@article{SCOPUS_ID:105027748200,

title = {DisProt in 2026: enhancing intrinsically disordered proteins accessibility, deposition, and annotation},

author = {Maria Victoria Nugnes and Kamel Eddine Adel Bouhraoua and Mehdi Zoubiri and Rita Pancsa and Erzsébet Fichó and Alexander M Monzon and Ana M Melo and Edoardo Salladini and Emanuela Leonardi and Federica Quaglia and Daniyal Nasiribavil and Hamidreza Ghafouri and Gobeill Julien and Emilie Pasche and Patrick Ruch and Paul Van Rijen and László Dobson and Marco Schiavina and Trinidad Cordero and Zsófia E Kálmán and Ximena Castro and Valentín Iglesias and István Reményi and Mahta Mehdiabadi and Gábor Erdős and Zsuzsanna Dosztányi and Peter Tompa and Damiano Piovesan and Silvio C. E Tosatto and Maria Cristina Aspromonte},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-105027748200&origin=inward},

doi = {10.1093/nar/gkaf1175},

year  = {2026},

date = {2026-01-01},

journal = {Nucleic Acids Research},

volume = {54},

number = {D1},

pages = {D383-D392},

publisher = {Oxford University Press},

abstract = {© 2025 The Author(s). Published by Oxford University Press.DisProt (https://disprot.org/) is an open database integrating experimental evidence on intrinsically disordered proteins (IDPs), intrinsically disordered regions (IDRs), and their functions. Over the past two years, the database has grown over 20%, now comprising 3201 IDPs and 13 347 pieces of evidence, including over 1500 new structural state annotations and >1300 new function annotations. DisProt has systematically adopted the Minimum Information About Disorder Experiments (MIADE) guidelines, more than doubling annotations with experimental details and improving the interpretability of disorder-related experiments. The website has evolved into a hybrid knowledgebase and deposition system, introducing a Deposition Page that allows direct submissions by external users. Through BLAST-based homology propagation in MobiDB, DisProt disorder regions and linear interacting peptides have been extended from hundreds to hundreds of thousands of proteins across >11 000 organisms. This new release marks a paradigm shift by integrating computational predictions as valid evidence and introducing major updates and restructuring of the IDP Ontology, enhancing accuracy, interoperability, and semantic clarity. DisProt continues to support community engagement through training resources together with DisTriage, an AI-based literature triage tool, providing curators with regularly updated lists of prioritized publications.},

note = {Cited by: 4; Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SCOPUS_ID:105014118997,

title = {Critical Assessment of Protein Intrinsic Disorder Round 3 - Predicting Disorder in the Era of Protein Language Models},

author = {Mahta Mehdiabadi and Alessio Del Conte and Maria Victoria Nugnes and Maria Cristina Aspromonte and Silvio C. E. Tosatto and Damiano Piovesan},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-105014118997&origin=inward},

doi = {10.1002/prot.70045},

year  = {2026},

date = {2026-01-01},

journal = {Proteins: Structure, Function and Bioinformatics},

volume = {94},

number = {1},

pages = {414-424},

publisher = {John Wiley and Sons Inc},

abstract = {© 2025 The Author(s). PROTEINS: Structure, Function, and Bioinformatics published by Wiley Periodicals LLC.Intrinsic disorder (ID) in proteins is a complex phenomenon, encompassing a continuum from entirely disordered regions to structured domains with flexible segments. The absence of a ground truth for all forms of disorder, combined with the possibility of structural transitions between ordered and disordered states under specific conditions, makes accurate prediction of ID especially challenging. The Critical Assessment of Protein Intrinsic Disorder (CAID) evaluates ID prediction methods using diverse benchmarks derived from DisProt, a manually curated database of experimentally validated annotations. This paper presents findings from the third round (CAID3), in which 24 new methods were assessed along with the predictors from previous rounds. Compared to CAID2, the top-performing methods in CAID3 demonstrated significant gains in average precision: over 31% improvement in predicting linker regions, and 15% in disorder prediction. This round introduces a new binding sub-challenge focused on identifying binding regions within known IDR boundaries. The results indicate that this task remains challenging, highlighting the potential for improvement. The top-performing methods in CAID3 are mostly new and commonly used embeddings from protein language models (pLMs), underscoring the growing impact of pLMs in tackling the complexities of disordered proteins and advancing ID prediction.},

note = {Cited by: 3; Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SCOPUS_ID:105031259193,

title = {Missense Constraint in Intrinsically Disordered Proteins Enhances Missense Variant Interpretation in Neurodevelopmental Disorders},

author = {Nazareth D. J. Robles and Silvio C. E. Tosatto and Maria Cristina Aspromonte},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-105031259193&origin=inward},

doi = {10.3390/genes17020219},

year  = {2026},

date = {2026-01-01},

journal = {Genes},

volume = {17},

number = {2},

publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},

abstract = {© 2026 by the authors.Background/Objectives: Interpreting missense variants in intrinsically disordered proteins (IDPs) remains a major challenge, as these proteins lack stable structure and are under-represented in experimental and clinical annotations. Variants occurring in IDPs are disproportionately classified as variants of uncertain significance (VUS), reflecting the absence of appropriate predictive tools rather than true biological neutrality. Here, we address this challenge using a curated dataset of neurodevelopmental disorder (NDD)-associated proteins. Methods: We integrated curated and predicted disorder annotations from DisProt and MobiDB to characterize the structural landscape of 339 NDD-associated proteins. To quantify a regional genetic constraint, we recalculated the Missense Tolerance Ratio (MTR) using a published framework adapted to the recent gnomAD release (v4.1.0). Integration with 33,124 ClinVar-reported missense variants revealed that, while mean constraint levels differ only modestly across structural states, ordered and structural transition regions show the strongest depletion of missense variation. Results: MTR identifies localized low-tolerance subregions within IDRs, indicating that these regions are not uniformly permissive and can harbor functionally essential elements. Conclusions: Overall, our results demonstrate that missense constraint in NDD proteins is highly localized and context-dependent, and that integrating high-quality disorder annotations with updated MTR profiles can improve the prioritization and interpretation of missense variants in IDRs and IDPs.},

note = {Cited by: 0; Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SCOPUS_ID:105027746750,

title = {The Gene Ontology knowledgebase in 2026},

author = {Suzi A Aleksander and James P Balhoff and Seth Carbon and J. Michael Cherry and Dustin Ebert and Marc Feuermann and Pascale Gaudet and Nomi L Harris and David P Hill and Patrick Kalita and Raymond Lee and Huaiyu Mi and Sierra Moxon and Christopher J Mungall and Anushya Muruganujan and Tremayne Mushayahama and Paul W Sternberg and Paul D Thomas and Kimberly Van Auken and Edith D Wong and Valerie Wood and Jolene Ramsey and Deborah A Siegele and Rex L Chisholm and Robert Dodson and Petra Fey and Maria Cristina Aspromonte and Maria Victoria Nugnes and Ximena Aixa Castro Naser and Silvio C. E Tosatto and Michelle Giglio and Suvarna Nadendla and Giulia Antonazzo and Helen Attrill and Nicholas H Brown and Gil Dos Santos and Steven Marygold and Katja Röper and Victor Strelets and Christopher J Tabone and Jim Thurmond and Pinglei Zhou and Rossana Zaru and Ruth C Lovering and Colin Logie and Daqing Chen and Alexandra Naba and Karen Christie and Lori Corbani and Li Ni and Dmitry Sitnikov and Cynthia Smith and James Seager and Laurel Cooper and Justin Elser and Pankaj Jaiswal and Parul Gupta and Sushma Naithani and Pascal Carme and Kim Rutherford and Jeffrey L De Pons and Melinda R Dwinell and G. Thomas Hayman and Mary L Kaldunski and Anne E Kwitek and Stanley J. F Laulederkind and Marek A Tutaj and Mahima Vedi and Shur-Jen Wang and Peter D'Eustachio and Lucila Aimo and Kristian Axelsen and Alan Bridge and Nevila Hyka-Nouspikel and Anne Morgat and Gene Goldbold and Stacia R Engel and Stuart R Miyasato and Robert S Nash and Gavin Sherlock and Shuai Weng and Erika Bakker and Tanya Z Berardini and Leonore Reiser and Andrea Auchincloss and Ghislaine Argoud-Puy and Marie-Claude Blatter and Emmanuel Boutet and Lionel Breuza and Cristina Casals-Casas and Elisabeth Coudert and Anne Estreicher and Maria Livia Famiglietti and Arnaud Gos and Nadine Gruaz-Gumowski and Chantal Hulo and Florence Jungo and Philippe Le Mercier and Damien Lieberherr and Patrick Masson and ...},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-105027746750&origin=inward},

doi = {10.1093/nar/gkaf1292},

year  = {2026},

date = {2026-01-01},

journal = {Nucleic Acids Research},

volume = {54},

number = {D1},

pages = {D1779-D1792},

publisher = {Oxford University Press},

abstract = {© 2025 The Author(s). Published by Oxford University Press.The Gene Ontology (GO) knowledgebase (https://geneontology.org) is a comprehensive resource describing the functions of genes. The GO knowledgebase is regularly updated and improved. We describe here the major updates that have been made in the past 3 years. The ontology and annotations have been expanded and revised, particularly in several areas of biology: cellular metabolism, multi-organism interactions (e.g. host-pathogen), extracellular matrix proteins, chromatin remodeling (e.g. the "histone code"), and noncoding RNA functions. We have released version 2 of a comprehensive set of integrated, reviewed annotations for human genes, which we call the "functionome."We have also dramatically increased the number of GO-CAM models, with over 1500 models of metabolic and signaling pathways, primarily in human, mouse, budding and fission yeast, and fruit fly. Finally, we discuss our current recommendations and future prospects of AI in the use and development of GO.},

note = {Cited by: 5; Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SCOPUS_ID:85217180047,

title = {CAGI6 ID panel challenge: assessment of phenotype and variant predictions in 415 children with neurodevelopmental disorders (NDDs)},

author = {Maria Cristina Aspromonte and Alessio Del Conte and Shaowen Zhu and Wuwei Tan and Yang Shen and Yexian Zhang and Qi Li and Maggie Haitian Wang and Giulia Babbi and Samuele Bovo and Pier Luigi Martelli and Rita Casadio and Azza Althagafi and Sumyyah Toonsi and Maxat Kulmanov and Robert Hoehndorf and Panagiotis Katsonis and Amanda Williams and Olivier Lichtarge and Su Xian and Wesley Surento and Vikas Pejaver and Sean D. Mooney and Uma Sunderam and Rajgopal Srinivasan and Alessandra Murgia and Damiano Piovesan and Silvio C. E. Tosatto and Emanuela Leonardi},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-85217180047&origin=inward},

doi = {10.1007/s00439-024-02722-w},

year  = {2025},

date = {2025-01-01},

journal = {Human Genetics},

volume = {144},

number = {2},

pages = {227-242},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {© The Author(s) 2025.The Genetics of Neurodevelopmental Disorders Lab in Padua provided a new intellectual disability (ID) Panel challenge for computational methods to predict patient phenotypes and their causal variants in the context of the Critical Assessment of the Genome Interpretation, 6th edition (CAGI6). Eight research teams submitted a total of 30 models to predict phenotypes based on the sequences of 74 genes (VCF format) in 415 pediatric patients affected by Neurodevelopmental Disorders (NDDs). NDDs are clinically and genetically heterogeneous conditions, with onset in infant age. Here, we assess the ability and accuracy of computational methods to predict comorbid phenotypes based on clinical features described in each patient and their causal variants. We also evaluated predictions for possible genetic causes in patients without a clear genetic diagnosis. Like the previous ID Panel challenge in CAGI5, seven clinical features (ID, ASD, ataxia, epilepsy, microcephaly, macrocephaly, hypotonia), and variants (Pathogenic/Likely Pathogenic, Variants of Uncertain Significance and Risk Factors) were provided. The phenotypic traits and variant data of 150 patients from the CAGI5 ID Panel Challenge were provided as training set for predictors. The CAGI6 challenge confirms CAGI5 results that predicting phenotypes from gene panel data is highly challenging, with AUC values close to random, and no method able to predict relevant variants with both high accuracy and precision. However, a significant improvement is noted for the best method, with recall increasing from 66% to 82%. Several groups also successfully predicted difficult-to-detect variants, emphasizing the importance of variants initially excluded by the Padua NDD Lab.},

note = {Cited by: 2; Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SCOPUS_ID:105022934716,

title = {Comprehensive Analysis of the Putative Substratome of FAM20C, the Master Serine Kinase of the Secretory Pathway},

author = {Luca Cesaro and Francesca Noventa and Trinidad De Los Angeles Cordero and Barbara Molon and Valentina Bosello Travain and Maria Cristina Aspromonte and Mauro Salvi},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-105022934716&origin=inward},

doi = {10.3390/biom15111582},

year  = {2025},

date = {2025-01-01},

journal = {Biomolecules},

volume = {15},

number = {11},

publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},

abstract = {© 2025 by the authors.FAM20C, previously known as Golgi casein kinase (GCK), is a serine/threonine kinase localized to the Golgi apparatus and classified within the acidophilic kinase family. Its phosphorylation motif is characterized by a glutamic acid residue at the +2 position relative to the target site. Before its molecular identity was established, analysis of a limited number of phosphosites in secreted proteins showed that around 70% matched the GCK consensus sequence, suggesting that GCK is the principal kinase for secreted proteins. Following the identification of GCK as FAM20C, the generation of FAM20C knockout cell lines and phosphoproteomic data confirmed its role: approximately 80% of serine/threonine phosphosites in the secretome of two different human cell lines were shown to depend on FAM20C. In this study, comparative analysis of in vitro phosphorylation datasets from a broad panel of recombinant Ser/Thr kinases confirmed that the FAM20C consensus sequence is distinct from those of other acidophilic kinases. Examination of experimentally identified human phosphosites within the secretory pathway revealed strong conservation of the FAM20C consensus, firmly establishing this enzyme as the master Ser kinase of the entire pathway. From this dataset, we defined the putative FAM20C substratome, comprising 443 phosphosites across 256 proteins, textasciitilde 77% of which had not been previously linked to FAM20C. This represents the most extensive FAM20C substratome to date and a valuable resource for functional studies. Notably, enrichment analysis highlights strong links between FAM20C and major extracellular pathways, including collagen fibril organization, complement activation, and blood coagulation, underscoring an underappreciated role for this kinase in regulating hemostasis and innate immunity.},

note = {Cited by: 0; Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SCOPUS_ID:85213063415,

title = {MOBIDB in 2025: integrating ensemble properties and function annotations for intrinsically disordered proteins},

author = {Damiano Piovesan and Alessio Del Conte and Mahta Mehdiabadi and Maria Cristina Aspromonte and Matthias Blum and Giulio Tesei and Sören Bülow and Kresten Lindorff-Larsen and Silvio C. E. Tosatto},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-85213063415&origin=inward},

doi = {10.1093/nar/gkae969},

year  = {2025},

date = {2025-01-01},

journal = {Nucleic Acids Research},

volume = {53},

number = {D1},

pages = {D495-D503},

publisher = {Oxford University Press},

abstract = {© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.The MobiDB database (URL: https://mobidb.org/) aims to provide structural and functional information about intrinsic protein disorder, aggregating annotations from the literature, experimental data, and predictions for all known protein sequences. Here, we describe the improvements made to our resource to capture more information, simplify access to the aggregated data, and increase documentation of all MobiDB features. Compared to the previous release, all underlying pipeline modules were updated. The prediction module is ten times faster and can detect if a predicted disordered region is structurally extended or compact. The PDB component is now able to process large cryo-EM structures extending the number of processed entries. The entry page has been restyled to highlight functional aspects of disorder and all graphical modules have been completely reimplemented for better flexibility and faster rendering. The server has been improved to optimise bulk downloads. Annotation provenance has been standardised by adopting ECO terms. Finally, we propagated disorder function (IDPO and GO terms) from the DisProt database exploiting sequence similarity and protein embeddings. These improvements, along with the addition of comprehensive training material, offer a more intuitive interface and novel functional knowledge about intrinsic disorder.},

note = {Cited by: 34; Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SCOPUS_ID:105025851995,

title = {Fostering and sustaining collaborative innovation: Insights from ELIXIR Europe's life science Communities},

author = {Clare Garrard and Katharina F Heil and Maria Cristina Aspromonte and Bérénice Batut and Magda Chegkazi and John M Hancock and Elaine Harrison and Naveed Ishaque and Giselle Kerry and Eija Korpelainen and Jerry Lanfear and Corinne Martin and Sebastian Schaaf and Serena Scollen and Yun-Yun Tseng and Sameer Velankar and Juan Antonio Vizcaíno and Robert M Waterhouse and Egon Willighagen and Niklas Blomberg and Peter Maccallum},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-105025851995&origin=inward},

doi = {10.12688/f1000research.168288.1},

year  = {2025},

date = {2025-01-01},

journal = {F1000Research},

volume = {14},

publisher = {F1000 Research Ltd},

abstract = {Copyright: © 2025 Garrard C et al.Communities of experts collaborating on scientific or technical projects are drivers of innovation across the life sciences. The ELIXIR research infrastructure organises scientific- and technological-themed communities as one of its key mechanisms to ensure that services are user-focused, while at the same time facilitating collaboration and creating scientific impact through the life science data generated across Europe. ELIXIR has rapidly expanded its communities portfolio in response to unmet needs and has developed a comprehensive process framework to facilitate the work of these communities. The ELIXIR Communities framework is made up of a suite of tools and processes that ensure effective community evolution and management, covering how communities are established, led, supported, and can collaborate across ELIXIR and beyond. Being aware of similar approaches in other contexts and in the interests of furthering community development in other research infrastructures and similar organisations, we share insights into the ELIXIR Communities framework and outline the skill set of a community manager and what this looks like in the ELIXIR context. Finally, to show the benefits of the communities, we share concrete examples of how the ELIXIR Communities have had an impact on the scientific landscape. By showcasing these outcomes we hope to demonstrate not only to other research infrastructures, but also to funders, that supporting scientific communities provides a valuable return on investment. We hope that these examples will encourage life scientists who may be interested in joining the ELIXIR Communities, and research infrastructure professionals whose roles require structured engagement with domain experts and users.},

note = {Cited by: 0; Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SCOPUS_ID:86000084600,

title = {Genetic variants and phenotypic data curated for the CAGI6 intellectual disability panel challenge},

author = {Maria Cristina Aspromonte and Alessio Del Conte and Roberta Polli and Demetrio Baldo and Francesco Benedicenti and Elisa Bettella and Stefania Bigoni and Stefania Boni and Claudia Ciaccio and Stefano D’Arrigo and Ilaria Donati and Elisa Granocchio and Isabella Mammi and Donatella Milani and Susanna Negrin and Margherita Nosadini and Fiorenza Soli and Franco Stanzial and Licia Turolla and Damiano Piovesan and Silvio C. E. Tosatto and Alessandra Murgia and Emanuela Leonardi},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-86000084600&origin=inward},

doi = {10.1007/s00439-025-02733-1},

year  = {2025},

date = {2025-01-01},

journal = {Human Genetics},

volume = {144},

number = {2},

pages = {309-326},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {© The Author(s) 2025.Neurodevelopmental disorders (NDDs) are common conditions including clinically diverse and genetically heterogeneous diseases, such as intellectual disability, autism spectrum disorders, and epilepsy. The intricate genetic underpinnings of NDDs pose a formidable challenge, given their multifaceted genetic architecture and heterogeneous clinical presentations. This work delves into the intricate interplay between genetic variants and phenotypic manifestations in neurodevelopmental disorders, presenting a dataset curated for the Critical Assessment of Genome Interpretation (CAGI6) ID Panel Challenge. The CAGI6 competition serves as a platform for evaluating the efficacy of computational methods in predicting phenotypic outcomes from genetic data. In this study, a targeted gene panel sequencing has been used to investigate the genetic causes of NDDs in a cohort of 415 paediatric patients. We identified 60 pathogenic and 49 likely pathogenic variants in 102 individuals that accounted for 25% of NDD cases in the cohort. The most mutated genes were ANKRD11, MECP2, ARID1B, ASH1L, CHD8, KDM5C, MED12 and PTCHD1 The majority of pathogenic variants were de novo, with some inherited from mildly affected parents. Loss-of-function variants were the most common type of pathogenic variant. In silico analysis tools were used to assess the potential impact of variants on splicing and structural/functional effects of missense variants. The study highlights the challenges in variant interpretation especially in cases with atypical phenotypic manifestations. Overall, this study provides valuable insights into the genetic causes of NDDs and emphasises the importance of understanding the underlying genetic factors for accurate diagnosis, and intervention development in neurodevelopmental conditions.},

note = {Cited by: 3; Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SCOPUS_ID:85176208048,

title = {DisProt in 2024: improving function annotation of intrinsically disordered proteins},

author = {Maria Cristina Aspromonte and Maria Victoria Nugnes and Federica Quaglia and Adel Bouharoua and Silvio C. E. Tosatto and Damiano Piovesan and Vasileios Sagris and Vasilis J. Promponas and Anastasia Chasapi and Erzsébet Fichó and Galo E. Balatti and Gustavo Parisi and Martín González Buitrón and Gabor Erdos and Matyas Pajkos and Zsuzsanna Dosztányi and Laszlo Dobson and Alessio Del Conte and Damiano Clementel and Edoardo Salladini and Emanuela Leonardi and Fatemeh Kordevani and Hamidreza Ghafouri and Luiggi G. Tenorio Ku and Alexander Miguel Monzon and Carlo Ferrari and Zsófia Kálmán and Juliet F. Nilsson and Jaime Santos and Carlos Pintado-Grima and Salvador Ventura and Veronika Ács and Rita Pancsa and Mariane Goncalves Kulik and Miguel A. Andrade-Navarro and Pedro José Barbosa Pereira and Sonia Longhi and Philippe Le Mercier and Julian Bergier and Peter Tompa and Tamas Lazar},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-85176208048&origin=inward},

doi = {10.1093/nar/gkad928},

year  = {2024},

date = {2024-01-01},

journal = {Nucleic Acids Research},

volume = {52},

number = {D1},

pages = {D434-D441},

publisher = {Oxford University Press},

abstract = {© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.DisProt (URL: https://disprot.org) is the gold standard database for intrinsically disordered proteins and regions, providing valuable information about their functions. The latest version of DisProt brings significant advancements, including a broader representation of functions and an enhanced curation process. These improvements aim to increase both the quality of annotations and their coverage at the sequence level. Higher coverage has been achieved by adopting additional evidence codes. Quality of annotations has been improved by systematically applying Minimum Information About Disorder Experiments (MIADE) principles and reporting all the details of the experimental setup that could potentially influence the structural state of a protein. The DisProt database now includes new thematic datasets and has expanded the adoption of Gene Ontology terms, resulting in an extensive functional repertoire which is automatically propagated to UniProtKB. Finally, we show that DisProt’s curated annotations strongly correlate with disorder predictions inferred from AlphaFold2 pLDDT (predicted Local Distance Difference Test) confidence scores. This comparison highlights the utility of DisProt in explaining apparent uncertainty of certain well-defined predicted structures, which often correspond to folding-upon-binding fragments. Overall, DisProt serves as a comprehensive resource, combining experimental evidence of disorder information to enhance our understanding of intrinsically disordered proteins and their functional implications.},

note = {Cited by: 94; Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}