Intrinsically Disordered Proteins Research Articles

Elastin-Like Peptide as a Model for Disordered Proteins: Diffusion Behaviour in Self-Crowding Conditions.

Despite the current high interest, there is limited information on diffusion data for intrinsically disordered proteins (IDPs). This study investigates the effect of crowding on the diffusion behaviour of an elastin-like peptide (ELP), by combined pulse field gradient (PFG) and static field gradient (SFG) NMR techniques. We interpret our findings in terms of highly dynamic chain assemblies with weak interactions, resulting in ELP diffusion that is primarily governed by the viscous flow of the solvent. The diffusion behaviour of the peptide appears to resemble that of globular proteins rather than flexible linear polymers over a wide concentration range.

Conserved molecular recognition by an intrinsically disordered region in the absence of sequence conservation.

Intrinsically disordered regions (IDRs) are critical for cellular function yet often appear to lack sequence conservation when assessed by multiple sequence alignments. This raises the question of if and how function can be encoded and preserved in these regions despite massive sequence variation. To address this question, we have applied coarse-grained molecular dynamics simulations to investigate non-specific RNA binding of coronavirus nucleocapsid proteins. Coronavirus nucleocapsid proteins consist of multiple interspersed disordered and folded domains that bind RNA. Here, we focus on the first two domains of coronavirus nucleocapsid proteins: the disordered N-terminal domain (NTD) and the folded RNA binding domain (RBD). While the NTD is highly variable across evolution, the RBD is structurally conserved. This combination makes the NTD-RBD a convenient model system for exploring the interplay between an IDR adjacent to a folded domain and how changes in IDR sequence can influence molecular recognition of a partner. Our results reveal a surprising degree of sequence-specificity encoded by both the composition and the precise order of the amino acids in the NTD. The presence of an NTD can - depending on the sequence - either suppress or enhance RNA binding. Despite this sensitivity, large-scale variation in NTD sequences is possible while certain sequence features are retained. Consequently, a conformationally-conserved dynamic and disordered RNA:protein complex is found across nucleocapsid protein orthologs despite large-scale changes in both NTD sequence and RBD surface chemistry. Taken together, these insights shed light on the ability of disordered regions to preserve functional characteristics despite their sequence variability.

Disordered region of nuclear membrane protein Bqt4 recruits phosphatidic acid to the nuclear envelope to maintain its structural integrity

The nuclear envelope (NE) is a permeable barrier that maintains nuclear–cytoplasmic compartmentalization and ensures nuclear function; however, it ruptures in various situations such as mechanical stress and mitosis. Although the protein components for sealing a ruptured NE have been identified, the mechanism by which lipid components are involved in this process remains to be elucidated. Here, we found that an inner nuclear membrane (INM) protein Bqt4 directly interacts with phosphatidic acid (PA) and serves as a platform for NE maintenance in the fission yeast Schizosaccharomyces pombe. The intrinsically disordered region (IDR) of Bqt4, proximal to the transmembrane domain, binds to PA and forms a solid aggregate in vitro. Excessive accumulation of Bqt4 IDR in INM results in membrane overproliferation and lipid droplet formation in the nucleus, leading to centromere dissociation from the NE and chromosome missegregation. Our findings suggest that Bqt4 IDR controls nuclear membrane homeostasis by recruiting PA to the INM, thereby maintaining the structural integrity of the NE.

Computer-Aided Design of Peptides for Suppressing Liquid-Liquid Phase Separation

Liquid-liquid phase separation (LLPS) is a fundamental process in cellular biology, critical for the formation of membraneless organelles. Dysregulation of LLPS is linked to various diseases, highlighting the need for targeted therapeutics. Traditional computer-aided drug design has struggled to address LLPS due to the involvement of intrinsically disordered regions (IDRs). In this study, we identified a peptide derived from the low-complexity (LC) region of FUS, with serine-to-glutamic acid mutations (S2E), which significantly suppresses LC phase separation. GPU-based molecular dynamics simulations reveal that the interaction between S2E and LC is essential for their suppressive effect. Inspired by this finding, we proposed a strategy that employs multivalent interactions to design peptides capable of inhibiting phase separation. As a proof of concept, we engineered peptides that combine the LARKS domain from FUS-LC with an E-rich sequence from HSP90, yielding two potent peptides. These peptides effectively inhibit phase separation, as validated by both computer simulation and experimental data. Our findings provide a new avenue for the primary design of peptides aimed at controlling phase separation and protein aggregation, with potential applications in therapeutic development for LLPS-related diseases.

Adding intrinsically disordered proteins to biological ageing clocks.

Research into how the young and old differ, and which biomarkers reflect the diverse biological processes underlying ageing, is a current and fast-growing field. Biological clocks provide a means to evaluate whether a molecule, cell, tissue or even an entire organism is old or young. Here we summarize established and emerging molecular clocks as timepieces. We emphasize that intrinsically disordered proteins (IDPs) tend to transform into a β-sheet-rich aggregated state and accumulate in non-dividing or slowly dividing cells as they age. We hypothesize that understanding these protein-based molecular ageing mechanisms might provide a conceptual pathway to determining a cell's health age by probing the aggregation state of IDPs, which we term the IDP clock.

Phase separation of SPIN1 through its IDR facilitates histone methylation readout and tumorigenesis.

Spindlin1 (SPIN1) is a unique multivalent histone modification reader that plays a role in ribosomal RNA transcription, chromosome segregation, and tumorigenesis. However, the function of the extended N-terminal region of SPIN1 has remained unclear. Here, we discovered that SPIN1 can form phase-separated and liquid-like condensates both in vitro and in vivo through its N-terminal intrinsically disordered region (IDR). The phase separation of SPIN1 recruits the histone methyltransferase MLL1 to the same condensates and enriches the H3K4 methylation marks. This process also facilitates the binding of SPIN1 to H3K4me3 and activates tumorigenesis-related genes. Moreover, SPIN1-IDR enhances the genome-wide chromatin binding of SPIN1 and facilitates its localization to genes associated with the MAPK signaling pathway. These findings provide new insights into the biological function of the IDR in regulating SPIN1 activity and reveal a previously unrecognized role of SPIN1-IDR in histone methylation readout. Our study uncovers the crucial role of appropriate biophysical properties of SPIN1 in facilitating gene expression and links phase separation to tumorigenesis, which provides a new perspective for understanding the function of SPIN1.

Structured and disordered regions of Ataxin-2 contribute differently to the specificity and efficiency of mRNP granule formation.

Ataxin-2 (ATXN2) is a gene implicated in spinocerebellar ataxia type II (SCA2), amyotrophic lateral sclerosis (ALS) and Parkinsonism. The encoded protein is a therapeutic target for ALS and related conditions. ATXN2 (or Atx2 in insects) can function in translational activation, translational repression, mRNA stability and in the assembly of mRNP-granules, a process mediated by intrinsically disordered regions (IDRs). Previous work has shown that the LSm (Like-Sm) domain of Atx2, which can help stimulate mRNA translation, antagonizes mRNP-granule assembly. Here we advance these findings through a series of experiments on Drosophila and human Ataxin-2 proteins. Results of Targets of RNA Binding Proteins Identified by Editing (TRIBE), co-localization and immunoprecipitation experiments indicate that a polyA-binding protein (PABP) interacting, PAM2 motif of Ataxin-2 may be a major determinant of the mRNA and protein content of Ataxin-2 mRNP granules. Experiments with transgenic Drosophila indicate that while the Atx2-LSm domain may protect against neurodegeneration, structured PAM2- and unstructured IDR- interactions both support Atx2-induced cytotoxicity. Taken together, the data lead to a proposal for how Ataxin-2 interactions are remodelled during translational control and how structured and non-structured interactions contribute differently to the specificity and efficiency of RNP granule condensation as well as to neurodegeneration.

Intrinsic disorder in flaviviral capsid proteins and its role in pathogenesis

Intrinsic disorder in flaviviral capsid proteins and its role in pathogenesis

A study on post-traumatic stress disorder and post-traumatic growth among patients infected with COVID-19 in Wuhan.

The purpose of this study is to assess the physical and psychological conditions of hospitalized patients who were infected with COVID-19 in Wuhan, China, including post-traumatic stress disorder (PTSD) and post-traumatic growth (PTG) scores and predictors. The test group consisted of 102 hospitalized patients diagnosed with COVID-19 in Wuhan between March 4, 2020 and April 5, 2020, whereas the control group comprised 168 healthy study participants. Relevant information of the study participants was obtained using online questionnaires, covering five aspects-general information, physical state, emotional state, PTSD, and PTG. In Wuhan, 37.3% of COVID-19-diagnosed hospitalized patients exhibited hyper-arousal symptoms of PTSD. This percentage is significantly higher than the 13.1% observed in the healthy population. Furthermore, the prevalence of PTG among the same group of hospitalized patients stood at 77.5%, surpassing the 66.1% rate found within the healthy population. It was determined that inconsistent sleep patterns during the hospitalization phase could be indicative of heightened vulnerability to hyperarousal symptoms of PTSD in COVID-19-diagnosed hospitalized patients. The study determined that inconsistent sleep patterns during hospitalization may be a predisposition factor that makes hospitalized patients diagnosed with covid-19 more susceptible to high arousal symptoms of post-traumatic stress disorder. Conversely, COVID-19-diagnosed hospitalized patients who maintained a tranquil demeanor and exhibited positive emotional perceptions during their hospitalization displayed reduced susceptibility to these PTSD symptoms. Factors such as possession of a bachelor's degree, history of severe acute respiratory syndrome (SARS) infection, and poor sleep patterns were identified as predictors elevating the risk of PTG. Whereas, a sentiment of happiness and consistent positive emotional perception during hospitalization were predictors of PTG. Intriguingly, a direct correlation was established between hyper-arousal symptoms of PTSD and PTG. Although the outbreak of COVID-19 has badly affected the physical and psychological well-being of patients, it has greatly enhanced their PTG.

Linear and Nonlinear Dielectric Response of Intrinsically Disordered Proteins.

Linear and nonlinear dielectric responses of solutions of intrinsically disordered proteins (IDPs) were analyzed by combining molecular dynamics simulations with formal theories. A large increment of the linear dielectric function over that of the solvent is found and related to large dipole moments of IDPs. The nonlinear dielectric effect (NDE) of the IDP far exceeds that of the bulk electrolyte, offering a route to interrogate protein conformational and rotational statistics and dynamics. Conformational flexibility of the IDP makes the dipole moment statistics consistent with the gamma/log-normal distributions and contributes to the NDE through the dipole moment's non-Gaussian parameter. The intrinsic non-Gaussian parameter of the dipole moment combines with the protein osmotic compressibility in the nonlinear dielectric susceptibility when dipolar correlations are screened by the electrolyte. The NDE is dominated by dipolar correlations when electrolyte screening is reduced.

AlphaFold2 modeling and molecular dynamics simulations of an intrinsically disordered protein.

We use AlphaFold2 (AF2) to model the monomer and dimer structures of an intrinsically disordered protein (IDP), Nvjp-1, assisted by molecular dynamics (MD) simulations. We observe relatively rigid dimeric structures of Nvjp-1 when compared with the monomer structures. We suggest that protein conformations from multiple AF2 models and those from MD trajectories exhibit a coherent trend: the conformations of an IDP are deviated from each other and the conformations of a well-folded protein are consistent with each other. We use a residue-residue interaction network (RIN) derived from the contact map which show that the residue-residue interactions in Nvjp-1 are mainly transient; however, those in a well-folded protein are mainly persistent. Despite the variation in 3D shapes, we show that the AF2 models of both disordered and ordered proteins exhibit highly consistent profiles of the pLDDT (predicted local distance difference test) scores. These results indicate a potential protocol to justify the IDPs based on multiple AF2 models and MD simulations.

Identification of Essential Components of RNA Binding Domain of TLS/FUS

TLS/FUS is RNA-binding protein having multiple functions of regulations of genes, homeostasis, and cellular growth. Recent studies show that TLS is involved in phase separation and occasionally forms precipitation related to neurodegenerative diseases like amyotrophic lateral sclerosis (ALS). RNA has been reported to suppress phase separation, droplet formation, and concomitant precipitation of TLS, suggesting that RNA is a possible candidate for ALS drug discovery. Our experiments demonstrated that a long noncoding RNA, promoter-associated noncoding RNA (pncRNA-D), specifically binds TLS and represses its phase separation and precipitation. To obtain competent drug seeds, it is essential to reveal mechanism of action of lncRNAs with specificity to TLS and inhibitory activity on phase separation and related precipitation. For this purpose, several lncRNAs (lncRNAs 1 to 6) were selected upon assays with GST-TLS binding and inhibition on the precipitation. With criteria of binding specificity for TLS, lncRNA3 has been selected for further analysis for RNA-binding ability. Initially, RNA-binding region at TLS amino acid sequence was identified from four fragments of TLS. RNA binding assay with biotinylated lncRNA3 precipitated with avidin magnetic beads indicated clearly that TLS binds the fragment 4 (373-526 aa), C-terminus end of TLS. Then, dissecting fragment 4 presents four regions, RGG2, zinc finger, RGG3, and the nuclear localization signal (NLS) region in this order. Experiments with extensive deletion mutants indicated that just one deletion out of the four regions irs not enough to delete the TLS binding, although combinatorial deletion of zinc finger with other three regions almost wiped off the lncRNA3 binding. Remarkably, each of four regions alone has no binding to TLS, either. Collectively, RGG2, zinc finger, RGG3, and NLS all are essential for binding to lncRNA3, but are required to work synergistically for full binding. These data indicate that dynamic assembly of RNA-binding domain works for action of lncRNAs and possibly has allosteric effect on intrinsically disordered region (IDR) of N-terminus of TLS, implying relation of RNA-binding with phase separation and the resultant precipitation.

Understanding the Energy Landscape of Intrinsically Disordered Protein Ensembles.

A substantial portion of various organisms' proteomes comprises intrinsically disordered proteins (IDPs) that lack a defined three-dimensional structure. These IDPs exhibit a diverse array of conformations, displaying remarkable spatiotemporal heterogeneity and exceptional conformational flexibility. Characterizing the structure or structural ensemble of IDPs presents significant conceptual and methodological challenges owing to the absence of a well-defined native structure. While databases such as the Protein Ensemble Database (PED) provide IDP ensembles obtained through a combination of experimental data and molecular modeling, the absence of reaction coordinates poses challenges in comprehensively understanding pertinent aspects of the system. In this study, we leverage the energy landscape visualization method (JCTC, 6482, 2019) to scrutinize four IDP ensembles sourced from PED. ELViM, a methodology that circumvents the need for a priori reaction coordinates, aids in analyzing the ensembles. The specific IDP ensembles investigated are as follows: two fragments of nucleoporin (NUL: 884-993 and NUS: 1313-1390), yeast sic 1 N-terminal (1-90), and the N-terminal SH3 domain of Drk (1-59). Utilizing ELViM enables the comprehensive validation of ensembles, facilitating the detection of potential inconsistencies in the sampling process. Additionally, it allows for identifying and characterizing the most prevalent conformations within an ensemble. Moreover, ELViM facilitates the comparative analysis of ensembles obtained under diverse conditions, thereby providing a powerful tool for investigating the functional mechanisms of IDPs.

Dynamics of Single-Chain Nanoparticles under Crowding: A Neutron Spin Echo Study.

We present a neutron spin echo (NSE) investigation to examine the impact of macromolecular crowding on the dynamics of single-chain nanoparticles (SCNPs), serving as synthetic models for biomacromolecules with flexibility and internal degrees of freedom, such as intrinsically disordered proteins (IDPs). In particular, we studied the dynamics of a medium-size poly(methyl methacrylate) (PMMA)-based SCNP (33 kDa) in solutions with low- (10 kDa) and high- (100 kDa) molecular weight analogous deuterated PMMA linear crowders. The dynamic structure factors of the SCNPs in dilute solution show certain degrees of freedom, yet the analysis in terms of the Zimm model reveals high internal friction that effectively stiffens the chain-a phenomenon also observed for IDPs. Under crowding conditions, the internal dynamics remains essentially unchanged, but the center-of-mass diffusion slows down. The effective viscosity felt by the SCNPs at the timescales probed by NSE is lower than the macroscopic viscosity of the crowder solution, and it does not depend significantly on the molecular weight.

Unveiling the Binding between the Armadillo-Repeat Domain of Plakophilin 1 and the Intrinsically Disordered Transcriptional Repressor RYBP.

Plakophilin 1 (PKP1), a member of the p120ctn subfamily of the armadillo (ARM)-repeat-containing proteins, is an important structural component of cell-cell adhesion scaffolds although it can also be ubiquitously found in the cytoplasm and the nucleus. RYBP (RING 1A and YY1 binding protein) is a multifunctional intrinsically disordered protein (IDP) best described as a transcriptional regulator. Both proteins are involved in the development and metastasis of several types of tumors. We studied the binding of the armadillo domain of PKP1 (ARM-PKP1) with RYBP by using in cellulo methods, namely immunofluorescence (IF) and proximity ligation assay (PLA), and in vitro biophysical techniques, namely fluorescence, far-ultraviolet (far-UV) circular dichroism (CD), and isothermal titration calorimetry (ITC). We also characterized the binding of the two proteins by using in silico experiments. Our results showed that there was binding in tumor and non-tumoral cell lines. Binding in vitro between the two proteins was also monitored and found to occur with a dissociation constant in the low micromolar range (~10 μM). Finally, in silico experiments provided additional information on the possible structure of the binding complex, especially on the binding ARM-PKP1 hot-spot. Our findings suggest that RYBP might be a rescuer of the high expression of PKP1 in tumors, where it could decrease the epithelial-mesenchymal transition in some cancer cells.

Isolation of nucleic acids using liquid–liquid phase separation of pH-sensitive elastin-like polypeptides

Extraction of nucleic acids (NAs) is critical for many methods in molecular biology and bioanalytical chemistry. NA extraction has been extensively studied and optimized for a wide range of applications and its importance to society has significantly increased. The COVID-19 pandemic highlighted the importance of early and efficient NA testing, for which NA extraction is a critical analytical step prior to the detection by methods like polymerase chain reaction. This study explores simple, new approaches to extraction using engineered smart nanomaterials, namely NA-binding, intrinsically disordered proteins (IDPs), that undergo triggered liquid–liquid phase separation (LLPS). Two types of NA-binding IDPs are studied, both based on genetically engineered elastin-like polypeptides (ELPs), model IDPs that exhibit a lower critical solution temperature in water and can be designed to exhibit LLPS at desired temperatures in a variety of biological solutions. We show that ELP fusion proteins with natural NA-binding domains can be used to extract DNA and RNA from physiologically relevant solutions. We further show that LLPS of pH responsive ELPs that incorporate histidine in their sequences can be used for both binding, extraction and release of NAs from biological solutions, and can be used to detect SARS-CoV-2 RNA in samples from COVID-positive patients.

Hydrodynamic Radii of Intrinsically Disordered Proteins: Fast Prediction by Minimum Dissipation Approximation and Experimental Validation.

The diffusion coefficients of globular and fully unfolded proteins can be predicted with high accuracy solely from their mass or chain length. However, this approach fails for intrinsically disordered proteins (IDPs) containing structural domains. We propose a rapid predictive methodology for estimating the diffusion coefficients of IDPs. The methodology uses accelerated conformational sampling based on self-avoiding random walks and includes hydrodynamic interactions between coarse-grained protein subunits, modeled using the generalized Rotne-Prager-Yamakawa approximation. To estimate the hydrodynamic radius, we rely on the minimum dissipation approximation recently introduced by Cichocki et al. Using a large set of experimentally measured hydrodynamic radii of IDPs over a wide range of chain lengths and domain contributions, we demonstrate that our predictions are more accurate than the Kirkwood approximation and phenomenological approaches. Our technique may prove to be valuable in predicting the hydrodynamic properties of both fully unstructured and multidomain disordered proteins.

DR-BERT: A protein language model to annotate disordered regions.

Despite their lack of a rigid structure, intrinsically disordered regions (IDRs) in proteins play important roles in cellular functions, including mediating protein-protein interactions. Therefore, it is important to computationally annotate IDRs with high accuracy. In this study, we present Disordered Region prediction using Bidirectional Encoder Representations from Transformers (DR-BERT), a compact protein language model. Unlike most popular tools, DR-BERT is pretrained on unannotated proteins and trained to predict IDRs without relying on explicit evolutionary or biophysical data. Despite this, DR-BERT demonstrates significant improvement over existing methods on the Critical Assessment of protein Intrinsic Disorder (CAID) evaluation datasetand outperforms competitors on two out of four test cases in the CAID 2 dataset, while maintaining competitiveness in the others. This performance is due to the information learned during pretraining and DR-BERT's ability to use contextual information.

Preserving condensate structure and composition by lowering sequence complexity

Biomolecular condensates play a vital role in organizing cellular chemistry. They selectively partition biomolecules, preventing unwanted cross talk and buffering against chemical noise. Intrinsically disordered proteins (IDPs) serve as primary components of these condensates due to their flexibility and ability to engage in multivalent interactions, leading to spontaneous aggregation. Theoretical advancements are critical at connecting IDP sequences with condensate emergent properties to establish the so-called molecular grammar. We proposed an extension to the stickers and spacers model, incorporating heterogeneous, nonspecific pairwise interactions between spacers alongside specific interactions among stickers. Our investigation revealed that although spacer interactions contribute to phase separation and co-condensation, their nonspecific nature leads to disorganized condensates. Specific sticker-sticker interactions drive the formation of condensates with well-defined networked structures and molecular composition. We discussed how evolutionary pressures might emerge to affect these interactions, leading to the prevalence of low-complexity domains in IDP sequences. These domains suppress spurious interactions and facilitate the formation of biologically meaningful condensates.

Taxonomy-specific assessment of intrinsic disorder predictions at residue and region levels in higher eukaryotes, protists, archaea, bacteria and viruses

Intrinsic disorder predictors were evaluated in several studies including the two large CAID experiments. However, these studies are biased towards eukaryotic proteins and focus primarily on the residue-level predictions. We provide first-of-its-kind assessment that comprehensively covers the taxonomy and evaluates predictions at the residue and disordered region levels. We curate a benchmark dataset that uniformly covers eukaryotic, archaeal, bacterial, and viral proteins. We find that predictive performance differs substantially across taxonomy, where viruses are predicted most accurately, followed by protists and higher eukaryotes, while bacterial and archaeal proteins suffer lower levels of accuracy. These trends are consistent across predictors. We also find that current tools, except for flDPnn, struggle with reproducing native distributions of the numbers and sizes of the disordered regions. Moreover, analysis of two variants of disorder predictions derived from the AlphaFold2 predicted structures reveals that they produce accurate residue-level propensities for archaea, bacteria and protists. However, they underperform for higher eukaryotes and generally struggle to accurately identify disordered regions. Our results motivate development of new predictors that target bacteria and archaea and which produce accurate results at both residue and region levels. We also stress the need to include the region-level assessments in future assessments.