Intrinsically Disordered Proteins Research Articles

Rapid Interpretation of Protein Backbone Rotation Dynamics Directly from Spin Relaxation Data.

Besides their structure, dynamics is pivotal for protein functions, particularly for intrinsically disordered proteins (IDPs) that do not fold into a fixed 3D structure. However, the detection of protein dynamics is difficult for IDPs and other disordered biomolecules. NMR spin relaxation rates are sensitive to the rapid rotations of chemical bonds, but their interpretation is arduous for IDPs or molecular assemblies with a complex dynamic landscape. Here we demonstrate numerically that the dynamics of a wide range of proteins, from short peptides to partially disordered proteins and peptides in micelles, can be characterized by calculating the total effective correlation times of protein backbone N-H bond rotations, τeff, from experimentally measured transverse 15N spin relaxation rates, R2, using a linear relation. Our results enable the determination of magnetic-field-independent and intuitively understandable parameters describing protein dynamics at different regions of the sequence directly from experiments. A practical advance of the approach is demonstrated by analyzing partially disordered proteins in which rotations of disordered regions occur with timescales of 1-2 ns, independent of their size, suggesting that rotations of disordered and folded regions are uncoupled in these proteins.

Transcription factor condensates, 3D clustering, and gene expression enhancement of the MET regulon.

Some transcription factors (TFs) can form liquid-liquid phase separated (LLPS) condensates. However, the functions of these TF condensates in 3-Dimentional (3D) genome organization and gene regulation remain elusive. In response to methionine (met) starvation, budding yeast TF Met4 and a few co-activators, including Met32, induce a set of genes involved in met biosynthesis. Here, we show that the endogenous Met4 and Met32 form co-localized puncta-like structures in yeast nuclei upon met depletion. Recombinant Met4 and Met32 form mixed droplets with LLPS properties in vitro. In relation to chromatin, Met4 puncta co-localize with target genes, and at least a subset of these target genes is clustered in 3D in a Met4-dependent manner. A MET3pr-GFP reporter inserted near several native Met4-binding sites becomes co-localized with Met4 puncta and displays enhanced transcriptional activity. A Met4 variant with a partial truncation of an intrinsically disordered region (IDR) shows less puncta formation, and this mutant selectively reduces the reporter activity near Met4-binding sites to the basal level. Overall, these results support a model where Met4 and co-activators form condensates to bring multiple target genes into a vicinity with higher local TF concentrations, which facilitates a strong response to methionine depletion.

Transcription factor condensates, 3D clustering, and gene expression enhancement of the MET regulon

Some transcription factors (TFs) can form liquid–liquid phase separated (LLPS) condensates. However, the functions of these TF condensates in 3-Dimentional (3D) genome organization and gene regulation remain elusive. In response to methionine (met) starvation, budding yeast TF Met4 and a few co-activators, including Met32, induce a set of genes involved in met biosynthesis. Here, we show that the endogenous Met4 and Met32 form co-localized puncta-like structures in yeast nuclei upon met depletion. Recombinant Met4 and Met32 form mixed droplets with LLPS properties in vitro. In relation to chromatin, Met4 puncta co-localize with target genes, and at least a subset of these target genes is clustered in 3D in a Met4-dependent manner. A MET3pr-GFP reporter inserted near several native Met4-binding sites becomes co-localized with Met4 puncta and displays enhanced transcriptional activity. A Met4 variant with a partial truncation of an intrinsically disordered region (IDR) shows less puncta formation, and this mutant selectively reduces the reporter activity near Met4-binding sites to the basal level. Overall, these results support a model where Met4 and co-activators form condensates to bring multiple target genes into a vicinity with higher local TF concentrations, which facilitates a strong response to methionine depletion.

Decoding Missense Variants by Incorporating Phase Separation via Machine Learning

Computational models have made significant progress in predicting the effect of protein variants. However, deciphering numerous variants of uncertain significance (VUS) located within intrinsically disordered regions (IDRs) remains challenging. To address this issue, we introduce phase separation, which is tightly linked to IDRs, into the investigation of missense variants. Phase separation is vital for multiple physiological processes. By leveraging missense variants that alter phase separation propensity, we develop a machine learning approach named PSMutPred to predict the impact of missense mutations on phase separation. PSMutPred demonstrates robust performance in predicting missense variants that affect natural phase separation. In vitro experiments further underscore its validity. By applying PSMutPred on over 522,000 ClinVar missense variants, it significantly contributes to decoding the pathogenesis of disease variants, especially those in IDRs. Our work provides insights into the understanding of a vast number of VUSs in IDRs, expediting clinical interpretation and diagnosis.

Inhibitor Development for α-Synuclein Fibril's Disordered Region to Alleviate Parkinson's Disease Pathology.

The amyloid fibrils of α-synuclein (α-syn) are crucial in the pathology of Parkinson's disease (PD), with the intrinsically disordered region (IDR) of its C-terminal playing a key role in interacting with receptors like LAG3 and RAGE, facilitating pathological neuronal spread and inflammation. In this study, we identified Givinostat (GS) as an effective inhibitor that disrupts the interaction of α-syn fibrils with receptors such as LAG3 and RAGE through high-throughput screening. By exploring the structure-activity relationship and optimizing GS, we developed several lead compounds, including GSD-16-24. Utilizing solution-state and solid-state NMR, along with cryo-EM techniques, we demonstrated that GSD-16-24 binds directly to the C-terminal IDR of α-syn monomer and fibril, preventing the fibril from binding to the receptors. Furthermore, GSD-16-24 significantly inhibits the association of α-syn fibrils with membrane receptors, thereby reducing neuronal propagation and pro-inflammatory effects of α-syn fibrils. Our findings introduce a novel approach to mitigate the pathological effects of α-syn fibrils by targeting their IDR with small molecules, offering potential leads for the development of clinical drugs to treat PD.

An integrative characterization of proline cis and trans conformers in a disordered peptide

Intrinsically disordered proteins (IDPs) often contain proline residues that undergo cis/trans isomerization. While molecular dynamics (MD) simulations have the potential to fully characterize the proline cis and trans subensembles, they are limited by the slow timescales of isomerization and force field inaccuracies. NMR spectroscopy can report on ensemble-averaged observables for both the cis-proline and trans-proline states, but a full atomistic characterization of these conformers is challenging. Given the importance of proline cis/trans isomerization for influencing the conformational sampling of disordered proteins, we employed a combination of all-atom MD simulations with enhanced sampling (metadynamics), NMR, and small-angle x-ray scattering (SAXS) to characterize the two subensembles of the ORF6 C-terminal region (ORF6CTR) from SARS-CoV-2 corresponding to the proline-57 (P57) cis and trans states. We performed MD simulations in three distinct force fields: AMBER03ws, AMBER99SB-disp, and CHARMM36m, which are all optimized for disordered proteins. Each simulation was run for an accumulated time of 180–220 μs until convergence was reached, as assessed by blocking analysis. A good agreement between the cis-P57 populations predicted from metadynamic simulations in AMBER03ws was observed with populations obtained from experimental NMR data. Moreover, we observed good agreement between the radius of gyration predicted from the metadynamic simulations in AMBER03ws and that measured using SAXS. Our findings suggest that both the cis-P57 and trans-P57 conformations of ORF6CTR are extremely dynamic and that interdisciplinary approaches combining both multiscale computations and experiments offer avenues to explore highly dynamic states that cannot be reliably characterized by either approach in isolation.

A Comparative Study of Large Language Models in Explaining Intrinsically Disordered Proteins

BACKGROUND: Artificial Intelligence (AI) models have shown potential in various educational contexts. However, their utility in explaining complex biological phenomena, such as Intrinsically Disordered Proteins (IDPs), requires further exploration. This study empirically evaluated the performance of various Large Language Models (LLMs) in the educational domain of IDPs. METHODS: Four LLMs, GPT-3.5, GPT-4, GPT-4 with Browsing, and Google Bard (PaLM 2), were assessed using a set of IDP-related questions. An expert evaluated their responses across five categories: accuracy, relevance, depth of understanding, clarity, and overall quality. Descriptive statistics, ANOVA, and Tukey's honesty significant difference tests were utilized for analysis. RESULTS: The GPT-4 model consistently outperformed the others across all evaluation categories. Although GPT-4 and GPT-3.5 were not statistically significantly different in performance (p>0.05), GPT-4 was preferred as the best response in 13 out of 15 instances. The AI models with browsing capabilities, GPT-4 with Browsing and Google Bard (PaLM 2) displayed lower performance metrics across the board with statistically significant differences (p<0.0001). CONCLUSION: Our findings underscore the potential of AI models, particularly LLMs such as GPT-4, in enhancing scientific education, especially in complex domains such as IDPs. Continued innovation and collaboration among AI developers, educators, and researchers are essential to fully harness the potential of AI for enriching scientific education.

Structural basis of the human transcriptional Mediator regulated by its dissociable kinase module

The eukaryotic transcriptional Mediator comprises a large core (cMED) and a dissociable CDK8 kinase module (CKM). cMED recruits RNA polymerase II (RNA Pol II) and promotes pre-initiation complex formation in a manner repressed by the CKM through mechanisms presently unknown. Herein, we report cryoelectron microscopy structures of the complete human Mediator and its CKM. The CKM binds to multiple regions on cMED through both MED12 and MED13, including a large intrinsically disordered region (IDR) in the latter. MED12 and MED13 together anchor the CKM to the cMED hook, positioning CDK8 downstream and proximal to the transcription start site. Notably, the MED13 IDR obstructs the recruitment of RNA Pol II/MED26 onto cMED by direct occlusion of their respective binding sites, leading to functional repression of cMED-dependent transcription. Combined with biochemical and functional analyses, these structures provide a conserved mechanistic framework to explain the basis for CKM-mediated repression of cMED function.

Prion-like Proteins in Plants: Key Regulators of Development and Environmental Adaptation via Phase Separation.

Prion-like domains (PrLDs), a unique type of low-complexity domain (LCD) or intrinsically disordered region (IDR), have been shown to mediate protein liquid-liquid phase separation (LLPS). Recent research has increasingly focused on how prion-like proteins (PrLPs) regulate plant growth, development, and stress responses. This review provides a comprehensive overview of plant PrLPs. We analyze the structural features of PrLPs and the mechanisms by which PrLPs undergo LLPS. Through gene ontology (GO) analysis, we highlight the diverse molecular functions of PrLPs and explore how PrLPs influence plant development and stress responses via phase separation. Finally, we address unresolved questions about PrLP regulatory mechanisms, offering prospects for future research.

Integrative Modeling of Protein-Polypeptide Complexes by Bayesian Model Selection using AlphaFold and NMR Chemical Shift Perturbation Data.

Protein-polypeptide interactions, including those involving intrinsically-disordered peptides and intrinsically-disordered regions of protein binding partners, are crucial for many biological functions. However, experimental structure determination of protein-peptide complexes can be challenging. Computational methods, while promising, generally require experimental data for validation and refinement. Here we present CSP_Rank, an integrated modeling approach to determine the structures of protein-peptide complexes. This method combines AlphaFold2 (AF2) enhanced sampling methods with a Bayesian conformational selection process based on experimental Nuclear Magnetic Resonance (NMR) Chemical Shift Perturbation (CSP) data and AF2 confidence metrics. Using a curated dataset of 108 protein-peptide complexes from the Biological Magnetic Resonance Data Bank (BMRB), we observe that while AF2 typically yields models with excellent consistency with experimental CSP data, applying enhanced sampling followed by data-guided conformational selection routinely results in ensembles of structures with improved agreement with NMR observables. For two systems, we cross-validate the CSP-selected models using independently acquired nuclear Overhauser effect (NOE) NMR data and demonstrate how CSP and NMR can be combined using our Bayesian framework for model selection. CSP_Rank is a novel method for integrative modeling of protein-peptide complexes and has broad implications for studies of protein-peptide interactions and aiding in understanding their biological functions.

Mapping Full Conformational Transition Dynamics of Intrinsically Disordered Proteins Using a Single-Molecule Nanocircuit.

Intrinsically disordered proteins (IDPs) are emerging therapeutic targets for human diseases. However, probing their transient conformations remains challenging because of conformational heterogeneity. To address this problem, we developed a biosensor using a point-functionalized silicon nanowire (SiNW) that allows for real-time sampling of single-molecule dynamics. A single IDP, N-terminal transactivation domain of tumor suppressor protein p53 (p53TAD1), was covalently conjugated to the SiNW through chemical engineering, and its conformational transition dynamics was characterized as current fluctuations. Furthermore, when a globular protein ligand in solution bound to the targeted p53TAD1, protein-protein interactions could be unambiguously distinguished from large-amplitude current signals. These proof-of-concept experiments enable semiquantitative, realistic characterization of the structural properties of IDPs and constitute the basis for developing a valuable tool for protein profiling and drug discovery in the future.

Replication licensing regulated by a short linear motif within an intrinsically disordered region of origin recognition complex

In eukaryotes, the origin recognition complex (ORC) faciliates the assembly of pre-replicative complex (pre-RC) at origin DNA for replication licensing. Here we show that the N-terminal intrinsically disordered region (IDR) of the yeast Orc2 subunit is crucial for this process. Removing a segment (residues 176-200) from Orc2-IDR or mutating a key isoleucine (194) significantly inhibits replication initiation across the genome. These Orc2-IDR mutants are capable of assembling the ORC-Cdc6-Cdt1-Mcm2-7 intermediate, which exhibits impaired ATP hydrolysis and fails to be convered into the subsequent Mcm2-7-ORC complex and pre-RC. These defects can be partially rescued by the Orc2-IDR peptide. Moreover, the phosphorylation of this Orc2-IDR region by S cyclin-dependent kinase blocks its binding to Mcm2-7 complex, causing a defective pre-RC assembly. Our findings provide important insights into the multifaceted roles of ORC in supporting origin licensing during the G1 phase and its regulation to restrict origin firing within the S phase.

ECT2 peptide sequences outside the YTH domain regulate its m6A-RNA binding

ABSTRACT The m6A epitranscriptomic mark is the most abundant and widespread internal RNA chemical modification, which through the control of RNA acts as an important factor of eukaryote reproduction, growth, morphogenesis and stress response. The main m6A readers constitute a super family of proteins with hundreds of members that share a so-called YTH RNA binding domain. The majority of YTH proteins carry no obvious additional domain except for an Intrinsically Disordered Region (IDR). In Arabidopsis thaliana IDRs are important for the functional specialization among the different YTH proteins, known as Evolutionarily Conserved C-Terminal region, ECT 1 to 12. Here by studying the ECT2 protein and using an in vitro biochemical characterization, we show that full-length ECT2 and its YTH domain alone have a distinct ability to bind m6A, conversely to previously characterized YTH readers. We identify peptide regions outside of ECT2 YTH domain, in the N-terminal IDR, that regulate its binding to m6A-methylated RNA. Furthermore, we show that the selectivity of ECT2 binding for m6A is enhanced by a high uridine content within its neighbouring sequence, where ECT2 N-terminal IDR is believed to contact the target RNA in vivo. Finally, we also identify small structural elements, located next to ECT2 YTH domain and conserved in a large set of YTH proteins, that enhance its binding to m6A-methylated RNA. We propose from these findings that some of these regulatory regions are not limited to ECT2 or YTH readers of flowering plants but may be widespread among eukaryotic YTH readers.

Multivalency drives interactions of alpha-synuclein fibrils with tau.

Age-related neurodegenerative disorders like Alzheimer's disease (AD) and Parkinson's disease (PD) are characterized by deposits of protein aggregates, or amyloid, in various regions of the brain. Historically, aggregation of a single protein was observed to be correlated with these different pathologies: tau in AD and α-synuclein (αS) in PD. However, there is increasing evidence that the pathologies of these two diseases overlap, and the individual proteins may even promote each other's aggregation. Both tau and αS are intrinsically disordered proteins (IDPs), lacking stable secondary and tertiary structure under physiological conditions. In this study we used a combination of biochemical and biophysical techniques to interrogate the interaction of tau with both soluble and fibrillar αS. Fluorescence correlation spectroscopy (FCS) was used to assess the interactions of specific domains of fluorescently labeled tau with full length and C-terminally truncated αS in both monomer and fibrillar forms. We found that full-length tau as well as individual tau domains interact with monomer αS weakly, but this interaction is much more pronounced with αS aggregates. αS aggregates also mildly slow the rate of tau aggregation, although not the final degree of aggregation. Our findings suggest that co-occurrence of tau and αS in disease are more likely to occur through monomer-fiber binding interactions, rather than monomer-monomer or co-aggregation.

A land plant phylogenetic framework for GLABROUS INFLORESCENCE STEMS (GIS), SUPERMAN, JAGGED and allies plus their TOPLESS co-repressor

Members of the plant specific family of C1-1i zincfinger transcriptionfactors (ZF-TFs), such as SUPERMAN, JAGGED, KNUCKLES or GIS,regulatediversedevelopmental processes including sexual reproduction. C1-1is consist of one zinc-finger and one to two EAR domains, connected by large intrinsically disordered regions (IDR). While the role of C1-i1 ZF-TFs in development processes is well known for some genes in Arabidopsis, rice or tomatoa comprehensive and broadphylogenetic background is lacking, yet knowledge of orthology is a requirement for a better understanding of C1-1i-Zf-TFs diverse roles in plants. Here, we provide a fine-grained and land plant wide classification of C1-1i sub-families and their known co-repressors TOPLESS and TOPLESS RELATED. Our work combines the identification of orthologous groups with Maximum-Likelihood phylogeny reconstructions and digital gene expression analyses mining high quality land plant genomes and transcriptomes to generate a comprehensive framework of C1-1i ZF-TF evolution. We show that C1-1i’s are low to moderate copy genesand that orthologous genesonly partiallyhaveconserved sub-family and life cycle stage dependent expression pattern across land plants while others are highly diverged. Our workprovides the phylogenetic framework for C1-1i ZF-TFs, s and strengthen C1-1 ZF-TFs as a potential model for IDR-research in plants.

A Few Charged Residues in Galectin-3's Folded and Disordered Regions Regulate Phase Separation.

Proteins with intrinsically disordered regions (IDRs) often undergo phase separation to control their functions spatiotemporally. Changing the pH alters the protonation levels of charged sidechains, which in turn affects the attractive or repulsive force for phase separation. In a cell, the rupture of membrane-bound compartments, such as lysosomes, creates an abrupt change in pH. However, how proteins' phase separation reacts to different pH environments remains largely unexplored. Here, using extensive mutagenesis, NMR spectroscopy, and biophysical techniques, it is shown that the assembly of galectin-3, a widely studied lysosomal damage marker, is driven by cation-π interactions between positively charged residues in its folded domain with aromatic residues in the IDR in addition to π-π interaction between IDRs. It is also found that the sole two negatively charged residues in its IDR sense pH changes for tuning the condensation tendency. Also, these two residues may prevent this prion-like IDR domain from forming rapid and extensive aggregates. These results demonstrate how cation-π, π-π, and electrostatic interactions can regulate protein condensation between disordered and structured domains and highlight the importance of sparse negatively charged residues in prion-like IDRs.

A pH-Dependent Coarse-Grained Model for Disordered Proteins: Histidine Interactions Modulate Conformational Ensembles.

Histidine (His) presents a unique challenge for modeling disordered protein conformations, as it is versatile and occurs in both the neutral (His0) and positively charged (His+) states. These His charge states, which are enabled by its imidazole side chain, influence the electrostatic and short-range interactions of His residues, which potentially engage in cation-π, π-π, and charge-charge interactions. Existing coarse-grained (CG) models often simplify His representation by assigning it an average charge, thereby neglecting these potential short-range interactions. To address this gap, we developed a model for intrinsically disordered proteins (IDPs) that accounts for the properties of histidine (H). The resulting IDPH model is a 21-amino acid CG model incorporating both His charge states. We show that interactions involving previously neglected His0 are critical for accurate modeling at high pH, where they significantly influence the compaction of His-rich IDPs such as Histatin-5 and CPEB4. These interactions contribute to structural stabilizations primarily via His0-His0 and His0-Arg interactions, which are overlooked in models focusing solely on the charged His+ state.

Balancing thermodynamic stability, dynamics, and kinetics in phase separation of intrinsically disordered proteins.

Intrinsically disordered proteins (IDPs) are prevalent participants in liquid-liquid phase separation due to their inherent potential for promoting multivalent binding. Understanding the underlying mechanisms of phase separation is challenging, as phase separation is a complex process, involving numerous molecules and various types of interactions. Here, we used a simplified coarse-grained model of IDPs to investigate the thermodynamic stability of the dense phase, conformational properties of IDPs, chain dynamics, and kinetic rates of forming condensates. We focused on the IDP system, in which the oppositely charged IDPs are maximally segregated, inherently possessing a high propensity for phase separation. By varying interaction strengths, salt concentrations, and temperatures, we observed that IDPs in the dense phase exhibited highly conserved conformational characteristics, which are more extended than those in the dilute phase. Although the chain motions and global conformational dynamics of IDPs in the condensates are slow due to the high viscosity, local chain flexibility at the short timescales is largely preserved with respect to that at the free state. Strikingly, we observed a non-monotonic relationship between interaction strengths and kinetic rates for forming condensates. As strong interactions of IDPs result in high stable condensates, our results suggest that the thermodynamics and kinetics of phase separation are decoupled and optimized by the speed-stability balance through underlying molecular interactions. Our findings contribute to the molecular-level understanding of phase separation and offer valuable insights into the developments of engineering strategies for precise regulation of biomolecular condensates.

Positive Selection Drives the Evolution of the Structural Maintenance of Chromosomes (SMC) Complexes.

Structural Maintenance of Chromosomes (SMC) complexes are an evolutionary conserved protein family. In most eukaryotes, three SMC complexes have been characterized, as follows: cohesin, condensin, and SMC5/6 complexes. These complexes are involved in a plethora of functions, and defects in SMC genes can lead to an increased risk of chromosomal abnormalities, infertility, and cancer. To investigate the evolution of SMC complex genes in mammals, we analyzed their selective patterns in an extended phylogeny. Signals of positive selection were identified for condensin NCAPG, for two SMC5/6 complex genes (SMC5 and NSMCE4A), and for all cohesin genes with almost exclusive meiotic expression (RAD21L1, REC8, SMC1B, and STAG3). For the latter, evolutionary rates correlate with expression during female meiosis, and most positively selected sites fall in intrinsically disordered regions (IDRs). Our results support growing evidence that IDRs are fast evolving, and that they most likely contribute to adaptation through modulation of phase separation. We suggest that the natural selection signals identified in SMC complexes may be the result of different selective pressures: a host-pathogen arms race in the condensin and SMC5/6 complexes, and an intragenomic conflict for meiotic cohesin genes that is similar to that described for centromeres and telomeres.

Design of intrinsically disordered protein variants with diverse structural properties.

Intrinsically disordered proteins (IDPs) perform a broad range of functions in biology, suggesting that the ability to design IDPs could help expand the repertoire of proteins with novel functions. Computational design of IDPs with specific conformational properties has, however, been difficult because of their substantial dynamics and structural complexity. We describe a general algorithm for designing IDPs with specific structural properties. We demonstrate the power of the algorithm by generating variants of naturally occurring IDPs that differ in compaction, long-range contacts, and propensity to phase separate. We experimentally tested and validated our designs and analyzed the sequence features that determine conformations. We show how our results are captured by a machine learning model, enabling us to speed up the algorithm. Our work expands the toolbox for computational protein design and will facilitate the design of proteins whose functions exploit the many properties afforded by protein disorder.