PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins.

The Protein Ensemble Database (PED) (URL: https://proteinensemble.org) is the primary resource for depositing structural ensembles of intrinsically disordered proteins. This updated version of PED reflects advancements in the field, denoting a continual expansion with a total of 461 entries and 538 ensembles, including those generated without explicit experimental data through novel machine learning (ML) techniques. With this significant increment in the number of ensembles, a few yet-unprecedented new entries entered the database, including those also determined or refined by electron paramagnetic resonance or circular dichroism data. In addition, PED was enriched with several new features, including a novel deposition service, improved user interface, new database cross-referencing options and integration with the 3D-Beacons network-all representing efforts to improve the FAIRness of the database. Foreseeably, PED will keep growing in size and expanding with new types of ensembles generated by accurate and fast ML-based generative models and coarse-grained simulations. Therefore, among future efforts, priority will be given to further develop the database to be compatible with ensembles modeled at a coarse-grained level.

ELM-the Eukaryotic Linear Motif resource-2024 update.

Short Linear Motifs (SLiMs) are the smallest structural and functional components of modular eukaryotic proteins. They are also the most abundant, especially when considering post-translational modifications. As well as being found throughout the cell as part of regulatory processes, SLiMs are extensively mimicked by intracellular pathogens. At the heart of the Eukaryotic Linear Motif (ELM) Resource is a representative (not comprehensive) database. The ELM entries are created by a growing community of skilled annotators and provide an introduction to linear motif functionality for biomedical researchers. The 2024 ELM update includes 346 novel motif instances in areas ranging from innate immunity to both protein and RNA degradation systems. In total, 39 classes of newly annotated motifs have been added, and another 17 existing entries have been updated in the database. The 2024 ELM release now includes 356 motif classes incorporating 4283 individual motif instances manually curated from 4274 scientific publications and including >700 links to experimentally determined 3D structures. In a recent development, the InterPro protein module resource now also includes ELM data. ELM is available at: http://elm.eu.org.

YbiB: a novel interactor of the GTPase ObgE.

Obg is a widely conserved and essential GTPase in bacteria, which plays a central role in a large range of important cellular processes, such as ribosome biogenesis, DNA replication, cell division and bacterial persistence. Nevertheless, the exact function of Obg in these processes and the interactions it makes within the associated pathways remain largely unknown. Here, we identify the DNA-binding TrpD2 protein YbiB as an interactor of the Escherichia coli Obg (ObgE). We show that both proteins interact with high affinity in a peculiar biphasic fashion, and pinpoint the intrinsically disordered and highly negatively charged C-terminal domain of ObgE as a main driver for this interaction. Molecular docking and X-ray crystallography, together with site-directed mutagenesis, are used to map the binding site of this ObgE C-terminal domain within a highly positively charged groove on the surface of the YbiB homodimer. Correspondingly, ObgE efficiently inhibits the binding of DNA to YbiB, indicating that ObgE competes with DNA for binding in the positive clefts of YbiB. This study thus forms an important step for the further elucidation of the interactome and cellular role of the essential bacterial protein Obg.

The Eukaryotic Linear Motif resource: 2022 release.

Almost twenty years after its initial release, the Eukaryotic Linear Motif (ELM) resource remains an invaluable source of information for the study of motif-mediated protein-protein interactions. ELM provides a comprehensive, regularly updated and well-organised repository of manually curated, experimentally validated short linear motifs (SLiMs). An increasing number of SLiM-mediated interactions are discovered each year and keeping the resource up-to-date continues to be a great challenge. In the current update, 30 novel motif classes have been added and five existing classes have undergone major revisions. The update includes 411 new motif instances mostly focused on cell-cycle regulation, control of the actin cytoskeleton, membrane remodelling and vesicle trafficking pathways, liquid-liquid phase separation and integrin signalling. Many of the newly annotated motif-mediated interactions are targets of pathogenic motif mimicry by viral, bacterial or eukaryotic pathogens, providing invaluable insights into the molecular mechanisms underlying infectious diseases. The current ELM release includes 317 motif classes incorporating 3934 individual motif instances manually curated from 3867 scientific publications. ELM is available at: http://elm.eu.org.

DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation.

The Database of Intrinsically Disordered Proteins (DisProt, URL: https://disprot.org) is the major repository of manually curated annotations of intrinsically disordered proteins and regions from the literature. We report here recent updates of DisProt version 9, including a restyled web interface, refactored Intrinsically Disordered Proteins Ontology (IDPO), improvements in the curation process and significant content growth of around 30%. Higher quality and consistency of annotations is provided by a newly implemented reviewing process and training of curators. The increased curation capacity is fostered by the integration of DisProt with APICURON, a dedicated resource for the proper attribution and recognition of biocuration efforts. Better interoperability is provided through the adoption of the Minimum Information About Disorder (MIADE) standard, an active collaboration with the Gene Ontology (GO) and Evidence and Conclusion Ontology (ECO) consortia and the support of the ELIXIR infrastructure.

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

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

In Silico Structural Analysis Exploring Conformational Folding of Protein Variants in Alzheimer's Disease.

Accurate protein structure prediction using computational methods remains a challenge in molecular biology. Recent advances in AI-powered algorithms provide a transformative effect in solving this problem. Even though AlphaFold's performance has improved since its release, there are still limitations that apply to its efficacy. In this study, a selection of proteins related to the pathology of Alzheimer's disease was modeled, with Presenilin-1 (PSN1) and its mutated variants in the foreground. Their structural predictions were evaluated using the ColabFold implementation of AlphaFold, which utilizes MMseqs2 for the creation of multiple sequence alignments (MSAs). A higher number of recycles than the one used in the AlphaFold DB was selected, and no templates were used. In addition, prediction by RoseTTAFold was also applied to address how structures from the two deep learning frameworks match reality. The resulting conformations were compared with the corresponding experimental structures, providing potential insights into the predictive ability of this approach in this particular group of proteins. Furthermore, a comprehensive examination was performed on features such as predicted regions of disorder and the potential effect of mutations on PSN1. Our findings consist of highly accurate superpositions with little or no deviation from experimentally determined domain-level models.

F/YGG-motif is an intrinsically disordered nucleic-acid binding motif.

Heterogeneous nuclear ribonucleoproteins (hnRNP) function in RNA processing, have RNA-recognition motifs (RRMs) and intrinsically disordered, low-complexity domains (LCDs). While RRMs are drivers of RNA binding, there is only limited knowledge about the RNA interaction by the LCD of some hnRNPs. Here, we show that the LCD of hnRNPA2 interacts with RNA via an embedded Tyr/Gly-rich region which is a disordered RNA-binding motif. RNA binding is maintained upon mutating tyrosine residues to phenylalanines, but abrogated by mutating to alanines, thus we term the RNA-binding region 'F/YGG motif'. The F/YGG motif can bind a broad range of structured (e.g. tRNA) and disordered (e.g. polyA) RNAs, but not rRNA. As the F/YGG otif can also interact with DNA, we consider it a general nucleic acid-binding motif. hnRNPA2 LCD can form dense droplets, by liquid-liquid phase separation (LLPS). Their formation is inhibited by RNA binding, which is mitigated by salt and 1,6-hexanediol, suggesting that both electrostatic and hydrophobic interactions feature in the F/YGG motif. The D290V mutant also binds RNA, which interferes with both LLPS and aggregation thereof. We found homologous regions in a broad range of RNA- and DNA-binding proteins in the human proteome, suggesting that the F/YGG motif is a general nucleic acid-interaction motif.

DisProt: intrinsic protein disorder annotation in 2020.

The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the 'dark' proteome.

Integration of Data from Liquid-Liquid Phase Separation Databases Highlights Concentration and Dosage Sensitivity of LLPS Drivers.

Liquid-liquid phase separation (LLPS) is a molecular process that leads to the formation of membraneless organelles, representing functionally specialized liquid-like cellular condensates formed by proteins and nucleic acids. Integrating the data on LLPS-associated proteins from dedicated databases revealed only modest agreement between them and yielded a high-confidence dataset of 89 human LLPS drivers. Analysis of the supporting evidence for our dataset uncovered a systematic and potentially concerning difference between protein concentrations used in a good fraction of the in vitro LLPS experiments, a key parameter that governs the phase behavior, and the proteomics-derived cellular abundance levels of the corresponding proteins. Closer scrutiny of the underlying experimental data enabled us to offer a sound rationale for this systematic difference, which draws on our current understanding of the cellular organization of the proteome and the LLPS process. In support of this rationale, we find that genes coding for our human LLPS drivers tend to be dosage-sensitive, suggesting that their cellular availability is tightly regulated to preserve their functional role in direct or indirect relation to condensate formation. Our analysis offers guideposts for increasing agreement between in vitro and in vivo studies, probing the roles of proteins in LLPS.

Distance-Based Metrics for Comparing Conformational Ensembles of Intrinsically Disordered Proteins.

Intrinsically disordered proteins are proteins whose native functional states represent ensembles of highly diverse conformations. Such ensembles are a challenge for quantitative structure comparisons because their conformational diversity precludes optimal superimposition of the atomic coordinates necessary for deriving common similarity measures such as the root mean-square deviation of these coordinates. Here, we introduce superimposition-free metrics that are based on computing matrices of the Cα-Cα distance distributions within ensembles and comparing these matrices between ensembles. Differences between two matrices yield information on the similarity between specific regions of the polypeptide, whereas the global structural similarity is captured by the root mean-square difference between the medians of the Cα-Cα distance distributions of two ensembles. Together, our metrics enable rigorous investigations of structure-function relationships in conformational ensembles of intrinsically disordered proteins derived using experimental restraints or by molecular simulations and for proteins containing both structured and disordered regions.

De novo missense variants in RAC3 cause a novel neurodevelopmental syndrome.

PURPOSE: RAC3 is an underexamined member of the Rho GTPase gene family that is expressed in the developing brain and linked to key cellular functions. De novo missense variants in the homolog RAC1 were recently associated with developmental disorders. In the RAC subfamily, transforming missense changes at certain shared residues have been observed in human cancers and previously characterized in experimental studies. The purpose of this study was to determine whether constitutional dysregulation of RAC3 is associated with human disease. METHODS: We discovered a RAC3 variant in the index case using genome sequencing, and searched for additional variants using international data-sharing initiatives. Functional effects of the variants were assessed using a multifaceted approach generalizable to most clinical laboratory settings. RESULTS: We rapidly identified five individuals with de novo monoallelic missense variants in RAC3, including one recurrent change. Every participant had severe intellectual disability and brain malformations. In silico protein modeling, and prior in vivo and in situ experiments, supported a transforming effect for each of the three different RAC3 variants. All variants were observed in databases of somatic variation in cancer. CONCLUSIONS: Missense variants in RAC3 cause a novel brain disorder, likely through a mechanism of constitutive protein activation.

DisProt 7.0: a major update of the database of disordered proteins.

The Database of Protein Disorder (DisProt, URL: www.disprot.org) has been significantly updated and upgraded since its last major renewal in 2007. The current release holds information on more than 800 entries of IDPs/IDRs, i.e. intrinsically disordered proteins or regions that exist and function without a well-defined three-dimensional structure. We have re-curated previous entries to purge DisProt from conflicting cases, and also upgraded the functional classification scheme to reflect continuous advance in the field in the past 10 years or so. We define IDPs as proteins that are disordered along their entire sequence, i.e. entirely lack structural elements, and IDRs as regions that are at least five consecutive residues without well-defined structure. We base our assessment of disorder strictly on experimental evidence, such as X-ray crystallography and nuclear magnetic resonance (primary techniques) and a broad range of other experimental approaches (secondary techniques). Confident and ambiguous annotations are highlighted separately. DisProt 7.0 presents classified knowledge regarding the experimental characterization and functional annotations of IDPs/IDRs, and is intended to provide an invaluable resource for the research community for a better understanding structural disorder and for developing better computational tools for studying disordered proteins.

Disordered Substrates of the 20S Proteasome Link Degradation with Phase Separation.

The 20S proteasome is known to degrade intrinsically disordered proteins (IDPs) via an ubiquitin-independent, disorder-driven mechanism. Unless protected within protein complexes or macromolecular assemblies, certain IDPs can undergo degradation mediated directly by the 20S core particle. In this issue of Proteomics, Myers et al. utilize a proteomics approach to identify ∼500 IDP substrates of the 20S proteasome. Bioinformatics analyses of these substrates demonstrate a large fraction of highly disordered RNA-binding proteins, enriched in low-complexity, prion-like domains. A number of these proteins are also known to form phase-separated membraneless organelles in amyotrophic lateral sclerosis (ALS) and other protein neuropathies. The Myers et al. study highlights potentially interesting connections between IDP degradation and the regulatory dynamics of phase-separated intracellular assemblies. Their work should stimulate further research into the mechanistic details of how the 20S proteasome controls cellular abundances of RNA-binding proteins and thereby regulates RNA-related biological functions within both physiological and pathological phase-separated assemblies.

Unique Physicochemical Patterns of Residues in Protein-Protein Interfaces.

Protein-protein interactions can be characterized by high-resolution structures of complexes, from which diverse features of the interfaces can be derived. For the majority of protein-protein interactions identified, however, there is no information on the structure of the complex or the interface involved in the interaction. Understanding what surface properties drive certain interactions is crucial in the functional evaluation of protein complexes. Here we show that the local patterning of the physicochemical properties of amino acids within surface patches is characteristic of interfaces. To describe this feature in a quantitative manner, we have defined a statistical potential, iPat, as a measure of surface patterning. iPat, which does not take evolutionary conservation or knowledge of the interaction partner into consideration, represents a function principally different from algorithms that consider intermolecular contacts. We assess its suitability for characterizing protein and peptide interfaces, and we demonstrate that iPat is uniquely descriptive for interfaces of proteins that undergo large conformational changes or that are involved in the binding of intrinsically disordered protein (IDP) partners. We suggest that as a stand-alone propensity or in combination with other features, iPat represents a new feature in analyzing the functional binding specificity of protein-protein interactions that has better predictive potential than other simple 1D features, such as hydrophobicity or stickiness.

A cyclin D1 intrinsically disordered domain accesses modified histone motifs to govern gene transcription.

The essential G1-cyclin, CCND1, is frequently overexpressed in cancer, contributing to tumorigenesis by driving cell-cycle progression. D-type cyclins are rate-limiting regulators of G1-S progression in mammalian cells via their ability to bind and activate CDK4 and CDK6. In addition, cyclin D1 conveys kinase-independent transcriptional functions of cyclin D1. Here we report that cyclin D1 associates with H2BS14 via an intrinsically disordered domain (IDD). The same region of cyclin D1 was necessary for the induction of aneuploidy, induction of the DNA damage response, cyclin D1-mediated recruitment into chromatin, and CIN gene transcription. In response to DNA damage H2BS14 phosphorylation occurs, resulting in co-localization with γH2AX in DNA damage foci. Cyclin D1 ChIP seq and γH2AX ChIP seq revealed ~14% overlap. As the cyclin D1 IDD functioned independently of the CDK activity to drive CIN, the IDD domain may provide a rationale new target to complement CDK-extinction strategies.

Degron masking outlines degronons, co-degrading functional modules in the proteome.

Effective organization of proteins into functional modules (networks, pathways) requires systems-level coordination between transcription, translation and degradation. Whereas the cooperation between transcription and translation was extensively studied, the cooperative degradation regulation of protein complexes and pathways has not been systematically assessed. Here we comprehensively analyzed degron masking, a major mechanism by which cellular systems coordinate degron recognition and protein degradation. For over 200 substrates with characterized degrons (E3 ligase targeting motifs, ubiquitination sites and disordered proteasomal entry sequences), we demonstrate that degrons extensively overlap with protein-protein interaction sites. Analysis of binding site information and protein abundance comparisons show that regulatory partners effectively outcompete E3 ligases, masking degrons from the ubiquitination machinery. Protein abundance variations between normal and cancer cells highlight the dynamics of degron masking components. Finally, integrative analysis of gene co-expression, half-life correlations and functional relationships between interacting proteins point towards higher-order, co-regulated degradation modules ('degronons') in the proteome.

Intrinsic protein disorder uncouples affinity from binding specificity.

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) of proteins often function by molecular recognition, in which they undergo induced folding. Based on prior generalizations, the idea prevails in the IDP field that due to the entropic penalty of induced folding, the major functional advantage associated with this binding mode is "uncoupling" specificity from binding strength. Nevertheless, both weaker binding and high specificity of IDPs/IDRs rest on limited experimental observations, making these assumptions more speculations than evidence-supported facts. The issue is also complicated by the rather vague concept of specificity that lacks an exact measure, such as the Kd for binding strength. We addressed these issues by creating and analyzing a comprehensive dataset of well-characterized ID/globular protein complexes, for which both the atomic structure of the complex and free energy (ΔG, Kd ) of interaction is known. Through this analysis, we provide evidence that the affinity distributions of IDP/globular and globular/globular complexes show different trends, whereas specificity does not connote to weaker binding strength of IDPs/IDRs. Furthermore, protein disorder extends the spectrum in the direction of very weak interactions, which may have important regulatory consequences and suggest that, in a biological sense, strict correlation of specificity and binding strength are uncoupled by structural disorder.

The evolution and polymorphism of mono-amino acid repeats in androgen receptor and their regulatory role in health and disease.

Androgen receptor (AR) is a key member of nuclear hormone receptors with the longest intrinsically disordered N-terminal domain (NTD) in its protein family. There are four mono-amino acid repeats (polyQ1, polyQ2, polyG, and polyP) located within its NTD, of which two are polymorphic (polyQ1 and polyG). The length of both polymorphic repeats shows clinically important correlations with disease, especially with cancer and neurodegenerative diseases, as shorter and longer alleles exhibit significant differences in expression, activity and solubility. Importantly, AR has also been shown to undergo condensation in the nucleus by liquid-liquid phase separation, a process highly sensitive to protein solubility and concentration. Nonetheless, in prostate cancer cells, AR variants also partition into transcriptional condensates, which have been shown to alter the expression of target gene products. In this review, we summarize current knowledge on the link between AR repeat polymorphisms and cancer types, including mechanistic explanations and models comprising the relationship between condensate formation, polyQ1 length and transcriptional activity. Moreover, we outline the evolutionary paths of these recently evolved amino acid repeats across mammalian species, and discuss new research directions with potential breakthroughs and controversies in the literature.