Search

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 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.

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.

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.

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.

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.

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.

Stress granules and P-bodies are cytosolic biomolecular condensates that dynamically form by the phase separation of RNAs and proteins. They participate in translational control and buffer the proteome. Upon stress, global translation halts and mRNAs bound to the translational machinery and other proteins coalesce to form stress granules (SGs). Similarly, translationally stalled mRNAs devoid of translation initiation factors shuttle to P-bodies (PBs). Here, we review the cumulative progress made in defining the protein components that associate with mammalian SGs and PBs. We discuss the composition of SG and PB proteomes, supported by a new user-friendly database (http://rnagranuledb.lunenfeld.ca/) that curates current literature evidence for genes or proteins associated with SGs or PBs. As previously observed, the SG and PB proteomes are biased toward intrinsically disordered regions and have a high propensity to contain primary sequence features favoring phase separation. We also provide an outlook on how the various components of SGs and PBs may cooperate to organize and form membraneless organelles., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Liquid-liquid phase separation (LLPS) of proteins and other biomolecules play a critical role in the organization of extracellular materials and membrane-less compartmentalization of intra-organismal spaces through the formation of condensates. Structural properties of such mesoscopic droplet-like states were studied by spectroscopy, microscopy, and other biophysical techniques. The temperature dependence of biomolecular LLPS has been studied extensively, indicating that phase-separated condensed states of proteins can be stabilized or destabilized by increasing temperature. In contrast, the physical and biological significance of hydrostatic pressure on LLPS is less appreciated. Summarized here are recent investigations of protein LLPS under pressures up to the kbar-regime. Strikingly, for the cases studied thus far, LLPSs of both globular proteins and intrinsically disordered proteins/regions are typically more sensitive to pressure than the folding of proteins, suggesting that organisms inhabiting the deep sea and sub-seafloor sediments, under pressures up to 1 kbar and beyond, have to mitigate this pressure-sensitivity to avoid unwanted destabilization of their functional biomolecular condensates. Interestingly, we found that trimethylamine-N-oxide (TMAO), an osmolyte upregulated in deep-sea fish, can significantly stabilize protein droplets under pressure, pointing to another adaptive advantage for increased TMAO concentrations in deep-sea organisms besides the osmolyte's stabilizing effect against protein unfolding. As life on Earth might have originated in the deep sea, pressure-dependent LLPS is pertinent to questions regarding prebiotic proto-cells. Herein, we offer a conceptual framework for rationalizing the recent experimental findings and present an outline of the basic thermodynamics of temperature-, pressure-, and osmolyte-dependent LLPS as well as a molecular-level statistical mechanics picture in terms of solvent-mediated interactions and void volumes., (© 2019 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Biological condensates, including membraneless organelles, can consist of hundreds of proteins, and it is important to identify which proteins are driving condensation and which proteins have evolved to regulate protein compartmentalization by liquid-liquid phase separation. Predictors that have been used for this purpose have emerged from a variety of perspectives and have diverse designs, sequence dependencies, and physical bases. Here, we describe, compare, and contrast a range of first-generation phase-separation predictors currently available to demonstrate their overlapping and unique predictions and to highlight the need for second-generation predictors that would more comprehensively incorporate the multiple features associated with phase separation., (Copyright © 2019. Published by Elsevier Ltd.)

Membraneless organelles involved in RNA processing are biomolecular condensates assembled by phase separation. Despite the important role of intrinsically disordered protein regions (IDRs), the specific interactions underlying IDR phase separation and its functional consequences remain elusive. To address these questions, we used minimal condensates formed from the C-terminal disordered regions of two interacting translational regulators, FMRP and CAPRIN1. Nuclear magnetic resonance spectroscopy of FMRP-CAPRIN1 condensates revealed interactions involving arginine-rich and aromatic-rich regions. We found that different FMRP serine/threonine and CAPRIN1 tyrosine phosphorylation patterns control phase separation propensity with RNA, including subcompartmentalization, and tune deadenylation and translation rates in vitro. The resulting evidence for residue-specific interactions underlying co-phase separation, phosphorylation-modulated condensate architecture, and enzymatic activity within condensates has implications for how the integration of signaling pathways controls RNA processing and translation., (Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

In this issue of Molecular Cell, Simon et al. (2019) demonstrate that phase separation of an engineered intrinsically disordered protein can be used to control in vitro translation via the formation of artificial ribonucleoprotein granules., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Bioinformatics and biophysical studies of intrinsically disordered proteins and regions (IDRs) note the high entropy at individual sequence positions and in conformations sampled in solution. This prevents application of the canonical sequence-structure-function paradigm to IDRs and motivates the development of new methods to extract information from IDR sequences. We argue that the information in IDR sequences cannot be fully revealed through positional conservation, which largely measures stable structural contacts and interaction motifs. Instead, considerations of evolutionary conservation of molecular features can reveal the full extent of information in IDRs. Experimental quantification of the large conformational entropy of IDRs is challenging but can be approximated through the extent of conformational sampling measured by a combination of NMR spectroscopy and lower-resolution structural biology techniques, which can be further interpreted with simulations. Conformational entropy and other biophysical features can be modulated by post-translational modifications that provide functional advantages to IDRs by tuning their energy landscapes and enabling a variety of functional interactions and modes of regulation. The diverse mosaic of functional states of IDRs and their conformational features within complexes demands novel metrics of information, which will reflect the complicated sequence-conformational ensemble-function relationship of IDRs.

Activity-dependent translation requires the transport of mRNAs within membraneless protein assemblies known as neuronal granules from the cell body toward synaptic regions. Translation of mRNA is inhibited in these granules during transport but quickly activated in response to neuronal stimuli at the synapse. This raises an important question: how does synaptic activity trigger translation of once-silenced mRNAs? Here, we demonstrate a strong connection between phase separation, the process underlying the formation of many different types of cellular granules, and in vitro inhibition of translation. By using the Fragile X Mental Retardation Protein (FMRP), an abundant neuronal granule component and translational repressor, we show that FMRP phase separates in vitro with RNA into liquid droplets mediated by its C-terminal low-complexity disordered region (i.e., FMRP LCR ). FMRP LCR posttranslational modifications by phosphorylation and methylation have opposing effects on in vitro translational regulation, which corroborates well with their critical concentrations for phase separation. Our results, combined with bioinformatics evidence, are supportive of phase separation as a general mechanism controlling activity-dependent translation., Competing Interests: Conflict of interest statement: J.D.F-K. and R.W.K. were coauthors on a 2016 review article. J.D.F-K., R.W.K., and G.S. were coeditors of a 2018 special issue of the Journal of Molecular Biology, and they coauthored an introduction to the issue.

Intraneuronal aggregation of TDP-43 is seen in 97% of all amyotrophic lateral sclerosis cases and occurs by a poorly understood mechanism. We developed a simple in vitro model system for the study of full-length TDP-43 aggregation in solution and in protein droplets. We found that soluble, YFP-tagged full-length TDP-43 (yTDP-43) dimers can be produced by refolding in low-salt HEPES buffer; these solutions are stable for several weeks. We found that physiological electrolytes induced reversible aggregation of yTDP-43 into 10-50 nm tufted particles, without amyloid characteristics. The order of aggregation induction potency was K + < Na + < Mg 2+ < Ca 2+ , which is the reverse of the Hofmeister series. The kinetics of aggregation were fit to a single-step model, and the apparent rate of aggregation was affected by yTDP-43 and NaCl concentrations. While yTDP-43 alone did not form stable liquid droplets, it partitioned into preformed Ddx4N1 droplets, showing dynamic diffusion behavior consistent with liquid-liquid phase transition, but then aggregated over time. Aggregation of yTDP-43 in droplets also occurred rapidly in response to changes in electrolyte concentrations, mirroring solution behavior. This was accompanied by changes to droplet localization and solvent exchange. Exposure to extracellular-like electrolyte conditions caused rapid aggregation at the droplet periphery. The aggregation behavior of yTDP-43 is controlled by ion-specific effects that occur at physiological concentrations, suggesting a mechanistic role for local electrolyte concentrations in TDP-43 proteinopathies.

RGG/RG motifs are RNA binding segments found in many proteins that can partition into membraneless organelles. They occur in the context of low-complexity disordered regions and often in multiple copies. Although short RGG/RG-containing regions can sometimes form high-affinity interactions with RNA structures, multiple RGG/RG repeats are generally required for high-affinity binding, suggestive of the dynamic, multivalent interactions that are thought to underlie phase separation in formation of cellular membraneless organelles. Arginine can interact with nucleotide bases via hydrogen bonding and π-stacking; thus, nucleotide conformers that provide access to the bases provide enhanced opportunities for RGG interactions. Methylation of RGG/RG regions, which is accomplished by protein arginine methyltransferase enzymes, occurs to different degrees in different cell types and may regulate the behavior of proteins containing these regions., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Protein phase separation is implicated in formation of membraneless organelles, signaling puncta and the nuclear pore. Multivalent interactions of modular binding domains and their target motifs can drive phase separation. However, forces promoting the more common phase separation of intrinsically disordered regions are less understood, with suggested roles for multivalent cation-pi, pi-pi, and charge interactions and the hydrophobic effect. Known phase-separating proteins are enriched in pi-orbital containing residues and thus we analyzed pi-interactions in folded proteins. We found that pi-pi interactions involving non-aromatic groups are widespread, underestimated by force-fields used in structure calculations and correlated with solvation and lack of regular secondary structure, properties associated with disordered regions. We present a phase separation predictive algorithm based on pi interaction frequency, highlighting proteins involved in biomaterials and RNA processing., Competing Interests: RV, PC, BT, TK, AB, PF, HL, JF No competing interests declared, (© 2018, Vernon et al.)

Characterization of the second nucleotide-binding domain (NBD2) of the cystic fibrosis transmembrane conductance regulator (CFTR) has lagged behind research into the NBD1 domain, in part because NBD1 contains the F508del mutation, which is the dominant cause of cystic fibrosis. Research on NBD2 has also been hampered by the overall instability of the domain and the difficulty of producing reagents. Nonetheless, multiple disease-causing mutations reside in NBD2, and the domain is critical for CFTR function, because channel gating involves NBD1/NBD2 dimerization, and NBD2 contains the catalytically active ATPase site in CFTR. Recognizing the paucity of structural and biophysical data on NBD2, here we have defined a bioinformatics-based method for manually identifying stabilizing substitutions in NBD2, and we used an iterative process of screening single substitutions against thermal melting points to both produce minimally mutated stable constructs and individually characterize mutations. We present a range of stable constructs with minimal mutations to help inform further research on NBD2. We have used this stabilized background to study the effects of NBD2 mutations identified in cystic fibrosis (CF) patients, demonstrating that mutants such as N1303K and G1349D are characterized by lower stability, as shown previously for some NBD1 mutations, suggesting a potential role for NBD2 instability in the pathology of CF., (© 2017 by The American Society for Biochemistry and Molecular Biology, Inc.)

Deletion of Phe-508 (F508del) in the first nucleotide-binding domain (NBD1) of the cystic fibrosis transmembrane conductance regulator (CFTR) results in destabilization of the domain, intramolecular interactions involving the domain, and the entire channel. The destabilization caused by F508del manifests itself in defective channel processing and channel gating defects. Here, we present NMR studies of the effect of F508del and the I539T stabilizing mutation on NBD1 dynamics, with a view to understanding these changes in stability. Qualitatively, F508del NMR spectra exhibit significantly more peak broadening than WT spectra due to the enhanced intermediate time scale (millisecond to microsecond) motions in the mutant. Unexpectedly, studies of fast (nanosecond to picosecond) motions revealed that F508del NBD1 tumbles more rapidly in solution than WT NBD1. Whereas F508del tumbles at a rate nearly consistent with the monomeric state, the WT protein tumbles significantly more slowly. Paramagnetic relaxation enhancement experiments confirm that NBD1 homodimerizes in solution in the expected head-to-tail orientation. NMR spectra of WT NBD1 reveal significant concentration-dependent chemical shift perturbations consistent with NBD1 dimerization. Chemical shift analysis suggests that the more rapid tumbling of F508del is the result of an impaired ability to dimerize. Based on previously published crystal structures and NMR spectra of various NBD1 mutants, we propose that deletion of Phe-508 affects Q-loop conformational sampling in a manner that inhibits dimerization. These results provide a potential mechanism for inhibition of channel opening by F508del and support the dimer interface as a target for cystic fibrosis therapeutics., (© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.)

Intrinsically disordered proteins play important roles in cell signalling, transcription, translation and cell cycle regulation. Although they lack stable tertiary structure, many intrinsically disordered proteins undergo disorder-to-order transitions upon binding to partners. Similarly, several folded proteins use regulated order-to-disorder transitions to mediate biological function. In principle, the function of intrinsically disordered proteins may be controlled by post-translational modifications that lead to structural changes such as folding, although this has not been observed. Here we show that multisite phosphorylation induces folding of the intrinsically disordered 4E-BP2, the major neural isoform of the family of three mammalian proteins that bind eIF4E and suppress cap-dependent translation initiation. In its non-phosphorylated state, 4E-BP2 interacts tightly with eIF4E using both a canonical YXXXXLΦ motif (starting at Y54) that undergoes a disorder-to-helix transition upon binding and a dynamic secondary binding site. We demonstrate that phosphorylation at T37 and T46 induces folding of residues P18-R62 of 4E-BP2 into a four-stranded β-domain that sequesters the helical YXXXXLΦ motif into a partly buried β-strand, blocking its accessibility to eIF4E. The folded state of pT37pT46 4E-BP2 is weakly stable, decreasing affinity by 100-fold and leading to an order-to-disorder transition upon binding to eIF4E, whereas fully phosphorylated 4E-BP2 is more stable, decreasing affinity by a factor of approximately 4,000. These results highlight stabilization of a phosphorylation-induced fold as the essential mechanism for phospho-regulation of the 4E-BP:eIF4E interaction and exemplify a new mode of biological regulation mediated by intrinsically disordered proteins.

Proteins are inherently plastic molecules, whose function often critically depends on excursions between different molecular conformations (conformers). However, a rigorous understanding of the relation between a protein's structure, dynamics and function remains elusive. This is because many of the conformers on its energy landscape are only transiently formed and marginally populated (less than a few per cent of the total number of molecules), so that they cannot be individually characterized by most biophysical tools. Here we study a lysozyme mutant from phage T4 that binds hydrophobic molecules and populates an excited state transiently (about 1 ms) to about 3% at 25 °C (ref. 5). We show that such binding occurs only via the ground state, and present the atomic-level model of the 'invisible', excited state obtained using a combined strategy of relaxation-dispersion NMR (ref. 6) and CS-Rosetta model building that rationalizes this observation. The model was tested using structure-based design calculations identifying point mutants predicted to stabilize the excited state relative to the ground state. In this way a pair of mutations were introduced, inverting the relative populations of the ground and excited states and altering function. Our results suggest a mechanism for the evolution of a protein's function by changing the delicate balance between the states on its energy landscape. More generally, they show that our approach can generate and validate models of excited protein states.

Several all-helical single-domain proteins have been shown to fold rapidly (microsecond time scale) to a compact intermediate state and subsequently rearrange more slowly to the native conformation. An understanding of this process has been hindered by difficulties in experimental studies of intermediates in cases where they are both low-populated and only transiently formed. One such example is provided by the on-pathway folding intermediate of the small four-helix bundle FF domain from HYPA/FBP11 that is populated at several percent with a millisecond lifetime at room temperature. Here we have studied the L24A mutant that has been shown previously to form nonnative interactions in the folding transition state. A suite of Carr-Purcell-Meiboom-Gill relaxation dispersion NMR experiments have been used to measure backbone chemical shifts and amide bond vector orientations of the invisible folding intermediate that form the input restraints in calculations of atomic resolution models of its structure. Despite the fact that the intermediate structure has many features that are similar to that of the native state, a set of nonnative contacts is observed that is even more extensive than noted previously for the wild-type (WT) folding intermediate. Such nonnative interactions, which must be broken prior to adoption of the native conformation, explain why the transition from the intermediate state to the native conformer (millisecond time scale) is significantly slower than from the unfolded ensemble to the intermediate and why the L24A mutant folds more slowly than the WT.

The Rosetta de novo structure prediction and loop modeling protocols begin with coarse grained Monte Carlo searches in which the moves are based on short fragments extracted from a database of known structures. Here we describe a new object oriented program for picking fragments that greatly extends the functionality of the previous program (nnmake) and opens the door for new approaches to structure modeling. We provide a detailed description of the code design and architecture, highlighting its modularity, and new features such as extensibility, total control over the fragment picking workflow and scoring system customization. We demonstrate that the program provides at least as good building blocks for ab-initio structure prediction as the previous program, and provide examples of the wide range of applications that are now accessible.