Intrinsically Disordered Proteins Research Articles

Evolutional heterochromatin condensation delineates chromocenter formation and retrotransposon silencing in plants.

Heterochromatic condensates (chromocenters) are critical for maintaining the silencing of heterochromatin. It is therefore puzzling that the presence of chromocenters is variable across plant species. Here we reveal that variations in the plant heterochromatin protein ADCP1 confer a diversity in chromocenter formation via phase separation. ADCP1 physically interacts with the high mobility group protein HMGA to form a complex and mediates heterochromatin condensation by multivalent interactions. The loss of intrinsically disordered regions (IDRs) in ADCP1 homologues during evolution has led to the absence of prominent chromocenter formation in various plant species, and introduction of IDR-containing ADCP1 with HMGA promotes heterochromatin condensation and retrotransposon silencing. Moreover, plants in the Cucurbitaceae group have evolved an IDR-containing chimaera of ADCP1 and HMGA, which remarkably enables formation of chromocenters. Together, our work uncovers a coevolved mechanism of phase separation in packing heterochromatin and silencing retrotransposons.

Proteome-scale characterisation of motif-based interactome rewiring by disease mutations.

Whole genome and exome sequencing are reporting on hundreds of thousands of missense mutations. Taking a pan-disease approach, we explored how mutations in intrinsically disordered regions (IDRs) break or generate protein interactions mediated by short linear motifs. We created a peptide-phage display library tiling ~57,000 peptides from the IDRs of the human proteome overlapping 12,301 single nucleotide variants associated with diverse phenotypes including cancer, metabolic diseases and neurological diseases. By screening 80 human proteins, we identified 366 mutation-modulated interactions, with half of the mutations diminishing binding, and half enhancing binding or creating novel interaction interfaces. The effects of the mutations were confirmed by affinity measurements. In cellular assays, the effects of motif-disruptive mutations were validated, including loss of a nuclear localisation signal in the cell division control protein CDC45 by a mutation associated with Meier-Gorlin syndrome. The study provides insights into how disease-associated mutations may perturb and rewire the motif-based interactome.

An extended interaction site determines binding between AP180 and AP2 in clathrin mediated endocytosis

The early phases of clathrin mediated endocytosis are organized through a highly complex interaction network mediated by clathrin associated sorting proteins (CLASPs) that comprise long intrinsically disordered regions (IDRs). AP180 is a CLASP exclusively expressed in neurons and comprises a long IDR of around 600 residues, whose function remains partially elusive. Using NMR spectroscopy, we discovered an extended and strong interaction site within AP180 with the major adaptor protein AP2, and describe its binding dynamics at atomic resolution. We find that the 70 residue-long site determines the overall interaction between AP180 and AP2 in a dynamic equilibrium between its bound and unbound states, while weaker binding sites contribute to the overall affinity at much higher concentrations of AP2. Our data suggest that this particular interaction site might play a central role in recruitment of adaptors to the clathrin coated pit, whereas more transient and promiscuous interactions allow reshaping of the interaction network until cargo uptake inside a coated vesicle.

O -glycosylation of intrinsically disordered regions regulates homeostasis of membrane proteins in streptococci.

Proteins harboring intrinsically disordered regions (IDRs) lacking stable secondary or tertiary structures are abundant across the three domains of life. These regions have not been systematically studied in prokaryotes. Our genome-wide analysis identifies extracytoplasmic serine/threonine-rich IDRs in several biologically important membrane proteins in streptococci. We demonstrate that these IDRs are O -glycosylated with glucose by glycosyltransferases GtrB and PgtC2 in Streptococcus pyogenes and Streptococcus pneumoniae , and with N-acetylgalactosamine by a Pgf-dependent mechanism in Streptococcus mutans . Absence of glycosylation leads to a defect in biofilm formation under ethanol-stressed conditions in S. mutans . We link this phenotype to the C-terminal IDR of a post-translocation secretion chaperone PrsA. O -glycosylation of the IDR protects this region from proteolytic degradation. The IDR length attenuates the efficiency of glycosylation and, consequently, the expression level of PrsA. Taken together, our data reveal that O -glycosylation of IDRs functions as a dynamic switch of protein homeostasis in streptococci.

Coarse-Grained Modeling of Liquid-Liquid Phase Separation in Cells: Challenges and Opportunities.

Liquid-liquid phase separation (LLPS) within cells gives rise to membraneless organelles, which play pivotal roles in numerous cellular functions. A comprehensive understanding of the functional aspects of intrinsically disordered protein (IDP) condensates necessitates elucidating their inherent structures and establishing correlations with biological functions. Coarse-grained (CG) molecular dynamics (MD) simulations present a promising avenue for gaining insights into LLPS mechanisms of biomacromolecules. Essential to this endeavor is the development of tailored CG force fields for MD simulations, incorporating the full spectrum of biomolecules involved in the formation of condensates and accounting for real-time biochemical reactions coupled to the LLPS. Moreover, developing accurate theoretical frameworks and establishing links between condensate structure and its function are imperative for a thorough comprehension of LLPS of biological systems.

Structural basis of the human transcriptional Mediator complex modulated by its dissociable Kinase module.

The eukaryotic Mediator, comprising a large Core (cMED) and a dissociable CDK8 kinase module (CKM), regulates RNA Polymerase II (Pol II)-dependent transcription. cMED recruits Pol II and promotes pre-initiation complex (PIC) formation in a manner inhibited by the CKM, which is also implicated in post-initiation control of gene expression. Herein we report cryo-electron microscopy structures of the human complete Mediator and its CKM, which explains the basis for CKM inhibition of cMED-activated transcription. The CKM binds to cMED through an intrinsically disordered region (IDR) in MED13 and HEAT repeats in MED12. The CKM inhibits transcription by allocating its MED13 IDR to occlude binding of Pol II and MED26 to cMED and further obstructing cMED-PIC assembly through steric hindrance with TFIIH and the +1 nucleosome. Notably, MED12 binds to the cMED Hook, positioning CDK8 downstream of the transcription start site, which sheds new light on its stimulatory function in post-initiation events.

A curated rotamer library for common post-translational modifications of proteins.

Sidechain rotamer libraries of the common amino acids of a protein are useful for folded protein structure determination and for generating ensembles of intrinsically disordered proteins (IDPs). However, much of protein function is modulated beyond the translated sequence through the introduction of post-translational modifications (PTMs). In this work, we have provided a curated set of side chain rotamers for the most common PTMs derived from the RCSB PDB database, including phosphorylated, methylated, and acetylated sidechains. Our rotamer libraries improve upon existing methods such as SIDEpro, Rosetta, and AlphaFold3 in predicting the experimental structures for PTMs in folded proteins. In addition, we showcase our PTM libraries in full use by generating ensembles with the Monte Carlo Side Chain Entropy (MCSCE) for folded proteins, and combining MCSCE with the Local Disordered Region Sampling algorithms within IDPConformerGenerator for proteins with intrinsically disordered regions. The codes for dihedral angle computations and library creation are available at https://github.com/THGLab/ptm_sc.git.

Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning.

Proteins are inherently dynamic, and their conformational ensembles are functionally important in biology. Large-scale motions may govern protein structure-function relationship, and numerous transient but stable conformations of intrinsically disordered proteins (IDPs) can play a crucial role in biological function. Investigating conformational ensembles to understand regulations and disease-related aggregations of IDPs is challenging both experimentally and computationally. In this paper we first introduced an unsupervised deep learning-based model, termed Internal Coordinate Net (ICoN), which learns the physical principles of conformational changes from molecular dynamics (MD) simulation data. Second, we selected interpolating data points in the learned latent space that rapidly identify novel synthetic conformations with sophisticated and large-scale sidechains and backbone arrangements. Third, with the highly dynamic amyloid-β 1-42 (Aβ42) monomer, our deep learning model provided a comprehensive sampling of Aβ42's conformational landscape. Analysis of these synthetic conformations revealed conformational clusters that can be used to rationalize experimental findings. Additionally, the method can identify novel conformations with important interactions in atomistic details that are not included in the training data. New synthetic conformations showed distinct sidechain rearrangements that are probed by our EPR and amino acid substitution studies. This approach is highly transferable and can be used for any available data for training. The work also demonstrated the ability for deep learning to utilize learned natural atomistic motions in protein conformation sampling.

Modulation of biophysical properties of nucleocapsid protein in the mutant spectrum of SARS-CoV-2.

Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we examine the impact of mutations across the spectrum of viable amino acid sequences on the biophysical phenotypes of the highly expressed and multifunctional nucleocapsid protein. We find variation in the physicochemical parameters of its extended intrinsically disordered regions (IDRs) sufficient to allow local plasticity, but also observe functional constraints that similarly occur in related coronaviruses. In biophysical experiments with several N-protein species carrying mutations associated with major variants, we find that point mutations in the IDRs can have nonlocal impact and modulate thermodynamic stability, secondary structure, protein oligomeric state, particle formation, and liquid-liquid phase separation. In the Omicron variant, distant mutations in different IDRs have compensatory effects in shifting a delicate balance of interactions controlling protein assembly properties, and include the creation of a new protein-protein interaction interface in the N-terminal IDR through the defining P13L mutation. A picture emerges where genetic diversity is accompanied by significant variation in biophysical characteristics of functional N-protein species, in particular in the IDRs.

Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning.

Proteins are inherently dynamic, and their conformational ensembles are functionally important in biology. Large-scale motions may govern protein structure-function relationship, and numerous transient but stable conformations of intrinsically disordered proteins (IDPs) can play a crucial role in biological function. Investigating conformational ensembles to understand regulations and disease-related aggregations of IDPs is challenging both experimentally and computationally. In this paper first an unsupervised deep learning-based model, termed Internal Coordinate Net (ICoN), is developed that learns the physical principles of conformational changes from molecular dynamics (MD) simulation data. Second, interpolating data points in the learned latent space are selected that rapidly identify novel synthetic conformations with sophisticated and large-scale sidechains and backbone arrangements. Third, with the highly dynamic amyloid-β1-42 (Aβ42) monomer, our deep learning model provided a comprehensive sampling of Aβ42's conformational landscape. Analysis of these synthetic conformations revealed conformational clusters that can be used to rationalize experimental findings. Additionally, the method can identify novel conformations with important interactions in atomistic details that are not included in the training data. New synthetic conformations showed distinct sidechain rearrangements that are probed by our EPR and amino acid substitution studies. The proposed approach is highly transferable and can be used for any available data for training. The work also demonstrated the ability for deep learning to utilize learned natural atomistic motions in protein conformation sampling.

Refining the pool of RNA-binding domains advances the classification and prediction of RNA-binding proteins.

From transcription to decay, RNA-binding proteins (RBPs) influence RNA metabolism. Using the RBP2GO database that combines proteome-wide RBP screens from 13 species, we investigated the RNA-binding features of 176896 proteins. By compiling published lists of RNA-binding domains (RBDs) and RNA-related protein family (Rfam) IDs with lists from the InterPro database, we analyzed the distribution of the RBDs and Rfam IDs in RBPs and non-RBPs to select RBDs and Rfam IDs that were enriched in RBPs. We also explored proteins for their content in intrinsically disordered regions (IDRs) and low complexity regions (LCRs). We found a strong positive correlation between IDRs and RBDs and a co-occurrence of specific LCRs. Our bioinformatic analysis indicated that RBDs/Rfam IDs were strong indicators of the RNA-binding potential of proteins and helped predicting new RBP candidates, especially in less investigated species. By further analyzing RBPs without RBD, we predicted new RBDs that were validated by RNA-bound peptides. Finally, we created the RBP2GO composite score by combining the RBP2GO score with new quality factors linked to RBDs and Rfam IDs. Based on the RBP2GO composite score, we compiled a list of 2018 high-confidence human RBPs. The knowledge collected here was integrated into the RBP2GO database at https://RBP2GO-2-Beta.dkfz.de.

A Practical Guide to All-Atom and Coarse-Grained Molecular Dynamics Simulations Using Amber and Gromacs: A Case Study of Disulfide-Bond Impact on the Intrinsically Disordered Amyloid Beta.

Intrinsically disordered proteins (IDPs) pose challenges to conventional experimental techniques due to their large-scale conformational fluctuations and transient structural elements. This work presents computational methods for studying IDPs at various resolutions using the Amber and Gromacs packages with both all-atom (Amber ff19SB with the OPC water model) and coarse-grained (Martini 3 and SIRAH) approaches. The effectiveness of these methodologies is demonstrated by examining the monomeric form of amyloid-β (Aβ42), an IDP, with and without disulfide bonds at different resolutions. Our results clearly show that the addition of a disulfide bond decreases the β-content of Aβ42; however, it increases the tendency of the monomeric Aβ42 to form fibril-like conformations, explaining the various aggregation rates observed in experiments. Moreover, analysis of the monomeric Aβ42 compactness, secondary structure content, and comparison between calculated and experimental chemical shifts demonstrates that all three methods provide a reasonable choice to study IDPs; however, coarse-grained approaches may lack some atomistic details, such as secondary structure recognition, due to the simplifications used. In general, this study not only explains the role of disulfide bonds in Aβ42 but also provides a step-by-step protocol for setting up, conducting, and analyzing molecular dynamics (MD) simulations, which is adaptable for studying other biomacromolecules, including folded and disordered proteins and peptides.

Intrinsically disordered regions regulate RhlE RNA helicase functions in bacteria.

RNA helicases-central enzymes in RNA metabolism-often feature intrinsically disordered regions (IDRs) that enable phase separation and complex molecular interactions. In the bacterial pathogen Pseudomonas aeruginosa, the non-redundant RhlE1 and RhlE2 RNA helicases share a conserved REC catalytic core but differ in C-terminal IDRs. Here, we show how the IDR diversity defines RhlE RNA helicase specificity of function. Both IDRs facilitate RNA binding and phase separation, localizing proteins in cytoplasmic clusters. However, RhlE2 IDR is more efficient in enhancing REC core RNA unwinding, exhibits a greater tendency for phase separation, and interacts with the RNase E endonuclease, a crucial player in mRNA degradation. Swapping IDRs results in chimeric proteins that are biochemically active but functionally distinct as compared to their native counterparts. The RECRhlE1-IDRRhlE2 chimera improves cold growth of a rhlE1 mutant, gains interaction with RNase E and affects a subset of both RhlE1 and RhlE2 RNA targets. The RECRhlE2-IDRRhlE1 chimera instead hampers bacterial growth at low temperatures in the absence of RhlE1, with its detrimental effect linked to aberrant RNA droplets. By showing that IDRs modulate both protein core activities and subcellular localization, our study defines the impact of IDR diversity on the functional differentiation of RNA helicases.

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.