Structural analysis of intrinsically disordered proteins by small-angle X-ray scattering

Binding mechanisms of intrinsically disordered proteins: Insights from experimental studies and structural predictions

Advances in the characterization of intrinsically disordered proteins (IDPs) have unveiled a remarkably complex and diverse interaction landscape, including coupled folding and binding, highly dynamic complexes, multivalent interactions, and even interactions between entirely disordered proteins. Here we review recent examples of IDP binding mechanisms elucidated by experimental techniques such as nuclear magnetic resonance spectroscopy, single-molecule Förster resonance energy transfer, and stopped-flow fluorescence. These techniques provide insights into the structural details of transition pathways and complex intermediates, and they capture the dynamics of IDPs within complexes. Furthermore, we discuss the growing role of artificial intelligence, exemplified by AlphaFold, in identifying interaction sites within IDPs and predicting their bound-state structures. Our review highlights the powerful complementarity between experimental methods and artificial intelligence-based approaches in advancing our understanding of the intricate interaction landscape of IDPs.

The strand exchange domain of tumor suppressor PALB2 is intrinsically disordered and promotes oligomerization-dependent DNA compaction

The partner and localizer of BRCA2 (PALB2) is a scaffold protein linking BRCA1 with BRCA2 and RAD51 during homologous recombination (HR). PALB2 interaction with DNA strongly enhances HR in cells, while the PALB2 DNA-binding domain (PALB2-DBD) supports DNA strand exchange in vitro. We determined that PALB2-DBD is intrinsically disordered beyond a single N-terminal α-helix. Coiled-coil mediated dimerization is stabilized by interaction between intrinsically disordered regions (IDRs) leading to a 2-fold structural compaction. Single-stranded (ss)DNA binding promotes additional structural compaction and protein tetramerization. Using confocal single-molecule FRET, we observed bimodal and oligomerization-dependent compaction of ssDNA bound to PALB2-DBD, suggesting a novel strand exchange mechanism. Bioinformatics analysis and preliminary observations indicate that PALB2 forms protein-nucleic acids condensates. Intrinsically disordered DBDs are prevalent in the human proteome. PALB2-DBD and similar IDRs may use a chaperone-like mechanism to aid formation and resolution of DNA and RNA multichain intermediates during DNA replication, repair and recombination.

SAXS of murine amelogenin identifies a persistent dimeric species from pH 5.0 to 8.0

Amelogenin is an intrinsically disordered protein essential to tooth enamel formation in mammals. Using advanced small angle X-ray scattering (SAXS) capabilities at synchrotrons and computational models, we revisited measuring the quaternary structure of murine amelogenin as a function of pH and phosphorylation at serine-16. The SAXS data shows that at the pH extremes, amelogenin exists as an extended monomer at pH 3.0 (Rg = 38.4 Å) and nanospheres at pH 8.0 (Rg = 84.0 Å), consistent with multiple previous observations. At pH 5.0 and above there was no evidence for a significant population of monomeric species. Instead, at pH 5.0, ∼80 % of the population is a heterogenous dimeric species that increases to ∼100 % at pH 5.5. The dimer population was observed at all pH > 5 conditions in dynamic equilibrium with a species in the pentamer range at pH < 6.5 and nanospheres at pH 8.0. At pH 8.0, ∼40 % of the amelogenin remained in the dimeric state. In general, serine-16 phosphorylation of amelogenin appears to modestly stabilize the population of the dimeric species.

Physics-Based Machine Learning Trains Hamiltonians and Decodes the Sequence-Conformation Relation in the Disordered Proteome

Intrinsically disordered proteins and regions (IDPs) are involved in vital biological processes. To understand the IDP function, often controlled by conformation, we need to find the link between sequence and conformation. We decode this link by integrating theory, simulation, and machine learning (ML) where sequence-dependent electrostatics is modeled analytically while nonelectrostatic interaction is extracted from simulations for many sequences and subsequently trained using ML. The resulting Hamiltonian, combining physics-based electrostatics and machine-learned nonelectrostatics, accurately predicts sequence-specific global and local measures of conformations beyond the original observable used from the simulation. This is in contrast to traditional ML approaches that train and predict a specific observable, not a Hamiltonian. Our formalism reproduces experimental measurements, predicts multiple conformational features directly from sequence with high throughput that will give insights into IDP design and evolution, and illustrates the broad utility of using physics-based ML to train unknown parts of a Hamiltonian, rather than a specific observable, in combination with known physics.

Weighted families of contact maps to characterize conformational ensembles of (highly-)flexible proteins

MOTIVATION

Characterizing the structure of flexible proteins, particularly within the realm of intrinsic disorder, presents a formidable challenge due to their high conformational variability. Currently, their structural representation relies on (possibly large) conformational ensembles derived from a combination of experimental and computational methods. The detailed structural analysis of these ensembles is a difficult task, for which existing tools have limited effectiveness.

RESULTS

This study proposes an innovative extension of the concept of contact maps to the ensemble framework, incorporating the intrinsic probabilistic nature of disordered proteins. Within this framework, a conformational ensemble is characterized through a weighted family of contact maps. To achieve this, conformations are first described using a refined definition of contact that appropriately accounts for the geometry of the inter-residue interactions and the sequence context. Representative structural features of the ensemble naturally emerge from the subsequent clustering of the resulting contact-based descriptors. Importantly, transiently populated structural features are readily identified within large ensembles. The performance of the method is illustrated by several use cases and compared with other existing approaches, highlighting its superiority in capturing relevant structural features of highly flexible proteins.

AVAILABILITY AND IMPLEMENTATION

An open-source implementation of the method is provided together with an easy-to-use Jupyter notebook, available at https://gitlab.laas.fr/moma/WARIO.

Deeper Insight of the Conformational Ensemble of Intrinsically Disordered Proteins

It is generally known that, unlike structured proteins, intrinsically disordered proteins, IDPs, exhibit various structures and conformers, the so-called conformational ensemble, CoE. This study aims to better understand the conformers that make up the IDP ensemble by decomposing the CoE into groups separated by their radius of gyration, Rg. A common approach to studying CoE for IDPs is to use low-resolution techniques, such as small-angle scattering, and combine those with computer simulations on different length scales. Herein, the well-studied antimicrobial saliva protein histatin 5 was utilized as a model peptide for an IDP; the average intensity curves were obtained from small-angle X-ray scattering; and compared with fully atomistic, explicit water, molecular dynamics simulations; then, the intensity curve was decomposed with respect to the different Rg values; and their secondary structure propensities were investigated. We foresee that this approach can provide important information on the CoE and the individual conformers within; in that case, it will serve as an additional tool for understanding the IDP structure-function relationship on a more detailed level.

Deciphering Photoinduced Catalytic Reaction Mechanisms in Natural and Artificial Photosynthetic Systems on Multiple Temporal and Spatial Scales Using X-ray Probes

Utilization of renewable energies for catalytically generating value-added chemicals is highly desirable in this era of rising energy demands and climate change impacts. Artificial photosynthetic systems or photocatalysts utilize light to convert abundant CO2, H2O, and O2 to fuels, such as carbohydrates and hydrogen, thus converting light energy to storable chemical resources. The emergence of intense X-ray pulses from synchrotrons, ultrafast X-ray pulses from X-ray free electron lasers, and table-top laser-driven sources over the past decades opens new frontiers in deciphering photoinduced catalytic reaction mechanisms on the multiple temporal and spatial scales. Operando X-ray spectroscopic methods offer a new set of electronic transitions in probing the oxidation states, coordinating geometry, and spin states of the metal catalytic center and photosensitizers with unprecedented energy and time resolution. Operando X-ray scattering methods enable previously elusive reaction steps to be characterized on different length scales and time scales. The methodological progress and their application examples collected in this review will offer a glimpse into the accomplishments and current state in deciphering reaction mechanisms for both natural and synthetic systems. Looking forward, there are still many challenges and opportunities at the frontier of catalytic research that will require further advancement of the characterization techniques.

Experimental methods to study the structure and dynamics of intrinsically disordered regions in proteins

Eukaryotic proteins often feature long stretches of amino acids that lack a well-defined three-dimensional structure and are referred to as intrinsically disordered proteins (IDPs) or regions (IDRs). Although these proteins challenge conventional structure-function paradigms, they play vital roles in cellular processes. Recent progress in experimental techniques, such as NMR spectroscopy, single molecule FRET, high speed AFM and SAXS, have provided valuable insights into the biophysical basis of IDP function. This review discusses the advancements made in these techniques particularly for the study of disordered regions in proteins. In NMR spectroscopy new strategies such as 13C detection, non-uniform sampling, segmental isotope labeling, and rapid data acquisition methods address the challenges posed by spectral overcrowding and low stability of IDPs. The importance of various NMR parameters, including chemical shifts, hydrogen exchange rates, and relaxation measurements, to reveal transient secondary structures within IDRs and IDPs are presented. Given the high flexibility of IDPs, the review outlines NMR methods for assessing their dynamics at both fast (ps-ns) and slow (μs-ms) timescales. IDPs exert their functions through interactions with other molecules such as proteins, DNA, or RNA. NMR-based titration experiments yield insights into the thermodynamics and kinetics of these interactions. Detailed study of IDPs requires multiple experimental techniques, and thus, several methods are described for studying disordered proteins, highlighting their respective advantages and limitations. The potential for integrating these complementary techniques, each offering unique perspectives, is explored to achieve a comprehensive understanding of IDPs.

High-throughput assay exploiting disorder-to-order conformational switches: application to the proteasomal Rpn10:E6AP complex

Conformational switching is pervasively driven by protein interactions, particularly for intrinsically disordered binding partners. We developed a dually orthogonal fluorescence-based assay to monitor such events, exploiting environmentally sensitive fluorophores. This assay is applied to E3 ligase E6AP, as its AZUL domain induces a disorder-to-order switch in an intrinsically disordered region of the proteasome, the so-named Rpn10 AZUL-binding domain (RAZUL). By testing various fluorophores, we developed an assay appropriate for high-throughput screening of Rpn10:E6AP-disrupting ligands. We found distinct positions in RAZUL for fluorophore labeling with either acrylodan or Atto610, which had disparate spectral responses to E6AP binding. E6AP caused a hypsochromic shift with increased fluorescence of acrylodan-RAZUL while decreasing fluorescence intensity of Atto610-RAZUL. Combining RAZUL labeled with either acrylodan or Atto610 into a common sample achieved robust and orthogonal measurement of the E6AP-induced conformational switch. This approach is generally applicable to disorder-to-order (or vice versa) transitions mediated by molecular interactions.

Sequence-dependent material properties of biomolecular condensates and their relation to dilute phase conformations

Material properties of phase-separated biomolecular condensates, enriched with disordered proteins, dictate many cellular functions. Contrary to the progress made in understanding the sequence-dependent phase separation of proteins, little is known about the sequence determinants of condensate material properties. Using the hydropathy scale and Martini models, we computationally decipher these relationships for charge-rich disordered protein condensates. Our computations yield dynamical, rheological, and interfacial properties of condensates that are quantitatively comparable with experimentally characterized condensates. Interestingly, we find that the material properties of model and natural proteins respond similarly to charge segregation, despite different sequence compositions. Molecular interactions within the condensates closely resemble those within the single-chain ensembles. Consequently, the material properties strongly correlate with molecular contact dynamics and single-chain structural properties. We demonstrate the potential to harness the sequence characteristics of disordered proteins for predicting and engineering the material properties of functional condensates, with insights from the dilute phase properties.

Magnetic tweezers characterization of the entropic elasticity of intrinsically disordered proteins and peptoids

Understanding the conformational behavior of biopolymers is essential to unlocking knowledge of their biophysical mechanisms and functional roles. Single-molecule force spectroscopy can provide a unique perspective on this by exploiting entropic elasticity to uncover key biopolymer structural parameters. A particularly powerful approach involves the use of magnetic tweezers, which can easily generate lower stretching forces (0.1-20 pN). For forces at the low end of this range, the elastic response of biopolymers is sensitive to excluded volume effects, and they can be described by Pincus blob elasticity model that allow robust extraction of the Flory polymer scaling exponent. Here, we detail protocols for the use of magnetic tweezers for force-extension measurements of intrinsically disordered proteins and peptoids. We also discuss procedures for fitting low-force elastic curves to the predictions of polymer physics models to extract key conformational parameters.

Fine structures of intrinsically disordered proteins

We report simulation studies of 33 single intrinsically disordered proteins (IDPs) using coarse-grained bead-spring models where interactions among different amino acids are introduced through a hydropathy matrix and additional screened Coulomb interaction for the charged amino acid beads. Our simulation studies of two different hydropathy scales (HPS1, HPS2) [Dignon et al., PLoS Comput. Biol. 14, e1005941 (2018); Tesei et al. Proc. Natl. Acad. Sci. U. S. A. 118, e2111696118 (2021)] and the comparison with the existing experimental data indicate an optimal interaction parameter ϵ = 0.1 and 0.2 kcal/mol for the HPS1 and HPS2 hydropathy scales. We use these best-fit parameters to investigate both the universal aspects as well as the fine structures of the individual IDPs by introducing additional characteristics. (i) First, we investigate the polymer-specific scaling relations of the IDPs in comparison to the universal scaling relations [Bair et al., J. Chem. Phys. 158, 204902 (2023)] for the homopolymers. By studying the scaled end-to-end distances ⟨RN2⟩/(2Lℓp) and the scaled transverse fluctuations l̃⊥2=⟨l⊥2⟩/L, we demonstrate that IDPs are broadly characterized with a Flory exponent of ν ≃ 0.56 with the conclusion that conformations of the IDPs interpolate between Gaussian and self-avoiding random walk chains. Then, we introduce (ii) Wilson charge index (W) that captures the essential features of charge interactions and distribution in the sequence space and (iii) a skewness index (S) that captures the finer shape variation of the gyration radii distributions as a function of the net charge per residue and charge asymmetry parameter. Finally, our study of the (iv) variation of ⟨Rg⟩ as a function of salt concentration provides another important metric to bring out finer characteristics of the IDPs, which may carry relevant information for the origin of life.

Biophysical characterization of the Plasmodium falciparum circumsporozoite protein's N-terminal domain

The circumsporozoite protein (CSP) is the main surface antigen of the Plasmodium sporozoite (SPZ) and forms the basis of the currently only licensed anti-malarial vaccine (RTS,S/AS01). CSP uniformly coats the SPZ and plays a pivotal role in its immunobiology, in both the insect and the vertebrate hosts. Although CSP's N-terminal domain (CSPN ) has been reported to play an important role in multiple CSP functions, a thorough biophysical and structural characterization of CSPN is currently lacking. Here, we present an alternative method for the recombinant production and purification of CSPN from Plasmodium falciparum (PfCSPN ), which provides pure, high-quality protein preparations with high yields. Through an interdisciplinary approach combining in-solution experimental methods and in silico analyses, we provide strong evidence that PfCSPN is an intrinsically disordered region displaying some degree of compaction.

Exploring novel and fast stability or sameness evaluation tool for different categories of injectable formulations

The establishment of drug product stability and sameness is the heart of generic formulation development. For regulatory filing, various instrumental methods are used on a case basis to establish the generic and innovator product sameness in multiple aspects. Here in the present study, we explored the applicability of the Time-correlated single photon counting (TCS-PC) technique as a fast, reliable, and nondestructive method for establishing the sameness of three different categories of injectable formulations, namely, Amphotericin B liposome for injection, enoxaparin injection, and iron sucrose injection. All three category formulations were evaluated in their native and artificially induced post degradation state to identify the discrimination power of the used instrumental techniques. The degradation of materials were confirmed by high performance liquid chromatography (HPLC). Based on the product category, pre and post-degradation samples were evaluated by selective instrumental methods like differential scanning calorimetry (DSC), nuclear magnetic resonance (NMR), fluorescence spectroscopy, particle size analysis by dynamic light scattering (DLS), small angle X-ray scattering (SAXS), Raman spectroscopy, inductively coupled plasma optical-emission spectrometry (ICP-OES) and circular dichroism study. All pre and post-degradation samples were further analyzed by TCS-PC. We observed that, TCS-PC can identify the differences between the initial and post degradation samples in very less time with promising discrimination power across the different injectable formulation types. Thus TCS-PC can be used as a fast and promising stability or sameness evaluation tool for different injectable drug products.

14-3-3 protein inhibits CaMKK1 by blocking the kinase active site with its last two C-terminal helices

Ca2+ /CaM-dependent protein kinase kinases 1 and 2 (CaMKK1 and CaMKK2) phosphorylate and enhance the catalytic activity of downstream kinases CaMKI, CaMKIV, and protein kinase B. Accordingly, CaMKK1 and CaMKK2 regulate key physiological and pathological processes, such as tumorigenesis, neuronal morphogenesis, synaptic plasticity, transcription factor activation, and cellular energy homeostasis, and promote cell survival. Both CaMKKs are partly inhibited by phosphorylation, which in turn triggers adaptor and scaffolding protein 14-3-3 binding. However, 14-3-3 binding only significantly affects CaMKK1 function. CaMKK2 activity remains almost unchanged after complex formation for reasons still unclear. Here, we aim at structurally characterizing CaMKK1:14-3-3 and CaMKK2:14-3-3 complexes by SAXS, H/D exchange coupled to MS, and fluorescence spectroscopy. The results revealed that complex formation suppresses the interaction of both phosphorylated CaMKKs with Ca2+ /CaM and affects the structure of their kinase domains and autoinhibitory segments. But these effects are much stronger on CaMKK1 than on CaMKK2 because the CaMKK1:14-3-3γ complex has a more compact and rigid structure in which the active site of the kinase domain directly interacts with the last two C-terminal helices of the 14-3-3γ protein, thereby inhibiting CaMKK1. In contrast, the CaMKK2:14-3-3 complex has a looser and more flexible structure, so 14-3-3 binding only negligibly affects the catalytic activity of CaMKK2. Therefore, Ca2+ /CaM binding suppression and the interaction of the kinase active site of CaMKK1 with the last two C-terminal helices of 14-3-3γ protein provide the structural basis for 14-3-3-mediated CaMKK1 inhibition.

Pincus blob elasticity in an intrinsically disordered protein

Understanding the dynamic structure of intrinsically disordered proteins (IDPs) is important to deciphering their biological functions. Here, we exploit precision entropic elasticity measurements to infer the conformational behavior of a model IDP construct formed from the disordered tail of the neurofilament low molecular weight protein. The IDP construct notably displays a low-force power-law elastic regime, consistent with the Pincus blob model, which allows direct extraction of the Flory exponent, [Formula: see text], from the force-extension relationship. We find [Formula: see text] increases with added denaturant, transitioning from a nearly ideal chain to a swollen chain in a manner quantitatively consistent with measurements of IDP dimensions from other experimental techniques. We suggest that measurements of entropic elasticity could be broadly useful in the study of IDP structure.

Structural characterization of an intrinsically disordered protein complex using integrated small-angle neutron scattering and computing

Characterizing structural ensembles of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) of proteins is essential for studying structure-function relationships. Due to the different neutron scattering lengths of hydrogen and deuterium, selective labeling and contrast matching in small-angle neutron scattering (SANS) becomes an effective tool to study dynamic structures of disordered systems. However, experimental timescales typically capture measurements averaged over multiple conformations, leaving complex SANS data for disentanglement. We hereby demonstrate an integrated method to elucidate the structural ensemble of a complex formed by two IDRs. We use data from both full contrast and contrast matching with residue-specific deuterium labeling SANS experiments, microsecond all-atom molecular dynamics (MD) simulations with four molecular mechanics force fields, and an autoencoder-based deep learning (DL) algorithm. From our combined approach, we show that selective deuteration provides additional information that helps characterize structural ensembles. We find that among the four force fields, a99SB-disp and CHARMM36m show the strongest agreement with SANS and NMR experiments. In addition, our DL algorithm not only complements conventional structural analysis methods but also successfully differentiates NMR and MD structures which are indistinguishable on the free energy surface. Lastly, we present an ensemble that describes experimental SANS and NMR data better than MD ensembles generated by one single force field and reveal three clusters of distinct conformations. Our results demonstrate a new integrated approach for characterizing structural ensembles of IDPs.

Not Only Expansion: Proline Content and Density Also Induce Disordered Protein Conformation Compaction

Intrinsically disordered proteins (IDPs) adopt a wide array of different conformations that can be constrained by the presence of proline residues, which are frequently found in IDPs. To assess the effects of proline, we designed a series of peptides that differ with respect to the number of prolines in the sequence and their organization. Using high-resolution atomistic molecular dynamics simulations, we found that accounting for whether the proline residues are clustered or isolated contributed significantly to explaining deviations in the experimentally-determined gyration radii of IDPs from the values expected based on the Flory scaling-law. By contrast, total proline content makes smaller contribution to explaining the effect of prolines on IDP conformation. Proline residues exhibit opposing effects depending on their organizational pattern in the IDP sequence. Clustered prolines (i.e., prolines with ≤2 intervening non-proline residues) result in expanded peptide conformations whereas isolated prolines (i.e., prolines with >2 intervening non-proline residues) impose compacted conformations. Clustered prolines were estimated to induce an expansion of ∼20% in IDP dimension (via formation of PPII structural elements) whereas isolated prolines were estimated to induce a compaction of ∼10% in IDP dimension (via the formation of backbone turns). This dual role of prolines provides a mechanism for conformational switching that does not rely on the kinetically much slower isomerization of cis proline to the trans form. Bioinformatic analysis demonstrates high populations of both isolated and clustered prolines and implementing them in coarse-grained molecular dynamics models illustrates that they improve the characterization of the conformational ensembles of IDPs.

Intramolecular structural heterogeneity altered by long-range contacts in an intrinsically disordered protein

Short-range interactions and long-range contacts drive the 3D folding of structured proteins. The proteins' structure has a direct impact on their biological function. However, nearly 40% of the eukaryotes proteome is composed of intrinsically disordered proteins (IDPs) and protein regions that fluctuate between ensembles of numerous conformations. Therefore, to understand their biological function, it is critical to depict how the structural ensemble statistics correlate to the IDPs' amino acid sequence. Here, using small-angle X-ray scattering and time-resolved Förster resonance energy transfer (trFRET), we study the intramolecular structural heterogeneity of the neurofilament low intrinsically disordered tail domain (NFLt). Using theoretical results of polymer physics, we find that the Flory scaling exponent of NFLt subsegments correlates linearly with their net charge, ranging from statistics of ideal to self-avoiding chains. Surprisingly, measuring the same segments in the context of the whole NFLt protein, we find that regardless of the peptide sequence, the segments' structural statistics are more expanded than when measured independently. Our findings show that while polymer physics can, to some level, relate the IDP's sequence to its ensemble conformations, long-range contacts between distant amino acids play a crucial role in determining intramolecular structures. This emphasizes the necessity of advanced polymer theories to fully describe IDPs ensembles with the hope that it will allow us to model their biological function.

The intrinsically disordered protein glue of the myelin major dense line: Linking AlphaFold2 predictions to experimental data

Numerous human proteins are classified as intrinsically disordered proteins (IDPs). Due to their physicochemical properties, high-resolution structural information about IDPs is generally lacking. On the other hand, IDPs are known to adopt local ordered structures upon interactions with e.g. other proteins or lipid membrane surfaces. While recent developments in protein structure prediction have been revolutionary, their impact on IDP research at high resolution remains limited. We took a specific example of two myelin-specific IDPs, the myelin basic protein (MBP) and the cytoplasmic domain of myelin protein zero (P0ct). Both of these IDPs are crucial for normal nervous system development and function, and while they are disordered in solution, upon membrane binding, they partially fold into helices, being embedded into the lipid membrane. We carried out AlphaFold2 predictions of both proteins and analysed the models in light of experimental data related to protein structure and molecular interactions. We observe that the predicted models have helical segments that closely correspond to the membrane-binding sites on both proteins. We furthermore analyse the fits of the models to synchrotron-based X-ray scattering and circular dichroism data from the same IDPs. The models are likely to represent the membrane-bound state of both MBP and P0ct, rather than the conformation in solution. Artificial intelligence-based models of IDPs appear to provide information on the ligand-bound state of these proteins, instead of the conformers dominating free in solution. We further discuss the implications of the predictions for mammalian nervous system myelination and their relevance to understanding disease aspects of these IDPs.

An ensemble of cadherin-catenin-vinculin complex employs vinculin as the major F-actin binding mode

The cell-cell adhesion cadherin-catenin complexes recruit vinculin to the adherens junction (AJ) to modulate the mechanical couplings between neighboring cells. However, it is unclear how vinculin influences the AJ structure and function. Here, we identified two patches of salt bridges that lock vinculin in the head-tail autoinhibited conformation and reconstituted the full-length vinculin activation mimetics bound to the cadherin-catenin complex. The cadherin-catenin-vinculin complex contains multiple disordered linkers and is highly dynamic, which poses a challenge for structural studies. We determined the ensemble conformation of this complex using small-angle x-ray and selective deuteration/contrast variation small-angle neutron scattering. In the complex, both α-catenin and vinculin adopt an ensemble of flexible conformations, but vinculin has fully open conformations with the vinculin head and actin-binding tail domains well separated from each other. F-actin binding experiments show that the cadherin-catenin-vinculin complex binds and bundles F-actin. However, when the vinculin actin-binding domain is removed from the complex, only a minor fraction of the complex binds to F-actin. The results show that the dynamic cadherin-catenin-vinculin complex employs vinculin as the primary F-actin binding mode to strengthen AJ-cytoskeleton interactions.

Overview Update: Computational Prediction of Intrinsic Disorder in Proteins

There are over 100 computational predictors of intrinsic disorder. These methods predict amino acid-level propensities for disorder directly from protein sequences. The propensities can be used to annotate putative disordered residues and regions. This unit provides a practical and holistic introduction to the sequence-based intrinsic disorder prediction. We define intrinsic disorder, explain the format of computational prediction of disorder, and identify and describe several accurate predictors. We also introduce recently released databases of intrinsic disorder predictions and use an illustrative example to provide insights into how predictions should be interpreted and combined. Lastly, we summarize key experimental methods that can be used to validate computational predictions. © 2023 Wiley Periodicals LLC.

The Analytical Flory Random Coil Is a Simple-to-Use Reference Model for Unfolded and Disordered Proteins

Denatured, unfolded, and intrinsically disordered proteins (collectively referred to here as unfolded proteins) can be described using analytical polymer models. These models capture various polymeric properties and can be fit to simulation results or experimental data. However, the model parameters commonly require users' decisions, making them useful for data interpretation but less clearly applicable as stand-alone reference models. Here we use all-atom simulations of polypeptides in conjunction with polymer scaling theory to parameterize an analytical model of unfolded polypeptides that behave as ideal chains (ν = 0.50). The model, which we call the analytical Flory random coil (AFRC), requires only the amino acid sequence as input and provides direct access to probability distributions of global and local conformational order parameters. The model defines a specific reference state to which experimental and computational results can be compared and normalized. As a proof-of-concept, we use the AFRC to identify sequence-specific intramolecular interactions in simulations of disordered proteins. We also use the AFRC to contextualize a curated set of 145 different radii of gyration obtained from previously published small-angle X-ray scattering experiments of disordered proteins. The AFRC is implemented as a stand-alone software package and is also available via a Google Colab notebook. In summary, the AFRC provides a simple-to-use reference polymer model that can guide intuition and aid in interpreting experimental or simulation results.

Conformational Disorder Analysis of the Conditionally Disordered Protein CP12 from Arabidopsis thaliana in Its Different Redox States

CP12 is a redox-dependent conditionally disordered protein universally distributed in oxygenic photosynthetic organisms. It is primarily known as a light-dependent redox switch regulating the reductive step of the metabolic phase of photosynthesis. In the present study, a small angle X-ray scattering (SAXS) analysis of recombinant Arabidopsis CP12 (AtCP12) in a reduced and oxidized form confirmed the highly disordered nature of this regulatory protein. However, it clearly pointed out a decrease in the average size and a lower level of conformational disorder upon oxidation. We compared the experimental data with the theoretical profiles of pools of conformers generated with different assumptions and show that the reduced form is fully disordered, whereas the oxidized form is better described by conformers comprising both the circular motif around the C-terminal disulfide bond detected in previous structural analysis and the N-terminal disulfide bond. Despite the fact that disulfide bridges are usually thought to confer rigidity to protein structures, in the oxidized AtCP12, their presence coexists with a disordered nature. Our results rule out the existence of significant amounts of structured and compact conformations of free AtCP12 in a solution, even in its oxidized form, thereby highlighting the importance of recruiting partner proteins to complete its structured final folding.

Critical Assessment of Self-Consistency Checks in the All-Atom Molecular Dynamics Simulation of Intrinsically Disordered Proteins

All atom simulations can be used to quantify conformational properties of Intrinsically Disordered Proteins (IDP). However, simulations must satisfy convergence checks to ensure observables computed from simulation are reliable and reproducible. While absolute convergence is purely a theoretical concept requiring infinitely long simulation, a more practical, yet rigorous, approach is to impose Self Consistency Checks (SCCs) to gain confidence in the simulated data. Currently there is no study of SCCs in IDPs, unlike their folded counterparts. In this paper, we introduce different criteria for self-consistency checks for IDPs. Next, we impose these SCCs to critically assess the performance of different simulation protocols using the N terminal domain of HIV Integrase and the linker region of SARS-CoV-2 Nucleoprotein as two model IDPs. All simulation protocols begin with all-atom implicit solvent Monte Carlo (MC) simulation and subsequent clustering of MC generated conformations to create the representative structures of the IDPs. These representative structures serve as the initial structure for subsequent molecular dynamics (MD) runs with explicit solvent. We conclude that generating multiple short (∼3 μs) MD simulation trajectories─all starting from the most representative MC generated conformation─and merging them is the protocol of choice due to (i) its ability to satisfy multiple SCCs, (ii) consistently reproducing experimental data, and (iii) the efficiency of running independent trajectories in parallel by harnessing multiple cores available in modern GPU clusters. Running one long trajectory (greater than 20 μs) can also satisfy the first two criteria but is less desirable due to prohibitive computation time. These findings help resolve the challenge of identifying a usable starting configuration, provide an objective measure of SCC, and establish rigorous criteria to determine the minimum length (for one long simulation) or number of trajectories needed in all-atom simulation of IDPs.

Modeling of flexible membrane-bound biomolecular complexes for solution small-angle scattering

Recent advances in protein expression protocols, sample handling, and experimental set up of small-angle scattering experiments have allowed users of the technique to structurally investigate biomolecules of growing complexity and structural disorder. Notable examples include intrinsically disordered proteins, multi-domain proteins and membrane proteins in suitable carrier systems. Here, we outline a modeling scheme for calculating the scattering profiles from such complex samples. This kind of modeling is necessary for structural information to be refined from the corresponding data. The scheme bases itself on a hybrid of classical form factor based modeling and the well-known spherical harmonics-based formulation of small-angle scattering amplitudes. Our framework can account for flexible domains alongside other structurally elaborate components of the molecular system in question. We demonstrate the utility of this modeling scheme through a recent example of a structural model of the growth hormone receptor membrane protein in a phospholipid bilayer nanodisc which is refined against experimental SAXS data. Additionally we investigate how the scattering profiles from the complex would appear under different scattering contrasts. For each contrast situation we discuss what structural information is contained and the related consequences for modeling of the data.

Interpreting Transient Interactions of Intrinsically Disordered Proteins

The flexible nature of intrinsically disordered proteins (IDPs) gives rise to a conformational ensemble with a diverse set of conformations. The simplest way to describe this ensemble is through a homopolymer model without any specific interactions. However, there has been growing evidence that the conformational properties of IDPs and their relevant functions can be affected by transient interactions between specific and even nonlocal pairs of amino acids. Interpreting these interactions from experimental methods, each of which is most sensitive to a different distance regime referred to as probing length, remains a challenging and unsolved problem. Here, we first show that transient interactions can be realized between short fragments of charged amino acids by generating conformational ensembles using model disordered peptides and coarse-grained simulations. Using these ensembles, we investigate how sensitive different types of experimental measurements are to the presence of transient interactions. We find methods with shorter probing lengths to be more appropriate for detecting these transient interactions, but one experimental method is not sufficient due to the existence of other weak interactions typically seen in IDPs. Finally, we develop an adjusted polymer model with an additional short-distance peak which can robustly reproduce the distance distribution function from two experimental measurements with complementary short and long probing lengths. This new model can suggest whether a homopolymer model is insufficient for describing a specific IDP and meets the challenge of quantitatively identifying specific, transient interactions from a background of nonspecific, weak interactions.

Fuzzy Drug Targets: Disordered Proteins in the Drug-Discovery Realm

Intrinsically disordered proteins (IDPs) and regions (IDRs) form a large part of the eukaryotic proteome. Contrary to the structure-function paradigm, the disordered proteins perform a myriad of functions in vivo. Consequently, they are involved in various disease pathways and are plausible drug targets. Unlike folded proteins, that have a defined structure and well carved out drug-binding pockets that can guide lead molecule selection, the disordered proteins require alternative drug-development methodologies that are based on an acceptable picture of their conformational ensemble. In this review, we discuss various experimental and computational techniques that contribute toward understanding IDP "structure" and describe representative pursuances toward IDP-targeting drug development. We also discuss ideas on developing rational drug design protocols targeting IDPs.

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.

Illuminating Intrinsically Disordered Proteins with Integrative Structural Biology

Intense study of intrinsically disordered proteins (IDPs) did not begin in earnest until the late 1990s when a few groups, working independently, convinced the community that these 'weird' proteins could have important functions. Over the past two decades, it has become clear that IDPs play critical roles in a multitude of biological phenomena with prominent examples including coordination in signaling hubs, enabling gene regulation, and regulating ion channels, just to name a few. One contributing factor that delayed appreciation of IDP functional significance is the experimental difficulty in characterizing their dynamic conformations. The combined application of multiple methods, termed integrative structural biology, has emerged as an essential approach to understanding IDP phenomena. Here, we review some of the recent applications of the integrative structural biology philosophy to study IDPs.

Functional Implications of Dynamic Structures of Intrinsically Disordered Proteins Revealed by High-Speed AFM Imaging

The unique functions of intrinsically disordered proteins (IDPs) depend on their dynamic protean structure that often eludes analysis. High-speed atomic force microscopy (HS-AFM) can conduct this difficult analysis by directly visualizing individual IDP molecules in dynamic motion at sub-molecular resolution. After brief descriptions of the microscopy technique, this review first shows that the intermittent tip-sample contact does not alter the dynamic structure of IDPs and then describes how the number of amino acids contained in a fully disordered region can be estimated from its HS-AFM images. Next, the functional relevance of a dumbbell-like structure that has often been observed on IDPs is discussed. Finally, the dynamic structural information of two measles virus IDPs acquired from their HS-AFM and NMR analyses is described together with its functional implications.

Incorporation of D2O-Induced Fluorine Chemical Shift Perturbations into Ensemble-Structure Characterization of the ERalpha Disordered Region

Structural characterization of intrinsically disordered proteins (IDPs) requires a concerted effort between experiments and computations by accounting for their conformational heterogeneity. Given the diversity of experimental tools providing local and global structural information, constructing an experimental restraint-satisfying structural ensemble remains challenging. Here, we use the disordered N-terminal domain (NTD) of the estrogen receptor alpha (ERalpha) as a model system to combine existing small-angle X-ray scattering (SAXS) and hydroxyl radical protein footprinting (HRPF) data and newly acquired solvent accessibility data via D2O-induced fluorine chemical shifting (DFCS) measurements. A new set of DFCS data for the solvent exposure of a set of 12 amino acid positions were added to complement previously acquired HRPF measurements for the solvent exposure of the other 16 nonoverlapping amino acids, thereby improving the NTD ensemble characterization considerably. We also found that while choosing an initial ensemble of structures generated from a different atomic-level force field or sampling/modeling method can lead to distinct contact maps even when the same sets of experimental measurements were used for ensemble-fitting, comparative analyses from these initial ensembles reveal commonly recurring structural features in their ensemble-averaged contact map. Specifically, nonlocal or long-range transient interactions were found consistently between the N-terminal segments and the central region, sufficient to mediate the conformational ensemble and regulate how the NTD interacts with its coactivator proteins.

Intrinsically Disordered Proteins: An Overview

Many proteins and protein segments cannot attain a single stable three-dimensional structure under physiological conditions; instead, they adopt multiple interconverting conformational states. Such intrinsically disordered proteins or protein segments are highly abundant across proteomes, and are involved in various effector functions. This review focuses on different aspects of disordered proteins and disordered protein regions, which form the basis of the so-called "Disorder-function paradigm" of proteins. Additionally, various experimental approaches and computational tools used for characterizing disordered regions in proteins are discussed. Finally, the role of disordered proteins in diseases and their utility as potential drug targets are explored.

Developing Bonded Potentials for a Coarse-Grained Model of Intrinsically Disordered Proteins

Recent advances in residue-level coarse-grained (CG) computational models have enabled molecular-level insights into biological condensates of intrinsically disordered proteins (IDPs), shedding light on the sequence determinants of their phase separation. The existing CG models that treat protein chains as flexible molecules connected via harmonic bonds cannot populate common secondary-structure elements. Here, we present a CG dihedral angle potential between four neighboring beads centered at Cα atoms to faithfully capture the transient helical structures of IDPs. In order to parameterize and validate our new model, we propose Cα-based helix assignment rules based on dihedral angles that succeed in reproducing the atomistic helicity results of a polyalanine peptide and folded proteins. We then introduce sequence-dependent dihedral angle potential parameters (εd) and use experimentally available helical propensities of naturally occurring 20 amino acids to find their optimal values. The single-chain helical propensities from the CG simulations for commonly studied prion-like IDPs are in excellent agreement with the NMR-based α-helix fraction, demonstrating that the new HPS-SS model can accurately produce structural features of IDPs. Furthermore, this model can be easily implemented for large-scale assembly simulations due to its simplicity.

An intrinsically disordered transcription activation domain increases the DNA binding affinity and reduces the specificity of NFκB p50/RelA

Many transcription factors contain intrinsically disordered transcription activation domains (TADs), which mediate interactions with coactivators to activate transcription. Historically, DNA-binding domains and TADs have been considered as modular units, but recent studies have shown that TADs can influence DNA binding. Whether these results can be generalized to more TADs is not clear. Here, we biophysically characterized the NFκB p50/RelA heterodimer including the RelA TAD and investigated the TAD's influence on NFκB-DNA interactions. In solution, we show the RelA TAD is disordered but compact, with helical tendency in two regions that interact with coactivators. We determined that the presence of the TAD increased the stoichiometry of NFκB-DNA complexes containing promoter DNA sequences with tandem κB recognition motifs by promoting the binding of NFκB dimers in excess of the number of κB sites. In addition, we measured the binding affinity of p50/RelA for DNA containing tandem κB sites and single κB sites. While the presence of the TAD enhanced the binding affinity of p50/RelA for all κB sequences tested, it also increased the affinity for nonspecific DNA sequences by over 10-fold, leading to an overall decrease in specificity for κB DNA sequences. In contrast, previous studies have generally reported that TADs decrease DNA-binding affinity and increase sequence specificity. Our results reveal a novel function of the RelA TAD in promoting binding to nonconsensus DNA, which sheds light on previous observations of extensive nonconsensus DNA binding by NFκB in vivo in response to strong inflammatory signals.

Loosely-packed dynamical structures with partially-melted surface being the key for thermophilic argonaute proteins achieving high DNA-cleavage activity

Prokaryotic Argonaute proteins (pAgos) widely participate in hosts to defend against the invasion of nucleic acids. Compared with the CRISPR-Cas system, which requires a specific motif on the target and can only use RNA as guide, pAgos exhibit precise endonuclease activity on any arbitrary target sequence and can use both RNA and DNA as guide, thus rendering great potential for genome editing applications. Hitherto, most in-depth studies on the structure-function relationship of pAgos were conducted on thermophilic ones, functioning at ∼60 to 100°C, whose structures were, however, determined experimentally at much lower temperatures (20-33°C). It remains unclear whether these low-temperature structures can represent the true conformations of the thermophilic pAgos under their physiological conditions. The present work studied three pAgos, PfAgo, TtAgo and CbAgo, whose physiological temperatures differ significantly (95, 75 and 37°C). By conducting thorough experimental and simulation studies, we found that thermophilic pAgos (PfAgo and TtAgo) adopt a loosely-packed structure with a partially-melted surface at the physiological temperatures, largely different from the compact crystalline structures determined at moderate temperatures. In contrast, the mesophilic pAgo (CbAgo) assumes a compact crystalline structure at its optimal function temperature. Such a partially-disrupted structure endows thermophilic pAgos with great flexibility both globally and locally at the catalytic sites, which is crucial for them to achieve high DNA-cleavage activity. To further prove this, we incubated thermophilic pAgos with urea to purposely disrupt their structures, and the resulting cleavage activity was significantly enhanced below the physiological temperature, even at human body temperature. Further testing of many thermophilic Agos present in various thermophilic prokaryotes demonstrated that their structures are generally disrupted under physiological conditions. Therefore, our findings suggest that the highly dynamical structure with a partially-melted surface, distinct from the low-temperature crystalline structure, could be a general strategy assumed by thermophilic pAgos to achieve the high DNA-cleavage activity.

Untangling the Conformational Plasticity of V66M Human proBDNF Polymorphism as a Modifier of Psychiatric Disorder Susceptibility

The human genetic variant BDNF (V66M) represents the first example of neurotrophin family member that has been linked to psychiatric disorders. In order to elucidate structural differences that account for the effects in cognitive function, this hproBDNF polymorph was expressed, refolded, purified, and compared directly to the WT variant for the first time for differences in their 3D structures by DSF, limited proteolysis, FT-IR, and SAXS measurements in solution. Our complementary studies revealed a deep impact of V66M polymorphism on hproBDNF conformations in solution. Although the mean conformation in solution appears to be more compact in the V66M variant, overall, we demonstrated a large increase in flexibility in solution upon V66M mutation. Thus, considering that plasticity in IDR is crucial for protein function, the observed alterations may be related to the functional alterations in hproBDNF binding to its receptors p75NTR, sortilin, HAP1, and SorCS2. These effects can provoke altered intracellular neuronal trafficking and/or affect proBDNF physiological functions, leading to many brain-associated diseases and conditions such as cognitive impairment and anxiety. The structural alterations highlighted in the present study may pave the way to the development of drug discovery strategies to provide greater therapeutic responses and of novel pharmacologic strategy in human populations with this common polymorphism, ultimately guiding personalized medicine for neuropsychiatric disorders.

Structural Insights into the Intrinsically Disordered GPCR C-Terminal Region, Major Actor in Arrestin-GPCR Interaction

Arrestin-dependent pathways are a central component of G protein-coupled receptor (GPCRs) signaling. However, the molecular processes regulating arrestin binding are to be further illuminated, in particular with regard to the structural impact of GPCR C-terminal disordered regions. Here, we used an integrated biophysical strategy to describe the basal conformations of the C-terminal domains of three class A GPCRs, the vasopressin V2 receptor (V2R), the growth hormone secretagogue or ghrelin receptor type 1a (GHSR) and the β2-adernergic receptor (β2AR). By doing so, we revealed the presence of transient secondary structures in these regions that are potentially involved in the interaction with arrestin. These secondary structure elements differ from those described in the literature in interaction with arrestin. This suggests a mechanism where the secondary structure conformational preferences in the C-terminal regions of GPCRs could be a central feature for optimizing arrestins recognition.

Protein Dynamics to Define and Refine Disordered Protein Ensembles

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

Intrinsically disordered proteins: Ensembles at the limits of Anfinsen's dogma

Intrinsically disordered proteins (IDPs) are proteins that lack rigid 3D structure. Hence, they are often misconceived to present a challenge to Anfinsen's dogma. However, IDPs exist as ensembles that sample a quasi-continuum of rapidly interconverting conformations and, as such, may represent proteins at the extreme limit of the Anfinsen postulate. IDPs play important biological roles and are key components of the cellular protein interaction network (PIN). Many IDPs can interconvert between disordered and ordered states as they bind to appropriate partners. Conformational dynamics of IDPs contribute to conformational noise in the cell. Thus, the dysregulation of IDPs contributes to increased noise and "promiscuous" interactions. This leads to PIN rewiring to output an appropriate response underscoring the critical role of IDPs in cellular decision making. Nonetheless, IDPs are not easily tractable experimentally. Furthermore, in the absence of a reference conformation, discerning the energy landscape representation of the weakly funneled IDPs in terms of reaction coordinates is challenging. To understand conformational dynamics in real time and decipher how IDPs recognize multiple binding partners with high specificity, several sophisticated knowledge-based and physics-based in silico sampling techniques have been developed. Here, using specific examples, we highlight recent advances in energy landscape visualization and molecular dynamics simulations to discern conformational dynamics and discuss how the conformational preferences of IDPs modulate their function, especially in phenotypic switching. Finally, we discuss recent progress in identifying small molecules targeting IDPs underscoring the potential therapeutic value of IDPs. Understanding structure and function of IDPs can not only provide new insight on cellular decision making but may also help to refine and extend Anfinsen's structure/function paradigm.

How well does molecular simulation reproduce environment-specific conformations of the intrinsically disordered peptides PLP, TP2 and ONEG?

Understanding the conformational ensembles of intrinsically disordered proteins and peptides (IDPs) in their various biological environments is essential for understanding their mechanisms and functional roles in the proteome, leading to a greater knowledge of, and potential treatments for, a broad range of diseases. To determine whether molecular simulation is able to generate accurate conformational ensembles of IDPs, we explore the structural landscape of the PLP peptide (an intrinsically disordered region of the proteolipid membrane protein) in aqueous and membrane-mimicking solvents, using replica exchange with solute scaling (REST2), and examine the ability of four force fields (ff14SB, ff14IDPSFF, CHARMM36 and CHARMM36m) to reproduce literature circular dichroism (CD) data. Results from variable temperature (VT) 1H and Rotating frame Overhauser Effect SpectroscopY (ROESY) nuclear magnetic resonance (NMR) experiments are also presented and are consistent with the structural observations obtained from the simulations and CD. We also apply the optimum simulation protocol to TP2 and ONEG (a cell-penetrating peptide (CPP) and a negative control peptide, respectively) to gain insight into the structural differences that may account for the observed difference in their membrane-penetrating abilities. Of the tested force fields, we find that CHARMM36 and CHARMM36m are best suited to the study of IDPs, and accurately predict a disordered to helical conformational transition of the PLP peptide accompanying the change from aqueous to membrane-mimicking solvents. We also identify an α-helical structure of TP2 in the membrane-mimicking solvents and provide a discussion of the mechanistic implications of this observation with reference to the previous literature on the peptide. From these results, we recommend the use of CHARMM36m with the REST2 protocol for the study of environment-specific IDP conformations. We believe that the simulation protocol will allow the study of a broad range of IDPs that undergo conformational transitions in different biological environments.

Conformational ensembles of intrinsically disordered proteins and flexible multidomain proteins

Intrinsically disordered proteins (IDPs) and multidomain proteins with flexible linkers show a high level of structural heterogeneity and are best described by ensembles consisting of multiple conformations with associated thermodynamic weights. Determining conformational ensembles usually involves the integration of biophysical experiments and computational models. In this review, we discuss current approaches to determine conformational ensembles of IDPs and multidomain proteins, including the choice of biophysical experiments, computational models used to sample protein conformations, models to calculate experimental observables from protein structure, and methods to refine ensembles against experimental data. We also provide examples of recent applications of integrative conformational ensemble determination to study IDPs and multidomain proteins and suggest future directions for research in the field.

Databases for intrinsically disordered proteins

Intrinsically disordered regions (IDRs) lacking a fixed three-dimensional protein structure are widespread and play a central role in cell regulation. Only a small fraction of IDRs have been functionally characterized, with heterogeneous experimental evidence that is largely buried in the literature. Predictions of IDRs are still difficult to estimate and are poorly characterized. Here, an overview of the publicly available knowledge about IDRs is reported, including manually curated resources, deposition databases and prediction repositories. The types, scopes and availability of the various resources are analyzed, and their complementarity and overlap are highlighted. The volume of information included and the relevance to the field of structural biology are compared.

Refining conformational ensembles of flexible proteins against small-angle x-ray scattering data

Intrinsically disordered proteins and flexible regions in multidomain proteins display substantial conformational heterogeneity. Characterizing the conformational ensembles of these proteins in solution typically requires combining one or more biophysical techniques with computational modeling or simulations. Experimental data can either be used to assess the accuracy of a computational model or to refine the computational model to get a better agreement with the experimental data. In both cases, one generally needs a so-called forward model (i.e., an algorithm to calculate experimental observables from individual conformations or ensembles). In many cases, this involves one or more parameters that need to be set, and it is not always trivial to determine the optimal values or to understand the impact on the choice of parameters. For example, in the case of small-angle x-ray scattering (SAXS) experiments, many forward models include parameters that describe the contribution of the hydration layer and displaced solvent to the background-subtracted experimental data. Often, one also needs to fit a scale factor and a constant background for the SAXS data but across the entire ensemble. Here, we present a protocol to dissect the effect of the free parameters on the calculated SAXS intensities and to identify a reliable set of values. We have implemented this procedure in our Bayesian/maximum entropy framework for ensemble refinement and demonstrate the results on four intrinsically disordered proteins and a protein with three domains connected by flexible linkers. Our results show that the resulting ensembles can depend on the parameters used for solvent effects and suggest that these should be chosen carefully. We also find a set of parameters that work robustly across all proteins.

Studying the Structures of Relaxed and Fuzzy Interactions: The Diverse World of S100 Complexes

S100 proteins are small, dimeric, Ca²⁺-binding proteins of considerable interest due to their associations with cancer and rheumatic and neurodegenerative diseases. They control the functions of numerous proteins by forming protein–protein complexes with them. Several of these complexes were found to display “fuzzy” properties. Examining these highly flexible interactions, however, is a difficult task, especially from a structural biology point of view. Here, we summarize the available in vitro techniques that can be deployed to obtain structural information about these dynamic complexes. We also review the current state of knowledge about the structures of S100 complexes, focusing on their often-asymmetric nature.

Extended disorder at the cell surface: The conformational landscape of the ectodomains of syndecans

Syndecans are membrane proteoglycans regulating extracellular matrix assembly, cell adhesion and signaling. Their ectodomains can be shed from the cell surface, and act as paracrine and autocrine effectors or as competitors of full-length syndecans. We report the first biophysical characterization of the recombinant ectodomains of the four human syndecans using biophysical techniques, and show that they behave like flexible random-coil intrinsically disordered proteins, and adopt several conformation ensembles in solution. We have characterized their conformational landscapes using native mass spectrometry (MS) and ion-mobility MS, and demonstrated that the syndecan ectodomains explore the majority of their conformational landscape, from minor compact, globular-like, conformations to extended ones. We also report that the ectodomain of syndecan-4, corresponding to a natural isoform, is able to dimerize via a disulfide bond. We have generated a three-dimensional model of the C-terminus of this dimer, which supports the dimerization via a disulfide bond. Furthermore, we have mapped the NXIP adhesion motif of syndecans and their sequences involved in the formation of ternary complexes with integrins and growth factor receptors on the major conformations of their ectodomains, and shown that these sequences are not accessible in all the conformations, suggesting that only some of them are biologically active. Lastly, although the syndecan ectodomains have a far lower number of amino acid residues than their membrane partners, their intrinsic disorder and flexibility allow them to adopt extended conformations, which have roughly the same size as the cell surface receptors (e.g., integrins and growth factor receptors) they bind to.

14-3-3 proteins inactivate DAPK2 by promoting its dimerization and protecting key regulatory phosphosites

Death-associated protein kinase 2 (DAPK2) is a CaM-regulated Ser/Thr protein kinase, involved in apoptosis, autophagy, granulocyte differentiation and motility regulation, whose activity is controlled by autoinhibition, autophosphorylation, dimerization and interaction with scaffolding proteins 14-3-3. However, the structural basis of 14-3-3-mediated DAPK2 regulation remains unclear. Here, we structurally and biochemically characterize the full-length human DAPK2:14-3-3 complex by combining several biophysical techniques. The results from our X-ray crystallographic analysis revealed that Thr369 phosphorylation at the DAPK2 C terminus creates a high-affinity canonical mode III 14-3-3-binding motif, further enhanced by the diterpene glycoside Fusicoccin A. Moreover, concentration-dependent DAPK2 dimerization is disrupted by Ca²⁺/CaM binding and stabilized by 14-3-3 binding in solution, thereby protecting the DAPK2 inhibitory autophosphorylation site Ser318 against dephosphorylation and preventing Ca²⁺/CaM binding. Overall, our findings provide mechanistic insights into 14-3-3-mediated DAPK2 inhibition and highlight the potential of the DAPK2:14-3-3 complex as a target for anti‐inflammatory therapies.

Horvath et al. structurally and biochemically characterize the full-length human DAPK2-14-3-3 complex to investigate the effects of binding to DAPK2 on its dimerization, activation by dephosphorylation of Ser318, and Ca²⁺/calmodulin binding. Their results provide mechanistic insights into 14- 3-3-mediated DAPK2 inhibition and highlight the potential of the DAPK2:14-3-3 complex as a target for anti-inflammatory therapies.