Structural study of the intrinsically disordered tardigrade damage suppressor protein (Dsup) and its complex with DNA.

Studies of proteins, found in one of the most stress-resistant animals tardigrade Ramazzottius varieornatus, aim to reveal molecular principles of extreme tolerance to various types of stress and developing applications based on them for medicine, biotechnology, pharmacy, and space research. Tardigrade DNA/RNA-binding damage suppressor protein (Dsup) reduces DNA damage caused by reactive oxygen spices (ROS) produced upon irradiation and oxidative stresses in Dsup-expressing transgenic organisms. This work is focused on the determination of structural features of Dsup protein and Dsup-DNA complex, which refines details of protective mechanism. For the first time, intrinsically disordered nature of Dsup protein with highly flexible structure was experimentally proven and characterized by the combination of small angle X-ray scattering (SAXS) technique, circular dichroism spectroscopy, and computational methods. Low resolution models of Dsup protein and an ensemble of conformations were presented. In addition, we have shown that Dsup forms fuzzy complex with DNA.

SHARK enables sensitive detection of evolutionary homologs and functional analogs in unalignable and disordered sequences.

Intrinsically disordered regions (IDRs) are structurally flexible protein segments with regulatory functions in multiple contexts, such as in the assembly of biomolecular condensates. Since IDRs undergo more rapid evolution than ordered regions, identifying homology of such poorly conserved regions remains challenging for state-of-the-art alignment-based methods that rely on position-specific conservation of residues. Thus, systematic functional annotation and evolutionary analysis of IDRs have been limited, despite them comprising ~21% of proteins. To accurately assess homology between unalignable sequences, we developed an alignment-free sequence comparison algorithm, SHARK (Similarity/Homology Assessment by Relating K-mers). We trained SHARK-dive, a machine learning homology classifier, which achieved superior performance to standard alignment-based approaches in assessing evolutionary homology in unalignable sequences. Furthermore, it correctly identified dissimilar but functionally analogous IDRs in IDR-replacement experiments reported in the literature, whereas alignment-based tools were incapable of detecting such functional relationships. SHARK-dive not only predicts functionally similar IDRs at a proteome-wide scale but also identifies cryptic sequence properties and motifs that drive remote homology and analogy, thereby providing interpretable and experimentally verifiable hypotheses of the sequence determinants that underlie such relationships. SHARK-dive acts as an alternative to alignment to facilitate systematic analysis and functional annotation of the unalignable protein universe.

Rapid Interpretation of Protein Backbone Rotation Dynamics Directly from Spin Relaxation Data.

Besides their structure, dynamics is pivotal for protein functions, particularly for intrinsically disordered proteins (IDPs) that do not fold into a fixed 3D structure. However, the detection of protein dynamics is difficult for IDPs and other disordered biomolecules. NMR spin relaxation rates are sensitive to the rapid rotations of chemical bonds, but their interpretation is arduous for IDPs or molecular assemblies with a complex dynamic landscape. Here we demonstrate numerically that the dynamics of a wide range of proteins, from short peptides to partially disordered proteins and peptides in micelles, can be characterized by calculating the total effective correlation times of protein backbone N-H bond rotations, τeff, from experimentally measured transverse 15N spin relaxation rates, R2, using a linear relation. Our results enable the determination of magnetic-field-independent and intuitively understandable parameters describing protein dynamics at different regions of the sequence directly from experiments. A practical advance of the approach is demonstrated by analyzing partially disordered proteins in which rotations of disordered regions occur with timescales of 1-2 ns, independent of their size, suggesting that rotations of disordered and folded regions are uncoupled in these proteins.

Disordered regions of human eIF4B orchestrate a dynamic self-association landscape.

Eukaryotic translation initiation factor eIF4B is required for efficient cap-dependent translation, it is overexpressed in cancer cells, and may influence stress granule formation. Due to the high degree of intrinsic disorder, eIF4B is rarely observed in cryo-EM structures of translation complexes and only ever by its single structured RNA recognition motif domain, leaving the molecular details of its large intrinsically disordered region (IDR) unknown. By integrating experiments and simulations we demonstrate that eIF4B IDR orchestrates and fine-tunes an intricate transition from monomers to a condensed phase, in which large-size dynamic oligomers form before mesoscopic phase separation. Single-molecule spectroscopy combined with molecular simulations enabled us to characterize the conformational ensembles and underlying intra- and intermolecular dynamics across the oligomerization transition. The observed sensitivity to ionic strength and molecular crowding in the self-association landscape suggests potential regulation of eIF4B nanoscopic and mesoscopic behaviors such as driven by protein modifications, binding partners or changes to the cellular environment.

Decoding Missense Variants by Incorporating Phase Separation via Machine Learning.

Computational models have made significant progress in predicting the effect of protein variants. However, deciphering numerous variants of uncertain significance (VUS) located within intrinsically disordered regions (IDRs) remains challenging. To address this issue, we introduce phase separation, which is tightly linked to IDRs, into the investigation of missense variants. Phase separation is vital for multiple physiological processes. By leveraging missense variants that alter phase separation propensity, we develop a machine learning approach named PSMutPred to predict the impact of missense mutations on phase separation. PSMutPred demonstrates robust performance in predicting missense variants that affect natural phase separation. In vitro experiments further underscore its validity. By applying PSMutPred on over 522,000 ClinVar missense variants, it significantly contributes to decoding the pathogenesis of disease variants, especially those in IDRs. Our work provides insights into the understanding of a vast number of VUSs in IDRs, expediting clinical interpretation and diagnosis.

Deciphering the intrinsically disordered characteristics of the FG-Nups through the lens of polymer physics.

The nuclear pore complex (NPC) is a critical gateway regulating molecular transport between the nucleus and cytoplasm. It allows small molecules to pass freely, while larger molecules require nuclear transport receptors to traverse the barrier. This selective permeability is maintained by phenylalanine-glycine-rich nucleoporins (FG-Nups), intrinsically disordered proteins that fill the NPC's central channel. The disordered and flexible nature of FG-Nups complicates their spatial characterization with conventional structural biology techniques. To address this challenge, polymer physics offers a valuable framework for describing FG-Nup behavior, reducing their complex structures to a few key parameters. In this review, we explore how polymer physics models FG-Nups using these parameters and discuss experimental efforts to quantify them in various contexts, providing insights into the conformational properties of FG-Nups.

Transcription regulation through selective partitioning: Weak interactions with a strong foundation.

In this issue of Molecular Cell, De La Cruz, Pradhan, Veettil et al.1 examine how selective partitioning of proteins via low-affinity IDR-dependent interactions may help regulate RNA polymerase II (RNA Pol II) function and identify sequence features that drive partitioning in cells.

Disorder-mediated interactions target proteins to specific condensates.

Selective compartmentalization of cellular contents is fundamental to the regulation of biochemistry. Although membrane-bound organelles control composition by using a semi-permeable barrier, biomolecular condensates rely on interactions among constituents to determine composition. Condensates are formed by dynamic multivalent interactions, often involving intrinsically disordered regions (IDRs) of proteins, yet whether distinct compositions can arise from these dynamic interactions is not known. Here, by comparative analysis of proteins differentially partitioned by two different condensates, we find that distinct compositions arise through specific IDR-mediated interactions. The IDRs of differentially partitioned proteins are necessary and sufficient for selective partitioning. Distinct sequence features are required for IDRs to partition, and swapping these sequence features changes the specificity of partitioning. Swapping whole IDRs retargets proteins and their biochemical activity to different condensates. Our results demonstrate that IDR-mediated interactions can target proteins to specific condensates, enabling the spatial regulation of biochemistry within the cell.

The protein domains of vertebrate species in which selection is more effective have greater intrinsic structural disorder.

The nearly neutral theory of molecular evolution posits variation among species in the effectiveness of selection. In an idealized model, the census population size determines both this minimum magnitude of the selection coefficient required for deleterious variants to be reliably purged, and the amount of neutral diversity. Empirically, an 'effective population size' is often estimated from the amount of putatively neutral genetic diversity and is assumed to also capture a species' effectiveness of selection. A potentially more direct measure of the effectiveness of selection is the degree to which selection maintains preferred codons. However, past metrics that compare codon bias across species are confounded by among-species variation in %GC content and/or amino acid composition. Here, we propose a new Codon Adaptation Index of Species (CAIS), based on Kullback-Leibler divergence, that corrects for both confounders. We demonstrate the use of CAIS correlations, as well as the Effective Number of Codons, to show that the protein domains of more highly adapted vertebrate species evolve higher intrinsic structural disorder.

Evolution is the process through which populations change over time, starting with mutations in the genetic sequence of an organism. Many of these mutations harm the survival and reproduction of an organism, but only by a very small amount. Some species, especially those with large populations, can purge these slightly harmful mutations more effectively than other species. This fact has been used by the 'drift barrier theory' to explain various profound differences amongst species, including differences in biological complexity. In this theory, the effectiveness of eliminating slightly harmful mutations is specified by an 'effective' population size, which depends on factors beyond just the number of individuals in the population. Effective population size is normally calculated from the amount of time a 'neutral' mutation (one with no effect at all) stays in the population before becoming lost or taking over. Estimating this time requires both representative data for genetic diversity and knowledge of the mutation rate. A major limitation is that these data are unavailable for most species. A second limitation is that a brief, temporary reduction in the number of individuals has an oversized impact on the metric, relative to its impact on the number of slighly harmful mutations accumulated. Weibel, Wheeler et al. developed a new metric to more directly determine how effectively a species purges slightly harmful mutations. Their approach is based on the fact that the genetic code has 'synonymous' sequences. These sequences code for the same amino acid building block, with one of these sequences being only slightly preferred over others. The metric by Weibel, Wheeler et al. quantifies the proportion of the genome from which less preferred synonymous sequences have been effectively purged. It judges a population to have a higher effective population size when the usage of synonymous sequences departs further from the usage predicted from mutational processes. The researchers expected that natural selection would favour 'ordered' proteins with robust three-dimensional structures, i.e., that species with a higher effective population size would tend to have more ordered versions of a protein. Instead, they found the opposite: species with a higher effective population size tend to have more disordered versions of the same protein. This changes our view of how natural selection acts on proteins. Why species are so different remains a fundamental question in biology. Weibel, Wheeler et al. provide a useful tool for future applications of drift barrier theory to a broad range of ways that species differ.

Replication licensing regulated by a short linear motif within an intrinsically disordered region of origin recognition complex.

In eukaryotes, the origin recognition complex (ORC) faciliates the assembly of pre-replicative complex (pre-RC) at origin DNA for replication licensing. Here we show that the N-terminal intrinsically disordered region (IDR) of the yeast Orc2 subunit is crucial for this process. Removing a segment (residues 176-200) from Orc2-IDR or mutating a key isoleucine (194) significantly inhibits replication initiation across the genome. These Orc2-IDR mutants are capable of assembling the ORC-Cdc6-Cdt1-Mcm2-7 intermediate, which exhibits impaired ATP hydrolysis and fails to be convered into the subsequent Mcm2-7-ORC complex and pre-RC. These defects can be partially rescued by the Orc2-IDR peptide. Moreover, the phosphorylation of this Orc2-IDR region by S cyclin-dependent kinase blocks its binding to Mcm2-7 complex, causing a defective pre-RC assembly. Our findings provide important insights into the multifaceted roles of ORC in supporting origin licensing during the G1 phase and its regulation to restrict origin firing within the S phase.

flDPnn2: Accurate and Fast Predictor of Intrinsic Disorder in Proteins.

Prediction of the intrinsic disorder in protein sequences is an active research area, with well over 100 predictors that were released to date. These efforts are motivated by the functional importance and high levels of abundance of intrinsic disorder, combined with relatively low amounts of experimental annotations. The disorder predictors are periodically evaluated by independent assessors in the Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiments. The recently completed CAID2 experiment assessed close to 40 state-of-the-art methods demonstrating that some of them produce accurate results. In particular, flDPnn2 method, which is the successor of flDPnn that performed well in the CAID1 experiment, secured the overall most accurate results on the Disorder-NOX dataset in CAID2. flDPnn2 implements a number of improvements when compared to its predecessor including changes to the inputs, increased size of the deep network model that we retrained on a larger training set, and addition of an alignment module. Using results from CAID2, we show that flDPnn2 produces accurate predictions very quickly, modestly improving over the accuracy of flDPnn and reducing the runtime by half, to about 27 s per protein. flDPnn2 is freely available as a convenient web server at http://biomine.cs.vcu.edu/servers/flDPnn2/.

Ordering the disordered.

In this Voices article, we introduce seven impressive young group leaders that presented their work at the recent Gordon Research Conference "Biophysics and biology of intrinsically disordered proteins" in Les Diablerets, Switzerland. We asked them to tell us more about their careers and their fascinating research on proteins that do not adopt a single-folded structure.

Conformational dependence of chemical shifts in the proline rich region of TAU protein.

Nuclear magnetic resonance (NMR) is an important method for structure elucidation of proteins, as it is an easily accessible and well understood method. To characterize intrinsically disordered proteins (IDPs) using computational models it is often necessary to analyze and integrate calculated observables with measurements derived from solution NMR experiments. In this case study, we investigate whether and which chemical shifts of the proline-rich region of Tau protein (residues 210-240) offer information about the conformational state to distinguish two different microscopic conformers. Using multiple computational methods, the chemical shifts of these two conformationally distinct structures are calculated. The different methods are compared regarding their ability to compute chemical shifts that are sensitive to conformational change. The analysis of the data shows significant differences between the available methods and gives suggestions for an improved pathway for ensemble reweighting. Nevertheless, the variation in the chemical shifts which are predicted for configurations that are commonly considered to belong to the same conformation is such that this obscures a comparison between distinct conformations. Conformational sensitivity is found for up to ∼26% of calculated chemical shifts. It is found to be unrelated to the atom element and has a minor relationship with the change in the corresponding ϕ dihedral angle.

ECT2 peptide sequences outside the YTH domain regulate its m6A-RNA binding.

The m6A epitranscriptomic mark is the most abundant and widespread internal RNA chemical modification, which through the control of RNA acts as an important factor of eukaryote reproduction, growth, morphogenesis and stress response. The main m6A readers constitute a super family of proteins with hundreds of members that share a so-called YTH RNA binding domain. The majority of YTH proteins carry no obvious additional domain except for an Intrinsically Disordered Region (IDR). In Arabidopsis thaliana IDRs are important for the functional specialization among the different YTH proteins, known as Evolutionarily Conserved C-Terminal region, ECT 1 to 12. Here by studying the ECT2 protein and using an in vitro biochemical characterization, we show that full-length ECT2 and its YTH domain alone have a distinct ability to bind m6A, conversely to previously characterized YTH readers. We identify peptide regions outside of ECT2 YTH domain, in the N-terminal IDR, that regulate its binding to m6A-methylated RNA. Furthermore, we show that the selectivity of ECT2 binding for m6A is enhanced by a high uridine content within its neighbouring sequence, where ECT2 N-terminal IDR is believed to contact the target RNA in vivo. Finally, we also identify small structural elements, located next to ECT2 YTH domain and conserved in a large set of YTH proteins, that enhance its binding to m6A-methylated RNA. We propose from these findings that some of these regulatory regions are not limited to ECT2 or YTH readers of flowering plants but may be widespread among eukaryotic YTH readers.

Time-resolved NMR detection of prolyl-hydroxylation in intrinsically disordered region of HIF-1α.

Prolyl-hydroxylation is an oxygen-dependent posttranslational modification (PTM) that is known to regulate fibril formation of collagenous proteins and modulate cellular expression of hypoxia-inducible factor (HIF) α subunits. However, our understanding of this important but relatively rare PTM has remained incomplete due to the lack of biophysical methodologies that can directly measure multiple prolyl-hydroxylation events within intrinsically disordered proteins. Here, we describe a real-time 13C-direct detection NMR-based assay for studying the hydroxylation of two evolutionarily conserved prolines (P402 and P564) simultaneously in the intrinsically disordered oxygen-dependent degradation domain of hypoxic-inducible factor 1α by exploiting the "proton-less" nature of prolines. We show unambiguously that P564 is rapidly hydroxylated in a time-resolved manner while P402 hydroxylation lags significantly behind that of P564. The differential hydroxylation rate was negligibly influenced by the binding affinity to prolyl-hydroxylase enzyme, but rather by the surrounding amino acid composition, particularly the conserved tyrosine residue at the +1 position to P564. These findings support the unanticipated notion that the evolutionarily conserved P402 seemingly has a minimal impact in normal oxygen-sensing pathway.

A pH-Dependent Coarse-Grained Model for Disordered Proteins: Histidine Interactions Modulate Conformational Ensembles.

Histidine (His) presents a unique challenge for modeling disordered protein conformations, as it is versatile and occurs in both the neutral (His0) and positively charged (His+) states. These His charge states, which are enabled by its imidazole side chain, influence the electrostatic and short-range interactions of His residues, which potentially engage in cation-π, π-π, and charge-charge interactions. Existing coarse-grained (CG) models often simplify His representation by assigning it an average charge, thereby neglecting these potential short-range interactions. To address this gap, we developed a model for intrinsically disordered proteins (IDPs) that accounts for the properties of histidine (H). The resulting IDPH model is a 21-amino acid CG model incorporating both His charge states. We show that interactions involving previously neglected His0 are critical for accurate modeling at high pH, where they significantly influence the compaction of His-rich IDPs such as Histatin-5 and CPEB4. These interactions contribute to structural stabilizations primarily via His0-His0 and His0-Arg interactions, which are overlooked in models focusing solely on the charged His+ state.

Mixtures of Intrinsically Disordered Neuronal Protein Tau and Anionic Liposomes Reveal Distinct Anionic Liposome-Tau Complexes Coexisting with Tau Liquid-Liquid Phase-Separated Coacervates.

Tau, an intrinsically disordered neuronal protein and polyampholyte with an overall positive charge, is a microtubule (MT) associated protein that binds to anionic domains of MTs and suppresses their dynamic instability. Aberrant tau-MT interactions are implicated in Alzheimer's and other neurodegenerative diseases. Here, we studied the interactions between full-length human protein tau and other negatively charged binding substrates, as revealed by differential interference contrast (DIC) and fluorescence microscopy. As a binding substrate, we chose anionic liposomes (ALs) containing either 1,2-dioleoyl-sn-glycero-3-phosphatidylserine (DOPS, -1e) or 1,2-dioleoyl-sn-glycero-3-phosphatidylglycerol (DOPG, -1e) mixed with zwitterionic 1,2-dioleoyl-sn-glycero-3-phosphatidylcholine (DOPC) to mimic anionic plasma membranes of axons where tau resides. At low salt concentrations (0 to 10 mM KCl or NaCl) with minimal charge screening, reaction mixtures of tau and ALs resulted in the formation of distinct states of AL-tau complexes coexisting with liquid-liquid phase-separated tau self-coacervates arising from the polyampholytic nature of tau containing cationic and anionic domains. AL-tau complexes (i.e. tau-lipoplexes) exhibited distinct types of morphologies. This included large ∼20-30 µm tau-decorated giant vesicles with additional smaller liposomes with bound tau attached to the giant vesicles and tau-mediated finite-size assemblies of small liposomes. As the salt concentration was increased to near and above 150 mM for 1:1 electrolytes, AL-tau complexes remained stable, while tau self-coacervate droplets were found to dissolve, indicative of the breaking of (anionic/cationic) electrostatic bonds between tau chains due to increased charge screening. The findings are consistent with the hypothesis that distinct cationic domains of tau may interact with anionic lipid domains of the lumen-facing monolayer of the axon's plasma membrane, suggesting the possibility of transient yet robust interactions near relevant ionic strengths found in neurons.

Balancing thermodynamic stability, dynamics, and kinetics in phase separation of intrinsically disordered proteins.

Intrinsically disordered proteins (IDPs) are prevalent participants in liquid-liquid phase separation due to their inherent potential for promoting multivalent binding. Understanding the underlying mechanisms of phase separation is challenging, as phase separation is a complex process, involving numerous molecules and various types of interactions. Here, we used a simplified coarse-grained model of IDPs to investigate the thermodynamic stability of the dense phase, conformational properties of IDPs, chain dynamics, and kinetic rates of forming condensates. We focused on the IDP system, in which the oppositely charged IDPs are maximally segregated, inherently possessing a high propensity for phase separation. By varying interaction strengths, salt concentrations, and temperatures, we observed that IDPs in the dense phase exhibited highly conserved conformational characteristics, which are more extended than those in the dilute phase. Although the chain motions and global conformational dynamics of IDPs in the condensates are slow due to the high viscosity, local chain flexibility at the short timescales is largely preserved with respect to that at the free state. Strikingly, we observed a non-monotonic relationship between interaction strengths and kinetic rates for forming condensates. As strong interactions of IDPs result in high stable condensates, our results suggest that the thermodynamics and kinetics of phase separation are decoupled and optimized by the speed-stability balance through underlying molecular interactions. Our findings contribute to the molecular-level understanding of phase separation and offer valuable insights into the developments of engineering strategies for precise regulation of biomolecular condensates.

An intrinsically disordered region in MED13 turns Mediator on/off on cue.

Complementary studies by Zhao et al.1 and Chen et al.2 reveal how an intrinsically disordered region in MED13 controls mutually exclusive binding of RNA Polymerase II and CDK8 kinase module to Mediator, switching Mediator and transcription activation on and off.

Extending computational protein design to intrinsically disordered proteins.

Advances in the accuracy and throughput of molecular simulations usher in a new era in the structural biology of disordered proteins.