NMR contributions to structural dynamics studies of intrinsically disordered proteins

Conformational Analyses of the AHD1-UBAN Region of TNIP1 Highlight Key Amino Acids for Interaction with Ubiquitin

Tumor necrosis factor ɑ (TNFɑ)-induced protein 3 (TNFAIP3)-interacting protein 1 (TNIP1) is genetically and functionally linked to limiting auto-immune and inflammatory responses. We have shown that TNIP1 (alias A20-binding inhibitor of NF-κB 1, ABIN1), functioning as a hub location to coordinate other proteins in repressing inflammatory signaling, aligns with biophysical traits indicative of its being an intrinsically disordered protein (IDP). IDPs move through a repertoire of three-dimensional structures rather than being in one set conformation. Here we employed bioinformatic analysis and biophysical interventions via amino acid mutations to assess and alter, respectively, conformational flexibility along a crucial region of TNIP1, encompassing the ABIN homology domain 1 and ubiquitin-binding domain in ABIN proteins and NEMO (AHD1-UBAN), by purposeful replacement of key residues. In vitro secondary structure measurements were mostly in line with, but not necessarily to the same degree as, expected results from in silico assessments. Notably, changes in single amino acids outside of the ubiquitin-binding region for gain-of-order effects had consequences along the length of the AHD1-UBAN propagating to that region. This is evidenced by differences in recognition of the partner protein polyubiquitin ≥ 28 residues away, depending on the mutation site, from the previously identified key binding site. These findings serve to demonstrate the role of conformational flexibility in protein partner recognition by TNIP1, thus identifying key amino acids likely to impact the molecular dynamics involved in TNIP1 repression of inflammatory signaling at large.

IDP-EDL: enhancing intrinsically disordered protein prediction by combining protein language model and ensemble deep learning

Identification of intrinsically disordered regions (IDRs) in proteins is essential for understanding fundamental cellular processes. The IDRs can be divided into long disordered regions (LDRs) and short disordered regions (SDRs) according to their lengths. In previous studies, most computational methods ignored the differences between LDRs and SDRs, and therefore failed to capture the different patterns of LDRs and SDRs. In this study, we propose IDP-EDL, an ensemble of three predictors. The component predictors were first built based on pretrained protein language model and applied task-specific fine-tuning for short, long, and generic disordered regions. A meta predictor was then trained to integrate three task-specific predictors into the final predictor. The results of experiments show that task-specific supervised fine-tuning can capture the different features of LDRs and SDRs and IDP-EDL can achieve stable performance on datasets with different ratios of LDRs and SDRs. More importantly, IDP-EDL can reach or even surpass state-of-the-art performance than other existing predictors on independent test sets. IDP-EDL is available at https://github.com/joestarXjx/IDP-EDL.

Implementation of Time-Averaged Restraints with UNRES Coarse-Grained Model of Polypeptide Chains

Time-averaged restraints from nuclear magnetic resonance (NMR) measurements have been implemented in the UNRES coarse-grained model of polypeptide chains in order to develop a tool for data-assisted modeling of the conformational ensembles of multistate proteins, intrinsically disordered proteins (IDPs) and proteins with intrinsically disordered regions (IDRs), many of which are essential in cell biology. A numerically stable variant of molecular dynamics with time-averaged restraints has been introduced, in which the total energy is conserved in sections of a trajectory in microcanonical runs, the bath temperature is maintained in canonical runs, and the time-average-restraint-force components are scaled up with the length of the memory window so that the restraints affect the simulated structures. The new approach restores the conformational ensembles used to generate ensemble-averaged distances, as demonstrated with synthetic restraints. The approach results in a better fitting of the ensemble-averaged interproton distances to those determined experimentally for multistate proteins and proteins with intrinsically disordered regions, which puts it at an advantage over all-atom approaches with regard to the determination of the conformational ensembles of proteins with diffuse structures, owing to a faster and more robust conformational search.

Molecular crowding and amyloidogenic self-assembly: Emergent perspectives from modern computations

In recent decades, the conventional protein folding paradigm has been challenged by intriguing properties of disordered peptide sequences that do not adopt stably folded conformations. Such intrinsically disordered proteins and protein regions (IDPs and IDRs) are poised uniquely in biology due to their propensity for self-aggregation, amyloidogenesis, and correlations with a cluster of debilitating diseases. Complexities underlying their structural and functional manifestations are enhanced in the presence of molecular crowding via non-specific protein-protein and protein-solvent contacts. Enabled by technological advances, physics-based algorithms, and data science, modern computer simulations provide unprecedented insights into the structure, function, dynamics, and thermodynamics of complex macromolecular systems. These characteristics are frequently correlated and manifest into unique observables. This chapter presents an overview of how such methodologies can lend insights and drive investigations into the molecular trifecta of crowding, protein self-aggregation, and amyloidogenesis. It begins with a general overview of disordered proteins in relation to biological function and of a suite of relevant experimental methods. Specific examples are showcased in the biological context. This is followed by a description of the computational approaches that supplant experimental efforts, with an elaboration on enhanced molecular simulation methods. The chapter concludes by alluding to expanded possibilities in disease amelioration.

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.

Genetic Encoding of Phosphorylated Amino Acids into Proteins

Reversible phosphorylation is a fundamental mechanism for controlling protein function. Despite the critical roles phosphorylated proteins play in physiology and disease, our ability to study individual phospho-proteoforms has been hindered by a lack of versatile methods to efficiently generate homogeneous proteins with site-specific phosphoamino acids or with functional mimics that are resistant to phosphatases. Genetic code expansion (GCE) is emerging as a transformative approach to tackle this challenge, allowing direct incorporation of phosphoamino acids into proteins during translation in response to amber stop codons. This genetic programming of phospho-protein synthesis eliminates the reliance on kinase-based or chemical semisynthesis approaches, making it broadly applicable to diverse phospho-proteoforms. In this comprehensive review, we provide a brief introduction to GCE and trace the development of existing GCE technologies for installing phosphoserine, phosphothreonine, phosphotyrosine, and their mimics, discussing both their advantages as well as their limitations. While some of the technologies are still early in their development, others are already robust enough to greatly expand the range of biologically relevant questions that can be addressed. We highlight new discoveries enabled by these GCE approaches, provide practical considerations for the application of technologies by non-GCE experts, and also identify avenues ripe for further development.

SOS1 tonoplast neo-localization and the RGG protein SALTY are important in the extreme salinity tolerance of Salicornia bigelovii

The identification of genes involved in salinity tolerance has primarily focused on model plants and crops. However, plants naturally adapted to highly saline environments offer valuable insights into tolerance to extreme salinity. Salicornia plants grow in coastal salt marshes, stimulated by NaCl. To understand this tolerance, we generated genome sequences of two Salicornia species and analyzed the transcriptomic and proteomic responses of Salicornia bigelovii to NaCl. Subcellular membrane proteomes reveal that SbiSOS1, a homolog of the well-known SALT-OVERLY-SENSITIVE 1 (SOS1) protein, appears to localize to the tonoplast, consistent with subcellular localization assays in tobacco. This neo-localized protein can pump Na+ into the vacuole, preventing toxicity in the cytosol. We further identify 11 proteins of interest, of which SbiSALTY, substantially improves yeast growth on saline media. Structural characterization using NMR identified it as an intrinsically disordered protein, localizing to the endoplasmic reticulum in planta, where it can interact with ribosomes and RNA, stabilizing or protecting them during salt stress.

A set of cross-correlated relaxation experiments to probe the correlation time of two different and complementary spin pairs

Intrinsically disordered proteins (IDPs) defy the conventional structure-function paradigm by lacking a well-defined tertiary structure and exhibiting inherent flexibility. This flexibility leads to distinctive spin relaxation modes, reflecting isolated and specific motions within individual peptide planes. In this work, we propose a new pulse sequence to measure the longitudinal 13C' CSA-13C'-13Cα DD CCR rate [Formula: see text] and present a novel 3D version of the transverse [Formula: see text] CCR rate, adopting the symmetrical reconversion approach. We combined these rates with the analogous ΓxyN/NH and ΓzN/NH CCR rates to derive residue-specific correlation times for both spin-pairs within the same peptide plane. The presented approach offers a straightforward and intuitive way to compare the correlation times of two different and complementary spin vectors, anticipated to be a valuable aid to determine IDPs backbone dihedral angles distributions. We performed the proposed experiments on two systems: a folded protein ubiquitin and Coturnix japonica osteopontin, a prototypical IDP. Comparative analyses of the results show that the correlation times of different residues vary more for IDPs than globular proteins, indicating that the dynamics of IDPs is largely heterogeneous and dominated by local fluctuations.

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.

Semisynthesis of segmentally isotope-labeled and site-specifically palmitoylated CD44 cytoplasmic tail

CD44, a ubiquitously expressed transmembrane receptor, plays a crucial role in cell growth, migration, and tumor progression. Dimerization of CD44 is a key event in signal transduction and has emerged as a potential target for anti-tumor therapies. Palmitoylation, a posttranslational modification, disrupts CD44 dimerization and promotes CD44 accumulation in ordered membrane domains. However, the effects of palmitoylation on the structure and dynamics of CD44 at atomic resolution remain poorly understood. Here, we present a semisynthetic approach combining solid-phase peptide synthesis, recombinant expression, and native chemical ligation to investigate the impact of palmitoylation on the cytoplasmic domain (residues 669-742) of CD44 (CD44ct) by NMR spectroscopy. A segmentally isotope-labeled and site-specifically palmitoylated CD44 variant enabled NMR studies, which revealed chemical shift perturbations and indicated local and long-range conformational changes induced by palmitoylation. The long-range effects suggest altered intramolecular interactions and potential modulation of membrane association patterns. Semisynthetic, palmitoylated CD44ct serves as the basis for studying CD44 clustering, conformational changes, and localization within lipid rafts, and could be used to investigate its role as a tumor suppressor and to explore its therapeutic potential.

Characterization of Intrinsically Disordered Proteins in Healthy and Diseased States by Nuclear Magnetic Resonance

INTRODUCTION

Intrinsically Disordered Proteins (IDPs) are active in different cellular procedures like ordered assembly of chromatin and ribosomes, interaction with membrane, protein, and ligand binding, molecular recognition, binding, and transportation via nuclear pores, microfilaments and microtubules process and disassembly, protein functions, RNA chaperone, and nucleic acid binding, modulation of the central dogma, cell cycle, and other cellular activities, post-translational qualification and substitute splicing, and flexible entropic linker and management of signaling pathways.

METHODS

The intrinsic disorder is a precise structural characteristic that permits IDPs/IDPRs to be involved in both one-to-many and many-to-one signaling. IDPs/IDPRs also exert some dynamical and structural ordering, being much less constrained in their activities than folded proteins. Nuclear magnetic resonance (NMR) spectroscopy is a major technique for the characterization of IDPs, and it can be used for dynamic and structural studies of IDPs.

RESULTS AND CONCLUSION

This review was carried out to discuss intrinsically disordered proteins and their different goals, as well as the importance and effectiveness of NMR in characterizing intrinsically disordered proteins in healthy and diseased states.

DeepDRP: Prediction of intrinsically disordered regions based on integrated view deep learning architecture from transformer-enhanced and protein information

Intrinsic disorder in proteins, a widely distributed phenomenon in nature, is related to many crucial biological processes and various diseases. Traditional determination methods tend to be costly and labor-intensive, therefore it is desirable to seek an accurate identification method of intrinsically disordered proteins (IDPs). In this paper, we proposed a novel Deep learning model for Intrinsically Disordered Regions in Proteins named DeepDRP. DeepDRP employed an innovative TimeDistributed strategy and Bi-LSTM architecture to predict IDPs and is driven by integrated view features of PSSM, Energy-based encoding, AAindex, and transformer-enhanced embeddings including DR-BERT, OntoProtein, Prot-T5, and ESM-2. The comparison of different feature combinations indicates that the transformer-enhanced features contribute far more than traditional features to predict IDPs and ESM-2 accounts for a larger contribution in the pre-trained fusion vectors. The ablation test verified that the TimeDistributed strategy surely increased the model performance and is an efficient approach to the IDP prediction. Compared with eight state-of-the-art methods on the DISORDER723, S1, and DisProt832 datasets, the Matthews correlation coefficient of DeepDRP significantly outperformed competing methods by 4.90 % to 36.20 %, 11.80 % to 26.33 %, and 4.82 % to 13.55 %. In brief, DeepDRP is a reliable model for IDP prediction and is freely available at https://github.com/ZX-COLA/DeepDRP.

Biochemistry and Protein Interactions of the CYREN Microprotein

Over the past decade, advances in genomics have identified thousands of additional protein-coding small open reading frames (smORFs) missed by traditional gene finding approaches. These smORFs encode peptides and small proteins, commonly termed micropeptides or microproteins. Several of these newly discovered microproteins have biological functions and operate through interactions with proteins and protein complexes within the cell. CYREN1 is a characterized microprotein that regulates double-strand break repair in mammalian cells through interaction with Ku70/80 heterodimer. Ku70/80 binds to and stabilizes double-strand breaks and recruits the machinery needed for nonhomologous end join repair. In this study, we examined the biochemical properties of CYREN1 to better understand and explain its cellular protein interactions. Our findings support that CYREN1 is an intrinsically disordered microprotein and this disordered structure allows it to enriches several proteins, including a newly discovered interaction with SF3B1 via a distinct short linear motif (SLiMs) on CYREN1. Since many microproteins are predicted to be disordered, CYREN1 is an exemplar of how microproteins interact with other proteins and reveals an unknown scaffolding function of this microprotein that may link NHEJ and splicing.

A disordered region controls cBAF activity via condensation and partner recruitment

Intrinsically disordered regions (IDRs) represent a large percentage of overall nuclear protein content. The prevailing dogma is that IDRs engage in non-specific interactions because they are poorly constrained by evolutionary selection. Here, we demonstrate that condensate formation and heterotypic interactions are distinct and separable features of an IDR within the ARID1A/B subunits of the mSWI/SNF chromatin remodeler, cBAF, and establish distinct "sequence grammars" underlying each contribution. Condensation is driven by uniformly distributed tyrosine residues, and partner interactions are mediated by non-random blocks rich in alanine, glycine, and glutamine residues. These features concentrate a specific cBAF protein-protein interaction network and are essential for chromatin localization and activity. Importantly, human disease-associated perturbations in ARID1B IDR sequence grammars disrupt cBAF function in cells. Together, these data identify IDR contributions to chromatin remodeling and explain how phase separation provides a mechanism through which both genomic localization and functional partner recruitment are achieved.

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.

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.

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.

Specific isotopic labelling and reverse labelling for protein NMR spectroscopy: using metabolic precursors in sample preparation

The study of protein structure, dynamics and function by NMR spectroscopy commonly requires samples that have been enriched ('labelled') with the stable isotopes 13C and/or 15N. The standard approach is to uniformly label a protein with one or both of these nuclei such that all C and/or N sites are in principle 'NMR-visible'. NMR spectra of uniformly labelled proteins can be highly complicated and suffer from signal overlap. Moreover, as molecular size increases the linewidths of NMR signals broaden, which decreases sensitivity and causes further spectral congestion. Both effects can limit the type and quality of information available from NMR data. Problems associated with signal overlap and signal broadening can often be alleviated though the use of alternative, non-uniform isotopic labelling patterns. Specific isotopic labelling 'turns on' signals at selected sites while the rest of the protein is NMR-invisible. Conversely, specific isotopic unlabelling (also called 'reverse' labelling) 'turns off' selected signals while the rest of the protein remains NMR-visible. Both approaches can simplify NMR spectra, improve sensitivity, facilitate resonance assignment and permit a range of different NMR strategies when combined with other labelling tools and NMR experiments. Here, we review methods for producing proteins with enrichment of stable NMR-visible isotopes, with particular focus on residue-specific labelling and reverse labelling using Escherichia coli expression systems. We also explore how these approaches can aid NMR studies of proteins.

DeepCLD: An Efficient Sequence-Based Predictor of Intrinsically Disordered Proteins

Intrinsic disorder is common in proteins, plays important roles in protein functionality, and is commonly associated with various human diseases. To have an accurate tool for the annotation of intrinsic disorder in proteins, this paper proposes a novel algorithm, DeepCLD, for sequence-based prediction of intrinsically disordered proteins. This algorithm uses amino acid position specific scoring matrix (PSSM) to capture the intrinsic variability characteristic of sequence patterns, ResNet to preserve feature space structure, and bidirectional CudnnLSTM as recurrent layer to further improve the efficiency. Futhermore, DeepCLD also utilized the attention mechanism to solve the problem of gradient disappearing in deep network. Comparative analyses show that DeepCLD has faster training speed and higher prediction accuracy than comparable methods.

Solvent paramagnetic relaxation enhancement as a versatile method for studying structure and dynamics of biomolecular systems

Solvent paramagnetic relaxation enhancement (sPRE) is a versatile nuclear magnetic resonance (NMR)-based method that allows characterization of the structure and dynamics of biomolecular systems through providing quantitative experimental information on solvent accessibility of NMR-active nuclei. Addition of soluble paramagnetic probes to the solution of a biomolecule leads to paramagnetic relaxation enhancement in a concentration-dependent manner. Here we review recent progress in the sPRE-based characterization of structural and dynamic properties of biomolecules and their complexes, and aim to deliver a comprehensive illustration of a growing number of applications of the method to various biological systems. We discuss the physical principles of sPRE measurements and provide an overview of available co-solute paramagnetic probes. We then explore how sPRE, in combination with complementary biophysical techniques, can further advance biomolecular structure determination, identification of interaction surfaces within protein complexes, and probing of conformational changes and low-population transient states, as well as deliver insights into weak, nonspecific, and transient interactions between proteins and co-solutes. In addition, we present examples of how the incorporation of solvent paramagnetic probes can improve the sensitivity of NMR experiments and discuss the prospects of applying sPRE to NMR metabolomics, drug discovery, and the study of intrinsically disordered proteins.

Conformational Plasticity of Centrin 1 from Toxoplasma gondii in Binding to the Centrosomal Protein SFI1

Centrins are calcium (Ca²⁺)-binding proteins that are involved in many cellular functions including centrosome regulation. A known cellular target of centrins is SFI1, a large centrosomal protein containing multiple repeats that represent centrin-binding motifs. Recently, a protein homologous to yeast and mammalian SFI1, denominated TgSFI1, which shares SFI1-repeat organization, was shown to colocalize at centrosomes with centrin 1 from Toxoplasma gondii (TgCEN1). However, the molecular details of the interaction between TgCEN1 and TgSFI1 remain largely unknown. Herein, combining different biophysical methods, including isothermal titration calorimetry, nuclear magnetic resonance, circular dichroism, and fluorescence spectroscopy, we determined the binding properties of TgCEN1 and its individual N- and C-terminal domains to synthetic peptides derived from distinct repeats of TgSFI1. Overall, our data indicate that the repeats in TgSFI1 constitute binding sites for TgCEN1, but the binding modes of TgCEN1 to the repeats differ appreciably in terms of binding affinity, Ca²⁺ sensitivity, and lobe-specific interaction. These results suggest that TgCEN1 displays remarkable conformational plasticity, allowing for the distinct repeats in TgSFI1 to possess precise modes of TgCEN1 binding and regulation during Ca²⁺ sensing, which appears to be crucial for the dynamic association of TgCEN1 with TgSFI1 in the centrosome architecture.

Enhanced Nuclear Magnetic Resonance Spectroscopy with Isotropic Mixing as a Pseudodimension

Chemical analysis based on liquid-state nuclear magnetic resonance spectroscopy exploits numerous observables, mainly chemical shifts, relaxation rates, and internuclear coupling constants. Regarding the latter, the efficiencies of internuclear coherence transfers may be encoded in spectral peak intensities. The dependencies of these intensities on the experimental parameter that influences the transfer, for example, mixing time, are an important source of structural information. Yet, they are costly to measure and difficult to analyze. Here, we show that peak intensity build-up curves in two-dimensional total correlation spectroscopy (2D TOCSY) experiments may be quickly measured by employing nonuniform sampling and that their analysis can be effective if supported by quantum mechanical calculations. Thus, such curves can be used to form a new, third pseudodimension of the TOCSY spectrum. Similarly to the other two frequency dimensions, this one also resolves ambiguities and provides characteristic information. We show how the approach supports the analysis of a fragment of protein Tau Repeat-4 domain. Yet, its potential applications are far broader, including the analysis of complex mixtures or other polymers.

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.

Expression and structure of the Chlamydia trachomatis DksA ortholog

Chlamydia trachomatis is a bacterial obligate intracellular parasite and a significant cause of human disease, including sexually transmitted infections and trachoma. The bacterial RNA polymerase-binding protein DksA is a transcription factor integral to the multicomponent bacterial stress response pathway known as the stringent response. The genome of C. trachomatis encodes a DksA ortholog (DksA_Ct) that is maximally expressed at 15–20 h post infection, a time frame correlating with the onset of transition between the replicative reticulate body (RB) and infectious elementary body (EB) forms of the pathogen. Ectopic overexpression of DksA_Ct in C. trachomatis prior to RB–EB transitions during infection of HeLa cells resulted in a 39.3% reduction in overall replication (yield) and a 49.6% reduction in recovered EBs. While the overall domain organization of DksA_Ct is similar to the DksA ortholog of Escherichia coli (DksA_Ec), DksA_Ct did not functionally complement DksA_Ec. Transcription of dksA_Ct is regulated by tandem promoters, one of which also controls expression of nrdR, encoding a negative regulator of deoxyribonucleotide biosynthesis. The phenotype resulting from ectopic expression of DksA_Ct and the correlation between dksA_Ct and nrdR expression is consistent with a role for DksA_Ct in the C. trachomatis developmental cycle.

A unifying framework for amyloid-mediated membrane damage: The lipid-chaperone hypothesis

Over the past thirty years, researchers have highlighted the role played by a class of proteins or polypeptides that forms pathogenic amyloid aggregates in vivo, including i) the amyloid Aβ peptide, which is known to form senile plaques in Alzheimer's disease; ii) α-synuclein, responsible for Lewy body formation in Parkinson's disease and iii) IAPP, which is the protein component of type 2 diabetes-associated islet amyloids. These proteins, known as intrinsically disordered proteins (IDPs), are present as highly dynamic conformational ensembles. IDPs can partially (mis) fold into (dys) functional conformations and accumulate as amyloid aggregates upon interaction with other cytosolic partners such as proteins or lipid membranes. In addition, an increasing number of reports link the toxicity of amyloid proteins to their harmful effects on membrane integrity. Still, the molecular mechanism underlying the amyloidogenic proteins transfer from the aqueous environment to the hydrocarbon core of the membrane is poorly understood. This review starts with a historical overview of the toxicity models of amyloidogenic proteins to contextualize the more recent lipid-chaperone hypothesis. Then, we report the early molecular-level events in the aggregation and ion-channel pore formation of Aβ, IAPP, and α-synuclein interacting with model membranes, emphasizing the complexity of these processes due to their different spatial-temporal resolutions. Next, we underline the need for a combined experimental and computational approach, focusing on the strengths and weaknesses of the most commonly used techniques. Finally, the last two chapters highlight the crucial role of lipid-protein complexes as molecular switches among ion-channel-like formation, detergent-like, and fibril formation mechanisms and their implication in fighting amyloidogenic diseases.

NMR of intrinsically disordered proteins: A note on the application of 15N-13Cα het-TOCSY mixing for 13Cα magnetisation transfers

Intrinsically disordered proteins (IDPs) or protein regions represent functionally important biomolecules without unique structure. Their inherent flexibility prevents high-resolution structure determination by X-ray or cryo-EM methods. In contrast, NMR spectroscopy provides an extensive and still growing set of experimental approaches to obtain detailed information on structure and dynamics of IDPs. Here, it is experimentally demonstrated that ¹⁵N-¹³C^α band-selective heteronuclear cross-polarisation that has been successfully employed recently to achieve the efficient transfer of ¹⁵N_x magnetisation from amino acid residue 'i' to 'i + 1' and 'i - 1' residues in uniformly (¹⁵N,¹³C)-labelled intrinsically disordered proteins can also be applied to transfer, without significant relaxation losses, ¹³C^α_x magnetisation from an amino acid residue to its neighbouring residues. The possibility to obtain in one-shot correlation spectra arising from the simultaneous transfer of ¹⁵N_x and ¹³C^α_x magnetisations from an amino acid residue to neighbouring residues is also demonstrated.

DeepIDP-2L: protein intrinsically disordered region prediction by combining convolutional attention network and hierarchical attention network

MOTIVATION

Intrinsically disordered regions (IDRs) are widely distributed in proteins. Accurate prediction of IDRs is critical for the protein structure and function analysis. The IDRs are divided into long disordered regions (LDRs) and short disordered regions (SDRs) according to their lengths. Previous studies have shown that LDRs and SDRs have different proprieties. However, the existing computational methods fail to extract different features for LDRs and SDRs separately. As a result, they achieve unstable performance on datasets with different ratios of LDRs and SDRs.

RESULTS

In this study, a two-layer predictor was proposed called DeepIDP-2L. In the first layer, two kinds of attention-based models are used to extract different features for LDRs and SDRs, respectively. The hierarchical attention network is used to capture the distribution pattern features of LDRs, and convolutional attention network is used to capture the local correlation features of SDRs. The second layer of DeepIDP-2L maps the feature extracted in the first layer into a new feature space. Convolutional network and bidirectional long short term memory are used to capture the local and long-range information for predicting both SDRs and LDRs. Experimental results show that DeepIDP-2L can achieve more stable performance than other exiting predictors on independent test sets with different ratios of SDRs and LDRs.

AVAILABILITY AND IMPLEMENTATION

For the convenience of most experimental scientists, a user-friendly and publicly accessible web-server for the new predictor has been established at http://bliulab.net/DeepIDP-2L/. It is anticipated that DeepIDP-2L will become a very useful tool for identification of intrinsically disordered regions.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Recent Developments in Data-Assisted Modeling of Flexible Proteins

Many proteins can fold into well-defined conformations. However, intrinsically-disordered proteins (IDPs) do not possess a defined structure. Moreover, folded multi-domain proteins often digress into alternative conformations. Collectively, the conformational dynamics enables these proteins to fulfill specific functions. Thus, most experimental observables are averaged over the conformations that constitute an ensemble. In this article, we review the recent developments in the concept and methods for the determination of the dynamic structures of flexible peptides and proteins. In particular, we describe ways to extract information from nuclear magnetic resonance small-angle X-ray scattering (SAXS), and chemical cross-linking coupled with mass spectroscopy (XL-MS) measurements. All these techniques can be used to obtain ensemble-averaged restraints or to re-weight the simulated conformational ensembles.

Biophysical investigation of the dual binding surfaces of human transcription factors FOXO4 and p53

Cellular senescence is protective against external oncogenic stress, but its accumulation causes aging-related diseases. Forkhead box O4 (FOXO4) and p53 are human transcription factors known to promote senescence by interacting with each other and activating p21 transcription. Inhibition of the interaction is a strategy for inducing apoptosis of senescent cells, but the binding surfaces that mediate the FOXO4-p53 interaction remain elusive. Here, we investigated two binding sites involved in the interaction between FOXO4 and p53 by NMR spectroscopy. NMR chemical shift perturbation analysis showed that the binding between FOXO4's forkhead domain (FHD) and p53's transactivation domain (TAD), and between FOXO4's C-terminal transactivation domain (CR3) and p53's DNA-binding domain (DBD), mediate the FOXO4-p53 interaction. Isothermal titration calorimetry data showed that both interactions have micromolar K_d values, and FOXO4 FHD-p53 TAD interaction has a higher binding affinity. We also showed that the intramolecular CR3-binding surface of FOXO4 FHD interacts with p53 TAD2, and FOXO4 CR3 interacts with the DNA/p53 TAD-binding surface of p53 DBD, suggesting a network of potentially competitive and/or coordinated interactions. Based on these results, we propose that a network of intramolecular and intermolecular interactions contributes to the two transcription factors' proper localisation on the p21 promoter and consequently promotes p21 transcription and cell senescence. This work provides structural information at the molecular level that is key to understanding the interplay of two proteins responsible for cellular senescence.

Simultaneous Assignment and Structure Determination of Proteins From Sparsely Labeled NMR Datasets

Sparsely labeled NMR samples provide opportunities to study larger biomolecular assemblies than is traditionally done by NMR. This requires new computational tools that can handle the sparsity and ambiguity in the NMR datasets. The MELD (modeling employing limited data) Bayesian approach was assessed to be the best performing in predicting structures from sparsely labeled NMR data in the 13th edition of the Critical Assessment of Structure Prediction (CASP) event—and limitations of the methodology were also noted. In this report, we evaluate the nature and difficulty in modeling unassigned sparsely labeled NMR datasets and report on an improved methodological pipeline leading to higher-accuracy predictions. We benchmark our methodology against the NMR datasets provided by CASP 13.

Aggregation and the Intrinsic Structural Disorder of Dipeptide Repeat Peptides of C9orf72-Related Amyotrophic Lateral Sclerosis and Frontotemporal Dementia Characterized by NMR

Dipeptide repeats (DPRs) are known to play important roles in C9ORF72-related amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Studies on DPRs have reported on the kinetics of aggregation, toxicity, and low-resolution morphology of the aggregates of these peptides. While the dipeptide hexa-repeats of Gly-Pro [(GP)₆] have been shown to be nonaggregating, Gly-Ala [(GA)₆] and Gly-Arg [(GR)₆] exhibited the formation of neurotoxic aggregates. However, structural studies of these DPRs have been elusive. In this study, we explored the feasibility of a high-resolution monitoring of a real-time aggregation of these peptides in a solution by using NMR experiments. Although (GP)₆ is disordered and nonaggregating, the existence of cis and trans conformations was observed from NMR spectra. It was remarkable that the (GR)₆ exhibited the formation of multiple conformations, whereas the hydrophobic and low-soluble (GA)₆ aggregated fast in a temperature-dependent manner. These results demonstrate the feasibility of monitoring the minor conformational changes from highly disordered peptides, aggregation kinetics, and the formation of small molecular weight aggregates by solution NMR experiments. The ability to detect cis and trans local isomerizations in (GP)₆ is noteworthy and could be valuable to study intrinsically disordered proteins/peptides by NMR. The early detection of minor conformational changes could be valuable in better understanding the mechanistic insights into the formation of toxic intermediates and the development of approaches to inhibit them and, potentially, aid in the development of compounds to treat the devastating C9ORF72-related ALS and FTD diseases.

Sortase-mediated segmental labeling: A method for segmental assignment of intrinsically disordered regions in proteins

A significant number of proteins possess sizable intrinsically disordered regions (IDRs). Due to the dynamic nature of IDRs, NMR spectroscopy is often the tool of choice for characterizing these segments. However, the application of NMR to IDRs is often hindered by their instability, spectral overlap and resonance assignment difficulties. Notably, these challenges increase considerably with the size of the IDR. In response to these issues, here we report the use of sortase-mediated ligation (SML) for segmental isotopic labeling of IDR-containing samples. Specifically, we have developed a ligation strategy involving a key segment of the large IDR and adjacent folded headpiece domain comprising the C-terminus of A. thaliana villin 4 (AtVLN4). This procedure significantly reduces the complexity of NMR spectra and enables group identification of signals arising from the labeled IDR fragment, a process we refer to as segmental assignment. The validity of our segmental assignment approach is corroborated by backbone residue-specific assignment of the IDR using a minimal set of standard heteronuclear NMR methods. Using segmental assignment, we further demonstrate that the IDR region adjacent to the headpiece exhibits nonuniform spectral alterations in response to temperature. Subsequent residue-specific characterization revealed two segments within the IDR that responded to temperature in markedly different ways. Overall, this study represents an important step toward the selective labeling and probing of target segments within much larger IDR contexts. Additionally, the approach described offers significant savings in NMR recording time, a valuable advantage for the study of unstable IDRs, their binding interfaces, and functional mechanisms.

Conformational landscape of multidomain SMAD proteins

SMAD transcription factors, the main effectors of the TGFβ (transforming growth factor β) network, have a mixed architecture of globular domains and flexible linkers. Such a complicated architecture precluded the description of their full-length (FL) structure for many years. In this study, we unravel the structures of SMAD4 and SMAD2 proteins through an integrative approach combining Small-angle X-ray scattering, Nuclear Magnetic Resonance spectroscopy, X-ray, and computational modeling. We show that both proteins populate ensembles of conformations, with the globular domains tethered by disordered and flexible linkers, which defines a new dimension of regulation. The flexibility of the linkers facilitates DNA and protein binding and modulates the protein structure. Yet, SMAD4FL is monomeric, whereas SMAD2FL is in different monomer-dimer-trimer states, driven by interactions of the MH2 domains. Dimers are present regardless of the SMAD2FL activation state and concentration. Finally, we propose that SMAD2FL dimers are key building blocks for the quaternary structures of SMAD complexes.

Polarizable and non-polarizable force fields: Protein folding, unfolding, and misfolding

Molecular dynamics simulations are an invaluable tool to characterize the dynamic motions of proteins in atomistic detail. However, the accuracy of models derived from simulations inevitably relies on the quality of the underlying force field. Here, we present an evaluation of current non-polarizable and polarizable force fields (AMBER ff14SB, CHARMM 36m, GROMOS 54A7, and Drude 2013) based on the long-standing biophysical challenge of protein folding. We quantify the thermodynamics and kinetics of the β-hairpin formation using Markov state models of the fast-folding mini-protein CLN025. Furthermore, we study the (partial) folding dynamics of two more complex systems, a villin headpiece variant and a WW domain. Surprisingly, the polarizable force field in our set, Drude 2013, consistently leads to destabilization of the native state, regardless of the secondary structure element present. All non-polarizable force fields, on the other hand, stably characterize the native state ensembles in most cases even when starting from a partially unfolded conformation. Focusing on CLN025, we find that the conformational space captured with AMBER ff14SB and CHARMM 36m is comparable, but the ensembles from CHARMM 36m simulations are clearly shifted toward disordered conformations. While the AMBER ff14SB ensemble overstabilizes the native fold, CHARMM 36m and GROMOS 54A7 ensembles both agree remarkably well with experimental state populations. In addition, GROMOS 54A7 also reproduces experimental folding times most accurately. Our results further indicate an over-stabilization of helical structures with AMBER ff14SB. Nevertheless, the presented investigations strongly imply that reliable (un)folding dynamics of small proteins can be captured in feasible computational time with current additive force fields.

How multisite phosphorylation impacts the conformations of intrinsically disordered proteins

Phosphorylation of intrinsically disordered proteins (IDPs) can produce changes in structural and dynamical properties and thereby mediate critical biological functions. How phosphorylation effects intrinsically disordered proteins has been studied for an increasing number of IDPs, but a systematic understanding is still lacking. Here, we compare the collapse propensity of four disordered proteins, Ash1, the C-terminal domain of RNA polymerase (CTD2’), the cytosolic domain of E-Cadherin, and a fragment of the p130Cas, in unphosphorylated and phosphorylated forms using extensive all-atom molecular dynamics (MD) simulations. We find all proteins to show V-shape changes in their collapse propensity upon multi-site phosphorylation according to their initial net charge: phosphorylation expands neutral or overall negatively charged IDPs and shrinks positively charged IDPs. However, force fields including those tailored towards and commonly used for IDPs overestimate these changes. We find quantitative agreement of MD results with SAXS and NMR data for Ash1 and CTD2’ only when attenuating protein electrostatic interactions by using a higher salt concentration (e.g. 350 mM), highlighting the overstabilization of salt bridges in current force fields. We show that phosphorylation of IDPs also has a strong impact on the solvation of the protein, a factor that in addition to the actual collapse or expansion of the IDP should be considered when analyzing SAXS data. Compared to the overall mild change in global IDP dimension, the exposure of active sites can change significantly upon phosphorylation, underlining the large susceptibility of IDP ensembles to regulation through post-translational modifications.

Intrinsically disordered proteins (IDPs) are a class of proteins that lack secondary and tertiary structures and instead explore a broad conformational ensemble. Their functions, from transcriptional regulation to signal transmission, are tightly regulated. IDPs are subject of extensive reversible post-translational modifications (PTMs), such as phosphorylation, methylation and glycosylation. Among these PTMs, phosphorylation is one of the most common and important PTMs. However, the mechanism of how phosphorylation affects the conformations and functions of IDPs remains unclear. To answer this question, we have performed extensive all-atom molecular dynamics simulations for four representative IDPs: Ash1, E-Cadherin, CTD2’ and p130Cas in their unphosphorylated and phosphorylated forms. Our results showed that all IDPs undergo a mild change upon multi-site phosphorylation, which is V-shaped: phosphorylation moderately expands neutral or overall negatively charged IDPs and shrinks positively charged IDPs. More importantly, in two of these IDPs, only two biologically relevant phosphorylation sites suffice to render the adjacent negatively charged active site significantly more exposed to the environment, which implies a higher probability to interact with other binding partners.

Neutron reflectometry and NMR spectroscopy of full-length Bcl-2 protein reveal its membrane localization and conformation

B-cell lymphoma 2 (Bcl-2) proteins are the main regulators of mitochondrial apoptosis. Anti-apoptotic Bcl-2 proteins possess a hydrophobic tail-anchor enabling them to translocate to their target membrane and to shift into an active conformation where they inhibit pro-apoptotic Bcl-2 proteins to ensure cell survival. To address the unknown molecular basis of their cell-protecting functionality, we used intact human Bcl-2 protein natively residing at the mitochondrial outer membrane and applied neutron reflectometry and NMR spectroscopy. Here we show that the active full-length protein is entirely buried into its target membrane except for the regulatory flexible loop domain (FLD), which stretches into the aqueous exterior. The membrane location of Bcl-2 and its conformational state seems to be important for its cell-protecting activity, often infamously upregulated in cancers. Most likely, this situation enables the Bcl-2 protein to sequester pro-apoptotic Bcl-2 proteins at the membrane level while sensing cytosolic regulative signals via its FLD region.

Identification of Intrinsically Disordered Protein Regions Based on Deep Neural Network-VGG16

The accurate of i identificationntrinsically disordered proteins or protein regions is of great importance, as they are involved in critical biological process and related to various human diseases. In this paper, we develop a deep neural network that is based on the well-known VGG16. Our deep neural network is then trained through using 1450 proteins from the dataset DIS1616 and the trained neural network is tested on the remaining 166 proteins. Our trained neural network is also tested on the blind test set R80 and MXD494 to further demonstrate the performance of our model. The MCC value of our trained deep neural network is 0.5132 on the test set DIS166, 0.5270 on the blind test set R80 and 0.4577 on the blind test set MXD494. All of these MCC values of our trained deep neural network exceed the corresponding values of existing prediction methods.

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.

The Disordered Spindly C-terminus Interacts with RZZ Subunits ROD-1 and ZWL-1 in the Kinetochore through the Same Sites in C. Elegans

Spindly is a dynein adaptor involved in chromosomal segregation during cell division. While Spindly's N-terminal domain binds to the microtubule motor dynein and its activator dynactin, the C-terminal domain (Spindly-C) binds its cargo, the ROD/ZW10/ZWILCH (RZZ) complex in the outermost layer of the kinetochore. In humans, Spindly-C binds to ROD, while in C. elegans Spindly-C binds to both Zwilch (ZWL-1) and ROD-1. Here, we employed various biophysical techniques to characterize the structure, dynamics and interaction sites of C. elegans Spindly-C. We found that despite the overall disorder, there are two regions with variable α-helical propensity. One of these regions is located in the C-terminal half and is compact; the second is sparsely populated in the N-terminal half. The interactions with both ROD-1 and ZWL-1 are mostly mediated by the same two sequentially remote disordered segments of Spindly-C, which are C-terminally adjacent to the helical regions. The findings suggest that the Spindly-C binding sites on ROD-1 in the ROD-1/ZWL-1 complex context are either shielded or conformationally weakened by the presence of ZWL-1 such that only ZWL-1 directly interacts with Spindly-C in C. elegans.

Mechanism of the small ATP-independent chaperone Spy is substrate specific

ATP-independent chaperones are usually considered to be holdases that rapidly bind to non-native states of substrate proteins and prevent their aggregation. These chaperones are thought to release their substrate proteins prior to their folding. Spy is an ATP-independent chaperone that acts as an aggregation inhibiting holdase but does so by allowing its substrate proteins to fold while they remain continuously chaperone bound, thus acting as a foldase as well. The attributes that allow such dual chaperoning behavior are unclear. Here, we used the topologically complex protein apoflavodoxin to show that the outcome of Spy's action is substrate specific and depends on its relative affinity for different folding states. Tighter binding of Spy to partially unfolded states of apoflavodoxin limits the possibility of folding while bound, converting Spy to a holdase chaperone. Our results highlight the central role of the substrate in determining the mechanism of chaperone action.

NMR spectroscopy captures the essential role of dynamics in regulating biomolecular function

Biomolecules are in constant motion. To understand how they function, and why malfunctions can cause disease, it is necessary to describe their three-dimensional structures in terms of dynamic conformational ensembles. Here, we demonstrate how nuclear magnetic resonance (NMR) spectroscopy provides an essential, dynamic view of structural biology that captures biomolecular motions at atomic resolution. We focus on examples that emphasize the diversity of biomolecules and biochemical applications that are amenable to NMR, such as elucidating functional dynamics in large molecular machines, characterizing transient conformations implicated in the onset of disease, and obtaining atomic-level descriptions of intrinsically disordered regions that make weak interactions involved in liquid-liquid phase separation. Finally, we discuss the pivotal role that NMR has played in driving forward our understanding of the biomolecular dynamics-function paradigm.

Temperature as an Extra Dimension in Multidimensional Protein NMR Spectroscopy

NMR spectroscopy is a particularly informative method for studying protein structures and dynamics in solution; however, it is also one of the most time-consuming. Modern approaches to biomolecular NMR spectroscopy are based on lengthy multidimensional experiments, the duration of which grows exponentially with the number of dimensions. The experimental time may even be several days in the case of 3D and 4D spectra. Moreover, the experiment often has to be repeated under several different conditions, for example, to measure the temperature-dependent effects in a spectrum (temperature coefficients (TCs)). Herein, a new approach that involves joint sampling of indirect evolution times and temperature is proposed. This allows TCs to be measured through 3D spectra in even less time than that needed to acquire a single spectrum by using the conventional approach. Two signal processing methods that are complementary, in terms of sensitivity and resolution, 1) dividing data into overlapping subsets followed by compressed sensing reconstruction, and 2) treating the complete data set with a variant of the Radon transform, are proposed. The temperature-swept 3D HNCO spectra of two intrinsically disordered proteins, osteopontin and CD44 cytoplasmic tail, show that this new approach makes it possible to determine TCs and their non-linearities effectively. Non-linearities, which indicate the presence of a compact state, are particularly interesting. The complete package of data acquisition and processing software for this new approach are provided.

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.

A kinetic ensemble of the Alzheimer's Aβ peptide

The conformational and thermodynamic properties of disordered proteins are commonly described in terms of structural ensembles and free energy landscapes. To provide information on the transition rates between the different states populated by these proteins, it would be desirable to generalize this description to kinetic ensembles. Approaches based on the theory of stochastic processes can be particularly suitable for this purpose. Here, we develop a Markov state model and apply it to determine a kinetic ensemble of Aβ42, a disordered peptide associated with Alzheimer's disease. Through the Google Compute Engine, we generated 315-µs all-atom molecular dynamics trajectories. Using a probabilistic-based definition of conformational states in a neural network approach, we found that Aβ42 is characterized by inter-state transitions on the microsecond timescale, exhibiting only fully unfolded or short-lived, partially folded states. Our results illustrate how kinetic ensembles provide effective information about the structure, thermodynamics and kinetics of disordered proteins.

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.

Roles, Characteristics, and Analysis of Intrinsically Disordered Proteins: A Minireview

In recent years, there has been a growing understanding that a significant fraction of the eukaryotic proteome is intrinsically disordered, and that these conformationally dynamic proteins play a myriad of vital biological roles in both normal and pathological states. In this review, selected examples of intrinsically disordered proteins are highlighted, with particular attention for a few which are relevant in neurological disorders and in viral infection. Next, the underlying causes for the intrinsic disorder are discussed, along with computational methods used to predict whether a given amino acid sequence is likely to adopt a folded or unfolded state in the solution. Finally, biophysical methods for the analysis of intrinsically disordered proteins will be discussed, as well as the unique challenges they pose in this context due to their highly dynamic nature.

Polyelectrolyte interactions enable rapid association and dissociation in high-affinity disordered protein complexes

Highly charged intrinsically disordered proteins can form complexes with very high affinity in which both binding partners fully retain their disorder and dynamics, exemplified by the positively charged linker histone H1.0 and its chaperone, the negatively charged prothymosin α. Their interaction exhibits another surprising feature: The association/dissociation kinetics switch from slow two-state-like exchange at low protein concentrations to fast exchange at higher, physiologically relevant concentrations. Here we show that this change in mechanism can be explained by the formation of transient ternary complexes favored at high protein concentrations that accelerate the exchange between bound and unbound populations by orders of magnitude. Molecular simulations show how the extreme disorder in such polyelectrolyte complexes facilitates (i) diffusion-limited binding, (ii) transient ternary complex formation, and (iii) fast exchange of monomers by competitive substitution, which together enable rapid kinetics. Biological polyelectrolytes thus have the potential to keep regulatory networks highly responsive even for interactions with extremely high affinities.

The Anti-Inflammatory Protein TNIP1 Is Intrinsically Disordered with Structural Flexibility Contributed by Its AHD1-UBAN Domain

TNFAIP3 interacting protein 1 (TNIP1) interacts with numerous non-related cellular, viral, and bacterial proteins. TNIP1 is also linked with multiple chronic inflammatory disorders on the gene and protein levels, through numerous single-nucleotide polymorphisms and reduced protein amounts. Despite the importance of TNIP1 function, there is limited investigation as to how its conformation may impact its apparent multiple roles. Hub proteins like TNIP1 are often intrinsically disordered proteins. Our initial in silico assessments suggested TNIP1 is natively unstructured, featuring numerous potentials intrinsically disordered regions, including the ABIN homology domain 1-ubiquitin binding domain in ABIN proteins and NEMO (AHD1-UBAN) domain associated with its anti-inflammatory function. Using multiple biophysical approaches, we demonstrate the structural flexibility of full-length TNIP1 and the AHD1-UBAN domain. We present evidence the AHD1-UBAN domain exists primarily as a pre-molten globule with limited secondary structure in solution. Data presented here suggest the previously described coiled-coil conformation of the crystallized UBAN-only region may represent just one of possibly multiple states for the AHD1-UBAN domain in solution. These data also characterize the AHD1-UBAN domain in solution as mostly monomeric with potential to undergo oligomerization under specific environmental conditions (e.g., binding partner availability, pH-dependence). This proposed intrinsic disorder across TNIP1 and within the AHD1-UBAN region is likely to impact TNIP1 function and interaction with its multiple partners.