Biology subjects

Dosztanyi, Z.

Publications and source records attributed to Dosztanyi, Z..

10 recordsLinked to original sources

bioRxiv2026

The Hidden Disorder Divide: Reconciling Benchmark Inconsistencies in Intrinsically Disordered Protein Binding Site Prediction

Computational predictors of protein-binding sites within intrinsically disordered regions (IDRs) show highly inconsistent performance across high-quality benchmark datasets. To understand the origins of these discrepancies, we systematically compared predictors across three independent test sets: two CAID datasets updated with the latest DisProt annotations and a composite dataset (DBs) assembled from DIBS, FuzDB, IDEAL, and MFIB. Predictors trained predominantly on DisProt data achieved substantially higher AUCs on the CAID sets but performed poorly on the DBs. In contrast, predictors trained on older, low-quality PDB-based datasets showed balanced performance across all sets, with a slight preference for DBs. Predictors with mixed training exposure displayed intermediate behavior. Through controlled experiments using identical CNN architectures and feature analysis, we demonstrate that the dominant factor driving these performance differences is the intrinsic disorder propensity of the binding sites themselves. Binding residues in DisProt-based datasets exhibit markedly higher average disorder propensity scores than those in PDB-derived datasets. This previously unrecognized selection bias -- literature studies preferentially characterizing more disordered binding sites, while PDB-derived annotations capture less disordered ones -- effectively splits IDR-protein binding sites into two distinct categories. Predictors optimized on one category therefore generalize poorly to the other. Binding-site length and sequence conservation play only minor or negligible roles in explaining the observed inconsistencies. These findings highlight a critical limitation in current benchmarking practices and training strategies for IDR-binding site prediction, underscoring the need for more balanced and disorder-aware reference datasets. Finally, the diagnostic techniques introduced here could prove valuable beyond the specific application examined in this study. The data and code used to generate all figures and tables are available at: https://github.com/NawarMalhis/HDD

bioinformatics↗

bioRxiv2025

Pathogenic Missense Mutations in Intrinsically Disordered Regions Reveal Functional and Clinical Signals

Intrinsically disordered regions (IDRs) play key roles in cellular signaling and regulation, yet their contribution to human disease remains poorly understood. Here we analyzed nearly one million ClinVar missense variants, focusing on those located within IDRs defined by curated and predicted annotations. We found that pathogenic variants were significantly enriched in short linear motifs (SLiMs) and disordered binding regions, consistent with their central functional importance. To extend these insights beyond existing annotations, we applied AlphaMissense, a deep-learning pathogenicity predictor, and uncovered localized "island-like" patterns of elevated pathogenicity within IDRs. Leveraging these signals, we developed a classifier to prioritize predicted ELM motifs (PEMs), revealing thousands of candidate functional sites linked to major disease classes, including neurological, cardiovascular, and cancer-associated genes. Case studies in POLK, FOXP2, and LMOD3 illustrate how this framework connects genetic variation to molecular mechanisms, providing a scalable route to interpret variants of uncertain significance and advancing our understanding of pathogenicity in the disordered proteome. SummaryThis study reveals how deep-learning pathogenicity predictions can uncover functional motifs within intrinsically disordered regions, providing a new framework for interpreting genetic variation in the disordered proteome.

bioinformatics↗

bioRxiv2025

The non-catalytic ϵ DNA polymerase subunit is an NPF motif recognition protein

Short linear motifs (SLiMs) in disordered protein regions direct numerous protein-protein interactions, yet most remain uncharacterized. The Asn-Pro-Phe (NPF) motif is a well-known EH-domain ligand implicated in endocytosis, but here we reveal that the non-catalytic subunit of human DNA polymerase {varepsilon} (POLE2) also serves as a general NPF-motif receptor. Using a quantitative "native holdup" assay, we find that POLE2 selectively binds diverse NPF-containing peptides, including canonical EH-domain ligands (e.g., SYNJ1) and previously uncharacterized motifs. Biochemical measurements and mutational analysis show that NPF motifs interact with a shallow pocket near the POLE2 C-terminus, and AlphaFold predictions confirm key roles for Y513, E520, and S522 in motif coordination. Proteome-scale affinity screens identify NPF-containing nuclear proteins (e.g., WDHD1, DONSON, TTF2) that bind POLE2 with micromolar affinities, and their motif mutations abolish binding in cell extracts. Although POLE2 primarily tethers the catalytic POLE subunit to replication forks, these results indicate that it can also recruit various NPF-bearing partners involved in replication, DNA repair, and transcription regulation. Notably, NPF motifs optimized for EH-domain binding can still associate with POLE2, highlighting the inherent degeneracy of SLiM-mediated networks. Overall, these findings establish POLE2 as a central hub linking replication with other processes via broad NPF-motif recognition.

biochemistry↗

bioRxiv2023

Entering new circles: Expansion of the LC8/DYNLL1 interactome in the ciliary-centrosomal network through system-driven motif evolution

LC8 is a eukaryotic hub protein that presents a highly conserved interface recognized by short linear motifs (SLiMs) in partner proteins. LC8 was originally associated with the dynein motor complex and was also suggested to promote dimerization of partner proteins. However, the growing list of validated partners with diverse functions suggests that LC8 plays a more general cellular role which is still not fully understood. In this work, we combined computational and experimental approaches in order to gain insights into the LC8 interaction network at the system level. Our machine-learning based pipeline together with functional enrichment analysis revealed that LC8 plays a central role in the ciliary-centrosomal system with several partners involved in various types of ciliopathies. By integrating proteomic data and functional annotations, we identified a high confidence, ciliary-centrosomal specific LC8 partner list of 57 proteins, 15 of which are central to centriole life-cycle organization. Validated binding motifs and the detailed characterization of the interaction with protein OFD1 emphasized the important role of LC8, which was confirmed by confocal microscopy. OFD1, which is a central player in this system, also stood out as an early and highly conserved LC8 partner. However, additional partners showed a more recent evolutionary origin featuring novel proteins as well as novel motifs. Altogether, our results highlight that LC8 plays a major role in the ciliary-centrosomal system and its interaction network underwent a major expansion. This system driven motif evolution contributed to the increased complexity of the organization and regulation of the ciliary-centrosomal system.

molecular biology↗

bioRxiv2022

Pipeline for transferring annotations between proteins beyond globular domains

BackgroundDisProt is the primary repository of Intrinsically Disordered Proteins. 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 verified disorder and other annotations, in such a way as to increase the number of proteins that could benefit from this valuable information. While the principles and practicalities of homology transfer are well-established for globular proteins, these are largely lacking for disordered proteins. MethodsWe 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). Global and regional quality of the MSAs was evaluated with the NorMD score. ResultsWe 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 1931 entries with 5,623 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.

bioinformatics↗

bioRxiv2022

MIADE metadata guidelines: Minimum Information About a Disorder Experiment

An unambiguous description of an experimental setup and analysis, and the subsequent biological observation is vital for accurate data interpretation and reproducible results. Consequently, experimental analyses should be described in a concise, unequivocal, and digestible manner. The aim of minimum information guidelines is to define the fundamental complement of data that can support an unambiguous conclusion on experimental observations. In this document, we present the Minimum Information About Disorder Experiments (MIADE) guidelines to define the minimal fundamental parameters required for non-experts to understand the key findings of an experiment studying intrinsically disordered proteins (IDPs) or intrinsically disordered protein regions (IDRs). MIADE guidelines provide recommendations for data producers to describe the results of their experiments at source, for curators to annotate experimental data to community resources and for database developers maintaining community resources to disseminate the data. We give examples of the application of these guidelines in common use cases and describe the implementation of an update to the DisProt IDP database to allow MIADE-compliant annotation. The MIADE guidelines will improve the interpretability of experimental results for data consumers, facilitate direct data submission, simplify data curation, improve data exchange among repositories and standardise the dissemination of the key metadata on an IDP experiment by IDP data sources.

scientific communication and education↗

bioRxiv2020

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 not only correspond 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 to 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.

bioinformatics↗

bioRxiv2020

Intrinsically disordered protein mutations can drive cancer and their targeted interference extends therapeutic options

Many proteins contain intrinsically disordered regions (IDRs) which carry out important functions without relying on a single well-defined conformation. IDRs are increasingly recognized as critical elements of regulatory networks and have been also associated with cancer. However, it is unknown whether mutations targeting IDRs represent a distinct class of driver events associated with specific molecular and system-level properties, cancer types and treatment options. Here, we used an integrative computational approach to explore the direct role of intrinsically disordered proteins/protein regions (IDPs/IDRs) driving cancer. We showed that around 20% of cancer drivers are primarily targeted through a disordered region. The detailed analysis of these IDRs revealed that they can function in multiple ways that are distinct from the functional mechanisms of ordered drivers. Disordered drivers play a central role in context-dependent interaction networks and are enriched in specific biological processes such as transcription, gene expression regulation and protein degradation. Furthermore, their modulation represents an alternative mechanism for the emergence of all known cancer hallmarks independently of the modulation of globular proteins. Disordered drivers are also highly relevant at the sample level, and their mutations can represent the key driving event in certain individual cancer patients. However, treatment options for such patients are currently severely limited. The presented study highlights a largely overlooked class of cancer drivers associated with specific cancer types that need novel therapeutic options.

bioinformatics↗

bioRxiv2018

Large-scale analysis of redox-sensitive conditionally disordered protein regions reveal their widespread nature and key roles in high-level eukaryotic processes

Recently developed quantitative redox proteomic studies enable the direct identification of redox-sensing cysteine residues that regulate the functional behavior of target proteins in response to changing levels of reactive oxygen species (ROS). At the molecular level, redox regulation can directly modify the active sites of enzymes, although a growing number of examples indicate the importance of an additional underlying mechanism that involves conditionally disordered proteins. These proteins alter their functional behavior by undergoing a disorder-to-order transition in response to changing redox conditions. However, the extent to which this mechanism is used in various proteomes is currently unknown. Here, we use a recently developed sequence-based prediction tool incorporated into the IUPred2A web server to estimate redox-sensitive conditionally disordered regions on a large scale. We show that redox-sensitive conditional disorder is fairly widespread in various proteomes and that its presence strongly correlates with the expansion of specific domains in multicellular organisms that largely rely on extra stability provided by disulfide bonds or zinc ion binding. The analyses of yeast redox proteomes and human disease data further underlie the significance of this phenomenon in the regulation of a wide range of biological processes, as well as its biomedical importance.

bioinformatics↗

bioRxiv2017

Interplay between folding and binding modulates protein sequences, structures, functions and regulation

Intrinsically Disordered Proteins (IDPs) fulfill critical biological roles without having the potential to fold on their own. While lacking inherent structure, the majority of IDPs do reach a folded state via interaction with a protein partner, presenting a deep entanglement of the folding and binding process. Protein disorder has been recognized as a major determinant in several properties of proteins; yet the way the binding process is reflected in these features in general lacks this detail of description. Recent advances in database development enabled us to identify three basic scenarios of the interplay between folding and binding in unprecedented detail. These scenarios have fundamentally different properties in terms of protein sequence, structure, function and regulation, depending on the structural properties of the interacting partners. Strikingly, the existence of a binding partner and its structural properties influence all analyzed properties of proteins to the same extent as the divide between inherent order or disorder. The appreciation of this interplay between folding and binding is the basis for the successful charting of unknown territories in the protein interactome, the understanding of how different binding modes assemble regulatory networks, and the development of future pharmaceutical applications.

bioinformatics↗