@article{SCOPUS_ID:105035676703,

title = {Effects of Mutations on Tandem-Repeat Proteins Conformation Mechanisms. Application to the Phosphatase PP2A},

author = {Matias Chiappinelli and Tadeo E. Saldaño and Silvio C E Tosatto and Sergei Grudinin and Gustavo Parisi and Sebastian Fernandez-Alberti},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-105035676703&origin=inward},

doi = {10.1021/acs.jcim.6c00133},

year  = {2026},

date = {2026-01-01},

journal = {Journal of chemical information and modeling},

volume = {66},

number = {7},

pages = {3976-3986},

abstract = {Tandem repeat proteins (TRPs) are composed of arrays of repeating structural units that assemble into extended, superhelical, or horseshoe-shaped architectures stabilized primarily by short-range interactions. The unique sequence-structure-dynamics-function relationships of TRPs have been the subject of extensive investigation, aiming to elucidate the molecular principles that distinguish them from globular proteins. Here we explore the effects of mutations on conformational mechanics of PR65, the HEAT-repeat scaffold of phosphatase PP2A that acts as an elastic connector between catalytic and regulatory subunits. We found that the effect of mutations on dynamics, that is associated with the collective conformational changes experienced by PR65 in its binding to the catalytic subunit, correlates with its evolutionary conservation. Besides, our study reveals a common pattern among repeat units in how mutations influence these dynamics, but it also highlights functional differences among the individual units. That is, mutations on individual units preserve a common influence on the collective dynamics of the TRP but their individual participation in function introduces additional differences in their corresponding effects of mutations. Finally, none of these aspects are observed for the subsequent conformational changes experienced during the binding of the dimer PR65-catalytic subunit complex with the regulatory subunit. We believe this work highlights both the similarities and differences between repeat units in how mutations affect their dynamics─insights that may advance our understanding of TRP mechanisms in pathogenicity─enable scaffold modifications for engineered ligand binding with diverse applications, and broadly expand our knowledge of TRP function.},

note = {Cited by: 0},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SCOPUS_ID:105033760847,

title = {Tandem repeats matter for the functional versatility of giant proteins},

author = {Zarifa Osmanli and Alexander Miguel Monzon and Silvio C. E. Tosatto},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-105033760847&origin=inward},

doi = {10.1016/j.tibs.2026.02.010},

year  = {2026},

date = {2026-01-01},

journal = {Trends in Biochemical Sciences},

publisher = {Elsevier Ltd},

abstract = {© 2026 Elsevier LtdGiant proteins play essential cellular roles but remain structurally challenging. Recent advances in structure determination and modeling reveal that tandem repeats are widespread in large proteins, providing modularity, adaptability, and multifunctionality. Examples including apolipoprotein B100, teneurins, and ryanodine receptors illustrate how repetition drives structural flexibility, regulatory precision, and evolutionary innovation.},

note = {Cited by: 0},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SCOPUS_ID:105030612709,

title = {Empowering biological knowledgebases: advances in human-in-the-loop AI-driven literature curation},

author = {Valerie Wood and Matt Jeffryes and Andrew F. Green and Matthias Blum and Sandra Orchard and Simona Panni and Federica Quaglia and Raul Rodriguez-Esteban and James Seager and Silvio C. E. Tosatto and Ulrike Wittig and Melissa Harrison},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-105030612709&origin=inward},

doi = {10.1093/bioadv/vbag028},

year  = {2026},

date = {2026-01-01},

journal = {Bioinformatics Advances},

volume = {6},

number = {1},

publisher = {Oxford University Press},

abstract = {© The Author(s) 2026. Published by Oxford University Press.Biological knowledgebases facilitate discovery across the life sciences by structuring experimental findings into human-readable and computable formats. These essential resources are maintained by a small number of professional biocurators worldwide and face combined chronic underfunding and the exponential growth of the literature. In this perspective, we review how artificial intelligence, particularly large language models and agentic systems, can augment literature-curation workflows. Applications include literature recommendation, entity recognition, data extraction, summarization, ontology development, and quality control with emphasis on published use cases at Global Core BioData Resources and ELIXIR Core Data Resources. We identify key challenges, including the scarcity of training data, difficulty in extracting complex relationships, and concerns about error propagation. To address these challenges, we propose a human-in-the-loop framework where generative artificial intelligence approaches accelerate routine tasks while curators provide critical evaluation and domain expertise. We also propose practical recommendations for the community, including the creation of shared benchmark datasets, harmonized evaluation frameworks, and best-practice guidelines for transparent human-in-the-loop AI deployment in biocuration. These synergistic partnerships will be critical to ensure biological rigour, accelerating knowledge integration while maintaining the quality essential for trusted biological resources.},

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: 9; Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SCOPUS_ID:105033513263,

title = {The missing link in FAIR data policy: biodata resources in life sciences},

author = {Lucy Poveda and Gavin Farrell and Silvio C. E. Tosatto and Monique Zahn-Zabal and Patrick Ruch and Julien Gobeill and Robert M. Waterhouse and Christophe Dessimoz},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-105033513263&origin=inward},

doi = {10.1038/s41597-026-06690-w},

year  = {2026},

date = {2026-01-01},

journal = {Scientific Data},

volume = {13},

number = {1},

publisher = {Nature Research},

abstract = {© The Author(s) 2026.In the life sciences, FAIR principles have reshaped research policy, but their implementation still relies largely on individual researchers – many of whom lack the expertise or support needed to make data truly reusable. Realising FAIR’s promise requires sustained investment in the infrastructures that organise, standardise, and curate data: deposition databases and knowledgebases. These biodata resources are especially critical for AI, which depends on large, high-quality, and consistent data. Landmark advances like AlphaFold and the COVID-19 response illustrate how sustained curation and standardisation in expert resources such as UniProt and the Protein Data Bank have enabled rapid innovation. Yet biodata resources remain precariously funded, jeopardising long-term sustainability and the expert workforce they require. To support ambitious, data-driven science, funders must align policy and budgets by establishing dedicated mechanisms that allocate a small (e.g., 1%), but strategic and stable share, of research funding to core data infrastructures. This would maximise the value of public investment, strengthen open science and international collaboration, and unlock the full potential of FAIR.},

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

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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:105029446962,

title = {Honokiol blocks tumor development and metastasis through mitochondrion-targeted effects},

author = {Martina Grandi and Francesco Boldrin and Giovanni Risato and Silvia Grillini and Natascia Tiso and Francesco Argenton and Emanuela Leonardi and Silvio Tosatto and Giancarlo Solaini and Alessandra Baracca and Valentina Giorgio},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-105029446962&origin=inward},

doi = {10.1038/s41419-026-08441-6},

year  = {2026},

date = {2026-01-01},

journal = {Cell Death and Disease},

volume = {17},

number = {1},

publisher = {Springer Nature},

abstract = {© The Author(s) 2026.IF1 is the natural inhibitor of the mitochondrial ATP synthase during hydrolytic activity. It has been found to be overexpressed in many tumors, where it acts as a pro-oncogenic protein. During oxidative phosphorylation, IF1 binds to a novel site on the OSCP subunit of ATP synthase and promotes tumorigenesis by protecting cancer cells from permeability transition pore (PTP)-dependent apoptosis. In this work, honokiol, a biphenolic compound, showed binding affinity for two sites on the OSCP subunit, as predicted by molecular docking analysis. It was shown to be effective in disrupting the IF1-OSCP interaction and sensitizing cancer cells to apoptosis. In vivo, xenografts of zebrafish injected with IF1-expressing HeLa cells showed tumor development. The same xenografts, treated with honokiol, showed a significant reduction in tumor mass, similar to untreated fish injected with IF1 KO HeLa cells. In vitro, honokiol inhibits colony formation in soft agar of IF1-expressing HeLa cells by promoting the PTP opening and cell death, without any effect on cell proliferation. Interestingly, honokiol was shown to block metastasis in fish xenografts and migration in a wound healing assay, by promoting mitochondrial swelling in both control and IF1 KO cell lines, when cells are moving to close the scratch area. In conclusion, honokiol appears to be a promising anti-cancer compound, with pro-apoptotic properties through the displacement of IF1 from the OSCP subunit of ATP synthase, and anti-metastatic effects that are due to mitochondrial PTP opening.},

note = {Cited by: 1; Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SCOPUS_ID:105034672381,

title = {STRPsearch Web Server: A User-friendly Interface for Rapid and Accurate Prediction of Structured Tandem Repeat Proteins},

author = {Yousra Hind Bouhraoua and Zarifa Osmanli and Silvio C. E. Tosatto and Alexander Miguel Monzon},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-105034672381&origin=inward},

doi = {10.1016/j.jmb.2026.169755},

year  = {2026},

date = {2026-01-01},

journal = {Journal of Molecular Biology},

publisher = {Academic Press},

abstract = {© 2026 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/AbstractStructured Tandem Repeat Proteins (STRPs) are a subset of repeat proteins characterized by recurring structural motifs, even in cases where sequence similarity between repeats is very low. Despite substantial sequence variability, STRPs preserve conserved secondary-structure elements that underpin a wide range of biological functions. Although millions of protein structures are now publicly available, the accurate detection of STRPs remains challenging. STRPsearch is a recently developed tool for the rapid identification and classification of STRPs. Here, we introduce the STRPsearch web server, an enhanced implementation featuring a user-friendly interface. The server is freely available https://strpsearch.biocomputingup.it/.},

note = {Cited by: 0; 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:105034187048,

title = {Toward a unified framework for determining conformational ensembles of disordered proteins},

author = {Hamidreza Ghafouri and Pavel Kadeřávek and Ana M. Melo and Maria Cristina Aspromonte and Pau Bernadó and Juan Cortés and Zsuzsanna Dosztányi and Gábor Erdős and Michael Feig and Giacomo Janson and Kresten Lindorff-Larsen and Frans A. A. Mulder and Peter Nagy and Richard Pestell and Damiano Piovesan and Marco Schiavina and Benjamin Schuler and Nathalie Sibille and Giulio Tesei and Peter Tompa and Michele Vendruscolo and Jiri Vondrasek and Wim Vranken and Lukas Zidek and Silvio C. E. Tosatto and Alexander Miguel Monzon},

url = {https://www.scopus.com/record/display.uri?eid=2-s2.0-105034187048&origin=inward},

doi = {10.1038/s41592-026-03003-2},

year  = {2026},

date = {2026-01-01},

journal = {Nature Methods},

volume = {23},

number = {4},

pages = {705-719},

publisher = {Nature Research},

abstract = {© Springer Nature America, Inc. 2026.Disordered proteins play essential roles in myriad cellular processes, yet their structural characterization remains a major challenge due to their dynamic and heterogeneous nature. Here we present a community-driven initiative to address this problem by advocating a unified framework for determining conformational ensembles of disordered proteins. Our aim is to integrate state-of-the-art experimental techniques with advanced computational methods, including knowledge-based sampling, enhanced molecular dynamics and machine learning models. The modular framework comprises three interconnected components: experimental data acquisition, computational ensemble generation and validation. The systematic development of this framework will ensure the accurate and reproducible determination of conformational ensembles of disordered proteins. We highlight the open challenges necessary to achieve this goal, including force-field accuracy, efficient sampling, and environmental dependence, advocating for collaborative benchmarking and standardized protocols.},

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

keywords = {},

pubstate = {published},

tppubtype = {article}

}