Structural characterization of intrinsically disordered proteins by NMR spectroscopy

Structures prediction and replica exchange molecular dynamics simulations of α-synuclein: A case study for intrinsically disordered proteins

In recent years, a variety of three-dimensional structure prediction tools, including AlphaFold2, AlphaFold3, I-TASSER, C-I-TASSER, Phyre2, ESMFold, and RoseTTAFold, have been employed in the investigation of intrinsically disordered proteins. However, a comprehensive validation of these tools specifically for intrinsically disordered proteins has yet to be conducted. In this study, we utilize AlphaFold2, AlphaFold3, I-TASSER, C-I-TASSER, Phyre2, ESMFold, and RoseTTAFold to predict the structure of a model intrinsically disordered α-synuclein protein. Additionally, extensive replica exchange molecular dynamics simulations of the intrinsically disordered protein are conducted. The resulting structures from both structure prediction tools and replica exchange molecular dynamics simulations are analyzed for radius of gyration, secondary and tertiary structure properties, as well as Cα and Hα chemical shift values. A comparison of the obtained results with experimental data reveals that replica exchange molecular dynamics simulations provide results in excellent agreement with experimental observations. However, none of the structure prediction tools utilized in this study can fully capture the structural characteristics of the model intrinsically disordered protein. This study shows that a cluster of ensembles are required for intrinsically disordered proteins. Artificial-intelligence based structure prediction tools such as AlphaFold3 and C-I-TASSER could benefit from stochastic sampling or Monte Carlo simulations for generating an ensemble of structures for intrinsically disordered proteins.

Exploring the Functional Landscape of the p53 Regulatory Domain: The Stabilizing Role of Post-Translational Modifications

This study focuses on the intrinsically disordered regulatory domain of p53 and the impact of post-translational modifications. Through fully atomistic explicit water molecular dynamics simulations, we show the wealth of information and detailed understanding that can be obtained by varying the number of phosphorylated amino acids and implementing a restriction in the conformational entropy of the N-termini of that intrinsically disordered region. The take-home message for the reader is to achieve a detailed understanding of the impact of phosphorylation with respect to (1) the conformational dynamics and flexibility, (2) structural effects, (3) protein interactivity, and (4) energy landscapes and conformational ensembles. Although our model system is the regulatory domain p53 of the tumor suppressor protein p53, this study contributes to understanding the general effects of intrinsically disordered phosphorylated proteins and the impact of phosphorylated groups, more specifically, how minor changes in the primary sequence can affect the properties mentioned above.

Effects of Charge Sequence Pattern and Lysine-to-Arginine Substitution on the Structural Stability of Bioinspired Polyampholytes

A comprehensive study focusing on the combined influence of the charge sequence pattern and the type of positively charged amino acids on the formation of secondary structures in sequence-specific polyampholytes is presented. The sequences of interest consisting exclusively of ionizable amino acids (lysine, K; arginine, R; and glutamic acid, E) are (EKEK)5, (EKKE)5, (ERER)5, (ERRE)5, and (EKER)5. The stability of the secondary structure was examined at three pH values in the presence of urea and NaCl. The results presented here underscore the combined prominent effects of the charge sequence pattern and the type of positively charged monomers on secondary structure formation. Additionally, (ERRE)5 readily aggregated across a wide range of pH. In contrast, sequences with the same charge pattern, (EKKE)5, as well as the sequences with the equivalent amino acid content, (ERER)5, exhibited no aggregate formation under equivalent pH and concentration conditions.

Mechanisms of bacterial resistance to environmental silver and antimicrobial strategies for silver: A review

The good antimicrobial properties of silver make it widely used in food, medicine, and environmental applications. However, the release and accumulation of silver-based antimicrobial agents in the environment is increasing with the extensive use of silver-based antimicrobials, and the prevalence of silver-resistant bacteria is increasing. To prevent the emergence of superbugs, it is necessary to exercise rational and strict control over drug use. The mechanism of bacterial resistance to silver has not been fully elucidated, and this article provides a review of the progress of research on the mechanism of bacterial resistance to silver. The results indicate that bacterial resistance to silver can occur through inducing silver particles aggregation and Ag+ reduction, inhibiting silver contact with and entry into cells, efflux of silver particles and Ag+ in cells, and activation of damage repair mechanisms. We propose that the bacterial mechanism of silver resistance involves a combination of interrelated systems. Finally, we discuss how this information can be used to develop the next generation of silver-based antimicrobials and antimicrobial therapies. And some antimicrobial strategies are proposed such as the "Trojan Horse" - camouflage, using efflux pump inhibitors to reduce silver efflux, working with "minesweeper", immobilization of silver particles.

A secreted bacterial protein protects bacteria from cationic antimicrobial peptides by entrapment in phase-separated droplets

Mammalian hosts combat bacterial infections through the production of defensive cationic antimicrobial peptides (CAPs). These immune factors are capable of directly killing bacterial invaders; however, many pathogens have evolved resistance evasion mechanisms such as cell surface modification, CAP sequestration, degradation, or efflux. We have discovered that several pathogenic and commensal proteobacteria, including the urgent human threat Neisseria gonorrhoeae, secrete a protein (lactoferrin-binding protein B, LbpB) that contains a low-complexity anionic domain capable of inhibiting the antimicrobial activity of host CAPs. This study focuses on a cattle pathogen, Moraxella bovis, that expresses the largest anionic domain of the LbpB homologs. We used an exhaustive biophysical approach employing circular dichroism, biolayer interferometry, cross-linking mass spectrometry, microscopy, size-exclusion chromatography with multi-angle light scattering coupled to small-angle X-ray scattering (SEC-MALS-SAXS), and NMR to understand the mechanisms of LbpB-mediated protection against CAPs. We found that the anionic domain of this LbpB displays an α-helical secondary structure but lacks a rigid tertiary fold. The addition of antimicrobial peptides derived from lactoferrin (i.e. lactoferricin) to the anionic domain of LbpB or full-length LbpB results in the formation of phase-separated droplets of LbpB together with the antimicrobial peptides. The droplets displayed a low rate of diffusion, suggesting that CAPs become trapped inside and are no longer able to kill bacteria. Our data suggest that pathogens, like M. bovis, leverage anionic intrinsically disordered domains for the broad recognition and neutralization of antimicrobials via the formation of biomolecular condensates.

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.

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.

The intrinsically disordered transcriptional activation domain of CIITA is functionally tuneable by single substitutions: An exception or a new paradigm?

During protein evolution, some amino acid substitutions modulate protein function ("tuneability"). In most proteins, the tuneable range is wide and can be sampled by a set of protein variants that each contains multiple amino acid substitutions. In other proteins, the full tuneable range can be accessed by a set of variants that each contains a single substitution. Indeed, in some globular proteins, the full tuneable range can be accessed by the set of site-saturating substitutions at an individual "rheostat" position. However, in proteins with intrinsically disordered regions (IDRs), most functional studies-which would also detect tuneability-used multiple substitutions or small deletions. In disordered transcriptional activation domains (ADs), studies with multiple substitutions led to the "acidic exposure" model, which does not anticipate the existence of rheostat positions. In the few studies that did assess effects of single substitutions on AD function, results were mixed: the ADs of two full-length transcription factors did not show tuneability, whereas a fragment of a third AD was tuneable by single substitutions. In this study, we tested tuneability in the AD of full-length human class II transactivator (CIITA). Sequence analyses and experiments showed that CIITA's AD is an IDR. Functional assays of singly-substituted AD variants showed that CIITA's function was highly tuneable, with outcomes not predicted by the acidic exposure model. Four tested positions showed rheostat behavior for transcriptional activation. Thus, tuneability of different IDRs can vary widely. Future studies are needed to illuminate the biophysical features that govern whether an IDR is tuneable by single substitutions.

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.

Intrinsically disordered regions are poised to act as sensors of cellular chemistry

Intrinsically disordered proteins and protein regions (IDRs) are abundant in eukaryotic proteomes and play a wide variety of essential roles. Instead of folding into a stable structure, IDRs exist in an ensemble of interconverting conformations whose structure is biased by sequence-dependent interactions. The absence of a stable 3D structure, combined with high solvent accessibility, means that IDR conformational biases are inherently sensitive to changes in their environment. Here, we argue that IDRs are ideally poised to act as sensors and actuators of cellular physicochemistry. We review the physical principles that underlie IDR sensitivity, the molecular mechanisms that translate this sensitivity to function, and recent studies where environmental sensing by IDRs may play a key role in their downstream function.

NMR characterization of the structure of the intrinsically disordered region of human origin recognition complex subunit 1, hORC1, and of its interaction with G-quadruplex DNAs

Human origin recognition complex (hORC) binds to the DNA replication origin and then initiates DNA replication. However, hORC does not exhibit DNA sequence-specificity and how hORC recognizes the replication origin on genomic DNA remains elusive. Previously, we found that hORC recognizes G-quadruplex structures potentially formed near the replication origin. Then, we showed that hORC subunit 1 (hORC1) preferentially binds to G-quadruplex DNAs using a hORC1 construct comprising residues 413 to 511 (hORC1413-511). Here, we investigate the structural characteristics of hORC1413-511 in its free and complex forms with G-quadruplex DNAs. Circular dichroism and nuclear magnetic resonance (NMR) spectroscopic studies indicated that hORC1413-511 is disordered except for a short α-helical region in both the free and complex forms. NMR chemical shift perturbation (CSP) analysis suggested that basic residues, arginines and lysines, and polar residues, serines and threonines, are involved in the G-quadruplex DNA binding. Then, this was confirmed by mutation analysis. Interestingly, CSP analysis indicated that hORC1413-511 binds to both parallel- and (3 + 1)-type G-quadruplex DNAs using the same residues, and thereby in the same manner. Our study suggests that hORC1 uses its intrinsically disordered G-quadruplex binding region to recognize parallel-type and (3 + 1)-type G-quadruplex structures at replication origin.

Comparison, Analysis, and Molecular Dynamics Simulations of Structures of a Viral Protein Modeled Using Various Computational Tools

The structural analysis of proteins is a major domain of biomedical research. Such analysis requires resolved three-dimensional structures of proteins. Advancements in computer technology have led to progress in biomedical research. In silico prediction and modeling approaches have facilitated the construction of protein structures, with or without structural templates. In this study, we used three neural network-based de novo modeling approaches-AlphaFold2 (AF2), Robetta-RoseTTAFold (Robetta), and transform-restrained Rosetta (trRosetta)-and two template-based tools-the Molecular Operating Environment (MOE) and iterative threading assembly refinement (I-TASSER)-to construct the structure of a viral capsid protein, hepatitis C virus core protein (HCVcp), whose structure have not been fully resolved by laboratory techniques. Templates with sufficient sequence identity for the homology modeling of complete HCVcp are currently unavailable. Therefore, we performed domain-based homology modeling for MOE simulations. The templates for each domain were obtained through sequence-based searches on NCBI and the Protein Data Bank. Then, the modeled domains were assembled to construct the complete structure of HCVcp. The full-length structure and two truncated forms modeled using various computational tools were compared. Molecular dynamics (MD) simulations were performed to refine the structures. The root mean square deviation of backbone atoms, root mean square fluctuation of Cα atoms, and radius of gyration were calculated to monitor structural changes and convergence in the simulations. The model quality was evaluated through ERRAT and phi-psi plot analysis. In terms of the initial prediction for protein modeling, Robetta and trRosetta outperformed AF2. Regarding template-based tools, MOE outperformed I-TASSER. MD simulations resulted in compactly folded protein structures, which were of good quality and theoretically accurate. Thus, the predicted structures of certain proteins must be refined to obtain reliable structural models. MD simulation is a promising tool for this purpose.

Analysis of the complex between MBD2 and the histone deacetylase core of NuRD reveals key interactions critical for gene silencing

The nucleosome remodeling and deacetylase (NuRD) complex modifies nucleosome positioning and chromatin compaction to regulate gene expression. The methyl-CpG-binding domain proteins 2 and 3 (MBD2 and MBD3) play a critical role in complex formation; however, the molecular details of how they interact with other NuRD components have yet to be fully elucidated. We previously showed that an intrinsically disordered region (IDR) of MBD2 is necessary and sufficient to bind to the histone deacetylase core of NuRD. Building on that work, we have measured the inherent structural propensity of the MBD2-IDR using solvent and site-specific paramagnetic relaxation enhancement measurements. We then used the AlphaFold2 machine learning software to generate a model of the complex between MBD2 and the histone deacetylase core of NuRD. This model is remarkably consistent with our previous studies, including the current paramagnetic relaxation enhancement data. The latter suggests that the free MBD2-IDR samples conformations similar to the bound structure. We tested this model of the complex extensively by mutating key contact residues and measuring binding using an intracellular bioluminescent resonance energy transfer assay. Furthermore, we identified protein contacts that, when mutated, disrupted gene silencing by NuRD in a cell model of fetal hemoglobin regulation. Hence, this work provides insights into the formation of NuRD and highlights critical binding pockets that may be targeted to block gene silencing for therapy. Importantly, we show that AlphaFold2 can generate a credible model of a large complex that involves an IDR that folds upon binding.

TAFPred: Torsion Angle Fluctuations Prediction from Protein Sequences

Protein molecules show varying degrees of flexibility throughout their three-dimensional structures. The flexibility is determined by the fluctuations in torsion angles, specifically phi (φ) and psi (ψ), which define the protein backbone. These angle fluctuations are derived from variations in backbone torsion angles observed in different models. By analyzing the fluctuations in Cartesian coordinate space, we can understand the structural flexibility of proteins. Predicting torsion angle fluctuations is valuable for determining protein function and structure when these angles act as constraints. In this study, a machine learning method called TAFPred is developed to predict torsion angle fluctuations using protein sequences directly. The method incorporates various features, such as disorder probability, position-specific scoring matrix profiles, secondary structure probabilities, and more. TAFPred, employing an optimized Light Gradient Boosting Machine Regressor (LightGBM), achieved high accuracy with correlation coefficients of 0.746 and 0.737 and mean absolute errors of 0.114 and 0.123 for the φ and ψ angles, respectively. Compared to the state-of-the-art method, TAFPred demonstrated significant improvements of 10.08% in MAE and 24.83% in PCC for the phi angle and 9.93% in MAE, and 22.37% in PCC for the psi angle.

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.

Interaction modules that impart specificity to disordered protein

Intrinsically disordered regions (IDRs) are especially enriched among proteins that regulate chromatin and transcription. As a result, mechanisms that influence specificity of IDR-driven interactions have emerged as exciting unresolved issues for understanding gene regulation. We review the molecular elements frequently found within IDRs that confer regulatory specificity. In particular, we summarize the differing roles of disordered low-complexity regions (LCRs) and short linear motifs (SLiMs) towards selective nuclear regulation. Examination of IDR-driven interactions highlights SLiMs as organizers of selectivity, with widespread roles in gene regulation and integration of cellular signals. Analysis of recurrent interactions between SLiMs and folded domains suggests diverse avenues for SLiMs to influence phase-separated condensates and highlights opportunities to manipulate these interactions for control of biological activity.

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.

Conformational ensemble of amyloid-forming semenogelin 1 peptide SEM1(68-107) by NMR spectroscopy and MD simulations

SEM1(68-107) is a peptide corresponding to the region of semenogelin 1 protein from 68 to 107 amino acid position. SEM1(68-107) is an abundant component of semen, which participates in HIV infection enhanced by amyloid fibrils forming. To understand the causes influencing amyloid fibril formation, it is necessary to determine the spatial structure of SEM1(68-107). It was shown that the determination of SEM1(68-107) structure is complicated by the non-informative NMR spectra due to the high intramolecular mobility of peptides. The complementary approach based on the geometric restrictions of individual peptide fragments and molecular modeling was used for the determination of the spatial structure of SEM1(68-107). The N- (SEM1(68-85)) and C-terminuses (SEM1(86-107)) of SEM1(68-107) were chosen as two individual peptide fragments. SEM1(68-85) and SEM1(86-107) structures were established with NMR and circular dichroism CD spectroscopies. These regions were used as geometric restraints for the SEM1(68-107) structure modeling. Even though most of the SEM1(68-107) peptide is unstructured, our detailed analysis revealed the following structured elements: N-terminus (70His-84Gln) forms an α-helix, (86Asp-94Thr) and (101Gly-103Ser) regions fold into 3₁₀-helixes. The absence of a SEM1(68-107) rigid conformation leads to instability of these secondary structure regions. The calculated SEM1(68-107) structure is in good agreement with experimental values of hydrodynamic radius and dihedral angles obtained by NMR spectroscopy. This testifies the adequacy of a combined approach based on the use of peptide fragment structures for the molecular modeling formation of full-size peptide spatial structure.

Improving IDP theoretical chemical shift accuracy and efficiency through a combined MD/ADMA/DFT and machine learning approach

This work extends the multi-scale computational scheme for the quantum mechanics (QM) calculations of Nuclear Magnetic Resonance (NMR) chemical shifts (CSs) in proteins that lack a well-defined 3D structure. The scheme couples the sampling of an intrinsically disordered protein (IDP) by classical molecular dynamics (MD) with protein fragmentation using the adjustable density matrix assembler (ADMA) and density functional theory (DFT) calculations. In contrast to our early investigation on IDPs (Pavlíková Přecechtělová et al., J. Chem. Theory Comput., 2019, 15, 5642-5658) and the state-of-the art NMR calculations for structured proteins, a partial re-optimization was implemented on the raw MD geometries in vibrational normal mode coordinates to enhance the accuracy of the MD/ADMA/DFT computational scheme. In addition, machine-learning based cluster analysis was performed on the scheme to explore its potential in producing protein structure ensembles (CLUSTER ensembles) that yield accurate CSs at a reduced computational cost. The performance of the cluster-based calculations is validated against results obtained with conventional structural ensembles consisting of MD snapshots extracted from the MD trajectory at regular time intervals (REGULAR ensembles). CS calculations performed with the refined MD/ADMA/DFT framework employed the 6-311++G(d,p) basis set that outperformed IGLO-III calculations with the same density functional approximation (B3LYP) and both explicit and implicit solvation. The partial geometry optimization did not universally improve the agreement of computed CSs with the experiment but substantially decreased errors associated with the ensemble averaging. A CLUSTER ensemble with 50 structures yielded ensemble averages close to those obtained with a REGULAR ensemble consisting of 500 MD frames. The cluster based calculations thus required only a fraction of the computational time.

Prediction of Intrinsic Disorder Using Rosetta ResidueDisorder and AlphaFold2

The combination of deep learning and sequence data has transformed protein structure prediction and modeling, evidenced in the success of AlphaFold (AF). For this reason, many methods have been developed to take advantage of this success in areas where inaccurate structural modeling may limit computational predictiveness. For example, many methods have been developed to predict protein intrinsic disorder from sequence, including our Rosetta ResidueDisorder (RRD) approach. Intrinsically disordered regions in proteins are parts of the sequence that do not form ordered, folded structures under typical physiological conditions. In the original implementation of RRD, Rosetta ab initio models were generated, and disordered regions were predicted based on residue scores (disordered residues typically exist in regions of unfavorable scores). In this work, we show that by (i) replacing the ab initio modeling with AF (using the same scoring and disorder assignment approach) and (ii) updating the score function, the predictiveness improved significantly. Residues were better ranked by the order/disorder, evidenced by an improvement in receiver operating characteristic area-under-the-curve from 0.69 to 0.78 on a large (229 protein) and balanced data set (relatively even ordered versus disordered residues). Finally, the binary prediction accuracy also improved from 62% to 74% on the same data set. Our results show that the combined AF-RRD approach was as good as or better than all existing methods by these metrics (AF-RRD had the highest prediction accuracy).

High-Resolution Conformational Analysis of RGDechi-Derived Peptides Based on a Combination of NMR Spectroscopy and MD Simulations

The crucial role of integrin in pathological processes such as tumor progression and metastasis formation has inspired intense efforts to design novel pharmaceutical agents modulating integrin functions in order to provide new tools for potential therapies. In the past decade, we have investigated the biological proprieties of the chimeric peptide RGDechi, containing a cyclic RGD motif linked to an echistatin C-terminal fragment, able to specifically recognize αvβ3 without cross reacting with αvβ5 and αIIbβ3 integrin. Additionally, we have demonstrated using two RGDechi-derived peptides, called RGDechi1-14 and ψRGDechi, that chemical modifications introduced in the C-terminal part of the peptide alter or abolish the binding to the αvβ3 integrin. Here, to shed light on the structural and dynamical determinants involved in the integrin recognition mechanism, we investigate the effects of the chemical modifications by exploring the conformational space sampled by RGDechi1-14 and ψRGDechi using an integrated natural-abundance NMR/MD approach. Our data demonstrate that the flexibility of the RGD-containing cycle is driven by the echistatin C-terminal region of the RGDechi peptide through a coupling mechanism between the N- and C-terminal regions.

Intrinsically disordered proteins in viral pathogenesis and infections

Disordered proteins serve a crucial part in many biological processes that go beyond the capabilities of ordered proteins. A large number of virus-encoded proteins have extremely condensed proteomes and genomes, which results in highly disordered proteins. The presence of these IDPs allows them to rapidly adapt to changes in their biological environment and play a significant role in viral replication and down-regulation of host defense mechanisms. Since viruses undergo rapid evolution and have a high rate of mutation and accumulation in their proteome, IDPs' insights into viruses are critical for understanding how viruses hijack cells and cause disease. There are many conformational changes that IDPs can adopt in order to interact with different protein partners and thus stabilize the particular fold and withstand high mutation rates. This chapter explains the molecular mechanism behind viral IDPs, as well as the significance of recent research in the field of IDPs, with the goal of gaining a deeper comprehension of the essential roles and functions played by viral proteins.

Insights into the client protein release mechanism of the ATP-independent chaperone Spy

Molecular chaperones play a central role in regulating protein homeostasis, and their active forms often contain intrinsically disordered regions (IDRs). However, how IDRs impact chaperone action remains poorly understood. Here, we discover that the disordered N terminus of the prototype chaperone Spy facilitates client release. With NMR spectroscopy and molecular dynamics simulations, we find that the N terminus can bind transiently to the client-binding cavity of Spy primarily through electrostatic interactions mediated by the N-terminal D26 residue. This intramolecular interaction results in a dynamic competition of the N terminus with the client for binding to Spy, which promotes client discharge. Our results reveal the mechanism by which Spy releases clients independent of energy input, thus enriching the current knowledge on how ATP-independent chaperones release their clients and highlighting the importance of synergy between IDRs and structural domains in regulating protein function.

AlphaFold2: A Role for Disordered Protein/Region Prediction?

The development of AlphaFold2 marked a paradigm-shift in the structural biology community. Herein, we assess the ability of AlphaFold2 to predict disordered regions against traditional sequence-based disorder predictors. We find that AlphaFold2 performs well at discriminating disordered regions, but also note that the disorder predictor one constructs from an AlphaFold2 structure determines accuracy. In particular, a naïve, but non-trivial assumption that residues assigned to helices, strands, and H-bond stabilized turns are likely ordered and all other residues are disordered results in a dramatic overestimation in disorder; conversely, the predicted local distance difference test (pLDDT) provides an excellent measure of residue-wise disorder. Furthermore, by employing molecular dynamics (MD) simulations, we note an interesting relationship between the pLDDT and secondary structure, that may explain our observations and suggests a broader application of the pLDDT for characterizing the local dynamics of intrinsically disordered proteins and regions (IDPs/IDRs).

NMR Provides Unique Insight into the Functional Dynamics and Interactions of Intrinsically Disordered Proteins

Intrinsically disordered proteins are ubiquitous throughout all known proteomes, playing essential roles in all aspects of cellular and extracellular biochemistry. To understand their function, it is necessary to determine their structural and dynamic behavior and to describe the physical chemistry of their interaction trajectories. Nuclear magnetic resonance is perfectly adapted to this task, providing ensemble averaged structural and dynamic parameters that report on each assigned resonance in the molecule, unveiling otherwise inaccessible insight into the reaction kinetics and thermodynamics that are essential for function. In this review, we describe recent applications of NMR-based approaches to understanding the conformational energy landscape, the nature and time scales of local and long-range dynamics and how they depend on the environment, even in the cell. Finally, we illustrate the ability of NMR to uncover the mechanistic basis of functional disordered molecular assemblies that are important for human health.

Targeting key proteins involved in transcriptional regulation for cancer therapy: Current strategies and future prospective

The key proteins involved in transcriptional regulation play convergent roles in cellular homeostasis, and their dysfunction mediates aberrant gene expressions that underline the hallmarks of tumorigenesis. As tumor progression is dependent on such abnormal regulation of transcription, it is important to discover novel chemical entities as antitumor drugs that target key tumor-associated proteins involved in transcriptional regulation. Despite most key proteins (especially transcription factors) involved in transcriptional regulation are historically recognized as undruggable targets, multiple targeting approaches at diverse levels of transcriptional regulation, such as epigenetic intervention, inhibition of DNA-binding of transcriptional factors, and inhibition of the protein-protein interactions (PPIs), have been established in preclinically or clinically studies. In addition, several new approaches have recently been described, such as targeting proteasomal degradation and eliciting synthetic lethality. This review will emphasize on accentuating these developing therapeutic approaches and provide a thorough conspectus of the drug development to target key proteins involved in transcriptional regulation and their impact on future oncotherapy.

The pathogenic R5L mutation disrupts formation of Tau complexes on the microtubule by altering local N-terminal structure

The microtubule-associated protein (MAP) Tau is an intrinsically disordered protein (IDP) primarily expressed in axons, where it functions to regulate microtubule dynamics, modulate motor protein motility, and participate in signaling cascades. Tau misregulation and point mutations are linked to neurodegenerative diseases, including progressive supranuclear palsy (PSP), Pick's disease, and Alzheimer's disease. Many disease-associated mutations in Tau occur in the C-terminal microtubule-binding domain of the protein. Effects of C-terminal mutations in Tau have led to the widely accepted disease-state theory that missense mutations in Tau reduce microtubule-binding affinity or increase Tau propensity to aggregate. Here, we investigate the effect of an N-terminal arginine to leucine mutation at position 5 in Tau (R5L), associated with PSP, on Tau-microtubule interactions using an in vitro reconstituted system. Contrary to the canonical disease-state theory, we determine that the R5L mutation does not reduce Tau affinity for the microtubule using total internal reflection fluorescence microscopy. Rather, the R5L mutation decreases the ability of Tau to form larger-order complexes, or Tau patches, at high concentrations of Tau. Using NMR, we show that the R5L mutation results in a local structural change that reduces interactions of the projection domain in the presence of microtubules. Altogether, these results challenge both the current paradigm of how mutations in Tau lead to disease and the role of the projection domain in modulating Tau behavior on the microtubule surface.

Intricate coupling between the transactivation and basic-leucine zipper domains governs phosphorylation of transcription factor ATF4 by casein kinase 2

Most transcription factors possess at least one long intrinsically disordered transactivation domain that binds to a variety of coactivators and corepressors and plays a key role in modulating the transcriptional activity. Despite the crucial importance of these domains, the structural and functional basis of transactivation remains poorly understood. Here, we focused on activating transcription factor 4 (ATF4)/cAMP response element-binding protein-2, an essential transcription factor for cellular stress adaptation. Bioinformatic sequence analysis of the ATF4 transactivation domain sequence revealed that the first 125 amino acids have noticeably less propensity for structural disorder than the rest of the domain. Using solution nuclear magnetic resonance spectroscopy complemented by a range of biophysical methods, we found that the isolated transactivation domain is predominantly yet not fully disordered in solution. We also observed that a short motif at the N-terminus of the transactivation domain has a high helical propensity. Importantly, we found that the N-terminal region of the transactivation domain is involved in transient long-range interactions with the basic-leucine zipper domain involved in DNA binding. Finally, in vitro phosphorylation assays with the casein kinase 2 show that the presence of the basic-leucine zipper domain is required for phosphorylation of the transactivation domain. This study uncovers the intricate coupling existing between the transactivation and basic-leucine zipper domains of ATF4, highlighting its potential regulatory significance.

Aggregation-Prone Structural Ensembles of Transthyretin Collected With Regression Analysis for NMR Chemical Shift

Monomer dissociation and subsequent misfolding of the transthyretin (TTR) is one of the most critical causative factors of TTR amyloidosis. TTR amyloidosis causes several human diseases, such as senile systemic amyloidosis and familial amyloid cardiomyopathy/polyneuropathy; therefore, it is important to understand the molecular details of the structural deformation and aggregation mechanisms of TTR. However, such molecular characteristics are still elusive because of the complicated structural heterogeneity of TTR and its highly sensitive nature to various environmental factors. Several nuclear magnetic resonance (NMR) spectroscopy and molecular dynamics (MD) studies of TTR variants have recently reported evidence of transient aggregation-prone structural states of TTR. According to these studies, the stability of the DAGH β-sheet, one of the two main β-sheets in TTR, is a crucial determinant of the TTR amyloidosis mechanism. In addition, its conformational perturbation and possible involvement of nearby structural motifs facilitates TTR aggregation. This study proposes aggregation-prone structural ensembles of TTR obtained by MD simulation with enhanced sampling and a multiple linear regression approach. This method provides plausible structural models that are composed of ensemble structures consistent with NMR chemical shift data. This study validated the ensemble models with experimental data obtained from circular dichroism (CD) spectroscopy and NMR order parameter analysis. In addition, our results suggest that the structural deformation of the DAGH β-sheet and the AB loop regions may correlate with the manifestation of the aggregation-prone conformational states of TTR. In summary, our method employing MD techniques to extend the structural ensembles from NMR experimental data analysis may provide new opportunities to investigate various transient yet important structural states of amyloidogenic proteins.

Backbone and nearly complete side-chain chemical shift assignments reveal the human uncharacterized protein CXorf51A as intrinsically disordered

Even though the human genome project showed that our DNA contains a mere 20,000 to 25,000 protein coding genes, an unexpectedly large number of these proteins remain functionally uncharacterized. A structural characterization of these "unknown" proteins may help to identify possible cellular tasks. We therefore used a combination of bioinformatics and nuclear magnetic resonance spectroscopy to structurally de-orphanize one of these gene products, the 108 amino acid human uncharacterized protein CXorf51A. Both our bioinformatics analysis as well as the [Formula: see text]H, [Formula: see text]C, [Formula: see text]N backbone and near-complete side-chain chemical shift assignments indicate that it is an intrinsically disordered protein.

NMR identification of a conserved Drp1 cardiolipin-binding motif essential for stress-induced mitochondrial fission

Mitochondria form tubular networks that undergo coordinated cycles of fission and fusion. Emerging evidence suggests that a direct yet unresolved interaction of the mechanoenzymatic GTPase dynamin-related protein 1 (Drp1) with mitochondrial outer membrane-localized cardiolipin (CL), externalized under stress conditions including mitophagy, catalyzes essential mitochondrial hyperfragmentation. Here, using a comprehensive set of structural, biophysical, and cell biological tools, we have uncovered a CL-binding motif (CBM) conserved between the Drp1 variable domain (VD) and the unrelated ADP/ATP carrier (AAC/ANT) that intercalates into the membrane core to effect specific CL interactions. CBM mutations that weaken VD-CL interactions manifestly impair Drp1-dependent fission under stress conditions and induce "donut" mitochondria formation. Importantly, VD membrane insertion and GTP-dependent conformational rearrangements mediate only transient CL nonbilayer topological forays and high local membrane constriction, indicating that Drp1-CL interactions alone are insufficient for fission. Our studies establish the structural and mechanistic bases of Drp1-CL interactions in stress-induced mitochondrial fission.

Investigating the Atomic and Mesoscale Interactions that Facilitate Spider Silk Protein Pre-Assembly

Black widow spider dragline silk is one of nature's high-performance biological polymers, exceeding the strength and toughness of most man-made materials including high tensile steel and Kevlar. Major ampullate (Ma), or dragline silk, is primarily comprised of two spidroin proteins (Sp) stored within the Ma gland. In the native gland environment, the MaSp1 and MaSp2 proteins self-associate to form hierarchical 200-300 nm superstructures despite being intrinsically disordered proteins (IDPs). Here, dynamic light scattering (DLS), three-dimensional (3D) triple resonance solution NMR, and diffusion NMR is utilized to probe the MaSp size, molecular structure, and dynamics of these protein pre-assemblies diluted in 4 M urea and identify specific regions of the proteins important for silk protein pre-assembly. 3D NMR indicates that the Gly-Ala-Ala and Ala-Ala-Gly motifs flanking the poly(Ala) runs, which comprise the β-sheet forming domains in fibers, are perturbed by urea, suggesting that these regions may be important for silk protein pre-assembly stabilization.

The Pathogenesis Mechanism, Structure Properties, Potential Drugs and Therapeutic Nanoparticles against the Small Oligomers of Amyloid-β

Alzheimer's Disease (AD) is a devastating neurodegenerative disease that affects millions of people in the world. The abnormal aggregation of amyloid β protein (Aβ) is regarded as the key event in AD onset. Meanwhile, the Aβ oligomers are believed to be the most toxic species of Aβ. Recent studies show that the Aβ dimers, which are the smallest form of Aβ oligomers, also have the neurotoxicity in the absence of other oligomers in physiological conditions. In this review, we focus on the pathogenesis, structure and potential therapeutic molecules against small Aβ oligomers, as well as the nanoparticles (NPs) in the treatment of AD. In this review, we firstly focus on the pathogenic mechanism of Aβ oligomers, especially the Aβ dimers. The toxicity of Aβ dimer or oligomers, which attributes to the interactions with various receptors and the disruption of membrane or intracellular environments, were introduced. Then the structure properties of Aβ dimers and oligomers are summarized. Although some structural information such as the secondary structure content is characterized by experimental technologies, detailed structures are still absent. Following that, the small molecules targeting Aβ dimers or oligomers are collected; nevertheless, all of these ligands have failed to come into the market due to the rising controversy of the Aβ-related "amyloid cascade hypothesis". At last, the recent progress about the nanoparticles as the potential drugs or the drug delivery for the Aβ oligomers are present.

Protein Phase Separation Arising from Intrinsic Disorder: First-Principles to Bespoke Applications

The phase separation of biomolecules has become the focus of intense research in the past decade, with a growing body of research implicating this phenomenon in essentially all biological functions, including but not limited to homeostasis, stress responses, gene regulation, cell differentiation, and disease. Excellent reviews have been published previously on the underlying physical basis of liquid-liquid phase separation (LLPS) of biological molecules (Nat. Phys. 2015, 11, 899-904) and LLPS as it occurs natively in physiology and disease (Science 2017, 357, eaaf4382; Biochemistry 2018, 57, 2479-2487; Chem. Rev. 2014, 114, 6844-6879). Here, we review how the theoretical physical basis of LLPS has been used to better understand the behavior of biomolecules that undergo LLPS in natural systems and how this understanding has also led to the development of novel synthetic systems that exhibit biomolecular phase separation, and technologies that exploit these phenomena. In part 1 of this Review, we explore the theory behind the phase separation of biomolecules and synthetic macromolecules and introduce a few notable phase-separating biomolecules. In part 2, we cover experimental and computational methods used to study phase-separating proteins and how these techniques have uncovered the mechanisms underlying phase separation in physiology and disease. Finally, in part 3, we cover the development and applications of engineered phase-separating polypeptides, ranging from control of their self-assembly to create defined supramolecular architectures to reprogramming biological processes using engineered IDPs that exhibit LLPS.

Ratiometric Single-Molecule FRET Measurements to Probe Conformational Subpopulations of Intrinsically Disordered Proteins

Over the past few decades, numerous examples have demonstrated that intrinsic disorder in proteins lies at the heart of many vital processes, including transcriptional regulation, stress response, cellular signaling, and most recently protein liquid-liquid phase separation. The so-called intrinsically disordered proteins (IDPs) involved in these processes have presented a challenge to the classic protein "structure-function paradigm," as their functions do not necessarily involve well-defined structures. Understanding the mechanisms of IDP function is likewise challenging because traditional structure determination methods often fail with such proteins or provide little information about the diverse array of structures that can be related to different functions of a single IDP. Single-molecule fluorescence methods can overcome this ensemble-average masking, allowing the resolution of subpopulations and dynamics and thus providing invaluable insights into IDPs and their function. In this protocol, we describe a ratiometric single-molecule Förster resonance energy transfer (smFRET) routine that permits the investigation of IDP conformational subpopulations and dynamics. We note that this is a basic protocol, and we provide brief information and references for more complex analysis schemes available for in-depth characterization. This protocol covers optical setup preparation and protein handling and provides insights into experimental design and outcomes, together with background information about theory and a brief discussion of troubleshooting. © 2020 by John Wiley & Sons, Inc. Basic Protocol: Ratiometric smFRET detection and analysis of IDPs Support Protocol 1: Fluorophore labeling of a protein through maleimide chemistry Support Protocol 2: Sample chamber preparation Support Protocol 3: Determination of direct excitation of acceptor by donor excitation and leakage of donor emission to acceptor emission channel.

Structures of the germline-specific Deadhead and thioredoxin T proteins from Drosophila melanogaster reveal unique features among thioredoxins

Thioredoxins (Trxs) are ubiquitous enzymes that regulate the redox state in cells. In Drosophila, there are two germline-specific Trxs, Deadhead (Dhd) and thioredoxin T (TrxT), that belong to the lethal(3)malignant brain tumor signature genes and to the 'survival network' of genes that mediate the cellular response to DNA damage. Dhd is a maternal protein required for early embryogenesis that promotes protamine-histone exchange in fertilized eggs and midblastula transition. TrxT is testis-specific and associates with the lampbrush loops of the Y chromosome. Here, the first structures of Dhd and TrxT are presented, unveiling new features of these two thioredoxins. Dhd has positively charged patches on its surface, in contrast to the negatively charged surfaces commonly found in most Trxs. This distinctive charge distribution helps to define initial encounter complexes with DNA/RNA that will lead to final specific interactions with cofactors to promote chromatin remodeling. TrxT contains a C-terminal extension, which is mostly unstructured and highly flexible, that wraps the conserved core through a closed conformation. It is believed that these new structures can guide future work aimed at understanding embryo development and redox homeostasis in Drosophila. Moreover, due to their restricted presence in Schizophora (a section of the true flies), these structures can help in the design of small-molecular binders to modulate native redox homeostasis, thereby providing new applications for the control of plagues that cause human diseases and/or bring about economic losses by damaging crop production.

Structural Insights into the Interaction of the Intrinsically Disordered Co-activator TIF2 with Retinoic Acid Receptor Heterodimer (RXR/RAR)

Retinoic acid receptors (RARs) and retinoid X receptors (RXRs) form heterodimers that activate target gene transcription by recruiting co-activator complexes in response to ligand binding. The nuclear receptor (NR) co-activator TIF2 mediates this recruitment by interacting with the ligand-binding domain (LBD) of NRs trough the nuclear receptor interaction domain (TIF2_NRID) containing three highly conserved α-helical LxxLL motifs (NR-boxes). The precise binding mode of this domain to RXR/RAR is not clear due to the disordered nature of TIF2. Here we present the structural characterization of TIF2_NRID by integrating several experimental (NMR, SAXS, Far-UV CD, SEC-MALS) and computational data. Collectively, the data are in agreement with a largely disordered protein with partially structured regions, including the NR-boxes and their flanking regions, which are evolutionary conserved. NMR and X-ray crystallographic data on TIF2_NRID in complex with RXR/RAR reveal a multisite binding of the three NR-boxes as well as an active role of their flanking regions in the interaction.

Crosslinking mass spectrometry: A link between structural biology and systems biology

Protein structure underpins functional roles in all biological processes; therefore, improved understanding of protein structures is of fundamental importance in nearly all biological and biomedical research areas. Traditional techniques such as X-ray crystallography and more recently, cryo-EM, can reveal structural features on isolated proteins/protein complexes at atomic resolution level and have become indispensable tools for structural biology. Crosslinking mass spectrometry (XL-MS), on the other hand, is an emerging technique capable of capturing transient and dynamic information on protein interactions and assemblies in their native environment. The combination of XL-MS with traditional techniques holds potential for bridging the gap between structural biology and systems biology approaches. Such a combination will enable visualization of protein structures and interactions within the crowded macromolecular environment in living systems that can dramatically increase understanding of biological functions. In this review, we first discuss general strategies of XL-MS and then survey recent examples to show how qualitative and quantitative XL-MS studies can be integrated with available protein structural data to better understand biological function at systems level.

Nanoscopic anatomy of dynamic multi-protein complexes at membranes resolved by graphene-induced energy transfer

Insights into the conformational organization and dynamics of proteins complexes at membranes is essential for our mechanistic understanding of numerous key biological processes. Here, we introduce graphene-induced energy transfer (GIET) to probe axial orientation of arrested macromolecules at lipid monolayers. Based on a calibrated distance-dependent efficiency within a dynamic range of 25 nm, we analyzed the conformational organization of proteins and complexes involved in tethering and fusion at the lysosome-like yeast vacuole. We observed that the membrane-anchored Rab7-like GTPase Ypt7 shows conformational reorganization upon interactions with effector proteins. Ensemble and time-resolved single-molecule GIET experiments revealed that the HOPS tethering complex, when recruited via Ypt7 to membranes, is dynamically alternating between a ‘closed’ and an ‘open’ conformation, with the latter possibly interacting with incoming vesicles. Our work highlights GIET as a unique spectroscopic ruler to reveal the axial orientation and dynamics of macromolecular complexes at biological membranes with sub-nanometer resolution.

Proteins are part of the building blocks of life and are essential for structure, function and regulation of every cell, tissue and organ of the body. Proteins adopt different conformations to work efficiently within the various environments of a cell. They can also switch between shapes.

One way to monitor how proteins change their shapes involves energy transfer. This approach can measure how close two proteins, or two parts of the same protein, are, by using dye labels that respond to each other when they are close together.

For example, in a method called FRET, one dye label absorbs light and transfers the energy to the other label, which emits it as a different color of light. However, FRET only works over short distances (less than 10nm apart or 1/100,000th of a millimeter), so it is not useful for larger proteins.

Here, Füllbrunn, Li et al. developed a method called GIET that uses graphene to analyze the dynamic structures of proteins on membrane surfaces. Graphene is a type of carbon nanomaterial that can absorb energy from dye labels and could provide a way to study protein interactions over longer distances.

Graphene was deposited on a glass surface where it was coated with single layer of membrane, which could then be used to capture specific proteins. The results showed that GIET worked over longer distances (up to 30 nm) than FRET and could be used to study proteins attached to the membrane around graphene. Füllbrunn, Li et al. used it to examine a specific complex of proteins called HOPS, which is linked to multiple diseases, including Ebola, measuring distances between the head or tail of HOPS and the membrane to understand protein shapes. This revealed that HOPS adopts an upright position on membranes and alternates between open and closed shapes.

The study of Füllbrunn, Li et al. highlights the ability of GIET to address unanswered questions about the function of protein complexes on membrane surfaces and sheds new light on the structural dynamics of HOPS in living cells. As it allows protein interactions to be studied over much greater distances, GIET could be a powerful new tool for cell biology research. Moreover, graphene is also useful in electron microscopy and both approaches combined could achieve a detailed structural picture of proteins in action.

PED in 2021: a major update of the protein ensemble database for intrinsically disordered proteins

The Protein Ensemble Database (PED) (https://proteinensemble.org), which holds structural ensembles of intrinsically disordered proteins (IDPs), has been significantly updated and upgraded since its last release in 2016. The new version, PED 4.0, has been completely redesigned and reimplemented with cutting-edge technology and now holds about six times more data (162 versus 24 entries and 242 versus 60 structural ensembles) and a broader representation of state of the art ensemble generation methods than the previous version. The database has a completely renewed graphical interface with an interactive feature viewer for region-based annotations, and provides a series of descriptors of the qualitative and quantitative properties of the ensembles. High quality of the data is guaranteed by a new submission process, which combines both automatic and manual evaluation steps. A team of biocurators integrate structured metadata describing the ensemble generation methodology, experimental constraints and conditions. A new search engine allows the user to build advanced queries and search all entry fields including cross-references to IDP-related resources such as DisProt, MobiDB, BMRB and SASBDB. We expect that the renewed PED will be useful for researchers interested in the atomic-level understanding of IDP function, and promote the rational, structure-based design of IDP-targeting drugs.

FOXO4 Transactivation Domain Interaction with Forkhead DNA Binding Domain and Effect on Selective DNA Recognition for Transcription Initiation

Forkhead box O4 (FOXO4) is a human transcription factor (TF) that participates in cell homeostasis. While the structure and DNA binding properties of the conserved forkhead domain (FHD) have been thoroughly investigated, how the transactivation domain (TAD) regulates the DNA binding properties of the protein remains elusive. Here, we investigated the role of TAD in modulating the DNA binding properties of FOXO4 using solution NMR. We found that TAD and FHD form an intramolecular complex mainly governed by hydrophobic interaction. Remarkably, TAD and DNA share the same surface of FHD for binding. While FHD did not differentiate binding to target and non-target DNA, the FHD-TAD complex showed different behaviors depending on the DNA sequence. In the presence of TAD, free and DNA-bound FHD exhibited a slow exchange with target DNA and a fast exchange with non-target DNA. The interaction of the two domains affected the kinetic function of FHD depending on the type of DNA. Based on these findings, we suggest a transcription initiation model by which TAD modulates FOXO4 recognition of its target promoter DNA sequences. This study describes the function of TAD in FOXO4 and provides a new kinetic perspective on target sequence selection by TFs.

Molecular simulations of IDPs: From ensemble generation to IDP interactions leading to disorder-to-order transitions

Intrinsically disordered proteins (IDPs) lack a well-defined three-dimensional structure but do exhibit some dynamical and structural ordering. The structural plasticity of IDPs indicates that entropy-driven motions are crucial for their function. Many IDPs undergo function-related disorder-to-order transitions upon by their interaction with specific binding partners. Approaches that are based on both experimental and theoretical tools enable the biophysical characterization of IDPs. Molecular simulations provide insights into IDP structural ensembles and disorder-to-order transition mechanisms. However, such studies depend strongly on the chosen force field parameters and simulation techniques. In this chapter, we provide an overview of IDP characteristics, review all-atom force fields recently developed for IDPs, and present molecular dynamics-based simulation methods that allow IDP ensemble generation as well as the characterization of disorder-to-order transitions. In particular, we introduce metadynamics, replica exchange molecular dynamics simulations, and also kinetic models resulting from Markov State modeling, and provide various examples for the successful application of these simulation methods to IDPs.

A combined NMR and EPR investigation on the effect of the disordered RGG regions in the structure and the activity of the RRM domain of FUS

Structural disorder represents a key feature in the mechanism of action of RNA-binding proteins (RBPs). Recent insights revealed that intrinsically disordered regions (IDRs) linking globular domains modulate their capability to interact with various sequences of RNA, but also regulate aggregation processes, stress-granules formation, and binding to other proteins. The FET protein family, which includes FUS (Fused in Sarcoma), EWG (Ewing Sarcoma) and TAF15 (TATA binding association factor 15) proteins, is a group of RBPs containing three different long IDRs characterized by the presence of RGG motifs. In this study, we present the characterization of a fragment of FUS comprising two RGG regions flanking the RNA Recognition Motif (RRM) alone and in the presence of a stem-loop RNA. From a combination of EPR and NMR spectroscopies, we established that the two RGG regions transiently interact with the RRM itself. These interactions may play a role in the recognition of stem-loop RNA, without a disorder-to-order transition but retaining high dynamics.

The human CRY1 tail controls circadian timing by regulating its association with CLOCK:BMAL1

Circadian rhythms are generated by interlocked transcription-translation feedback loops that establish cell-autonomous biological timing of ∼24 h. Mutations in core clock genes that alter their stability or affinity for one another lead to changes in circadian period. The human CRY1Δ11 mutant lengthens circadian period to cause delayed sleep phase disorder (DSPD), characterized by a very late onset of sleep. CRY1 is a repressor that binds to the transcription factor CLOCK:BMAL1 to inhibit its activity and close the core feedback loop. We previously showed how the PHR (photolyase homology region) domain of CRY1 interacts with distinct sites on CLOCK and BMAL1 to sequester the transactivation domain from coactivators. However, the Δ11 variant alters an intrinsically disordered tail in CRY1 downstream of the PHR. We show here that the CRY1 tail, and in particular the region encoded by exon 11, modulates the affinity of the PHR domain for CLOCK:BMAL1. The PHR-binding epitope in exon 11 is necessary and sufficient to disrupt the interaction between CRY1 and the subunit CLOCK. Moreover, PHR-tail interactions are conserved in the paralog CRY2 and reduced when either CRY is bound to the circadian corepressor PERIOD2. Discovery of this autoregulatory role for the mammalian CRY1 tail and conservation of PHR-tail interactions in both mammalian cryptochromes highlights functional conservation with plant and insect cryptochromes, which also utilize PHR-tail interactions to reversibly control their activity.

Capturing the Conformational Ensemble of the Mixed Folded Polyglutamine Protein Ataxin-3

Ataxin-3 is a deubiquitinase involved in protein quality control and other essential cellular functions. It preferentially interacts with polyubiquitin chains of four or more units attached to proteins delivered to the ubiquitin-proteasome system. Ataxin-3 is composed of an N-terminal Josephin domain and a flexible C terminus that contains two or three ubiquitin-interacting motifs (UIMs) and a polyglutamine tract, which, when expanded beyond a threshold, leads to protein aggregation and misfolding and causes spinocerebellar ataxia type 3. The high-resolution structure of the Josephin domain is available, but the structural and dynamical heterogeneity of ataxin-3 has so far hindered the structural description of the full-length protein. Here, we characterize non-expanded and expanded variants of ataxin-3 in terms of conformational ensembles adopted by the proteins in solution by jointly using experimental data from nuclear magnetic resonance and small-angle X-ray scattering with coarse-grained simulations. Our results pave the way to a molecular understanding of polyubiquitin recognition.

Power of Pure Shift HαCα Correlations: A Way to Characterize Biomolecules under Physiological Conditions

Intrinsically disordered proteins (IDPs) constitute an important class of biomolecules with high flexibility. Atomic-resolution studies for these molecules are essentially limited to NMR spectroscopy, which should be performed under physiological pH and temperature to populate relevant conformational ensembles. In this context, however, fundamental problems arise with established triple resonance NMR experiments: high solvent accessibility of IDPs promotes water exchange, which disfavors classical amide ¹H-detection, while ¹³C-detection suffers from significantly reduced sensitivity. A favorable alternative, the conventional detection of nonexchangeable ¹Hα, so far resulted in broad signals with insufficient resolution and sensitivity. To overcome this, we introduce here a selective Hα,Cα-correlating pure shift detection scheme, the selective Hα,Cα-HSQC (SHACA-HSQC), using extensive hetero- and homonuclear decoupling applicable to aqueous samples (≥90% H₂O) and tested on small molecules and proteins. SHACA-HSQC spectra acquired on IDPs provide uncompromised resolution and sensitivity (up to fivefold increased S/N compared to the standard ¹H,¹³C-HSQC), as shown for resonance distinction and unambiguous assignment on the disordered transactivation domain of the tumor suppressor p53, α-synuclein, and folded ubiquitin. The detection scheme can be implemented in any ¹Hα-detected triple resonance experiment and may also form the basis for the detection of isotope-labeled markers in biological studies or compound libraries.

ODiNPred: comprehensive prediction of protein order and disorder

Structural disorder is widespread in eukaryotic proteins and is vital for their function in diverse biological processes. It is therefore highly desirable to be able to predict the degree of order and disorder from amino acid sequence. It is, however, notoriously difficult to predict the degree of local flexibility within structured domains and the presence and nuances of localized rigidity within intrinsically disordered regions. To identify such instances, we used the CheZOD database, which encompasses accurate, balanced, and continuous-valued quantification of protein (dis)order at amino acid resolution based on NMR chemical shifts. To computationally forecast the spectrum of protein disorder in the most comprehensive manner possible, we constructed the sequence-based protein order/disorder predictor ODiNPred, trained on an expanded version of CheZOD. ODiNPred applies a deep neural network comprising 157 unique sequence features to 1325 protein sequences together with the experimental NMR chemical shift data. Cross-validation for 117 protein sequences shows that ODiNPred better predicts the continuous variation in order along the protein sequence, suggesting that contemporary predictors are limited by the quality of training data. The inclusion of evolutionary features reduces the performance gap between ODiNPred and its peers, but analysis shows that it retains greater accuracy for the more challenging prediction of intermediate disorder.

The Cold-Unfolded State Is Expanded but Contains Long- and Medium-Range Contacts and Is Poorly Described by Homopolymer Models

Cold unfolding of proteins is predicted by the Gibbs-Helmholtz equation and is thought to be driven by a strongly temperature-dependent interaction of protein nonpolar groups with water. Studies of the cold-unfolded state provide insight into protein energetics, partially structured states, and folding cooperativity and are of practical interest in biotechnology. However, structural characterization of the cold-unfolded state is much less extensive than studies of thermally or chemically denatured unfolded states, in large part because the midpoint of the cold unfolding transition is usually below freezing. We exploit a rationally designed point mutation (I98A) in the hydrophobic core of the C-terminal domain of the ribosomal protein L9 that allows the cold denatured state ensemble to be observed above 0 °C at near neutral pH and ambient pressure in the absence of added denaturants. A combined approach consisting of paramagnetic relaxation enhancement measurements, analysis of small-angle X-ray scattering data, all-atom simulations, and polymer theory provides a detailed description of the cold-unfolded state. Despite a globally expanded ensemble, as determined by small-angle X-ray scattering, sequence-specific medium- and long-range interactions in the cold-unfolded state give rise to deviations from homopolymer-like behavior. Our results reveal that the cold-denatured state is heterogeneous with local and long-range intramolecular interactions that may prime the folded state and also demonstrate that significant long-range interactions are compatible with expanded unfolded ensembles. The work also highlights the limitations of homopolymer-based descriptions of unfolded states of proteins.