of Parkinson's disease. Native monomeric αSyn exists in an intrinsically disordered ensemble of interconverting conformations, which has made its therapeutic targeting by small molecules highly challenging. Nonetheless, here we successfully target the monomeric structural ensemble of αSyn and thereby identify novel drug-like small molecules that impact multiple pathogenic processes. Using a surface plasmon resonance high-throughput screen, in which monomeric αSyn is incubated with microchips arrayed with tethered compounds, we identified novel αSyn interacting drug-like compounds. Because these small molecules could impact a variety of αSyn forms present in the ensemble, we tested representative hits for impact on multiple αSyn malfunctions in vitro and in cells including aggregation and perturbation of vesicular dynamics. We thereby identified a compound that inhibits αSyn misfolding and is neuroprotective, multiple compounds that restore phagocytosis impaired by αSyn overexpression, and a compound blocking cellular transmission of αSyn. Our studies demonstrate that drug-like small molecules that interact with native αSyn can impact a variety of its pathological processes. Thus, targeting the intrinsically disordered ensemble of αSyn offers a unique approach to the development of small molecule research tools and therapeutics for Parkinson's disease.

Folded proteins show a high degree of structural order and undergo (fairly constrained) collective motions related to their functions. On the other hand, intrinsically disordered proteins (IDPs), while lacking a well-defined three-dimensional structure, do exhibit some structural and dynamical ordering, but are less constrained in their motions than folded proteins. The larger structural plasticity of IDPs emphasizes the importance of entropically driven motions. Many IDPs undergo function-related disorder-to-order transitions driven by their interaction with specific binding partners. As experimental techniques become more sensitive and become better integrated with computational simulations, we are beginning to see how the modest structural ordering and large amplitude collective motions of IDPs endow them with an ability to mediate multiple interactions with different partners in the cell. To illustrate these points, here, we use Prostate-associated gene 4 (PAGE4), an IDP implicated in prostate cancer (PCa) as an example. We first review our previous efforts using molecular dynamics simulations based on atomistic AWSEM to study the conformational dynamics of PAGE4 and how its motions change in its different physiologically relevant phosphorylated forms. Our simulations quantitatively reproduced experimental observations and revealed how structural and dynamical ordering are encoded in the sequence of PAGE4 and can be modulated by different extents of phosphorylation by the kinases HIPK1 and CLK2. This ordering is reflected in changing populations of certain secondary structural elements as well as in the regularity of its collective motions. These ordered features are directly correlated with the functional interactions of WT-PAGE4, HIPK1-PAGE4 and CLK2-PAGE4 with the AP-1 signaling axis. These interactions give rise to repeated transitions between (high HIPK1-PAGE4, low CLK2-PAGE4) and (low HIPK1-PAGE4, high CLK2-PAGE4) cell phenotypes, which possess differing sensitivities to the standard PCa therapies, such as androgen deprivation therapy (ADT). We argue that, although the structural plasticity of an IDP is important in promoting promiscuous interactions, the modulation of the structural ordering is important for sculpting its interactions so as to rewire with agility biomolecular interaction networks with significant functional consequences.