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Poly(ADP-ribose) polymerase 1 (PARP1) is one of the first responders to DNA damage and plays crucial roles in recruiting DNA repair proteins through its activity - poly(ADP-ribosyl)ation (PARylation). The enrichment of DNA repair proteins at sites of DNA damage has been described as the formation of a biomolecular condensate. However, it remains unclear how exactly PARP1 and PARylation contribute to the formation and organization of DNA repair condensates. Using recombinant human single-strand repair proteins in vitro, we find that PARP1 readily forms viscous biomolecular condensates in a DNA-dependent manner and that this depends on its three zinc finger (ZnF) domains. PARylation enhances PARP1 condensation in a PAR chain length-dependent manner and increases the internal dynamics of PARP1 condensates. DNA and single-strand break repair proteins XRCC1, LigIII, Polβ, and FUS partition in PARP1 condensates, although in different patterns. While Polβ and FUS are both homogeneously mixed within PARP1 condensates, FUS enrichment is greatly enhanced upon PARylation whereas Polβ partitioning is not. XRCC1 and LigIII display an inhomogeneous organization within PARP1 condensates; their enrichment in these multiphase condensates is enhanced by PARylation. Functionally, PARP1 condensates concentrate short DNA fragments, which correlates with PARP1 clusters compacting long DNA and bridging DNA ends. Furthermore, the presence of PARP1 condensates significantly promotes DNA ligation upon PARylation. These findings provide insight into how PARP1 condensation and PARylation regulate the assembly and biochemical activities of DNA repair factors, which may inform on how PARPs function in DNA repair foci and other PAR-driven condensates in cells., (© 2024. The Author(s).)

Biomolecules can be sequestered into membrane-less compartments, referred to as biomolecular condensates. Experimental and computational methods have helped define the physical-chemical properties of condensates. Less is known about how the high macromolecule concentrations in condensed phases contribute "solvent" interactions that can remodel the free-energy landscape of other condensate-resident proteins, altering thermally accessible conformations and, in turn, modulating function. Here, we use solution NMR spectroscopy to obtain atomic resolution insights into the interactions between the immature form of superoxide dismutase 1 (SOD1), which can mislocalize and aggregate in stress granules, and the RNA-binding protein CAPRIN1, a component of stress granules. NMR studies of CAPRIN1:SOD1 interactions, focused on both unfolded and folded SOD1 states in mixed phase and demixed CAPRIN1-based condensates, establish that CAPRIN1 shifts the SOD1 folding equilibrium toward the unfolded state through preferential interactions with the unfolded ensemble, with little change to the structure of the folded conformation. Key contacts between CAPRIN1 and the H80-H120 region of unfolded SOD1 are identified, as well as SOD1 interaction sites near both the arginine-rich and aromatic-rich regions of CAPRIN1. Unfolding of immature SOD1 in the CAPRIN1 condensed phase is shown to be coupled to aggregation, while a more stable zinc-bound, dimeric form of SOD1 is less susceptible to unfolding when solvated by CAPRIN1. Our work underscores the impact of the condensate solvent environment on the conformational states of resident proteins and supports the hypothesis that ALS mutations that decrease metal binding or dimerization function as drivers of aggregation in condensates., Competing Interests: Competing interests statement:The authors declare no competing interest.

Biomolecular condensates can influence cellular function in a number of ways, including by changing the structural dynamics and conformational equilibria of the molecules partitioned within them. Here we use methyl transverse relaxation optimized spectroscopy (methyl-TROSY) NMR in conjunction with 2'- O -methyl labeling of RNA to characterize the thermodynamics and kinetics of RNA-RNA base pairing in condensates formed by the C-terminal intrinsically disordered region of CAPRIN1, an RNA-binding protein involved in RNA transport, translation, and stability. CAPRIN1 condensates destabilize RNA-RNA base pairing, resulting from a ∼270-fold decrease and a concomitant ∼15-fold increase in the on- and off-rates for duplex formation, respectively. The ∼30-fold slower diffusion of RNA single strands within the condensed phase partially accounts for the reduced on-rate, but the further ∼9-fold reduction likely reflects shedding of CAPRIN1 chains that are interacting with the RNA prior to hybridization. Our study emphasizes the important role of protein solvation in modulating nucleic acid recognition processes inside condensates.

The ability to sense and respond to osmotic fluctuations is critical for the maintenance of cellular integrity. We used gene co-essentiality analysis to identify an unappreciated relationship between TSC22D2, WNK1, and NRBP1 in regulating cell volume homeostasis. All of these genes have paralogs and are functionally buffered for osmo-sensing and cell volume control. Within seconds of hyperosmotic stress, TSC22D, WNK, and NRBP family members physically associate into biomolecular condensates, a process that is dependent on intrinsically disordered regions (IDRs). A close examination of these protein families across metazoans revealed that TSC22D genes evolved alongside a domain in NRBPs that specifically binds to TSC22D proteins, which we have termed NbrT (NRBP binding region with TSC22D), and this co-evolution is accompanied by rapid IDR length expansion in WNK-family kinases. Our study reveals that TSC22D, WNK, and NRBP genes evolved in metazoans to co-regulate rapid cell volume changes in response to osmolarity., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

The compaction of chromatin into mitotic chromosomes is essential for faithful transmission of the genome during cell division. In eukaryotes, chromosome morphogenesis is regulated by the condensin complex, though the exact mechanism used to target condensin to chromatin and initiate condensation is not understood. Here, we reveal that condensin contains an intrinsically disordered region (IDR) that modulates its association with chromatin in early mitosis and exhibits phase separation. We describe DNA-binding motifs within the IDR that, upon deletion, inflict striking defects in chromosome condensation and segregation, ill-timed condensin turnover on chromatin, and cell death. Importantly, we demonstrate that the condensin IDR can impart cell cycle regulatory functions when transferred to other subunits within the complex, indicating its autonomous nature. Collectively, our study unveils the molecular basis for the initiation of chromosome condensation in early mitosis and how this process ultimately promotes genomic stability and faultless cell division., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

In his commentary in this issue of Molecular Cell, 1 Struhl reasons that the term "intrinsically disordered regions" represents a vague and confusing concept for protein function. However, the term "intrinsically disordered" highlights the important physicochemical characteristic of conformational heterogeneity. Thus, "intrinsically disordered" is the counterpart to the term "folded, " with neither term having specific functional implications., Competing Interests: Declaration of interests The authors declare no conflict of interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Nucleosomes, the basic structural units of chromatin, hinder recruitment and activity of various DNA repair proteins, necessitating modifications that enhance DNA accessibility. Poly(ADP-ribosyl)ation (PARylation) of proteins near damage sites is an essential initiation step in several DNA-repair pathways; however, its effects on nucleosome structural dynamics and organization are unclear. Using NMR, cryoelectron microscopy (cryo-EM), and biochemical assays, we show that PARylation enhances motions of the histone H3 tail and DNA, leaving the configuration of the core intact while also stimulating nuclease digestion and ligation of nicked nucleosomal DNA by LIG3. PARylation disrupted interactions between nucleosomes, preventing self-association. Addition of LIG3 and XRCC1 to PARylated nucleosomes generated condensates that selectively partition DNA repair-associated proteins in a PAR- and phosphorylation-dependent manner in vitro. Our results establish that PARylation influences nucleosomes across different length scales, extending from the atom-level motions of histone tails to the mesoscale formation of condensates with selective compositions., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 Elsevier Inc. All rights reserved.)

We developed a medium-throughput assay that can measure the time-dependent distribution of RNA products generated as a deadenylase degrades a polyadenosine (poly(A)) RNA tract, thereby providing insight into the mechanism of deadenylation. Importantly, this assay can be performed in both homogeneous and heterogeneous environments without relying on gel electrophoresis of RNA products or coupled enzymatic reactions that indirectly report on the RNA distribution through the detection of freed adenosine monophosphate. In parallel, we have established an open-source, Python-based command-line software package, deadenylationkinetics, that can be used to numerically simulate and/or fit the datasets afforded by our assay with different deadenylation mechanisms to determine the most likely case and estimate the associated rate constants. In this chapter, we detail the implementation of our method and the quantification of poly(A) RNA binding and degradation kinetics in application to a truncated version of CNOT7 from the CCR4-NOT deadenylation complex, which serves as a model deadenylase with enhanced activity., (© 2024. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.)

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 LDRS's Python API for scripting the same way they can use any part of IDPConformerGenerator's 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 IDPConformerGenerator's official documentation pages (https://idpconformergenerator.readthedocs.io/en/latest/)., (© The Author(s) 2023. Published by Oxford University Press.)

Accurate potential energy models of proteins must describe the many different types of noncovalent interactions that contribute to a protein's stability and structure. Pi-pi contacts are ubiquitous structural motifs in all proteins, occurring between aromatic and nonaromatic residues and play a nontrivial role in protein folding and in the formation of biomolecular condensates. Guided by a geometric criterion for isolating pi-pi contacts from classical molecular dynamics simulations of proteins, we use quantum mechanical energy decomposition analysis to determine the molecular interactions that stabilize different pi-pi contact motifs. We find that neutral pi-pi interactions in proteins are dominated by Pauli repulsion and London dispersion rather than repulsive quadrupole electrostatics, which is central to the textbook Hunter-Sanders model. This results in a notable lack of variability in the interaction profiles of neutral pi-pi contacts even with extreme changes in the dielectric medium, explaining the prevalence of pi-stacked arrangements in and between proteins. We also find interactions involving pi-containing anions and cations to be extremely malleable, interacting like neutral pi-pi contacts in polar media and like typical ion-pi interactions in nonpolar environments. Like-charged pairs such as arginine-arginine contacts are particularly sensitive to the polarity of their immediate surroundings and exhibit canonical pi-pi stacking behavior only if the interaction is mediated by environmental effects, such as aqueous solvation.

The AlphaFold Protein Structure Database contains predicted structures for millions of proteins. For the majority of human proteins that contain intrinsically disordered regions (IDRs), which do not adopt a stable structure, it is generally assumed that these regions have low AlphaFold2 confidence scores that reflect low-confidence structural predictions. Here, we show that AlphaFold2 assigns confident structures to nearly 15% of human IDRs. By comparison to experimental NMR data for a subset of IDRs that are known to conditionally fold (i.e., upon binding or under other specific conditions), we find that AlphaFold2 often predicts the structure of the conditionally folded state. Based on databases of IDRs that are known to conditionally fold, we estimate that AlphaFold2 can identify conditionally folding IDRs at a precision as high as 88% at a 10% false positive rate, which is remarkable considering that conditionally folded IDR structures were minimally represented in its training data. We find that human disease mutations are nearly fivefold enriched in conditionally folded IDRs over IDRs in general and that up to 80% of IDRs in prokaryotes are predicted to conditionally fold, compared to less than 20% of eukaryotic IDRs. These results indicate that a large majority of IDRs in the proteomes of human and other eukaryotes function in the absence of conditional folding, but the regions that do acquire folds are more sensitive to mutations. We emphasize that the AlphaFold2 predictions do not reveal functionally relevant structural plasticity within IDRs and cannot offer realistic ensemble representations of conditionally folded IDRs.

The intrinsically disordered 4E-BP2 protein regulates mRNA cap-dependent translation through interaction with the predominantly folded eukaryotic initiation factor 4E (eIF4E). Phosphorylation of 4E-BP2 dramatically reduces the level of eIF4E binding, in part by stabilizing a binding-incompatible folded domain. Here, we used a Rosetta-based sampling algorithm optimized for IDRs to generate initial ensembles for two phospho forms of 4E-BP2, non- and 5-fold phosphorylated (NP and 5P, respectively), with the 5P folded domain flanked by N- and C-terminal IDRs (N-IDR and C-IDR, respectively). We then applied an integrative Bayesian approach to obtain NP and 5P conformational ensembles that agree with experimental data from nuclear magnetic resonance, small-angle X-ray scattering, and single-molecule Förster resonance energy transfer (smFRET). For the NP state, inter-residue distance scaling and 2D maps revealed the role of charge segregation and pi interactions in driving contacts between distal regions of the chain (∼70 residues apart). The 5P ensemble shows prominent contacts of the N-IDR region with the two phosphosites in the folded domain, pT37 and pT46, and, to a lesser extent, delocalized interactions with the C-IDR region. Agglomerative hierarchical clustering led to partitioning of each of the two ensembles into four clusters with different global dimensions and contact maps. This helped delineate an NP cluster that, based on our smFRET data, is compatible with the eIF4E-bound state. 5P clusters were differentiated by interactions of C-IDR with the folded domain and of the N-IDR with the two phosphosites in the folded domain. Our study provides both a better visualization of fundamental structural poses of 4E-BP2 and a set of falsifiable insights on intrachain interactions that bias folding and binding of this protein.

We consider a generic representation problem of internal coordinates (bond lengths, valence angles, and dihedral angles) and their transformation to 3-dimensional Cartesian coordinates of a biomolecule. We show that the internal-to-Cartesian process relies on correctly predicting chemically subtle correlations among the internal coordinates themselves, and learning these correlations increases the fidelity of the Cartesian representation. We developed a machine learning algorithm, Int2Cart, to predict bond lengths and bond angles from backbone torsion angles and residue types of a protein, which allows reconstruction of protein structures better than using fixed bond lengths and bond angles or a static library method that relies on backbone torsion angles and residue types in a local environment. The method is able to be used for structure validation, as we show that the agreement between Int2Cart-predicted bond geometries and those from an AlphaFold 2 model can be used to estimate model quality. Additionally, by using Int2Cart to reconstruct an IDP ensemble, we are able to decrease the clash rate during modeling. The Int2Cart algorithm has been implemented as a publicly accessible python package at https://github.com/THGLab/int2cart.

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., (© 2023 Author(s). Published under an exclusive license by AIP Publishing.)

O-GlcNAc transferase (OGT) is an essential glycosylating enzyme that catalyzes the addition of N-acetylglucosamine to serine or threonine residues of nuclear and cytoplasmic proteins. The enzyme glycosylates a broad range of peptide sequences and the prediction of glycosylation sites has proven challenging. The lack of an experimentally verified set of polypeptide sequences that are not glycosylated by OGT has made prediction of legitimate glycosylation sites more difficult. Here, we tested a number of intrinsically disordered protein regions as substrates of OGT to establish a set of sequences that are not glycosylated by OGT. The negative data set suggests an amino acid compositional bias for OGT targets. This compositional bias was validated by modifying the amino acid composition of the protein fused in sarcoma (FUS) to enhance glycosylation. NMR experiments demonstrate that the tetratricopeptide repeat region of OGT can bind FUS and that glycosylation-promoting mutations enhance binding. These results provide evidence that the tetratricopeptide repeat region recognizes disordered segments of substrates with particular compositions to promote glycosylation, providing insight into the broad specificity of OGT., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2023. Published by Elsevier Inc.)

As phase separation is found in an increasing variety of biological contexts, additional challenges have arisen in understanding the underlying principles of condensate formation and function. We spoke with researchers across disciplines about their views on the ever-changing landscape of biomolecular condensates., Competing Interests: Declaration of interests Geraldine Seydoux is a member of the scientific advisory board of Dewpoint Therapeutics, Inc. Pilong Li is a member of the advisory board of Molecular Cell., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Biomolecular condensates concentrate proteins, nucleic acids, and small molecules and play an essential role in many biological processes. Their formation is tuned by a balance between energetically favorable and unfavorable contacts, with charge-charge interactions playing a central role in some systems. The positively charged intrinsically disordered carboxy-terminal region of the RNA-binding protein CAPRIN1 is one such example, phase separating upon addition of negatively charged ATP or high concentrations of sodium chloride (NaCl). Using solution NMR spectroscopy, we measured residue-specific near-surface electrostatic potentials (ϕ ENS ) of CAPRIN1 along its NaCl-induced phase separation trajectory to compare with those obtained using ATP. In both cases, electrostatic shielding decreases ϕ ENS values, yet surface potentials of CAPRIN1 in the two condensates can be different, depending on the amount of NaCl or ATP added. Our results establish that even small differences in ϕ ENS can significantly affect the level of protein enrichment and the mechanical properties of the condensed phase, leading, potentially, to the regulation of biological processes., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

The spatial and temporal organization of interactions between proteins underlie the regulation of most cellular processes. The requirement for such interactions to be specific predisposes a view that protein-protein interactions are relatively static and are formed through the stable complementarity of the interacting partners. A growing body of reports indicate, however, that many interactions lead to fuzzy complexes with an ensemble of conformations in dynamic exchange accounting for the observed binding. Here, we discuss how NMR has facilitated the characterization of these discrete, dynamic complexes and how such characterization has aided the understanding of dynamic, condensed phases of phase-separating proteins with exchanging multivalent interactions., (© 2022 The Author(s).)

How the cuticles of the roughly 4.5 million species of ecdysozoan animals are constructed is not well understood. Here, we systematically mine gene expression datasets to uncover the spatiotemporal blueprint for how the chitin-based pharyngeal cuticle of the nematode Caenorhabditis elegans is built. We demonstrate that the blueprint correctly predicts expression patterns and functional relevance to cuticle development. We find that as larvae prepare to molt, catabolic enzymes are upregulated and the genes that encode chitin synthase, chitin cross-linkers, and homologs of amyloid regulators subsequently peak in expression. Forty-eight percent of the gene products secreted during the molt are predicted to be intrinsically disordered proteins (IDPs), many of which belong to four distinct families whose transcripts are expressed in overlapping waves. These include the IDPAs, IDPBs, and IDPCs, which are introduced for the first time here. All four families have sequence properties that drive phase separation and we demonstrate phase separation for one exemplar in vitro. This systematic analysis represents the first blueprint for cuticle construction and highlights the massive contribution that phase-separating materials make to the structure., Competing Interests: MK, LT, JK, PM, JJ, HC, JW, MH, KT, XC, JP, VG, MK, JF, PR No competing interests declared, (© 2022, Kamal, Tokmakjian, Knox et al.)

The precise regulation of gene expression is fundamental to neurodevelopment, plasticity and cognitive function. Although several studies have profiled transcription in the developing human brain, there is a gap in understanding of accompanying translational regulation. In this study, we performed ribosome profiling on 73 human prenatal and adult cortex samples. We characterized the translational regulation of annotated open reading frames (ORFs) and identified thousands of previously unknown translation events, including small ORFs that give rise to human-specific and/or brain-specific microproteins, many of which we independently verified using proteomics. Ribosome profiling in stem-cell-derived human neuronal cultures corroborated these findings and revealed that several neuronal activity-induced non-coding RNAs encode previously undescribed microproteins. Physicochemical analysis of brain microproteins identified a class of proteins that contain arginine-glycine-glycine (RGG) repeats and, thus, may be regulators of RNA metabolism. This resource expands the known translational landscape of the human brain and illuminates previously unknown brain-specific protein products., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

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.

Electrostatic interactions and charge balance are important for the formation of biomolecular condensates involving proteins and nucleic acids. However, a detailed, atomistic picture of the charge distribution around proteins during the phase-separation process is lacking. Here, we use solution NMR spectroscopy to measure residue-specific near-surface electrostatic potentials ( ϕ ENS ) of the positively charged carboxyl-terminal intrinsically disordered 103 residues of CAPRIN1, an RNA-binding protein localized to membraneless organelles playing an important role in messenger RNA (mRNA) storage and translation. Measured ϕ ENS values have been mapped along the adenosine triphosphate (ATP)-induced phase-separation trajectory. In the absence of ATP, ϕ ENS values for the mixed state of CAPRIN1 are positive and large and progressively decrease as ATP is added. This is coupled to increasing interchain interactions, particularly between aromatic-rich and arginine-rich regions of the protein. Upon phase separation, CAPRIN1 molecules in the condensed phase are neutral ( ϕ ENS [Formula: see text] 0 mV), with ∼five molecules of ATP associated with each CAPRIN1 chain. Increasing the ATP concentration further inverts the CAPRIN1 electrostatic potential, so that molecules become negatively charged, especially in aromatic-rich regions, leading to re-entrance into a mixed phase. Our results collectively show that a subtle balance between electrostatic repulsion and interchain attractive interactions regulates CAPRIN1 phase separation and provides insight into how nucleotides, such as ATP, can induce formation of and subsequently dissolve protein condensates.

Protein phase separation is increasingly understood to be an important mechanism of biological organization and biomaterial formation. Intrinsically disordered protein regions (IDRs) are often significant drivers of protein phase separation. A number of protein phase-separation-prediction algorithms are available, with many being specific for particular classes of proteins and others providing results that are not amenable to the interpretation of the contributing biophysical interactions. Here, we describe LLPhyScore, a new predictor of IDR-driven phase separation, based on a broad set of physical interactions or features. LLPhyScore uses sequence-based statistics from the RCSB PDB database of folded structures for these interactions, and is trained on a manually curated set of phase-separation-driving proteins with different negative training sets including the PDB and human proteome. Competitive training for a variety of physical chemical interactions shows the greatest contribution of solvent contacts, disorder, hydrogen bonds, pi-pi contacts, and kinked beta-structures to the score, with electrostatics, cation-pi contacts, and the absence of a helical secondary structure also contributing. LLPhyScore has strong phase-separation-prediction recall statistics and enables a breakdown of the contribution from each physical feature to a sequence's phase-separation propensity, while recognizing the interdependence of many of these features. The tool should be a valuable resource for guiding experiments and providing hypotheses for protein function in normal and pathological states, as well as for understanding how specificity emerges in defining individual biomolecular condensates.

Intrinsically disordered proteins (IDPs) play critical roles in regulatory protein interactions, but detailed structural/dynamic characterization of their ensembles remain challenging, both in isolation and when they form dynamic "fuzzy" complexes. Such is the case for mRNA cap-dependent translation initiation, which is regulated by the interaction of the predominantly folded eukaryotic initiation factor 4E (eIF4E) with the intrinsically disordered eIF4E binding proteins (4E-BPs) in a phosphorylation-dependent manner. Single-molecule Förster resonance energy transfer showed that the conformational changes of 4E-BP2 induced by binding to eIF4E are non-uniform along the sequence; while a central region containing both motifs that bind to eIF4E expands and becomes stiffer, the C-terminal region is less affected. Fluorescence anisotropy decay revealed a non-uniform segmental flexibility around six different labeling sites along the chain. Dynamic quenching of these fluorescent probes by intrinsic aromatic residues measured via fluorescence correlation spectroscopy report on transient intra- and inter-molecular contacts on nanosecond-to-microsecond timescales. Upon hyperphosphorylation, which induces folding of ∼40 residues in 4E-BP2, the quenching rates decreased at most labeling sites. The chain dynamics around sites in the C-terminal region far away from the two binding motifs significantly increased upon binding to eIF4E, suggesting that this region is also involved in the highly dynamic 4E-BP2:eIF4E complex. Our time-resolved fluorescence data paint a sequence-level rigidity map of three states of 4E-BP2 differing in phosphorylation or binding status and distinguish regions that form contacts with eIF4E. This study adds complementary structural and dynamics information to recent studies of 4E-BP2, and it constitutes an important step toward a mechanistic understanding of this important IDP via integrative modeling., Competing Interests: Declaration of interests The authors report no competing financial interest., (Copyright © 2022 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

A major challenge to the characterization of intrinsically disordered regions (IDRs), which are widespread in the proteome, but relatively poorly understood, is the identification of molecular features that mediate functions of these regions, such as short motifs, amino acid repeats and physicochemical properties. Here, we introduce a proteome-scale feature discovery approach for IDRs. Our approach, which we call "reverse homology", exploits the principle that important functional features are conserved over evolution. We use this as a contrastive learning signal for deep learning: given a set of homologous IDRs, the neural network has to correctly choose a held-out homolog from another set of IDRs sampled randomly from the proteome. We pair reverse homology with a simple architecture and standard interpretation techniques, and show that the network learns conserved features of IDRs that can be interpreted as motifs, repeats, or bulk features like charge or amino acid propensities. We also show that our model can be used to produce visualizations of what residues and regions are most important to IDR function, generating hypotheses for uncharacterized IDRs. Our results suggest that feature discovery using unsupervised neural networks is a promising avenue to gain systematic insight into poorly understood protein sequences., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: AMM is a Consultant to Dewpoint Therapeutics Inc.

Abbreviations: BioID: proximity-dependent biotin identification; GO: gene ontology; OSBPL: oxysterol binding protein like; VAPA: VAMP associated protein A; VAPB: VAMP associated protein B and C.

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 R 2 relaxation rates and Lipari-Szabo order parameters ( S 2 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.

Exciting recent work has highlighted that numerous cellular compartments lack encapsulating lipid bilayers (often called "membraneless organelles"), and that their structure and function are central to the regulation of key biological processes, including transcription, RNA splicing, translation, and more. These structures have been described as "biomolecular condensates" to underscore that biomolecules can be significantly concentrated in them. Many condensates, including RNA granules and processing bodies, are enriched in proteins and nucleic acids. Biomolecular condensates exhibit a range of material states from liquid- to gel-like, with the physical process of liquid-liquid phase separation implicated in driving or contributing to their formation. To date, in vitro studies of phase separation have provided mechanistic insights into the formation and function of condensates. However, the link between the often micron-sized in vitro condensates with nanometer-sized cellular correlates has not been well established. Consequently, questions have arisen as to whether cellular structures below the optical resolution limit can be considered biomolecular condensates. Similarly, the distinction between condensates and discrete dynamic hub complexes is debated. Here we discuss the key features that define biomolecular condensates to help understand behaviors of structures containing and generating RNA., (© 2022 Forman-Kay et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.)

Autism Spectrum Disorder (ASD) is genetically complex with ~100 copy number variants and genes involved. To try to establish more definitive genotype and phenotype correlations in ASD, we searched genome sequence data, and the literature, for recurrent predicted damaging sequence-level variants affecting single genes. We identified 18 individuals from 16 unrelated families carrying a heterozygous guanine duplication (c.3679dup; p.Ala1227Glyfs*69) occurring within a string of 8 guanines (genomic location [hg38]g.50,721,512dup) affecting SHANK3, a prototypical ASD gene (0.08% of ASD-affected individuals carried the predicted p.Ala1227Glyfs*69 frameshift variant). Most probands carried de novo mutations, but five individuals in three families inherited it through somatic mosaicism. We scrutinized the phenotype of p.Ala1227Glyfs*69 carriers, and while everyone (17/17) formally tested for ASD carried a diagnosis, there was the variable expression of core ASD features both within and between families. Defining such recurrent mutational mechanisms underlying an ASD outcome is important for genetic counseling and early intervention., (© 2021. The Author(s).)

Many membraneless organelles are thought to be biomolecular condensates formed by phase separation of proteins and other biopolymers. Post-translational modifications (PTMs) can impact protein phase separation behavior, although for many PTMs this aspect of their function is unknown. O -linked β-D- N -acetylglucosaminylation ( O -GlcNAcylation) is an abundant form of intracellular glycosylation whose roles in regulating biomolecular condensate assembly and dynamics have not been delineated. Using an in vitro approach, we found that O -GlcNAcylation reduces the phase separation propensity of the EWS N -terminal low complexity region (LCR N ) under different conditions, including in the presence of the arginine- and glycine-rich RNA-binding domains (RBD). O -GlcNAcylation enhances fluorescence recovery after photobleaching (FRAP) within EWS LCR N condensates and causes the droplets to exhibit more liquid-like relaxation following fusion. Following extended incubation times, EWS LCR N +RBD condensates exhibit diminished FRAP, indicating a loss of fluidity, while condensates containing the O -GlcNAcylated LCR N do not. In HeLa cells, EWS is less O -GlcNAcylated following OGT knockdown, which correlates with its increased accumulation in a filter retardation assay. Relative to the human proteome, O -GlcNAcylated proteins are enriched with regions that are predicted to phase separate, suggesting a general role of O -GlcNAcylation in regulation of biomolecular condensates.

FUsed in Sarcoma (FUS) is a multifunctional RNA binding protein (RBP). FUS mutations lead to its cytoplasmic mislocalization and cause the neurodegenerative disease amyotrophic lateral sclerosis (ALS). Here, we use mouse and human models with endogenous ALS-associated mutations to study the early consequences of increased cytoplasmic FUS. We show that in axons, mutant FUS condensates sequester and promote the phase separation of fragile X mental retardation protein (FMRP), another RBP associated with neurodegeneration. This leads to repression of translation in mouse and human FUS-ALS motor neurons and is corroborated in vitro, where FUS and FMRP copartition and repress translation. Last, we show that translation of FMRP-bound RNAs is reduced in vivo in FUS-ALS motor neurons. Our results unravel new pathomechanisms of FUS-ALS and identify a novel paradigm by which mutations in one RBP favor the formation of condensates sequestering other RBPs, affecting crucial biological functions, such as protein translation., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).)

The role of biomolecular condensates in regulating biological function and the importance of dynamic interactions involving intrinsically disordered protein regions (IDRs) in their assembly are increasingly appreciated. While computational and theoretical approaches have provided significant insights into IDR phase behavior, establishing the critical interactions that govern condensation with atomic resolution through experiment is more difficult, given the lack of applicability of standard structural biological tools to study these highly dynamic large-scale associated states. NMR can be a valuable method, but the dynamic and viscous nature of condensed IDRs presents challenges. Using the C-terminal IDR (607 to 709) of CAPRIN1, an RNA-binding protein found in stress granules, P bodies, and messenger RNA transport granules, we have developed and applied a variety of NMR methods for studies of condensed IDR states to provide insights into interactions driving and modulating phase separation. We identify ATP interactions with CAPRIN1 that can enhance or reduce phase separation. We also quantify specific side-chain and backbone interactions within condensed CAPRIN1 that define critical sequences for phase separation and that are reduced by O -GlcNAcylation known to occur during cell cycle and stress. This expanded NMR toolkit that has been developed for characterizing IDR condensates has generated detailed interaction information relevant for understanding CAPRIN1 biology and informing general models of phase separation, with significant potential future applications to illuminate dynamic structure-function relationships in other biological condensates., Competing Interests: The authors declare no competing interest.

Regulation of messenger RNA (mRNA) transcription, processing and translation occurs in the context of biomolecular condensates. How the physical properties of condensates connect with their biological regulatory functions is an ongoing area of interest, particularly for RNA metabolic pathways. Phosphorylation has emerged as an important mechanism for regulating protein phase separation propensities and localization patterns into different condensates, affecting compositions and dynamics. Key factors in transcription, mRNA processing and translation exhibit such phosphorylation-dependent changes in their roles within condensates, including their catalytic activities. Phosphorylation is increasingly understood to regulate the exchange of proteins through functionally linked condensates to fulfil their mRNA metabolic functions., Competing Interests: Conflict of interest statement Nothing declared., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

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.

In previous work, we showed that intrinsically disordered regions (IDRs) of proteins contain sequence-distributed molecular features that are conserved over evolution, despite little sequence similarity that can be detected in alignments (Zarin et al., 2019). Here, we aim to use these molecular features to predict specific biological functions for individual IDRs and identify the molecular features within them that are associated with these functions. We find that the predictable functions are diverse. Examining the associated molecular features, we note some that are consistent with previous reports and identify others that were previously unknown. We experimentally confirm that elevated isoelectric point and hydrophobicity, features that are positively associated with mitochondrial localization, are necessary for mitochondrial targeting function. Remarkably, increasing isoelectric point in a synthetic IDR restores weak mitochondrial targeting. We believe feature analysis represents a new systematic approach to understand how biological functions of IDRs are specified by their protein sequences., Competing Interests: TZ, BS, GP, IP, JF No competing interests declared, AM Reviewing editor, eLife, (© 2021, Zarin et al.)

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., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Nephrotic syndrome (NS) is a leading cause of chronic kidney disease. We found recessive NOS1AP variants in two families with early-onset NS by exome sequencing. Overexpression of wild-type (WT) NOS1AP , but not cDNA constructs bearing patient variants, increased active CDC42 and promoted filopodia and podosome formation. Pharmacologic inhibition of CDC42 or its effectors, formin proteins, reduced NOS1AP-induced filopodia formation. NOS1AP knockdown reduced podocyte migration rate (PMR), which was rescued by overexpression of WT Nos1ap but not by constructs bearing patient variants. PMR in NOS1AP knockdown podocytes was also rescued by constitutively active CDC42 Q61L or the formin DIAPH3 Modeling a NOS1AP patient variant in knock-in human kidney organoids revealed malformed glomeruli with increased apoptosis. Nos1ap Ex3-/Ex3- mice recapitulated the human phenotype, exhibiting proteinuria, foot process effacement, and glomerulosclerosis. These findings demonstrate that recessive NOS1AP variants impair CDC42/DIAPH-dependent actin remodeling, cause aberrant organoid glomerulogenesis, and lead to a glomerulopathy in humans and mice., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

It is unclear how disease mutations impact intrinsically disordered protein regions (IDRs), which lack a stable folded structure. These mutations, while prevalent in disease, are frequently neglected or annotated as variants of unknown significance. Biomolecular phase separation, a physical process often mediated by IDRs, has increasingly appreciated roles in cellular organization and regulation. We find that autism spectrum disorder (ASD)- and cancer-associated proteins are enriched for predicted phase separation propensities, suggesting that IDR mutations disrupt phase separation in key cellular processes. More generally, we hypothesize that combinations of small-effect IDR mutations perturb phase separation, potentially contributing to "missing heritability" in complex disease susceptibility., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Endeavoring toward a transferable, predictive coarse-grained explicit-chain model for biomolecular condensates underlain by liquid-liquid phase separation (LLPS) of proteins, we conducted multiple-chain simulations of the N-terminal intrinsically disordered region (IDR) of DEAD-box helicase Ddx4, as a test case, to assess roles of electrostatic, hydrophobic, cation-π, and aromatic interactions in amino acid sequence-dependent LLPS. We evaluated three different residue-residue interaction schemes with a shared electrostatic potential. Neither a common hydrophobicity scheme nor one augmented with arginine/lysine-aromatic cation-π interactions consistently accounted for available experimental LLPS data on the wild-type, a charge-scrambled, a phenylalanine-to-alanine (FtoA), and an arginine-to-lysine (RtoK) mutant of Ddx4 IDR. In contrast, interactions based on contact statistics among folded globular protein structures reproduce the overall experimental trend, including that the RtoK mutant has a much diminished LLPS propensity. Consistency between simulation and experiment was also found for RtoK mutants of P-granule protein LAF-1, underscoring that, to a degree, important LLPS-driving π-related interactions are embodied in classical statistical potentials. Further elucidation is necessary, however, especially of phenylalanine's role in condensate assembly because experiments on FtoA and tyrosine-to-phenylalanine mutants suggest that LLPS-driving phenylalanine interactions are significantly weaker than posited by common statistical potentials. Protein-protein electrostatic interactions are modulated by relative permittivity, which in general depends on aqueous protein concentration. Analytical theory suggests that this dependence entails enhanced interprotein interactions in the condensed phase but more favorable protein-solvent interactions in the dilute phase. The opposing trends lead to only a modest overall impact on LLPS., Competing Interests: The authors declare no competing interest.

What do we know about the molecular evolution of functional protein condensation? The capacity of proteins to form biomolecular condensates (compact, protein-rich states, not bound by membranes, but still separated from the rest of the contents of the cell) appears in many cases to be bestowed by weak, transient interactions within one or between proteins. Natural selection is expected to remove or fix amino acid changes, insertions or deletions that preserve and change this condensation capacity when doing so is beneficial to the cell. A few recent studies have begun to explore this frontier of phylogenetics at the intersection of biophysics and cell biology., (© 2020 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.)

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.

Phosphorylation of intrinsically disordered eIF4E binding proteins (4E-BPs) regulates cap-dependent translation by weakening their ability to compete with eIF4G for eIF4E binding within the translation initiation complex. We previously showed that phosphorylation of T37 and T46 in 4E-BP2 induces folding of a four-stranded beta-fold domain, partially sequestering the canonical eIF4E-binding helix. The C-terminal intrinsically disordered region (C-IDR), remaining disordered after phosphorylation, contains the secondary eIF4E-binding site and three other phospho-sites, whose mechanisms in inhibiting binding are not understood. Here we report that the domain is non-cooperatively folded, with exchange between beta strands and helical conformations. C-IDR phosphorylation shifts the conformational equilibrium, controlling access to eIF4E binding sites. The hairpin turns formed by pT37/pT46 are remarkably stable and function as transplantable units for phospho-regulation of stability. These results demonstrate how non-cooperative folding and conformational exchange leads to graded inhibition of 4E-BP2:eIF4E binding, shifting 4E-BP2 into an eIF4E binding-incompatible conformation and regulating translation initiation.

Microexons represent the most highly conserved class of alternative splicing, yet their functions are poorly understood. Here, we focus on closely related neuronal microexons overlapping prion-like domains in the translation initiation factors, eIF4G1 and eIF4G3, the splicing of which is activity dependent and frequently disrupted in autism. CRISPR-Cas9 deletion of these microexons selectively upregulates synaptic proteins that control neuronal activity and plasticity and further triggers a gene expression program mirroring that of activated neurons. Mice lacking the Eif4g1 microexon display social behavior, learning, and memory deficits, accompanied by altered hippocampal synaptic plasticity. We provide evidence that the eIF4G microexons function as a translational brake by causing ribosome stalling, through their propensity to promote the coalescence of cytoplasmic granule components associated with translation repression, including the fragile X mental retardation protein FMRP. The results thus reveal an autism-disrupted mechanism by which alternative splicing specializes neuronal translation to control higher order cognitive functioning., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Intrinsically disordered proteins (IDPs) or regions of intrinsic disorder in otherwise folded proteins (IDRs) play important roles in many different biological processes, including formation of biological condensates via liquid-liquid phase separation. NMR spectroscopy is a powerful tool for obtaining site-specific structural and dynamical information on IDPs/IDRs, and recent efforts have focused on the development of experiments for atomic-resolution studies of these molecules. These include triple-resonance experiments that are based on 13 CO-direct detection of magnetization, exploiting increased sensitivity of cryogenically cooled probes. In order to evaluate the different classes of experiment for studies of IDRs or IDPs in both dilute and phase-separated environments, in particular at neutral and higher pHs where many of these proteins phase separate, we compared 13 CO-detect versus 1 H α -detect experiments, showing that significant sensitivity gains are achieved via proton detection under the conditions of our experiments. A suite of 1 H α -detect experiments was subsequently developed for studies of IDPs/IDRs and applied to the dilute phase of a 103-residue disordered region of CAPRIN1 that phase separates at neutral pH. Residue-specific chemical shifts derived from our study enable the accurate prediction of the importance of the N-terminal Arg-containing region of this construct for promoting phase separation relative to other Arg-rich stretches of sequence, subsequently confirmed by mutagenesis. Our study emphasizes that the sequence positions of key residues can be a critical factor in controlling phase separation and highlights the unique role of NMR in establishing the relations between amino acid sequence and phase-separation propensity.

Proteins with intrinsic or unfolded state disorder comprise a new frontier in structural biology, requiring the characterization of diverse and dynamic structural ensembles. We introduce a comprehensive Bayesian framework, the Extended Experimental Inferential Structure Determination (X-EISD) method, that calculates the maximum log-likelihood of a disordered protein ensemble. X-EISD accounts for the uncertainties of a range of experimental data and back-calculation models from structures, including NMR chemical shifts, J-couplings, Nuclear Overhauser Effects (NOEs), paramagnetic relaxation enhancements (PREs), residual dipolar couplings (RDCs), hydrodynamic radii ( R h ), single molecule fluorescence Förster resonance energy transfer (smFRET) and small angle X-ray scattering (SAXS). We apply X-EISD to the joint optimization against experimental data for the unfolded drkN SH3 domain and find that combining a local data type, such as chemical shifts or J-couplings, paired with long-ranged restraints such as NOEs, PREs or smFRET, yields structural ensembles in good agreement with all other data types if combined with representative IDP conformers.