Detection of correlated conformational fluctuations in intrinsically disordered proteins through paramagnetic relaxation interference

Magnetic resonance investigation of conformational responses of tau protein to specific phosphorylation

Intrinsically disordered proteins (IDPs) are known to adopt many rapidly interconverting structures, making it difficult to pinpoint the specific conformational states that are relevant for their function. Tau is an important IDP, and its conformation is known to be affected by post-translational modifications (PTMs), such as phosphorylation. To investigate the effect of specific phosphorylation on full-length Tau's dynamic global conformation, we employed a combination of nuclear magnetic resonance-based paramagnetic relaxation interference methods and electron paramagnetic resonance spectroscopy. By reproducing the AT8 epitope, comprising exclusive phosphorylation at residues S202 and T205, we were able to identify conformations specific to phosphorylated Tau, which exhibited a tendency towards less compact states. These mechanistic details are of significance to understand the path leading from soluble Tau to the ordered structure of Tau fibers. This approach proved to be successful for studying the conformational changes of (phosphorylated) full-length Tau and can potentially be extended to the study of other IDPs that undergo various PTMs.

Biophysical and Integrative Characterization of Protein Intrinsic Disorder as a Prime Target for Drug Discovery

Protein intrinsic disorder is increasingly recognized for its biological and disease-driven functions. However, it represents significant challenges for biophysical studies due to its high conformational flexibility. In addressing these challenges, we highlight the complementary and distinct capabilities of a range of experimental and computational methods and further describe integrative strategies available for combining these techniques. Integrative biophysics methods provide valuable insights into the sequence–structure–function relationship of disordered proteins, setting the stage for protein intrinsic disorder to become a promising target for drug discovery. Finally, we briefly summarize recent advances in the development of new small molecule inhibitors targeting the disordered N-terminal domains of three vital transcription factors.

Improved predictions of phase behaviour of intrinsically disordered proteins by tuning the interaction range

The formation and viscoelastic properties of condensates of intrinsically disordered proteins (IDPs) is dictated by amino acid sequence and solution conditions. Because of the involvement of biomolecular condensates in cell physiology and disease, advancing our understanding of the relationship between protein sequence and phase separation (PS) may have important implications in the formulation of new therapeutic hypotheses. Here, we present CALVADOS 2, a coarse-grained model of IDPs that accurately predicts conformational properties and propensities to undergo PS for diverse sequences and solution conditions. In particular, we systematically study the effect of varying the range of the nonionic interactions and use our findings to improve the temperature scale of the model. We further optimize the residue-specific model parameters against experimental data on the conformational properties of 55 proteins, while also leveraging 70 hydrophobicity scales from the literature to avoid overfitting the training data. Extensive testing shows that the model accurately predicts chain compaction and PS propensity for sequences of diverse length and charge patterning, as well as at different temperatures and salt concentrations.

Improved predictions of phase behaviour of intrinsically disordered proteins by tuning the interaction range

The formation and viscoelastic properties of condensates of intrinsically disordered proteins (IDPs) is dictated by amino acid sequence and solution conditions. Because of the involvement of biomolecular condensates in cell physiology and disease, advancing our understanding of the relationship between protein sequence and phase separation (PS) may have important implications in the formulation of new therapeutic hypotheses. Here, we present CALVADOS 2, a coarse-grained model of IDPs that accurately predicts conformational properties and propensities to undergo PS for diverse sequences and solution conditions. In particular, we systematically study the effect of varying the range of the nonionic interactions and use our findings to improve the temperature scale of the model. We further optimize the residue-specific model parameters against experimental data on the conformational properties of 55 proteins, while also leveraging 70 hydrophobicity scales from the literature to avoid overfitting the training data. Extensive testing shows that the model accurately predicts chain compaction and PS propensity for sequences of diverse length and charge patterning, as well as at different temperatures and salt concentrations.

Deciphering the Structure and Formation of Amyloids in Neurodegenerative Diseases With Chemical Biology Tools

Protein aggregation into highly ordered, regularly repeated cross-β sheet structures called amyloid fibrils is closely associated to human disorders such as neurodegenerative diseases including Alzheimer's and Parkinson's diseases, or systemic diseases like type II diabetes. Yet, in some cases, such as the HET-s prion, amyloids have biological functions. High-resolution structures of amyloids fibrils from cryo-electron microscopy have very recently highlighted their ultrastructural organization and polymorphisms. However, the molecular mechanisms and the role of co-factors (posttranslational modifications, non-proteinaceous components and other proteins) acting on the fibril formation are still poorly understood. Whether amyloid fibrils play a toxic or protective role in the pathogenesis of neurodegenerative diseases remains to be elucidated. Furthermore, such aberrant protein-protein interactions challenge the search of small-molecule drugs or immunotherapy approaches targeting amyloid formation. In this review, we describe how chemical biology tools contribute to new insights on the mode of action of amyloidogenic proteins and peptides, defining their structural signature and aggregation pathways by capturing their molecular details and conformational heterogeneity. Challenging the imagination of scientists, this constantly expanding field provides crucial tools to unravel mechanistic detail of amyloid formation such as semisynthetic proteins and small-molecule sensors of conformational changes and/or aggregation. Protein engineering methods and bioorthogonal chemistry for the introduction of protein chemical modifications are additional fruitful strategies to tackle the challenge of understanding amyloid formation.

Accurate model of liquid-liquid phase behavior of intrinsically disordered proteins from optimization of single-chain properties

Many intrinsically disordered proteins (IDPs) may undergo liquid-liquid phase separation (LLPS) and participate in the formation of membraneless organelles in the cell, thereby contributing to the regulation and compartmentalization of intracellular biochemical reactions. The phase behavior of IDPs is sequence dependent, and its investigation through molecular simulations requires protein models that combine computational efficiency with an accurate description of intramolecular and intermolecular interactions. We developed a general coarse-grained model of IDPs, with residue-level detail, based on an extensive set of experimental data on single-chain properties. Ensemble-averaged experimental observables are predicted from molecular simulations, and a data-driven parameter-learning procedure is used to identify the residue-specific model parameters that minimize the discrepancy between predictions and experiments. The model accurately reproduces the experimentally observed conformational propensities of a set of IDPs. Through two-body as well as large-scale molecular simulations, we show that the optimization of the intramolecular interactions results in improved predictions of protein self-association and LLPS.

Accurate model of liquid-liquid phase behavior of intrinsically disordered proteins from optimization of single-chain properties

Many intrinsically disordered proteins (IDPs) may undergo liquid-liquid phase separation (LLPS) and participate in the formation of membraneless organelles in the cell, thereby contributing to the regulation and compartmentalization of intracellular biochemical reactions. The phase behavior of IDPs is sequence dependent, and its investigation through molecular simulations requires protein models that combine computational efficiency with an accurate description of intramolecular and intermolecular interactions. We developed a general coarse-grained model of IDPs, with residue-level detail, based on an extensive set of experimental data on single-chain properties. Ensemble-averaged experimental observables are predicted from molecular simulations, and a data-driven parameter-learning procedure is used to identify the residue-specific model parameters that minimize the discrepancy between predictions and experiments. The model accurately reproduces the experimentally observed conformational propensities of a set of IDPs. Through two-body as well as large-scale molecular simulations, we show that the optimization of the intramolecular interactions results in improved predictions of protein self-association and LLPS.

Characterization of Weak Protein Domain Structure by Spin-Label Distance Distributions

Function of intrinsically disordered proteins may depend on deviation of their conformational ensemble from that of a random coil. Such deviation may be hard to characterize and quantify, if it is weak. We explored the potential of distance distributions between spin labels, as they can be measured by electron paramagnetic resonance techniques, for aiding such characterization. On the example of the intrinsically disordered N-terminal domain 1-267 of fused in sarcoma (FUS) we examined what such distance distributions can and cannot reveal on the random-coil reference state. On the example of the glycine-rich domain 188-320 of heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1) we studied whether deviation from a random-coil ensemble can be robustly detected with 19 distance distribution restraints. We discuss limitations imposed by ill-posedness of the conversion of primary data to distance distributions and propose overlap of distance distributions as a fit criterion that can tackle this problem. For testing consistency and size sufficiency of the restraint set, we propose jack-knife resampling. At current desktop computers, our approach is expected to be viable for domains up to 150 residues and for between 10 and 50 distance distribution restraints.

Inference of Joint Conformational Distributions from Separately Acquired Experimental Measurements

Flexible proteins serve vital roles in a multitude of biological processes. However, determining their full conformational ensembles is extremely difficult because this requires detailed knowledge about the heterogeneity of the protein's degrees of freedom. Label-based experiments such as double electron-electron resonance (DEER) are very useful in studying flexible proteins, as they provide distributional data on heterogeneity. These experiments are typically performed separately, so information about correlation between distributions is lost. We have developed a method to recover correlation information using nonequilibrium work estimates in molecular dynamics refinement. We tested this method on a simple model of an alternating-access transporter for which the true joint distributions are known, and it successfully recovered the true joint distribution. We also applied our method to the protein syntaxin-1a, where it discarded physically implausible conformations. Our method thus provides a way to recover correlation structure in separate experimental measurements of conformational ensembles and refines the resulting structural ensemble.

Interactions by Disorder - A Matter of Context

Living organisms depend on timely and organized interactions between proteins linked in interactomes of high complexity. The recent increased precision by which protein interactions can be studied, and the enclosure of intrinsic structural disorder, suggest that it is time to zoom out and embrace protein interactions beyond the most central points of physical encounter. The present paper discusses protein-protein interactions in the view of structural disorder with an emphasis on flanking regions and contexts of disorder-based interactions. Context constitutes an overarching concept being of physicochemical, biomolecular, and physiological nature, but it also includes the immediate molecular context of the interaction. For intrinsically disordered proteins, which often function by exploiting short linear motifs, context contributes in highly regulatory and decisive manners and constitute a yet largely unrecognized source of interaction potential in a multitude of biological processes. Through selected examples, this review emphasizes how multivalency, charges and charge clusters, hydrophobic patches, dynamics, energetic frustration, and ensemble redistribution of flanking regions or disordered contexts are emerging as important contributors to allosteric regulation, positive and negative cooperativity, feedback regulation and negative selection in binding. The review emphasizes that understanding context, and in particular the role the molecular disordered context and flanking regions take on in protein interactions, constitute an untapped well of energetic modulation potential, also of relevance to drug discovery and development.

Impact of the Hereditary P301L Mutation on the Correlated Conformational Dynamics of Human Tau Protein Revealed by the Paramagnetic Relaxation Enhancement NMR Experiments

Tau forms intracellular insoluble aggregates as a neuropathological hallmark of Alzheimer’s disease. Tau is largely unstructured, which complicates the characterization of the tau aggregation process. Recent studies have demonstrated that tau samples two distinct conformational ensembles, each of which contains the soluble and aggregation-prone states of tau. A shift to populate the aggregation-prone ensemble may promote tau fibrillization. However, the mechanism of this ensemble transition remains elusive. In this study, we explored the conformational dynamics of a tau fragment by using paramagnetic relaxation enhancement (PRE) and interference (PRI) NMR experiments. The PRE correlation map showed that tau is composed of segments consisting of residues in correlated motions. Intriguingly, residues forming the β-structures in the heparin-induced tau filament coincide with residues in these segments, suggesting that each segment behaves as a structural unit in fibrillization. PRI data demonstrated that the P301L mutation exclusively alters the transiently formed tau structures by changing the short- and long-range correlated motions among residues. The transient conformations of P301L tau expose the amyloid motif PHF6 to promote tau self-aggregation. We propose the correlated motions among residues within tau determine the population sizes of the conformational ensembles, and perturbing the correlated motions populates the aggregation-prone form.

Long-range Regulation of Partially Folded Amyloidogenic Peptides

Neurodegeneration involves abnormal aggregation of intrinsically disordered amyloidogenic peptides (IDPs), usually mediated by hydrophobic protein-protein interactions. There is mounting evidence that formation of α-helical intermediates is an early event during self-assembly of amyloid-β42 (Aβ42) and α-synuclein (αS) IDPs in Alzheimer’s and Parkinson’s disease pathogenesis, respectively. However, the driving force behind on-pathway molecular assembly of partially folded helical monomers into helical oligomers assembly remains unknown. Here, we employ extensive molecular dynamics simulations to sample the helical conformational sub-spaces of monomeric peptides of both Aβ42 and αS. Our computed free energies, population shifts, and dynamic cross-correlation network analyses reveal a common feature of long-range intra-peptide modulation of partial helical folds of the amyloidogenic central hydrophobic domains via concerted coupling with their charged terminal tails (N-terminus of Aβ42 and C-terminus of αS). The absence of such inter-domain fluctuations in both fully helical and completely unfolded (disordered) states suggests that long-range coupling regulates the dynamicity of partially folded helices, in both Aβ42 and αS peptides. The inter-domain coupling suggests a form of intra-molecular allosteric regulation of the aggregation trigger in partially folded helical monomers. This approach could be applied to study the broad range of amyloidogenic peptides, which could provide a new path to curbing pathogenic aggregation of partially folded conformers into oligomers, by inhibition of sites far from the hydrophobic core.

The Ambivalent Role of Proline Residues in an Intrinsically Disordered Protein: From Disorder Promoters to Compaction Facilitators

Intrinsically disordered proteins (IDPs) carry out many biological functions. They lack a stable three-dimensional structure, but rather adopt many different conformations in dynamic equilibrium. The interplay between local dynamics and global rearrangements is key for their function. In IDPs, proline residues are significantly enriched. Given their unique physicochemical and structural properties, a more detailed understanding of their potential role in stabilizing partially folded states in IDPs is highly desirable. Nuclear magnetic resonance (NMR) spectroscopy, and in particular ¹³C-detected NMR, is especially suitable to address these questions. We applied a ¹³C-detected strategy to study Osteopontin, a largely disordered IDP with a central compact region. By using the exquisite sensitivity and spectral resolution of these novel techniques, we gained unprecedented insight into cis-Pro populations, their local structural dynamics, and their role in mediating long-range contacts. Our findings clearly call for a reassessment of the structural and functional role of proline residues in IDPs. The emerging picture shows that proline residues have ambivalent structural roles. They are not simply disorder promoters but rather can, depending on the primary sequence context, act as nucleation sites for structural compaction in IDPs. These unexpected features provide a versatile mechanistic toolbox to enrich the conformational ensembles of IDPs with specific features for adapting to changing molecular and cellular environments.

Capturing a dynamically interacting inhibitor by paramagnetic NMR spectroscopy

Transient and fuzzy intermolecular interactions are fundamental to many biological processes. Despite their importance, they are notoriously challenging to characterize. Effects induced by paramagnetic ligands in the NMR spectra of interacting biomolecules provide an opportunity to amplify subtle manifestations of weak intermolecular interactions observed for diamagnetic ligands. Here, we present an approach to characterizing dynamic interactions between a partially flexible dimeric protein, HIV-1 protease, and a metallacarborane-based ligand, a system for which data obtained by standard NMR approaches do not enable detailed structural interpretation. We show that for the case where the experimental data are significantly averaged to values close to zero the standard fitting of pseudocontact shifts cannot provide reliable structural information. We based our approach on generating a large ensemble of full atomic models, for which the experimental data can be predicted, ensemble averaged and finally compared to the experiment. We demonstrate that a combination of paramagnetic NMR experiments, quantum chemical calculations, and molecular dynamics simulations offers a route towards structural characterization of dynamic protein-ligand complexes.

DNP-Enhanced MAS NMR: A Tool to Snapshot Conformational Ensembles of α-Synuclein in Different States

Intrinsically disordered proteins dynamically sample a wide conformational space and therefore do not adopt a stable and defined three-dimensional conformation. The structural heterogeneity is related to their proper functioning in physiological processes. Knowledge of the conformational ensemble is crucial for a complete comprehension of this kind of proteins. We here present an approach that utilizes dynamic nuclear polarization-enhanced solid-state NMR spectroscopy of sparsely isotope-labeled proteins in frozen solution to take snapshots of the complete structural ensembles by exploiting the inhomogeneously broadened line-shapes. We investigated the intrinsically disordered protein α-synuclein (α-syn), which plays a key role in the etiology of Parkinson’s disease, in three different physiologically relevant states. For the free monomer in frozen solution we could see that the so-called “random coil conformation” consists of α-helical and β-sheet-like conformations, and that secondary chemical shifts of neighboring amino acids tend to be correlated, indicative of frequent formation of secondary structure elements. Based on these results, we could estimate the number of disordered regions in fibrillar α-syn as well as in α-syn bound to membranes in different protein-to-lipid ratios. Our approach thus provides quantitative information on the propensity to sample transient secondary structures in different functional states. Molecular dynamics simulations rationalize the results.

Distance-independent Cross-correlated Relaxation and Isotropic Chemical Shift Modulation in Protein Dynamics Studies

Cross-correlated relaxation (CCR) in multiple-quantum coherences differs from other relaxation phenomena in its theoretical ability to be mediated across an infinite distance. The two interfering relaxation mechanisms may be dipolar interactions, chemical shift anisotropies, chemical shift modulations or quadrupolar interactions. These properties make multiple-quantum CCR an attractive probe for structure and dynamics of biomacromolecules not accessible from other measurements. Here, we review the use of multiple-quantum CCR measurements in dynamics studies of proteins. We compile a list of all experiments proposed for CCR rate measurements, provide an overview of the theory with a focus on protein dynamics, and present applications to various protein systems.

NMR Characterization of Long-Range Contacts in Intrinsically Disordered Proteins from Paramagnetic Relaxation Enhancement in 13 C Direct-Detection Experiments

Intrinsically disordered proteins (IDPs) carry out many biological functions. They lack a stable 3D structure and are able to adopt many different conformations in dynamic equilibrium. The interplay between local dynamics and global rearrangements is key for their function. A widely used experimental NMR spectroscopy approach to study long-range contacts in IDPs exploits paramagnetic effects, and ¹ H detection experiments are generally used to determine paramagnetic relaxation enhancement (PRE) for amide protons. However, under physiological conditions, exchange broadening hampers the detection of solvent-exposed amide protons, which reduces the content of information available. Herein, we present an experimental approach based on direct carbon detection of PRE that provides improved resolution, reduced sensitivity to exchange broadening, and complementary information derived from the use of different starting polarization sources.

Modulation of Correlated Segment Fluctuations in IDPs upon Complex Formation as an Allosteric Regulatory Mechanism

Molecular recognition of and by intrinsically disordered proteins (IDPs) is an intriguing and still largely elusive phenomenon. Typically, protein recognition involving IDPs requires either folding upon binding or, alternatively, the formation of "fuzzy complexes." Here we show via correlation analyses of paramagnetic relaxation enhancement data unprecedented and striking alterations of the concerted fluctuations within the conformational ensemble of IDPs upon ligand binding. We study the binding of α-synuclein to calmodulin, a ubiquitous calcium-binding protein, and the binding of the extracellular matrix IDP osteopontin to heparin, a mimic of the extracellular matrix ligand hyaluronic acid. In both cases, binding leads to reduction of correlated long-range motions in these two IDPs and thus indicates a loosening of structural compaction upon binding. Most importantly, however, the simultaneous presence of correlated and anti-correlated fluctuations in IDPs suggests the prevalence of "energetic frustration" and provides an explanation for the puzzling observation of disordered allostery in IDPs.

Intramolecular Fuzzy Interactions Involving Intrinsically Disordered Domains

Structural disorder is an essential ingredient for function in many proteins and protein complexes. Fuzzy complexes describe the many instances where disorder is maintained as a critical element of protein interactions. In this minireview we discuss how intramolecular fuzzy interactions function in signaling complexes. Focussing on the Src family of kinases, we argue that the intrinsically disordered domains that are unique for each of the family members and display a clear fingerprint of long range interactions in Src, might have critical roles as functional sensor or effectors and mediate allosteric communication via fuzzy interactions.

NMR probing and visualization of correlated structural fluctuations in intrinsically disordered proteins

A novel statistical analysis of paramagnetic relaxation enhancement (PRE) and paramagnetic relaxation interference (PRI) based nuclear magnetic resonance (NMR) data is proposed based on the computation of correlation matrices. The technique is demonstrated with an example of the intrinsically disordered proteins (IDPs) osteopontin (OPN) and brain acid soluble protein 1 (BASP1). The correlation analysis visualizes in detail the subtleties of conformational averaging in IDPs and highlights the presence of correlated structural fluctuations of individual sub-domains in IDPs.

A critical assessment of methods to recover information from averaged data

Conformational heterogeneity is key to the function of many biomacromolecules, but only a few groups have tried to characterize it until recently. Now, thanks to the increased throughput of experimental data and the increased computational power, the problem of the characterization of protein structural variability has become more and more popular. Several groups have devoted their efforts in trying to create quantitative, reliable and accurate protocols for extracting such information from averaged data. We analyze here different approaches, discussing strengths and weaknesses of each. All approaches can roughly be clustered into two groups: those satisfying the maximum entropy principle and those recovering ensembles composed of a restricted number of molecular conformations. In the first case, the solution focuses on the features that are common to all the infinite solutions satisfying the experimental data; in the second case, the reconstructed ensemble shows the conformational regions where a large probability can be placed. The upper limits for conformational probabilities (MaxOcc) can also be calculated. We also give an overview of the mainstream experimental observables, with considerations on the assumptions underlying their usage.