The Origin of Discrepancies between Predictions and Annotations in Intrinsically Disordered Proteins.

Disorder prediction methods that can discriminate between ordered and disordered regions have contributed fundamentally to our understanding of the properties and prevalence of intrinsically disordered proteins (IDPs) in proteomes as well as their functional roles. However, a recent large-scale assessment of the performance of these methods indicated that there is still room for further improvements, necessitating novel approaches to understand the strengths and weaknesses of individual methods. In this study, we compared two methods, IUPred and disorder prediction, based on the pLDDT scores derived from AlphaFold2 (AF2) models. We evaluated these methods using a dataset from the DisProt database, consisting of experimentally characterized disordered regions and subsets associated with diverse experimental methods and functions. IUPred and AF2 provided consistent predictions in 79% of cases for long disordered regions; however, for 15% of these cases, they both suggested order in disagreement with annotations. These discrepancies arose primarily due to weak experimental support, the presence of intermediate states, or context-dependent behavior, such as binding-induced transitions. Furthermore, AF2 tended to predict helical regions with high pLDDT scores within disordered segments, while IUPred had limitations in identifying linker regions. These results provide valuable insights into the inherent limitations and potential biases of disorder prediction methods.

Pipeline for transferring annotations between proteins beyond globular domains.

DisProt is the primary repository of Intrinsically Disordered Proteins (IDPs). This database is manually curated and the annotations there have strong experimental support. Currently, DisProt contains a relatively small number of proteins highlighting the importance of transferring annotations regarding verified disorder state and corresponding functions to homologous proteins in other species. In such a way, providing them with highly valuable information to better understand their biological roles. While the principles and practicalities of homology transfer are well-established for globular proteins, these are largely lacking for disordered proteins. We used DisProt to evaluate the transferability of the annotation terms to orthologous proteins. For each protein, we looked for their orthologs, with the assumption that they will have a similar function. Then, for each protein and their orthologs, we made multiple sequence alignments (MSAs). Disordered sequences are fast evolving and can be hard to align, therefore, we implemented alignment quality control steps ensuring robust alignments before mapping the annotations. We have designed a pipeline to obtain good-quality MSAs and to transfer annotations from any protein to their orthologs. Applying the pipeline to DisProt proteins, from the 1731 entries with 5623 annotations, we can reach 97,555 orthologs and transfer a total of 301,190 terms by homology. We also provide a web server for consulting the results of DisProt proteins and execute the pipeline for any other protein. The server Homology Transfer IDP (HoTIDP) is accessible at http://hotidp.leloir.org.ar.

DisCanVis: Visualizing integrated structural and functional annotations to better understand the effect of cancer mutations located within disordered proteins.

Intrinsically disordered proteins (IDPs) play important roles in a wide range of biological processes and have been associated with various diseases, including cancer. In the last few years, cancer genome projects have systematically collected genetic variations underlying multiple cancer types. In parallel, the number and different types of disordered proteins characterized by experimental methods have also significantly increased. Nevertheless, the role of IDPs in various types of cancer is still not well understood. In this work, we present DisCanVis, a novel visualization tool for cancer mutations with a special focus on IDPs. In order to aid the interpretation of observed mutations, genome level information is combined with information about the structural and functional properties of proteins. The web server enables users to inspect individual proteins, collect examples with existing annotations of protein disorder and associated function or to discover currently uncharacterized examples with likely disease relevance. Through a REST API interface and precompiled tables the analysis can be extended to a group of proteins.

Acetylation of nuclear receptors in health and disease: an update.

Lysine acetylation is a common reversible post-translational modification of proteins that plays a key role in regulating gene expression. Nuclear receptors (NRs) include ligand-inducible transcription factors and orphan receptors for which the ligand is undetermined, which together regulate the expression of genes involved in development, metabolism, homeostasis, reproduction and human diseases including cancer. Since the original finding that the ERα, AR and HNF4 are acetylated, we now understand that the vast majority of NRs are acetylated and that this modification has profound effects on NR function. Acetylation sites are often conserved and involve both ordered and disordered regions of NRs. The acetylated residues function as part of an intramolecular signalling platform intersecting phosphorylation, methylation and other modifications. Acetylation of NR has been shown to impact recruitment into chromatin, co-repressor and coactivator complex formation, sensitivity and specificity of regulation by ligand and ligand antagonists, DNA binding, subcellular distribution and transcriptional activity. A growing body of evidence in mice indicates a vital role for NR acetylation in metabolism. Additionally, mutations of the NR acetylation site occur in human disease. This review focuses on the role of NR acetylation in coordinating signalling in normal physiology and disease.

The interaction between LC8 and LCA5 reveals a novel oligomerization function of LC8 in the ciliary-centrosome system.

Dynein light chain LC8 is a small dimeric hub protein that recognizes its partners through short linear motifs and is commonly assumed to drive their dimerization. It has more than 100 known binding partners involved in a wide range of cellular processes. Recent large-scale interaction studies suggested that LC8 could also play a role in the ciliary/centrosome system. However, the cellular function of LC8 in this system remains elusive. In this work, we characterized the interaction of LC8 with the centrosomal protein lebercilin (LCA5), which is associated with a specific form of ciliopathy. We showed that LCA5 binds LC8 through two linear motifs. In contrast to the commonly accepted model, LCA5 forms dimers through extensive coiled coil formation in a LC8-independent manner. However, LC8 enhances the oligomerization ability of LCA5 that requires a finely balanced interplay of coiled coil segments and both binding motifs. Based on our results, we propose that LC8 acts as an oligomerization engine that is responsible for the higher order oligomer formation of LCA5. As LCA5 shares several common features with other centrosomal proteins, the presented LC8 driven oligomerization could be widespread among centrosomal proteins, highlighting an important novel cellular function of LC8.

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.

Functions of intrinsically disordered proteins through evolutionary lenses.

Protein sequences are the result of an evolutionary process that involves the balancing act of experimenting with novel mutations and selecting out those that have an undesirable functional outcome. In the case of globular proteins, the function relies on a well-defined conformation, therefore, there is a strong evolutionary pressure to preserve the structure. However, different evolutionary rules might apply for the group of intrinsically disordered regions and proteins (IDR/IDPs) that exist as an ensemble of fluctuating conformations. The function of IDRs can directly originate from their disordered state or arise through different types of molecular recognition processes. There is an amazing variety of ways IDRs can carry out their functions, and this is also reflected in their evolutionary properties. In this chapter we give an overview of the different types of evolutionary behavior of disordered proteins and associated functions in normal and disease settings.

IUPred3: prediction of protein disorder enhanced with unambiguous experimental annotation and visualization of evolutionary conservation.

Intrinsically disordered proteins and protein regions (IDPs/IDRs) exist without a single well-defined conformation. They carry out important biological functions with multifaceted roles which is also reflected in their evolutionary behavior. Computational methods play important roles in the characterization of IDRs. One of the commonly used disorder prediction methods is IUPred, which relies on an energy estimation approach. The IUPred web server takes an amino acid sequence or a Uniprot ID/accession as an input and predicts the tendency for each amino acid to be in a disordered region with an option to also predict context-dependent disordered regions. In this new iteration of IUPred, we added multiple novel features to enhance the prediction capabilities of the server. First, learning from the latest evaluation of disorder prediction methods we introduced multiple new smoothing functions to the prediction that decreases noise and increases the performance of the predictions. We constructed a dataset consisting of experimentally verified ordered/disordered regions with unambiguous annotations which were added to the prediction. We also introduced a novel tool that enables the exploration of the evolutionary conservation of protein disorder coupled to sequence conservation in model organisms. The web server is freely available to users and accessible at https://iupred3.elte.hu.

Ancient Evolutionary Origin of Intrinsically Disordered Cancer Risk Regions.

Cancer is a heterogeneous genetic disease that alters the proper functioning of proteins involved in key regulatory processes such as cell cycle, DNA repair, survival, or apoptosis. Mutations often accumulate in hot-spots regions, highlighting critical functional modules within these proteins that need to be altered, amplified, or abolished for tumor formation. Recent evidence suggests that these mutational hotspots can correspond not only to globular domains, but also to intrinsically disordered regions (IDRs), which play a significant role in a subset of cancer types. IDRs have distinct functional properties that originate from their inherent flexibility. Generally, they correspond to more recent evolutionary inventions and show larger sequence variations across species. In this work, we analyzed the evolutionary origin of disordered regions that are specifically targeted in cancer. Surprisingly, the majority of these disordered cancer risk regions showed remarkable conservation with ancient evolutionary origin, stemming from the earliest multicellular animals or even beyond. Nevertheless, we encountered several examples where the mutated region emerged at a later stage compared with the origin of the gene family. We also showed the cancer risk regions become quickly fixated after their emergence, but evolution continues to tinker with their genes with novel regulatory elements introduced even at the level of humans. Our concise analysis provides a much clearer picture of the emergence of key regulatory elements in proteins and highlights the importance of taking into account the modular organisation of proteins for the analyses of evolutionary origin.

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.

Novel linear motif filtering protocol reveals the role of the LC8 dynein light chain in the Hippo pathway.

Protein-protein interactions (PPIs) formed between short linear motifs and globular domains play important roles in many regulatory and signaling processes but are highly underrepresented in current protein-protein interaction databases. These types of interactions are usually characterized by a specific binding motif that captures the key amino acids shared among the interaction partners. However, the computational proteome-level identification of interaction partners based on the known motif is hindered by the huge number of randomly occurring matches from which biologically relevant motif hits need to be extracted. In this work, we established a novel bioinformatic filtering protocol to efficiently explore interaction network of a hub protein. We introduced a novel measure that enabled the optimization of the elements and parameter settings of the pipeline which was built from multiple sequence-based prediction methods. In addition, data collected from PPI databases and evolutionary analyses were also incorporated to further increase the biological relevance of the identified motif hits. The approach was applied to the dynein light chain LC8, a ubiquitous eukaryotic hub protein that has been suggested to be involved in motor-related functions as well as promoting the dimerization of various proteins by recognizing linear motifs in its partners. From the list of putative binding motifs collected by our protocol, several novel peptides were experimentally verified to bind LC8. Altogether 71 potential new motif instances were identified. The expanded list of LC8 binding partners revealed the evolutionary plasticity of binding partners despite the highly conserved binding interface. In addition, it also highlighted a novel, conserved function of LC8 in the upstream regulation of the Hippo signaling pathway. Beyond the LC8 system, our work also provides general guidelines that can be applied to explore the interaction network of other linear motif binding proteins or protein domains.

Is there a biological cost of protein disorder? Analysis of cancer-associated mutations.

As many diseases can be traced back to altered protein function, studying the effect of genetic variations at the level of proteins can provide a clue to understand how changes at the DNA level lead to various diseases. Cellular processes rely not only on proteins with well-defined structure but can also involve intrinsically disordered proteins (IDPs) that exist as highly flexible ensembles of conformations. Disordered proteins are mostly involved in signaling and regulatory processes, and their functional repertoire largely complements that of globular proteins. However, it was also suggested that protein disorder entails an increased biological cost. This notion was supported by a set of individual IDPs involved in various diseases, especially in cancer, and the increased amount of disorder observed among disease-associated proteins. In this work, we tested if there is any biological risk associated with protein disorder at the level of single nucleotide mutations. Specifically, we analyzed the distribution of mutations within ordered and disordered segments. Our results demonstrated that while neutral polymorphisms were more likely to occur within disordered segments, cancer-associated mutations had a preference for ordered regions. Additionally, we proposed an alternative explanation for the association of protein disorder and the involvement in cancer with the consideration of functional annotations. Individual examples also suggested that although disordered segments are fundamental functional elements, their presence is not necessarily accompanied with an increased mutation rate in cancer. The presented study can help to understand how the different structural properties of proteins influence the consequences of genetic mutations.