publications

@article{Aleksander2023,

title = {The Gene Ontology knowledgebase in 2023},

author = {Suzi A. Aleksander and James Balhoff and Seth Carbon and J. Michael Cherry and Harold J. Drabkin and Dustin Ebert and Marc Feuermann and Pascale Gaudet and Nomi L. Harris and David P. Hill and Raymond Lee and Huaiyu Mi and Sierra Moxon and Christopher J. Mungall and Anushya Muruganugan and Tremayne Mushayahama and Paul W. Sternberg and Paul D. Thomas and Kimberly Van Auken and Jolene Ramsey and Deborah A. Siegele and Rex L. Chisholm and Petra Fey and Maria Cristina Aspromonte and Maria Victoria Nugnes and Federica Quaglia and Silvio Tosatto and Michelle Giglio and Suvarna Nadendla and Giulia Antonazzo and Helen Attrill and Gil Dos Santos and Steven Marygold and Victor Strelets and Christopher J. Tabone and Jim Thurmond and Pinglei Zhou and Saadullah H. Ahmed and Praoparn Asanitthong and Diana Luna Buitrago and Meltem N. Erdol and Matthew C. Gage and Mohamed Ali Kadhum and Kan Yan Chloe Li and Miao Long and Aleksandra Michalak and Angeline Pesala and Armalya Pritazahra and Shirin C. C. Saverimuttu and Renzhi Su and Kate E. Thurlow and Ruth C Lovering and Colin Logie and Snezhana Oliferenko and Judith Blake and Karen Christie and Lori Corbani and Mary E. Dolan and Li Ni and Dmitry Sitnikov and Cynthia Smith and Alayne Cuzick and James Seager and Laurel Cooper and Justin Elser and Pankaj Jaiswal and Parul Gupta and Sushma Naithani and Manuel Lera-Ramirez and Kim Rutherford and Valerie Wood 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 Stacia R. Engel and Kalpana Karra and Stuart R. Miyasato and Robert S. Nash and Marek S. Skrzypek and Shuai Weng and Edith D. Wong 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 Ivo Pedruzzi and Lucille Pourcel and Sylvain Poux and Catherine Rivoire and Shyamala Sundaram and Alex Bateman and Emily Bowler-Barnett and Hema Bye-A-Jee and Paul Denny and Alexandr Ignatchenko and Rizwan Ishtiaq and Antonia Lock and Yvonne Lussi and Michele Magrane and Maria J. Martin and Sandra Orchard and Pedro Raposo and Elena Speretta and Nidhi Tyagi and Kate Warner and Rossana Zaru and Alexander D. Diehl and Juancarlos Chan and Stavros Diamantakis and Daniela Raciti and Magdalena Zarowiecki and Malcolm Fisher and Christina James-Zorn and Virgilio Ponferrada and Aaron Zorn and Sridhar Ramachandran and Leyla Ruzicka and Monte Westerfield},

url = {https://www.scopus.com/pages/publications/85164785564?origin=resultslist},

doi = {10.1093/genetics/iyad031},

issn = {00166731},

year  = {2023},

date = {2023-01-01},

journal = {Genetics},

volume = {224},

number = {1},

publisher = {Oxford University Press},

abstract = {The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO - a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations - evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs) - mechanistic models of molecular "pathways"(GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project. © 2023 The Author(s). Published by Oxford University Press on behalf of The Genetics Society of America.},

note = {Cited by: 2453; All Open Access; Green Open Access; Hybrid Gold Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Vos2023351,

title = {DNA methylation episignatures are sensitive and specific biomarkers for detection of patients with KAT6A/KAT6B variants},

author = {Niels Vos and Jack Reilly and Mariet W Elting and Philippe M Campeau and David Coman and Zornitza Stark and Tiong Yang Tan and David J Amor and Simran Kaur and Miya Stjohn and Angela T Morgan and Benjamin A Kamien and Chirag Patel and Matthew L Tedder and Giuseppe Merla and Paolo Prontera and Marco Castori and Kai Muru and Felicity Collins and John Christodoulou and Janine Smith and Bruria Ben Zeev and Alessandra Murgia and Emanuela Leonardi and Natacha Esber and Antonio Martinez-Monseny and Didac Casas-Alba and Matthew Wallis and Marcel Mannens and Michael A Levy and Raissa Relator and Marielle Alders and Bekim Sadikovic},

url = {https://www.scopus.com/pages/publications/85160965403?origin=resultslist},

doi = {10.2217/epi-2023-0079},

issn = {17501911},

year  = {2023},

date = {2023-01-01},

journal = {Epigenomics},

volume = {15},

number = {6},

pages = {351 - 367},

publisher = {Newlands Press Ltd},

abstract = {Accurate diagnosis for patients living with neurodevelopmental disorders is often met with numerous challenges, related to the ambiguity of findings and lack of specificity in genetic variants leading to pathology. Genome-wide DNA methylation analysis has been used to develop highly sensitive and specific 'episignatures' as biomarkers capable of differentiating and classifying complex neurodevelopmental disorders. In this study we describe distinct episignatures for KAT6A syndrome, caused by pathogenic variants in the lysine acetyltransferase A gene (KAT6A), and for the two neurodevelopmental disorders associated with lysine acetyl transferase B (KAT6B). We demonstrate the ability of our models to differentiate between highly overlapping episignatures, increasing the ability to effectively identify and diagnose these conditions. © 2023 Future Medicine Ltd.},

note = {Cited by: 8; All Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DelConte2023,

title = {RING-PyMOL: residue interaction networks of structural ensembles and molecular dynamics},

author = {Alessio Del Conte and Alexander Miguel Monzon and Damiano Clementel and Giorgia F. Camagni and Giovanni Minervini and Silvio C. E. Tosatto and Damiano Piovesan},

url = {https://www.scopus.com/pages/publications/85159553803?origin=resultslist},

doi = {10.1093/bioinformatics/btad260},

issn = {13674803},

year  = {2023},

date = {2023-01-01},

journal = {Bioinformatics},

volume = {39},

number = {5},

publisher = {Oxford University Press},

abstract = {RING-PyMOL is a plugin for PyMOL providing a set of analysis tools for structural ensembles and molecular dynamic simulations. RING-PyMOL combines residue interaction networks, as provided by the RING software, with structural clustering to enhance the analysis and visualization of the conformational complexity. It combines precise calculation of non-covalent interactions with the power of PyMOL to manipulate and visualize protein structures. The plugin identifies and highlights correlating contacts and interaction patterns that can explain structural allostery, active sites, and structural heterogeneity connected with molecular function. It is easy to use and extremely fast, processing and rendering hundreds of models and long trajectories in seconds. RING-PyMOL generates a number of interactive plots and output files for use with external tools. The underlying RING software has been improved extensively. It is 10 times faster, can process mmCIF files and it identifies typed interactions also for nucleic acids. © The Author(s) 2023. Published by Oxford University Press.},

note = {Cited by: 32; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Hatos2023W198,

title = {FuzPred: A web server for the sequence-based prediction of the context-dependent binding modes of proteins},

author = {Andras Hatos and João M. C Teixeira and Susana Barrera-Vilarmau and Attila Horvath and Silvio C. E Tosatto and Michele Vendruscolo and Monika Fuxreiter},

url = {https://www.scopus.com/pages/publications/85164245294?origin=resultslist},

doi = {10.1093/nar/gkad214},

issn = {03051048},

year  = {2023},

date = {2023-01-01},

journal = {Nucleic Acids Research},

volume = {51},

number = {W1},

pages = {W198 - W206},

publisher = {Oxford University Press},

abstract = {Proteins form complex interactions in the cellular environment to carry out their functions. They exhibit a wide range of binding modes depending on the cellular conditions, which result in a variety of ordered or disordered assemblies. To help rationalise the binding behavior of proteins, the FuzPred server predicts their sequence-based binding modes without specifying their binding partners. The binding mode defines whether the bound state is formed through a disorder-To-order transition resulting in a well-defined conformation, or through a disorder-To-disorder transition where the binding partners remain conformationally heterogeneous. To account for the context-dependent nature of the binding modes, the FuzPred method also estimates the multiplicity of binding modes, the likelihood of sampling multiple binding modes. Protein regions with a high multiplicity of binding modes may serve as regulatory sites or hot-spots for structural transitions in the assembly. To facilitate the interpretation of the predictions, protein regions with different interaction behaviors can be visualised on protein structures generated by AlphaFold. The FuzPred web server (https://fuzpred.bio.unipd.it) thus offers insights into the structural and dynamical changes of proteins upon interactions and contributes to development of structure-function relationships under a variety of cellular conditions. © 2023 The Author(s). Published by Oxford University Press on behalf of Nucleic Acids Research.},

note = {Cited by: 20; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Mészáros20231291,

title = {Minimum information guidelines for experiments structurally characterizing intrinsically disordered protein regions},

author = {Bálint Mészáros and András Hatos and Nicolas Palopoli and Federica Quaglia and Edoardo Salladini and Kim Van Roey and Haribabu Arthanari and Zsuzsanna Dosztányi and Isabella C. Felli and Patrick D. Fischer and Jeffrey C. Hoch and Cy M. Jeffries and Sonia Longhi and Emiliano Maiani and Sandra Orchard and Rita Pancsa and Elena Papaleo and Roberta Pierattelli and Damiano Piovesan and Iva Pritisanac and Luiggi Tenorio and Thibault Viennet and Peter Tompa and Wim Vranken and Silvio C. E. Tosatto and Norman E. Davey},

url = {https://www.scopus.com/pages/publications/85164196588?origin=resultslist},

doi = {10.1038/s41592-023-01915-x},

issn = {15487091},

year  = {2023},

date = {2023-01-01},

journal = {Nature Methods},

volume = {20},

number = {9},

pages = {1291 - 1303},

publisher = {Nature Research},

abstract = {An unambiguous description of an experiment, and the subsequent biological observation, is vital for accurate data interpretation. Minimum information guidelines define the fundamental complement of data that can support an unambiguous conclusion based on experimental observations. We present the Minimum Information About Disorder Experiments (MIADE) guidelines to define the parameters required for the wider scientific community to understand the findings of an experiment studying the structural properties of intrinsically disordered 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. 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 standardize the dissemination of the key metadata on an IDR experiment by IDR data sources. © 2023, Springer Nature America, Inc.},

note = {Cited by: 18; All Open Access; Bronze Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Gehin2023,

title = {CERT1 mutations perturb human development by disrupting sphingolipid homeostasis},

author = {Charlotte Gehin and Museer A. Lone and Winston Lee and Laura Capolupo and Sylvia Ho and Adekemi M. Adeyemi and Erica H. Gerkes and Alexander P. A. Stegmann and Estrella López-Martín and Eva Bermejo-Sánchez and Beatriz Martínez-Delgado and Christiane Zweier and Cornelia Kraus and Bernt Popp and Vincent Strehlow and Daniel Gräfe and Ina Knerr and Eppie R. Jones and Stefano Zamuner and Luciano A. Abriata and Vidya Kunnathully and Brandon E. Moeller and Anthony Vocat and Samuel Rommelaere and Jean-Philippe Bocquete and Evelyne Ruchti and Greta Limoni and Marine Van Campenhoudt and Samuel Bourgeat and Petra Henklein and Christian Gilissen and Bregje W. Bon and Rolph Pfundt and Marjolein H. Willemsen and Jolanda H. Schieving and Emanuela Leonardi and Fiorenza Soli and Alessandra Murgia and Hui Guo and Qiumeng Zhang and Kun Xia and Christina R. Fagerberg and Christoph P. Beier and Martin J. Larsen and Irene Valenzuela and Paula Fernández-Álvarez and Shiyi Xiong and Robert Śmigiel and Vanesa López-González and Lluís Armengol and Manuela Morleo and Angelo Selicorni and Annalaura Torella and Moira Blyth and Nicola S. Cooper and Valerie Wilson and Renske Oegema and Yvan Herenger and Aurore Garde and Ange-Line Bruel and Frederic Tran Mau-Them and Alexis B. R. Maddocks and Jennifer M. Bain and Musadiq A. Bhat and Gregory Costain and Peter Kannu and Ashish Marwaha and Neena L. Champaigne and Michael J. Friez and Ellen B. Richardson and Vykuntaraju K. Gowda and Varunvenkat M. Srinivasan and Yask Gupta and Tze Y. Lim and Simone Sanna-Cherchi and Bruno Lemaitre and Toshiyuki Yamaji and Kentaro Hanada and John E. Burke and Ana Marjia Jakšić and Brian D. McCabe and Paolo De Los Rios and Thorsten Hornemann and Giovanni D’Angelo and Vincenzo A. Gennarino},

url = {https://www.scopus.com/pages/publications/85159733545?origin=resultslist},

doi = {10.1172/JCI165019},

issn = {00219738},

year  = {2023},

date = {2023-01-01},

journal = {Journal of Clinical Investigation},

volume = {133},

number = {10},

publisher = {American Society for Clinical Investigation},

abstract = {Neural differentiation, synaptic transmission, and action potential propagation depend on membrane sphingolipids, whose metabolism is tightly regulated. Mutations in the ceramide transporter CERT (CERT1), which is involved in sphingolipid biosynthesis, are associated with intellectual disability, but the pathogenic mechanism remains obscure. Here, we characterize 31 individuals with de novo missense variants in CERT1. Several variants fall into a previously uncharacterized dimeric helical domain that enables CERT homeostatic inactivation, without which sphingolipid production goes unchecked. The clinical severity reflects the degree to which CERT autoregulation is disrupted, and inhibiting CERT pharmacologically corrects morphological and motor abnormalities in a Drosophila model of the disease, which we call ceramide transporter (CerTra) syndrome. These findings uncover a central role for CERT autoregulation in the control of sphingolipid biosynthetic flux, provide unexpected insight into the structural organization of CERT, and suggest a possible therapeutic approach for patients with CerTra syndrome. © 2023, Gehin et al.},

note = {Cited by: 23; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Piovesan2023D438,

title = {MobiDB: 10 years of intrinsically disordered proteins},

author = {Damiano Piovesan and Alessio Del Conte and Damiano Clementel and Alexander Miguel Monzon and Martina Bevilacqua and Maria Cristina Aspromonte and Javier A Iserte and Fernando E Orti and Cristina Marino-Buslje and Silvio C. E Tosatto},

url = {https://www.scopus.com/pages/publications/85145966264?origin=resultslist},

doi = {10.1093/nar/gkac1065},

issn = {03051048},

year  = {2023},

date = {2023-01-01},

journal = {Nucleic Acids Research},

volume = {51},

number = {1 D},

pages = {D438 - D444},

publisher = {Oxford University Press},

abstract = {The MobiDB database (URL: https://mobidb.org/) is a knowledge base of intrinsically disordered proteins. MobiDB aggregates disorder annotations derived from the literature and from experimental evidence along with predictions for all known protein sequences. MobiDB generates new knowledge and captures the functional significance of disordered regions by processing and combining complementary sources of information. Since its first release 10 years ago, the MobiDB database has evolved in order to improve the quality and coverage of protein disorder annotations and its accessibility. MobiDB has now reached its maturity in terms of data standardization and visualization. Here, we present a new release which focuses on the optimization of user experience and database content. The major advances compared to the previous version are the integration of AlphaFoldDB predictions and the re-implementation of the homology transfer pipeline, which expands manually curated annotations by two orders of magnitude. Finally, the entry page has been restyled in order to provide an overview of the available annotations along with two separate views that highlight structural disorder evidence and functions associated with different binding modes. © 2023 The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.},

note = {Cited by: 120; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Arrías2023,

title = {The repetitive structure of DNA clamps: An overlooked protein tandem repeat},

author = {Paula Nazarena Arrías and Alexander Miguel Monzon and Damiano Clementel and Soroush Mozaffari and Damiano Piovesan and Andrey V. Kajava and Silvio C. E. Tosatto},

url = {https://www.scopus.com/pages/publications/85165364940?origin=resultslist},

doi = {10.1016/j.jsb.2023.108001},

issn = {10478477},

year  = {2023},

date = {2023-01-01},

journal = {Journal of Structural Biology},

volume = {215},

number = {3},

publisher = {Academic Press Inc.},

abstract = {Structured tandem repeats proteins (STRPs) are a specific kind of tandem repeat proteins characterized by a modular and repetitive three-dimensional structure arrangement. The majority of STRPs adopt solenoid structures, but with the increasing availability of experimental structures and high-quality predicted structural models, more STRP folds can be characterized. Here, we describe “Box repeats”, an overlooked STRP fold present in the DNA sliding clamp processivity factors, which has eluded classification although structural data has been available since the late 1990s. Each Box repeat is a β⍺βββ module of about 60 residues, which forms a class V “beads-on-a-string” type STRP. The number of repeats present in processivity factors is organism dependent. Monomers of PCNA proteins in both Archaea and Eukarya have 4 repeats, while the monomers of bacterial beta-sliding clamps have 6 repeats. This new repeat fold has been added to the RepeatsDB database, which now provides structural annotation for 66 Box repeat proteins belonging to different organisms, including viruses. © 2023},

note = {Cited by: 5; All Open Access; Green Open Access; Hybrid Gold Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DelConte2023W62,

title = {CAID prediction portal: A comprehensive service for predicting intrinsic disorder and binding regions in proteins},

author = {Alessio Del Conte and Adel Bouhraoua and Mahta Mehdiabadi and Damiano Clementel and Alexander Miguel Monzon and Silvio C. E. Tosatto and Damiano Piovesan and Alex S. Holehouse and Daniel Griffith and Ryan J. Emenecker and Ashwini Patil and Ronesh Sharma and Tatsuhiko Tsunoda and Alok Sharma and Yi Jun Tang and Bin Liu and Claudio Mirabello and Björn Wallner and Burkhard Rost and Dagmar Ilzhöfer and Maria Littmann and Michael Heinzinger and Lea I. M. Krautheimer and Michael Bernhofer and Liam J. McGuffin and Isabelle Callebaut and Tristan Bitard Feildel and Jian Liu and Jianlin Cheng and Zhiye Guo and Jinbo Xu and Sheng Wang and Nawar Malhis and Jörg Gsponer and Chol-Song Kim and Kun-Sop Han and Myong-Chol Ma and Lukasz Kurgan and Sina Ghadermarzi and Akila Katuwawala and Bi Zhao and Zhenling Peng and Zhonghua Wu and Gang Hu and Kui Wang and Md Tamjidul Hoque and Md Wasi Ul Kabir and Michele Vendruscolo and Pietro Sormanni and Min Li and Fuhao Zhang and Pengzhen Jia and Yida Wang and Michail Yu Lobanov and Oxana V. Galzitskaya and Wim Vranken and Adrián Díaz and Thomas Litfin and Yaoqi Zhou and Jack Hanson and Kuldip Paliwal and Zsuzsanna Dosztányi and Gábor Erdős},

url = {https://www.scopus.com/pages/publications/85163958831?origin=resultslist},

doi = {10.1093/nar/gkad430},

issn = {03051048},

year  = {2023},

date = {2023-01-01},

journal = {Nucleic Acids Research},

volume = {51},

number = {W1},

pages = {W62 - W69},

publisher = {Oxford University Press},

abstract = {Intrinsic disorder (ID) in proteins is well-established in structural biology, with increasing evidence for its involvement in essential biological processes. As measuring dynamic ID behavior experimentally on a large scale remains difficult, scores of published ID predictors have tried to fill this gap. Unfortunately, their heterogeneity makes it difficult to compare performance, confounding biologists wanting to make an informed choice. To address this issue, the Critical Assessment of protein Intrinsic Disorder (CAID) benchmarks predictors for ID and binding regions as a community blind-test in a standardized computing environment. Here we present the CAID Prediction Portal, a web server executing all CAID methods on user-defined sequences. The server generates standardized output and facilitates comparison between methods, producing a consensus prediction highlighting high-confidence ID regions. The website contains extensive documentation explaining the meaning of different CAID statistics and providing a brief description of all methods. Predictor output is visualized in an interactive feature viewer and made available for download in a single table, with the option to recover previous sessions via a private dashboard. The CAID Prediction Portal is a valuable resource for researchers interested in studying ID in proteins. The server is available at the URL: https://caid.idpcentral.org. © 2023 The Author(s). Published by Oxford University Press on behalf of Nucleic Acids Research.},

note = {Cited by: 50; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Deutsch2023287,

title = {Proteomics Standards Initiative at Twenty Years: Current Activities and Future Work},

author = {Eric W. Deutsch and Juan Antonio Vizcaíno and Andrew R. Jones and Pierre-Alain Binz and Henry Lam and Joshua Klein and Wout Bittremieux and Yasset Perez-Riverol and David L. Tabb and Mathias Walzer and Sylvie Ricard-Blum and Henning Hermjakob and Steffen Neumann and Tytus D. Mak and Shin Kawano and Luis Mendoza and Tim Van Den Bossche and Ralf Gabriels and Nuno Bandeira and Jeremy Carver and Benjamin Pullman and Zhi Sun and Nils Hoffmann and Jim Shofstahl and Yunping Zhu and Luana Licata and Federica Quaglia and Silvio C. E. Tosatto and Sandra E. Orchard},

url = {https://www.scopus.com/pages/publications/85146633740?origin=resultslist},

doi = {10.1021/acs.jproteome.2c00637},

issn = {15353893},

year  = {2023},

date = {2023-01-01},

journal = {Journal of Proteome Research},

volume = {22},

number = {2},

pages = {287 - 301},

publisher = {American Chemical Society},

abstract = {The Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) has been successfully developing guidelines, data formats, and controlled vocabularies (CVs) for the proteomics community and other fields supported by mass spectrometry since its inception 20 years ago. Here we describe the general operation of the PSI, including its leadership, working groups, yearly workshops, and the document process by which proposals are thoroughly and publicly reviewed in order to be ratified as PSI standards. We briefly describe the current state of the many existing PSI standards, some of which remain the same as when originally developed, some of which have undergone subsequent revisions, and some of which have become obsolete. Then the set of proposals currently being developed are described, with an open call to the community for participation in the forging of the next generation of standards. Finally, we describe some synergies and collaborations with other organizations and look to the future in how the PSI will continue to promote the open sharing of data and thus accelerate the progress of the field of proteomics. © 2023 The Authors. Published by American Chemical Society.},

note = {Cited by: 62; All Open Access; Green Open Access; Hybrid Gold Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Piol2023,

title = {Antagonistic effect of cyclin-dependent kinases and a calcium-dependent phosphatase on polyglutamine-expanded androgen receptor toxic gain of function},

author = {Diana Piol and Laura Tosatto and Emanuela Zuccaro and Eric N. Anderson and Antonella Falconieri and Maria J. Polanco and Caterina Marchioretti and Federica Lia and Joseph White and Elisa Bregolin and Giovanni Minervini and Sara Parodi and Xavier Salvatella and Giorgio Arrigoni and Andrea Ballabio and Albert R. La Spada and Silvio C. E. Tosatto and Fabio Sambataro and Diego L. Medina and Udai B. Pandey and Manuela Basso and Maria Pennuto},

url = {https://www.scopus.com/pages/publications/85145870213?origin=resultslist},

doi = {10.1126/sciadv.ade1694},

issn = {23752548},

year  = {2023},

date = {2023-01-01},

journal = {Science Advances},

volume = {9},

number = {1},

publisher = {American Association for the Advancement of Science},

abstract = {Spinal and bulbar muscular atrophy is caused by polyglutamine (polyQ) expansions in androgen receptor (AR), generating gain-of-function toxicity that may involve phosphorylation. Using cellular and animal models, we investigated what kinases and phosphatases target polyQ-expanded AR, whether polyQ expansions modify AR phosphorylation, and how this contributes to neurodegeneration. Mass spectrometry showed that polyQ expansions preserve native phosphorylation and increase phosphorylation at conserved sites controlling AR stability and transactivation. In small-molecule screening, we identified that CDC25/CDK2 signaling could enhance AR phosphorylation, and the calcium-sensitive phosphatase calcineurin had opposite effects. Pharmacologic and genetic manipulation of these kinases and phosphatases modified polyQ-expanded AR function and toxicity in cells, flies, and mice. Ablation of CDK2 reduced AR phosphorylation in the brainstem and restored expression of Myc and other genes involved in DNA damage, senescence, and apoptosis, indicating that the cell cycle–regulated kinase plays more than a bystander role in SBMA-vulnerable postmitotic cells. Copyright © 2023 The Authors, some rights reserved;},

note = {Cited by: 12; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Camagni2023,

title = {Structural Characterization of Hypoxia Inducible Factor α—Prolyl Hydroxylase Domain 2 Interaction through MD Simulations},

author = {Giorgia F. Camagni and Giovanni Minervini and Silvio C. E. Tosatto},

url = {https://www.scopus.com/pages/publications/85149881431?origin=resultslist},

doi = {10.3390/ijms24054710},

issn = {16616596},

year  = {2023},

date = {2023-01-01},

journal = {International Journal of Molecular Sciences},

volume = {24},

number = {5},

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

abstract = {The Prolyl Hydroxylases (PHDs) are an enzymatic family that regulates cell oxygen-sensing. PHDs hydroxylate hypoxia-inducible transcription factors α (HIFs-α) driving their proteasomal degradation. Hypoxia inhibits PHDs activity, inducing HIFs-α stabilization and cell adaptation to hypoxia. As a hallmark of cancer, hypoxia promotes neo-angiogenesis and cell proliferation. PHD isoforms are thought to have a variable impact on tumor progression. All isoforms hydroxylate HIF-α (HIF-1,2,3α) with different affinities. However, what determines these differences and how they pair with tumor growth is poorly understood. Here, molecular dynamics simulations were used to characterize the PHD2 binding properties in complexes with HIF-1α and HIF-2α. In parallel, conservation analysis and binding free energy calculations were performed to better understand PHD2 substrate affinity. Our data suggest a direct association between the PHD2 C-terminus and HIF-2α that is not observed in the PHD2/HIF-1α complex. Furthermore, our results indicate that phosphorylation of a PHD2 residue, Thr405, causes a variation in binding energy, despite the fact that this PTM has only a limited structural impact on PHD2/HIFs-α complexes. Collectively, our findings suggest that the PHD2 C-terminus may act as a molecular regulator of PHD’s activity. © 2023 by the authors.},

note = {Cited by: 11; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Leonardi2023202,

title = {Expanding the genetics and phenotypic spectrum of Lysine-specific demethylase 5C (KDM5C): a report of 13 novel variants},

author = {Emanuela Leonardi and Maria Cristina Aspromonte and Denise Drongitis and Elisa Bettella and Lucia Verrillo and Roberta Polli and Meriel McEntagart and Laura Licchetta and Robertino Dilena and Stefano D’Arrigo and Claudia Ciaccio and Silvia Esposito and Vincenzo Leuzzi and Annalaura Torella and Demetrio Baldo and Fortunato Lonardo and Giulia Bonato and Serena Pellegrin and Franco Stanzial and Renata Posmyk and Ewa Kaczorowska and Miryam Carecchio and Monika Gos and Sylwia Rzońca-Niewczas and Maria Giuseppina Miano and Alessandra Murgia},

url = {https://www.scopus.com/pages/publications/85142646250?origin=resultslist},

doi = {10.1038/s41431-022-01233-4},

issn = {10184813},

year  = {2023},

date = {2023-01-01},

journal = {European Journal of Human Genetics},

volume = {31},

number = {2},

pages = {202 - 215},

publisher = {Springer Nature},

abstract = {Lysine-specific demethylase 5C (KDM5C) has been identified as an important chromatin remodeling gene, contributing to X-linked neurodevelopmental disorders (NDDs). The KDM5C gene, located in the Xp22 chromosomal region, encodes the H3K4me3-me2 eraser involved in neuronal plasticity and dendritic growth. Here we report 30 individuals carrying 13 novel and one previously identified KDM5C variants. Our cohort includes the first reported case of somatic mosaicism in a male carrying a KDM5C nucleotide substitution, and a dual molecular finding in a female carrying a homozygous truncating FUCA1 alteration together with a de novo KDM5C variant. With the use of next generation sequencing strategies, we detected 1 frameshift, 1 stop codon, 2 splice-site and 10 missense variants, which pathogenic role was carefully investigated by a thorough bioinformatic analysis. The pattern of X-chromosome inactivation was found to have an impact on KDM5C phenotypic expression in females of our cohort. The affected individuals of our case series manifested a neurodevelopmental condition characterized by psychomotor delay, intellectual disability with speech disorders, and behavioral features with particular disturbed sleep pattern; other observed clinical manifestations were short stature, obesity and hypertrichosis. Collectively, these findings expand the current knowledge about the pathogenic mechanisms leading to dysfunction of this important chromatin remodeling gene and contribute to a refinement of the KDM5C phenotypic spectrum. © 2022, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.},

note = {Cited by: 14; All Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Paysan-Lafosse2023D418,

title = {InterPro in 2022},

author = {Typhaine Paysan-Lafosse and Matthias Blum and Sara Chuguransky and Tiago Grego and Beatriz Lázaro Pinto and Gustavo A. Salazar and Maxwell L. Bileschi and Peer Bork and Alan Bridge and Lucy Colwell and Julian Gough and Daniel H. Haft and Ivica Letunić and Aron Marchler-Bauer and Huaiyu Mi and Darren A. Natale and Christine A. Orengo and Arun P. Pandurangan and Catherine Rivoire and Christian J. A. Sigrist and Ian Sillitoe and Narmada Thanki and Paul D. Thomas and Silvio C. E. Tosatto and Cathy H. Wu and Alex Bateman},

url = {https://www.scopus.com/pages/publications/85159577204?origin=resultslist},

doi = {10.1093/nar/gkac993},

issn = {03051048},

year  = {2023},

date = {2023-01-01},

journal = {Nucleic Acids Research},

volume = {51},

number = {D1},

pages = {D418 - D427},

publisher = {Oxford University Press},

abstract = {The InterPro database (https://www.ebi.ac.uk/ interpro/) provides an integrative classification of protein sequences into families, and identifies functionally important domains and conserved sites. Here, we report recent developments with InterPro (version 90.0) and its associated software, including updates to data content and to the website. These developments extend and enrich the information provided by InterPro, and provide a more user friendly access to the data. Additionally, we have worked on adding Pfam website features to the InterPro website, as the Pfam website will be retired in late 2022. We also show that InterPro’s sequence coverage has kept pace with the growth of UniProtKB. Moreover, we report the development of a card game as a method of engaging the non-scientific community. Finally, we discuss the benefits and challenges brought by the use of artificial intelligence for protein structure prediction. © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.},

note = {Cited by: 2046; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Fusto2022,

title = {Expanding the clinical-pathological and genetic spectrum of RYR1-related congenital myopathies with cores and minicores: an Italian population study},

author = {Aurora Fusto and Denise Cassandrini and Chiara Fiorillo and Valentina Codemo and Guja Astrea and Adele D’Amico and Lorenzo Maggi and Francesca Magri and Marika Pane and Giorgio Tasca and Daniele Sabbatini and Luca Bello and Roberta Battini and Pia Bernasconi and Fabiana Fattori and Enrico Silvio Bertini and Giacomo Comi and Sonia Messina and Tiziana Mongini and Isabella Moroni and Chiara Panicucci and Angela Berardinelli and Alice Donati and Vincenzo Nigro and Antonella Pini and Melania Giannotta and Claudia Dosi and Enzo Ricci and Eugenio Mercuri and Giovanni Minervini and Silvio Tosatto and Filippo Santorelli and Claudio Bruno and Elena Pegoraro},

url = {https://www.scopus.com/pages/publications/85128316270?origin=resultslist},

doi = {10.1186/s40478-022-01357-0},

issn = {20515960},

year  = {2022},

date = {2022-01-01},

journal = {Acta Neuropathologica Communications},

volume = {10},

number = {1},

publisher = {BioMed Central Ltd},

abstract = {Mutations in the RYR1 gene, encoding ryanodine receptor 1 (RyR1), are a well-known cause of Central Core Disease (CCD) and Multi-minicore Disease (MmD). We screened a cohort of 153 patients carrying an histopathological diagnosis of core myopathy (cores and minicores) for RYR1 mutation. At least one RYR1 mutation was identified in 69 of them and these patients were further studied. Clinical and histopathological features were collected. Clinical phenotype was highly heterogeneous ranging from asymptomatic or paucisymptomatic hyperCKemia to severe muscle weakness and skeletal deformity with loss of ambulation. Sixty-eight RYR1 mutations, generally missense, were identified, of which 16 were novel. The combined analysis of the clinical presentation, disease progression and the structural bioinformatic analyses of RYR1 allowed to associate some phenotypes to mutations in specific domains. In addition, this study highlighted the structural bioinformatics potential in the prediction of the pathogenicity of RYR1 mutations. Further improvement in the comprehension of genotype–phenotype relationship of core myopathies can be expected in the next future: the actual lack of the human RyR1 crystal structure paired with the presence of large intrinsically disordered regions in RyR1, and the frequent presence of more than one RYR1 mutation in core myopathy patients, require designing novel investigation strategies to completely address RyR1 mutation effect. © 2022, The Author(s).},

note = {Cited by: 16; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Piovesan2022144,

title = {Databases for intrinsically disordered proteins},

author = {Damiano Piovesan and Alexander Miguel Monzon and Federica Quaglia and Silvio C. E. Tosatto},

url = {https://www.scopus.com/pages/publications/85123972941?origin=resultslist},

doi = {10.1107/S2059798321012109},

issn = {20597983},

year  = {2022},

date = {2022-01-01},

journal = {Acta Crystallographica Section D: Structural Biology},

volume = {78},

pages = {144 - 151},

publisher = {International Union of Crystallography},

abstract = {Intrinsically disordered regions (IDRs) lacking a fixed three-dimensional protein structure are widespread and play a central role in cell regulation. Only a small fraction of IDRs have been functionally characterized, with heterogeneous experimental evidence that is largely buried in the literature. Predictions of IDRs are still difficult to estimate and are poorly characterized. Here, an overview of the publicly available knowledge about IDRs is reported, including manually curated resources, deposition databases and prediction repositories. The types, scopes and availability of the various resources are analyzed, and their complementarity and overlap are highlighted. The volume of information included and the relevance to the field of structural biology are compared. © 2022.},

note = {Cited by: 15; All Open Access; Green Open Access; Hybrid Gold Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Escobedo20224959,

title = {CoDNaS-Q: a database of conformational diversity of the native state of proteins with quaternary structure},

author = {Nahuel Escobedo and Ronaldo Romario Tunque Cahui and Gastón Caruso and Emilio García Ríos and Layla Hirsh and Alexander Miguel Monzon and Gustavo Parisi and Nicolas Palopoli},

url = {https://www.scopus.com/pages/publications/85141004727?origin=resultslist},

doi = {10.1093/bioinformatics/btac627},

issn = {13674803},

year  = {2022},

date = {2022-01-01},

journal = {Bioinformatics},

volume = {38},

number = {21},

pages = {4959 - 4961},

publisher = {Oxford University Press},

abstract = {A collection of conformers that exist in a dynamical equilibrium defines the native state of a protein. The structural differences between them describe their conformational diversity, a defining characteristic of the protein with an essential role in multiple cellular processes. Since most proteins carry out their functions by assembling into complexes, we have developed CoDNaS-Q, the first online resource to explore conformational diversity in homooligomeric proteins. It features a curated collection of redundant protein structures with known quaternary structure. CoDNaS-Q integrates relevant annotations that allow researchers to identify and explore the extent and possible reasons of conformational diversity in homooligomeric protein complexes. © The Author(s) 2022. Published by Oxford University Press. All rights reserved.},

note = {Cited by: 5},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Nadendla2022D1515,

title = {ECO: The Evidence and Conclusion Ontology, an update for 2022},

author = {Suvarna Nadendla and Rebecca Jackson and James Munro and Federica Quaglia and Bálint Mészáros and Dustin Olley and Elizabeth T. Hobbs and Stephen M. Goralski and Marcus Chibucos and Christopher John Mungall and Silvio C. E. Tosatto and Ivan Erill and Michelle G. Giglio},

url = {https://www.scopus.com/pages/publications/85123230658?origin=resultslist},

doi = {10.1093/nar/gkab1025},

issn = {03051048},

year  = {2022},

date = {2022-01-01},

journal = {Nucleic Acids Research},

volume = {50},

number = {D1},

pages = {D1515 - D1521},

publisher = {Oxford University Press},

abstract = {The Evidence and Conclusion Ontology (ECO) is a community resource that provides an ontology of terms used to capture the type of evidence that supports biomedical annotations and assertions. Consistent capture of evidence information with ECO allows tracking of annotation provenance, establishment of quality control measures, and evidence-based data mining. ECO is in use by dozens of data repositories and resources with both specific and general areas of focus. ECO is continually being expanded and enhanced in response to user requests as well as our aim to adhere to community best-practices for ontology development. The ECO support team engages in multiple collaborations with other ontologies and annotating groups. Here we report on recent updates to the ECO ontology itself as well as associated resources that are available through this project. © 2022 The Author(s).},

note = {Cited by: 41; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Hatos2022W337,

title = {FuzDrop on AlphaFold: visualizing the sequence-dependent propensity of liquid-liquid phase separation and aggregation of proteins},

author = {Andras Hatos and Silvio C. E Tosatto and Michele Vendruscolo and Monika Fuxreiter},

url = {https://www.scopus.com/pages/publications/85134406800?origin=resultslist},

doi = {10.1093/nar/gkac386},

issn = {03051048},

year  = {2022},

date = {2022-01-01},

journal = {Nucleic Acids Research},

volume = {50},

number = {W1},

pages = {W337 - W344},

publisher = {Oxford University Press},

abstract = {Many proteins perform their functions within membraneless organelles, where they form a liquid-like condensed state, also known as droplet state. The FuzDrop method predicts the probability of spontaneous liquid-liquid phase separation of proteins and provides a sequence-based score to identify the regions that promote this process. Furthermore, the FuzDrop method estimates the propensity of conversion of proteins to the amyloid state, and identifies aggregation hot-spots, which can drive the irreversible maturation of the liquid-like droplet state. These predictions can also identify mutations that can induce formation of amyloid aggregates, including those implicated in human diseases. To facilitate the interpretation of the predictions, the droplet-promoting and aggregation-promoting regions can be visualized on protein structures generated by AlphaFold. The FuzDrop server (https://fuzdrop.bio.unipd.it) thus offers insights into the complex behavior of proteins in their condensed states and facilitates the understanding of the functional relationships of proteins. © 2022 The Author(s). Published by Oxford University Press on behalf of Nucleic Acids Research.},

note = {Cited by: 126; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Clementel2022W651,

title = {RING 3.0: fast generation of probabilistic residue interaction networks from structural ensembles},

author = {Damiano Clementel and Alessio Del Conte and Alexander Miguel Monzon and Giorgia F Camagni and Giovanni Minervini and Damiano Piovesan and Silvio C. E Tosatto},

url = {https://www.scopus.com/pages/publications/85134391344?origin=resultslist},

doi = {10.1093/nar/gkac365},

issn = {03051048},

year  = {2022},

date = {2022-01-01},

journal = {Nucleic Acids Research},

volume = {50},

number = {W1},

pages = {W651 - W656},

publisher = {Oxford University Press},

abstract = {Residue interaction networks (RINs) are used to represent residue contacts in protein structures. Thanks to the advances in network theory, RINs have been proved effective as an alternative to coordinate data in the analysis of complex systems. The RING server calculates high quality and reliable non-covalent molecular interactions based on geometrical parameters. Here, we present the new RING 3.0 version extending the previous functionality in several ways. The underlying software library has been re-engineered to improve speed by an order of magnitude. RING now also supports the mmCIF format and provides typed interactions for the entire PDB chemical component dictionary, including nucleic acids. Moreover, RING now employs probabilistic graphs, where multiple conformations (e.g. NMR or molecular dynamics ensembles) are mapped as weighted edges, opening up new ways to analyze structural data. The web interface has been expanded to include a simultaneous view of the RIN alongside a structure viewer, with both synchronized and clickable. Contact evolution across models (or time) is displayed as a heatmap and can help in the discovery of correlating interaction patterns. The web server, together with an extensive help and tutorial, is available from URL: https://ring.biocomputingup.it/. © 2022 The Author(s). Published by Oxford University Press on behalf of Nucleic Acids Research.},

note = {Cited by: 149; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Monzon2022,

title = {Molecular Determinants of Selectivity in Disordered Complexes May Shed Light on Specificity in Protein Condensates},

author = {Alexander Miguel Monzon and Damiano Piovesan and Monika Fuxreiter},

url = {https://www.scopus.com/pages/publications/85122180762?origin=resultslist},

doi = {10.3390/biom12010092},

issn = {2218273X},

year  = {2022},

date = {2022-01-01},

journal = {Biomolecules},

volume = {12},

number = {1},

publisher = {MDPI},

abstract = {Biomolecular condensates challenge the classical concepts of molecular recognition. The variable composition and heterogeneous conformations of liquid‐like protein droplets are bottlenecks for high‐resolution structural studies. To obtain atomistic insights into the organization of these assemblies, here we have characterized the conformational ensembles of specific disordered complexes, including those of droplet‐driving proteins. First, we found that these specific complexes exhibit a high degree of conformational heterogeneity. Second, we found that residues forming contacts at the interface also sample many conformations. Third, we found that different patterns of contacting residues form the specific interface. In addition, we observed a wide range of sequence motifs mediating disordered interactions, including charged, hydrophobic and polar contacts. These results demonstrate that selective recognition can be realized by variable patterns of weakly defined interaction motifs in many different binding configurations. We propose that these principles also play roles in determining the selectivity of biomolecular condensates. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.},

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

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Leonardi2022,

title = {Molecular Effects of Mutations in Human Genetic Diseases},

author = {Emanuela Leonardi and Castrense Savojardo and Giovanni Minervini},

url = {https://www.scopus.com/pages/publications/85131521999?origin=resultslist},

doi = {10.3390/ijms23126408},

issn = {16616596},

year  = {2022},

date = {2022-01-01},

journal = {International Journal of Molecular Sciences},

volume = {23},

number = {12},

publisher = {MDPI},

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

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Falconieri2022,

title = {Characterization of the pVHL Interactome in Human Testis Using High-Throughput Library Screening},

author = {Antonella Falconieri and Giovanni Minervini and Federica Quaglia and Geppo Sartori and Silvio C. E. Tosatto},

url = {https://www.scopus.com/pages/publications/85124955220?origin=resultslist},

doi = {10.3390/cancers14041009},

issn = {20726694},

year  = {2022},

date = {2022-01-01},

journal = {Cancers},

volume = {14},

number = {4},

publisher = {MDPI},

abstract = {Functional impairment of the von Hippel–Lindau tumor suppressor (pVHL) is causative of a familiar increased risk of developing cancer. As an E3 substrate recognition particle, pVHL marks the hypoxia inducible factor 1α (HIF-1α) for degradation in normoxic conditions, thus acting as a key regulator of both acute and chronic cell adaptation to hypoxia. The male mice model carrying VHL gene conditional knockout presents significant abnormalities in testis development paired with defects in spermatogenesis and infertility, indicating that pVHL exerts testis-specific roles. Here we aimed to explore whether pVHL could have a similar role in humans by performing a testis-tissue library screening complemented with in-depth bioinformatics analysis. We identified 55 novel pVHL binding proteins directly involved in spermatogenesis, cell differentiation and reproductive metabolism. In addition, computational investigation of these new interactors identified multiple pVHL-specific binding motifs and demonstrated that somatic mutations described in human cancers reside in these binding regions. Collectively, these findings suggest that, in addition to its role in cancer formation, pVHL may also be pivotal in normal gonadal development in humans. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.},

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

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Piovesan2022,

title = {Intrinsic protein disorder and conditional folding in AlphaFoldDB},

author = {Damiano Piovesan and Alexander Miguel Monzon and Silvio C. E. Tosatto},

url = {https://www.scopus.com/pages/publications/85141005149?origin=resultslist},

doi = {10.1002/pro.4466},

issn = {09618368},

year  = {2022},

date = {2022-01-01},

journal = {Protein Science},

volume = {31},

number = {11},

publisher = {John Wiley and Sons Inc},

abstract = {Intrinsically disordered regions (IDRs) defying the traditional protein structure–function paradigm have been difficult to analyze. The availability of accurate structure predictions on a large scale in AlphaFoldDB offers a fresh perspective on IDR prediction. Here, we establish three baselines for IDR prediction from AlphaFoldDB models based on the recent CAID dataset. Surprisingly, AlphaFoldDB is highly competitive for predicting both IDRs and conditionally folded binding regions, demonstrating the plasticity of the disorder to structure continuum. © 2022 The Authors. Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.},

note = {Cited by: 117; All Open Access; Green Open Access; Hybrid Gold Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Cousin2022,

title = {Gain and loss of TASK3 channel function and its regulation by novel variation cause KCNK9 imprinting syndrome},

author = {Margot A. Cousin and Emma L. Veale and Nikita R. Dsouza and Swarnendu Tripathi and Robyn G. Holden and Maria Arelin and Geoffrey Beek and Mir Reza Bekheirnia and Jasmin Beygo and Vikas Bhambhani and Martin Bialer and Stefania Bigoni and Cyrus Boelman and Jenny Carmichael and Thomas Courtin and Benjamin Cogne and Ivana Dabaj and Diane Doummar and Laura Fazilleau and Alessandra Ferlini and Ralitza H. Gavrilova and John M. Graham and Tobias B. Haack and Jane Juusola and Sarina G. Kant and Saima Kayani and Boris Keren and Petra Ketteler and Chiara Klöckner and Tamara T. Koopmann and Teresa M. Kruisselbrink and Alma Kuechler and Laëtitia Lambert and Xénia Latypova and Robert Roger Lebel and Magalie S. Leduc and Emanuela Leonardi and Andrea M. Lewis and Wendy Liew and Keren Machol and Samir Mardini and Kirsty McWalter and Cyril Mignot and Julie McLaughlin and Alessandra Murgia and Vinodh Narayanan and Caroline Nava and Sonja Neuser and Mathilde Nizon and Davide Ognibene and Joohyun Park and Konrad Platzer and Céline Poirsier and Maximilian Radtke and Keri Ramsey and Cassandra K. Runke and Maria J. Guillen Sacoto and Fernando Scaglia and Marwan Shinawi and Stephanie Spranger and Ee Shien Tan and John Taylor and Anne-Sophie Trentesaux and Filippo Vairo and Rebecca Willaert and Neda Zadeh and Raul Urrutia and Dusica Babovic-Vuksanovic and Michael T. Zimmermann and Alistair Mathie and Eric W. Klee},

url = {https://www.scopus.com/pages/publications/85131795908?origin=resultslist},

doi = {10.1186/s13073-022-01064-4},

issn = {1756994X},

year  = {2022},

date = {2022-01-01},

journal = {Genome Medicine},

volume = {14},

number = {1},

publisher = {BioMed Central Ltd},

abstract = {Background: Genomics enables individualized diagnosis and treatment, but large challenges remain to functionally interpret rare variants. To date, only one causative variant has been described for KCNK9 imprinting syndrome (KIS). The genotypic and phenotypic spectrum of KIS has yet to be described and the precise mechanism of disease fully understood. Methods: This study discovers mechanisms underlying KCNK9 imprinting syndrome (KIS) by describing 15 novel KCNK9 alterations from 47 KIS-affected individuals. We use clinical genetics and computer-assisted facial phenotyping to describe the phenotypic spectrum of KIS. We then interrogate the functional effects of the variants in the encoded TASK3 channel using sequence-based analysis, 3D molecular mechanic and dynamic protein modeling, and in vitro electrophysiological and functional methodologies. Results: We describe the broader genetic and phenotypic variability for KIS in a cohort of individuals identifying an additional mutational hotspot at p.Arg131 and demonstrating the common features of this neurodevelopmental disorder to include motor and speech delay, intellectual disability, early feeding difficulties, muscular hypotonia, behavioral abnormalities, and dysmorphic features. The computational protein modeling and in vitro electrophysiological studies discover variability of the impact of KCNK9 variants on TASK3 channel function identifying variants causing gain and others causing loss of conductance. The most consistent functional impact of KCNK9 genetic variants, however, was altered channel regulation. Conclusions: This study extends our understanding of KIS mechanisms demonstrating its complex etiology including gain and loss of channel function and consistent loss of channel regulation. These data are rapidly applicable to diagnostic strategies, as KIS is not identifiable from clinical features alone and thus should be molecularly diagnosed. Furthermore, our data suggests unique therapeutic strategies may be needed to address the specific functional consequences of KCNK9 variation on channel function and regulation. © 2022, The Author(s).},

note = {Cited by: 17; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Godler2022,

title = {Feasibility of Screening for Chromosome 15 Imprinting Disorders in 16579 Newborns by Using a Novel Genomic Workflow},

author = {David E. Godler and Ling Ling and Dinusha Gamage and Emma K. Baker and Minh Bui and Michael J. Field and Carolyn Rogers and Merlin G. Butler and Alessandra Murgia and Emanuela Leonardi and Roberta Polli and Charles E. Schwartz and Cindy D. Skinner and Angelica M. Alliende and Lorena Santa Maria and James Pitt and Ronda Greaves and David Francis and Ralph Oertel and Min Wang and Cas Simons and David J. Amor},

url = {https://www.scopus.com/pages/publications/85122738953?origin=resultslist},

doi = {10.1001/jamanetworkopen.2021.41911},

issn = {25743805},

year  = {2022},

date = {2022-01-01},

journal = {JAMA Network Open},

volume = {5},

number = {1},

publisher = {American Medical Association},

abstract = {Importance: Newborn screening for Angelman syndrome (AS), Prader-Willi syndrome (PWS), and chromosome 15 duplication syndrome (Dup15q) may lead to benefit from early diagnosis and treatment. Objective: To examine the feasibility of newborn screening for these chromosome 15 imprinting disorders at population scale. Design, Setting, and Participants: In this diagnostic study, the validation data set for the first-tier SNRPN test, called methylation-specific quantitative melt analysis (MS-QMA), included 109 PWS, 48 AS, 9 Dup15q, and 1190 population control newborn blood spots (NBS) and peripheral tissue samples from participants recruited from January 2000 to December 2016. The test data set included NBS samples from 16579 infants born in 2011. Infants with an NBS identified as positive for PWS, AS, or Dup15q by the first-tier test were referred for droplet digital polymerase chain reaction, real-time polymerase chain reaction, and low-coverage whole-genome sequencing for confirmatory testing. Data analyses were conducted between February 12, 2015, and August 15, 2020. Results: In the validation data set, the median age for the 77 patients with PWS was 3.00 years (IQR, 0.01-44.50 years); for the 46 patients with AS, 2.76 years (IQR, 0.028 to 49.00 years); and for the 9 patients with Dup15q, 4.00 years (IQR, 1.00 to 28.00 years). Thirty-eight patients (51.4%) in the PWS group, 20 patients (45.5%) in the AS group, and 6 patients (66.7%) in the Dup15q group who had sex reported were male. The validation data set showed MS-QMA sensitivity of 99.0% for PWS, 93.8% for AS, and 77.8% for Dup15q; specificity of 100% for PWS, AS, and Dup15q; positive predictive and negative predictive values of 100% for PWS and AS; and a positive predictive value of 87.5% and negative predictive value of 100% for Dup15q. In the test data set of NBS samples from 16579 infants, 92 had a positive test result using a methylation ratio cut-off of 3 standard deviations from the mean. Of these patients, 2 were confirmed to have PWS; 2, AS; and 1, maternal Dup15q. With the use of more conservative PWS- and AS-specific thresholds for positive calls from the validation data set, 9 positive NBS results were identified by MS-QMA in this cohort. The 2 PWS and 2 AS calls were confirmed by second-tier testing, but the 1 Dup15q case was not confirmed. Together, these results provided prevalence estimates of 1 in 8290 for both AS and PWS and 1 in 16579 for maternal Dup15q, with positive predictive values for first-tier testing at 67.0% for AS, 33.0% for PWS, and 44.0% for combined detection of chromosome 15 imprinting disorders for the validation data set. Conclusions and Relevance: The findings of this diagnostic study suggest that it is feasible to screen for all chromosome 15 imprinting disorders using SNRPN methylation analysis, with 5 individuals identified with these disorders out of 16579 infants screened.. © 2022 American Medical Association. All rights reserved.},

note = {Cited by: 33; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Quaglia2022D480,

title = {DisProt in 2022: Improved quality and accessibility of protein intrinsic disorder annotation},

author = {Federica Quaglia and Bálint Meszáros and Edoardo Salladini and András Hatos and Rita Pancsa and Lucía B. Chemes and Mátyás Pajkos and Tamas Lazar and Samuel Peña-Díaz and Jaime Santos and Veronika Ács and Nazanin Farahi and Erzsebet Fichó and Maria Cristina Aspromonte and Claudio Bassot and Anastasia Chasapi and Norman E. Davey and Radoslav Davidović and Laszlo Dobson and Arne Elofsson and Gábor Erdos and Pascale Gaudet and Michelle Giglio and Juliana Glavina and Javier Iserte and Valentín Iglesias and Zsófia Kálmán and Matteo Lambrughi and Emanuela Leonardi and Sonia Longhi and Sandra Macedo-Ribeiro and Emiliano Maiani and Julia Marchetti and Cristina Marino-Buslje and Attila Meszáros and Alexander Miguel Monzon and Giovanni Minervini and Suvarna Nadendla and Juliet F. Nilsson and Marian Novotný and Christos A. Ouzounis and Nicolás Palopoli and Elena Papaleo and Pedro Jose Barbosa Pereira and Gabriele Pozzati and Vasilis J. Promponas and Jordi Pujols and Alma Carolina Sanchez Rocha and Martin Salas and Luciana Rodriguez Sawicki and Eva Schad and Aditi Shenoy and Tamás Szaniszló and Konstantinos D. Tsirigos and Nevena Veljkovic and Gustavo Parisi and Salvador Ventura and Zsuzsanna Dosztányi and Peter Tompa and Silvio C. E. Tosatto and Damiano Piovesan},

url = {https://www.scopus.com/pages/publications/85125157608?origin=resultslist},

doi = {10.1093/nar/gkab1082},

issn = {03051048},

year  = {2022},

date = {2022-01-01},

journal = {Nucleic Acids Research},

volume = {50},

number = {D1},

pages = {D480 - D487},

publisher = {Oxford University Press},

abstract = {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. © 2022 The Author(s). Published by Oxford University Press on behalf of Nucleic Acids Research.},

note = {Cited by: 141; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Quaglia2022,

title = {Exploring Manually Curated Annotations of Intrinsically Disordered Proteins with DisProt},

author = {Federica Quaglia and András Hatos and Edoardo Salladini and Damiano Piovesan and Silvio C. E. Tosatto},

url = {https://www.scopus.com/pages/publications/85133241328?origin=resultslist},

doi = {10.1002/cpz1.484},

issn = {26911299},

year  = {2022},

date = {2022-01-01},

journal = {Current Protocols},

volume = {2},

number = {7},

publisher = {John Wiley and Sons Inc},

abstract = {DisProt is the major repository of manually curated data for intrinsically disordered proteins collected from the literature. Although lacking a stable three-dimensional structure under physiological conditions, intrinsically disordered proteins carry out a plethora of biological functions, some of them directly arising from their flexible nature. A growing number of scientific studies have been published during the last few decades to shed light on their unstructured state, their binding modes, and their functions. DisProt makes use of a team of expert biocurators to provide up-to-date annotations of intrinsically disordered proteins from the literature, making them available to the scientific community. Here we present a comprehensive description on how to use DisProt in different contexts and provide a detailed explanation of how to explore and interpret manually curated annotations of intrinsically disordered proteins. We describe how to search DisProt annotations, both using the web interface and the API for programmatic access. Finally, we explain how to visualize and interpret a DisProt entry, the SARS-CoV-2 Nucleoprotein, characterized by the presence of unstructured N-terminal and C-terminal regions and a flexible linker. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Performing a search in DisProt. Support Protocol 1: Downloading options. Support Protocol 2: Programmatic access with DisProt REST API. Basic Protocol 2: Exploring the DisProt Ontology page. Basic Protocol 3: Visualizing and interpreting DisProt entries–the SARS-CoV-2 Nucleoprotein use case. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC.},

note = {Cited by: 5; All Open Access; Green Open Access; Hybrid Gold Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Varadi2022D534,

title = {PDBe-KB: collaboratively defining the biological context of structural data},

author = {Mihaly Varadi and Stephen Anyango and David Armstrong and John Berrisford and Preeti Choudhary and Mandar Deshpande and Nurul Nadzirin and Sreenath S. Nair and Lukas Pravda and Ahsan Tanweer and Bissan Al-Lazikani and Claudia Andreini and Geoffrey J. Barton and David Bednar and Karel Berka and Tom Blundell and Kelly P. Brock and Jose Maria Carazo and Jiri Damborsky and Alessia David and Sucharita Dey and Roland Dunbrack and Juan Fernandez Recio and Franca Fraternali and Toby Gibson and Manuela Helmer-Citterich and David Hoksza and Thomas Hopf and David Jakubec and Natarajan Kannan and Radoslav Krivak and Manjeet Kumar and Emmanuel D. Levy and Nir London and Jose Ramon Macias and Madhusudhan M. Srivatsan and Debora S. Marks and Lennart Martens and Stuart A. McGowan and Jake E. McGreig and Vivek Modi and R. Gonzalo Parra and Gerardo Pepe and Damiano Piovesan and Jaime Prilusky and Valeria Putignano and Leandro G. Radusky and Pathmanaban Ramasamy and Atilio O. Rausch and Nathalie Reuter and Luis A. Rodriguez and Nathan J. Rollins and Antonio Rosato and Paweł Rubach and Luis Serrano and Gulzar Singh and Petr Skoda and Carlos Oscar S. Sorzano and Jan Stourac and Joanna I. Sulkowska and Radka Svobodova and Natalia Tichshenko and Silvio C. E. Tosatto and Wim Vranken and Mark N. Wass and Dandan Xue and Daniel Zaidman and Janet Thornton and Michael Sternberg and Christine Orengo and Sameer Velankar},

url = {https://www.scopus.com/pages/publications/85125170185?origin=resultslist},

doi = {10.1093/nar/gkab988},

issn = {03051048},

year  = {2022},

date = {2022-01-01},

journal = {Nucleic Acids Research},

volume = {50},

number = {D1},

pages = {D534 - D542},

publisher = {Oxford University Press},

abstract = {The Protein Data Bank in Europe – Knowledge Base (PDBe-KB, https://pdbe-kb.org) is an open collaboration between world-leading specialist data resources contributing functional and biophysical annotations derived from or relevant to the Protein Data Bank (PDB). The goal of PDBe-KB is to place macromolecular structure data in their biological context by developing standardised data exchange formats and integrating functional annotations from the contributing partner resources into a knowledge graph that can provide valuable biological insights. Since we described PDBe-KB in 2019, there have been significant improvements in the variety of available annotation data sets and user functionality. Here, we provide an overview of the consortium, highlighting the addition of annotations such as predicted covalent binders, phosphorylation sites, effects of mutations on the protein structure and energetic local frustration. In addition, we describe a library of reusable web-based visualisation components and introduce new features such as a bulk download data service and a novel superposition service that generates clusters of superposed protein chains weekly for the whole PDB archive. © The Author(s) 2021.},

note = {Cited by: 77; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Hatos2022D509,

title = {FuzDB: A new phase in understanding fuzzy interactions},

author = {Andras Hatos and Alexander Miguel Monzon and Silvio C. E. Tosatto and Damiano Piovesan and Monika Fuxreiter},

url = {https://www.scopus.com/pages/publications/85122220907?origin=resultslist},

doi = {10.1093/nar/gkab1060},

issn = {03051048},

year  = {2022},

date = {2022-01-01},

journal = {Nucleic Acids Research},

volume = {50},

number = {D1},

pages = {D509 - D517},

publisher = {Oxford University Press},

abstract = {Fuzzy interactions are specific, variable contacts between proteins and other biomolecules (proteins, DNA, RNA, small molecules) formed in accord to the cellular context. Fuzzy interactions have recently been demonstrated to regulate biomolecular condensates generated by liquid-liquid phase separation. The FuzDB v4.0 database (https://fuzdb.org) assembles experimentally identified examples of fuzzy interactions, where disordered regions mediate functionally important, context-dependent contacts between the partners in stoichiometric and higher-order assemblies. The new version of FuzDB establishes cross-links with databases on structure (PDB, BMRB, PED), function (ELM, UniProt) and biomolecular condensates (PhaSepDB, PhaSePro, LLPSDB). FuzDB v4.0 is a source to decipher molecular basis of complex cellular interaction behaviors, including those in protein droplets. © 2022 The Author(s). Published by Oxford University Press on behalf of Nucleic Acids Research.},

note = {Cited by: 50; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Pradelli20224440,

title = {Mocafe: a comprehensive Python library for simulating cancer development with Phase Field Models},

author = {Franco Pradelli and Giovanni Minervini and Silvio C. E. Tosatto},

url = {https://www.scopus.com/pages/publications/85141891628?origin=resultslist},

doi = {10.1093/bioinformatics/btac521},

issn = {13674803},

year  = {2022},

date = {2022-01-01},

journal = {Bioinformatics},

volume = {38},

number = {18},

pages = {4440 - 4441},

publisher = {Oxford University Press},

abstract = {Summary: Mathematical models are effective in studying cancer development at different scales from metabolism to tissue. Phase Field Models (PFMs) have been shown to reproduce accurately cancer growth and other related phenomena, including expression of relevant molecules, extracellular matrix remodeling and angiogenesis. However, implementations of such models are rarely published, reducing access to these techniques. To reduce this gap, we developed Mocafe, a modular open-source Python package that implements some of the most important PFMs reported in the literature. Mocafe is designed to handle both PFMs purely based on differential equations and hybrid agent-based PFMs. Moreover, Mocafe is meant to be extensible, allowing the inclusion of new models in future releases. © 2022 The Author(s). Published by Oxford University Press. All rights reserved.},

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

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Bevilacqua20221129,

title = {ProSeqViewer: an interactive, responsive and efficient TypeScript library for visualization of sequences and alignments in web applications},

author = {Martina Bevilacqua and Lisanna Paladin and Silvio C. E. Tosatto and Damiano Piovesan},

url = {https://www.scopus.com/pages/publications/85130453196?origin=resultslist},

doi = {10.1093/bioinformatics/btab764},

issn = {13674803},

year  = {2022},

date = {2022-01-01},

journal = {Bioinformatics},

volume = {38},

number = {4},

pages = {1129 - 1130},

publisher = {Oxford University Press},

abstract = {Biological data is ever-increasing in amount and complexity. The mapping of this data to biological entities such as nucleotide and amino acid sequences supports biological data analysis, classification and prediction. Sequence alignments and comparison allow the transfer of knowledge to evolutionary-related entities, the mapping of functional domains, the identification of binding and modification sites. To support these types of studies, we developed ProSeqViewer, a tool to visualize annotation on single sequences and multiple sequence alignments. This state-of-the-art multifunctional library was developed as a modular component to be integrated into static or dynamic web resources and support intuitive visualization of sequence features. ProseSeqViewer is extremely lightweight, fast, interactive, dynamic, responsive and works at any screen size. It generates pure HTML which is compatible with any browser and operating system. ProSeqViewer can exchange events with other visualization components and is already used by multiple biological databases. © 2022 Oxford University Press. All rights reserved.},

note = {Cited by: 7; All Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Quaglia20224240,

title = {SARS-CoV-2 variants preferentially emerge at intrinsically disordered protein sites helping immune evasion},

author = {Federica Quaglia and Edoardo Salladini and Marco Carraro and Giovanni Minervini and Silvio C. E. Tosatto and Philippe Le Mercier},

url = {https://www.scopus.com/pages/publications/85124603120?origin=resultslist},

doi = {10.1111/febs.16379},

issn = {1742464X},

year  = {2022},

date = {2022-01-01},

journal = {FEBS Journal},

volume = {289},

number = {14},

pages = {4240 - 4250},

publisher = {John Wiley and Sons Inc},

abstract = {The SARS-CoV-2 pandemic is maintained by the emergence of successive variants, highlighting the flexibility of the protein sequences of the virus. We show that experimentally determined intrinsically disordered regions (IDRs) are abundant in the SARS-CoV-2 viral proteins, making up to 28% of disorder content for the S1 subunit of spike and up to 51% for the nucleoprotein, with the vast majority of mutations occurring in the 13 major variants mapped to these IDRs. Strikingly, antigenic sites are enriched in IDRs, in the receptor-binding domain (RBD) and in the N-terminal domain (NTD), suggesting a key role of structural flexibility in the antigenicity of the SARS-CoV-2 protein surface. Mutations occurring in the S1 subunit and nucleoprotein (N) IDRs are critical for immune evasion and antibody escape, suggesting potential additional implications for vaccines and monoclonal therapeutic strategies. Overall, this suggests the presence of variable regions on S1 and N protein surfaces, which confer sequence and antigenic flexibility to the virus without altering its protein functions. © 2022 The Authors. The FEBS Journal published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.},

note = {Cited by: 34; All Open Access; Green Open Access; Hybrid Gold Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Varadi2022,

title = {3D-Beacons: Decreasing the gap between protein sequences and structures through a federated network of protein structure data resources},

author = {Mihaly Varadi and Sreenath Nair and Ian Sillitoe and Gerardo Tauriello and Stephen Anyango and Stefan Bienert and Clemente Borges and Mandar Deshpande and Tim Green and Demis Hassabis and Andras Hatos and Tamas Hegedus and Maarten L Hekkelman and Robbie Joosten and John Jumper and Agata Laydon and Dmitry Molodenskiy and Damiano Piovesan and Edoardo Salladini and Steven L Salzberg and Markus J Sommer and Martin Steinegger and Erzsebet Suhajda and Dmitri Svergun and Luiggi Tenorio-Ku and Silvio Tosatto and Kathryn Tunyasuvunakool and Andrew Mark Waterhouse and Augustin Zídek and Torsten Schwede and Christine Orengo and Sameer Velankar},

url = {https://www.scopus.com/pages/publications/85143181019?origin=resultslist},

doi = {10.1093/gigascience/giac118},

issn = {2047217X},

year  = {2022},

date = {2022-01-01},

journal = {GigaScience},

volume = {11},

publisher = {Oxford University Press},

abstract = {While scientists can often infer the biological function of proteins from their 3-dimensional quaternary structures, the gap between the number of known protein sequences and their experimentally determined structures keeps increasing. A potential solution to this problem is presented by ever more sophisticated computational protein modeling approaches. While often powerful on their own, most methods have strengths and weaknesses. Therefore, it benefits researchers to examine models from various model providers and perform comparative analysis to identify what models can best address their specific use cases. To make data from a large array of model providers more easily accessible to the broader scientific community, we established 3D-Beacons, a collaborative initiative to create a federated network with unified data access mechanisms. The 3D-Beacons Network allows researchers to collate coordinate files and metadata for experimentally determined and theoretical protein models from state-of-The-Art and specialist model providers and also from the Protein Data Bank. © 2022 The Author(s). Published by Oxford University Press GigaScience.},

note = {Cited by: 23; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Mistry2021D412,

title = {Pfam: The protein families database in 2021},

author = {Jaina Mistry and Sara Chuguransky and Lowri Williams and Matloob Qureshi and Gustavo A. Salazar and Erik L. L. Sonnhammer and Silvio C. E. Tosatto and Lisanna Paladin and Shriya Raj and Lorna J. Richardson and Robert D. Finn and Alex Bateman},

url = {https://www.scopus.com/pages/publications/85099428285?origin=resultslist},

doi = {10.1093/nar/gkaa913},

issn = {03051048},

year  = {2021},

date = {2021-01-01},

journal = {Nucleic Acids Research},

volume = {49},

number = {D1},

pages = {D412 - D419},

publisher = {Oxford University Press},

abstract = {The Pfam database is a widely used resource for classifying protein sequences into families and domains. Since Pfam was last described in this journal, over 350 new families have been added in Pfam 33.1 and numerous improvements have been made to existing entries. To facilitate research on COVID-19, we have revised the Pfam entries that cover the SARS-CoV-2 proteome, and built new entries for regions that were not covered by Pfam. We have reintroduced Pfam-B which provides an automatically generated supplement to Pfam and contains 136 730 novel clusters of sequences that are not yet matched by a Pfam family. The new Pfam-B is based on a clustering by the MMseqs2 software. We have compared all of the regions in the RepeatsDB to those in Pfam and have started to use the results to build and refine Pfam repeat families. Pfam is freely available for browsing and download at http://pfam.xfam.org/. © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.},

note = {Cited by: 5350; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Balatti202113366,

title = {Intrinsically Disordered Region Modulates Ligand Binding in Glutaredoxin 1 from Trypanosoma Brucei},

author = {Galo. E. Balatti and G. Patricio Barletta and Gustavo Parisi and Silvio. C. E. Tosatto and Massimo Bellanda and Sebastian Fernandez-Alberti},

url = {https://www.scopus.com/pages/publications/85121123474?origin=resultslist},

doi = {10.1021/acs.jpcb.1c07035},

issn = {15206106},

year  = {2021},

date = {2021-01-01},

journal = {Journal of Physical Chemistry B},

volume = {125},

number = {49},

pages = {13366 - 13375},

publisher = {American Chemical Society},

abstract = {Glutaredoxins are small proteins that share a common well-conserved thioredoxin-fold and participate in a wide variety of biological processes. Among them, class II Grx are redox-inactive proteins involved in iron–sulfur (Fe-S) metabolism. In the present work, we report different structural and dynamics aspects of 1CGrx1 from the pathogenic parasite Trypanosoma brucei that differentiate it from other orthologues by the presence of a parasite-specific unstructured N-terminal extension whose role has not been fully elucidated yet. Previous nuclear magnetic resonance (NMR) studies revealed significant differences with respect to the mutant lacking the disordered tail. Herein, we have performed atomistic molecular dynamics simulations that, complementary to NMR studies, confirm the intrinsically disordered nature of the N-terminal extension. Moreover, we confirm the main role of these residues in modulating the conformational dynamics of the glutathione-binding pocket. We observe that the N-terminal extension modifies the ligand cavity stiffening it by specific interactions that ultimately modulate its intrinsic flexibility, which may modify its role in the storage and/or transfer of preformed iron–sulfur clusters. These unique structural and dynamics aspects of Trypanosoma brucei 1CGrx1 differentiate it from other orthologues and could have functional relevance. In this way, our results encourage the study of other similar protein folding families with intrinsically disordered regions whose functional roles are still unrevealed and the screening of potential 1CGrx1 inhibitors as antitrypanosomal drug candidates. © 2021 American Chemical Society},

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

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Csizmadia2021D355,

title = {The MemMoRF database for recognizing disordered protein regions interacting with cellular membranes},

author = {Georgina Csizmadia and Gábor Erdős and Hedvig Tordai and Rita Padányi and Silvio Tosatto and Zsuzsanna Dosztányi and Tamás Hegedűs},

url = {https://www.scopus.com/pages/publications/85099428815?origin=resultslist},

doi = {10.1093/nar/gkaa954},

issn = {03051048},

year  = {2021},

date = {2021-01-01},

journal = {Nucleic Acids Research},

volume = {49},

number = {D1},

pages = {D355 - D360},

publisher = {Oxford University Press},

abstract = {Protein and lipid membrane interactions play fundamental roles in a large number of cellular processes (e.g. signalling, vesicle trafficking, or viral invasion). A growing number of examples indicate that such interactions can also rely on intrinsically disordered protein regions (IDRs), which can form specific reversible interactions not only with proteins but also with lipids. We named IDRs involved in such membrane lipid-induced disorder-to-order transition as MemMoRFs, in an analogy to IDRs exhibiting disorder-to-order transition upon interaction with protein partners termed Molecular Recognition Features (MoRFs). Currently, both the experimental detection and computational characterization of MemMoRFs are challenging, and information about these regions are scattered in the literature. To facilitate the related investigations we generated a comprehensive database of experimentally validated MemMoRFs based on manual curation of literature and structural data. To characterize the dynamics of MemMoRFs, secondary structure propensity and flexibility calculated from nuclear magnetic resonance chemical shifts were incorporated into the database. These data were supplemented by inclusion of sentences from papers, functional data and disease-related information. The MemMoRF database can be accessed via a user-friendly interface at https://memmorf.hegelab.org, potentially providing a central resource for the characterization of disordered regions in transmembrane and membrane-associated proteins. © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com},

note = {Cited by: 13; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Laquatra2021,

title = {HIF1α-dependent induction of the mitochondrial chaperone TRAP1 regulates bioenergetic adaptations to hypoxia},

author = {Claudio Laquatra and Carlos Sanchez-Martin and Alberto Dinarello and Giuseppe Cannino and Giovanni Minervini and Elisabetta Moroni and Marco Schiavone and Silvio Tosatto and Francesco Argenton and Giorgio Colombo and Paolo Bernardi and Ionica Masgras and Andrea Rasola},

url = {https://www.scopus.com/pages/publications/85105148823?origin=resultslist},

doi = {10.1038/s41419-021-03716-6},

issn = {20414889},

year  = {2021},

date = {2021-01-01},

journal = {Cell Death and Disease},

volume = {12},

number = {5},

publisher = {Springer Nature},

abstract = {The mitochondrial paralog of the Hsp90 chaperone family TRAP1 is often induced in tumors, but the mechanisms controlling its expression, as well as its physiological functions remain poorly understood. Here, we find that TRAP1 is highly expressed in the early stages of Zebrafish development, and its ablation delays embryogenesis while increasing mitochondrial respiration of fish larvae. TRAP1 expression is enhanced by hypoxic conditions both in developing embryos and in cancer models of Zebrafish and mammals. The TRAP1 promoter contains evolutionary conserved hypoxic responsive elements, and HIF1α stabilization increases TRAP1 levels. TRAP1 inhibition by selective compounds or by genetic knock-out maintains a high level of respiration in Zebrafish embryos after exposure to hypoxia. Our data identify TRAP1 as a primary regulator of mitochondrial bioenergetics in highly proliferating cells following reduction in oxygen tension and HIF1α stabilization. © 2021, The Author(s).},

note = {Cited by: 33; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Quaglia2021,

title = {Exploring Curated Conformational Ensembles of Intrinsically Disordered Proteins in the Protein Ensemble Database},

author = {Federica Quaglia and Tamas Lazar and András Hatos and Peter Tompa and Damiano Piovesan and Silvio C. E. Tosatto},

url = {https://www.scopus.com/pages/publications/85111647557?origin=resultslist},

doi = {10.1002/cpz1.192},

issn = {26911299},

year  = {2021},

date = {2021-01-01},

journal = {Current Protocols},

volume = {1},

number = {7},

publisher = {John Wiley and Sons Inc},

abstract = {The Protein Ensemble Database (PED; https://proteinensemble.org/) is the major repository of conformational ensembles of intrinsically disordered proteins (IDPs). Conformational ensembles of IDPs are primarily provided by their authors or occasionally collected from literature, and are subsequently deposited in PED along with the corresponding structured, manually curated metadata. The modeling of conformational ensembles usually relies on experimental data from small-angle X-ray scattering (SAXS), fluorescence resonance energy transfer (FRET), NMR spectroscopy, and molecular dynamics (MD) simulations, or a combination of these techniques. The growing number of scientific studies based on these data, along with the astounding and swift progress in the field of protein intrinsic disorder, has required a significant update and upgrade of PED, first published in 2014. To this end, the database was entirely renewed in 2020 and now has a dedicated team of biocurators providing manually curated descriptions of the methods and conditions applied to generate the conformational ensembles and for checking consistency of the data. Here, we present a detailed description on how to explore PED with its protein pages and experimental pages, and how to interpret entries of conformational ensembles. We describe how to efficiently search conformational ensembles deposited in PED by means of its web interface and API. We demonstrate how to make sense of the PED protein page and its associated experimental entry pages with reference to the yeast Sic1 use case. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Performing a search in PED. Support Protocol 1: Programmatic access with the PED API. Basic Protocol 2: Interpreting the protein page and the experimental entry page—the Sic1 use case. Support Protocol 2: Downloading options. Support Protocol 3: Understanding the validation report—the Sic1 use case. Basic Protocol 3: Submitting new conformational ensembles to PED. Basic Protocol 4: Providing feedback in PED. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC.},

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

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Dassie2021732,

title = {Neurocognitive assessment and DNA sequencing expand the phenotype and genotype spectrum of Alström syndrome},

author = {Francesca Dassie and Riccardina Lorusso and Silvia Benavides-Varela and Gabriella Milan and Francesca Favaretto and Edward Callus and Stefano Cagnin and Francesco Reggiani and Giovanni Minervini and Silvio Tosatto and Roberto Vettor and Carlo Semenza and Pietro Maffei},

url = {https://www.scopus.com/pages/publications/85099072292?origin=resultslist},

doi = {10.1002/ajmg.a.62029},

issn = {15524825},

year  = {2021},

date = {2021-01-01},

journal = {American Journal of Medical Genetics, Part A},

volume = {185},

number = {3},

pages = {732 - 742},

publisher = {John Wiley and Sons Inc},

abstract = {Alström syndrome (OMIM#203800) is an ultra-rare autosomal recessive monogenic disease presenting pathogenic variants in ALMS1 (chromosome 2p13). It is characterized by early onset of blindness, hearing loss and systemic comorbidities, with delayed development without cognitive impairment. We aimed to investigate the cognitive functions and describe new pathogenic variants in Alström syndrome patients. Nineteen patients (13 adults, 6 children) underwent a thorough clinical, genetic, laboratory, instrumental, and neurocognitive assessment. Six new pathogenic variants in ALMS1 including the first described in exon 6 were identified. Four patients displayed a “mild phenotype” characterized by slow disease onset or absence of complications, including childhood obesity and association with at least one pathogenic variant in exon 5 or 6. At neurocognitive testing, a significant proportion of patients had deficits in three neurocognitive domains: similarities, phonological memory, and apraxia. In particular, 53% of patients showed difficulties in the auditory working memory test. We found ideomotor and buccofacial apraxia in 74% of patients. “Mild phenotype” patients performed better on auditory working memory and ideomotor apraxia test than “typical phenotype” ones (91.9 + 16.3% vs. 41.7 + 34.5% of correct answers},

note = {Cited by: 8},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Blum2021D344,

title = {The InterPro protein families and domains database: 20 years on},

author = {Matthias Blum and Hsin-Yu Chang and Sara Chuguransky and Tiago Grego and Swaathi Kandasaamy and Alex Mitchell and Gift Nuka and Typhaine Paysan-Lafosse and Matloob Qureshi and Shriya Raj and Lorna Richardson and Gustavo A. Salazar and Lowri Williams and Peer Bork and Alan Bridge and Julian Gough and Daniel H. Haft and Ivica Letunic and Aron Marchler-Bauer and Huaiyu Mi and Darren A. Natale and Marco Necci and Christine A. Orengo and Arun P. Pandurangan and Catherine Rivoire and Christian J. A. Sigrist and Ian Sillitoe and Narmada Thanki and Paul D. Thomas and Silvio C. E. Tosatto and Cathy H. Wu and Alex Bateman and Robert D. Finn},

url = {https://www.scopus.com/pages/publications/85099149539?origin=resultslist},

doi = {10.1093/nar/gkaa977},

issn = {03051048},

year  = {2021},

date = {2021-01-01},

journal = {Nucleic Acids Research},

volume = {49},

number = {D1},

pages = {D344 - D354},

publisher = {Oxford University Press},

abstract = {The InterPro database (https://www.ebi.ac.uk/interpro/) provides an integrative classification of protein sequences into families, and identifies functionally important domains and conserved sites. InterProScan is the underlying software that allows protein and nucleic acid sequences to be searched against InterPro's signatures. Signatures are predictive models which describe protein families, domains or sites, and are provided by multiple databases. InterPro combines signatures representing equivalent families, domains or sites, and provides additional information such as descriptions, literature references and Gene Ontology (GO) terms, to produce a comprehensive resource for protein classification. Founded in 1999, InterPro has become one of the most widely used resources for protein family annotation. Here, we report the status of InterPro (version 81.0) in its 20th year of operation and its associated software, including updates to database content, the release of a new website and REST API, and performance improvements in InterProScan. © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.},

note = {Cited by: 1807; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Bertolio2021,

title = {A Novel Splice Variant of Human TGF-β Type II Receptor Encodes a Soluble Protein and Its Fc-Tagged Version Prevents Liver Fibrosis in vivo},

author = {Marcela Soledad Bertolio and Anabela La Colla and Alejandra Carrea and Ana Romo and Gabriela Canziani and Stella Maris Echarte and Sabrina Campisano and German Patricio Barletta and Alexander Miguel Monzon and Tania Melina Rodríguez and Andrea Nancy Chisari and Ricardo Alfredo Dewey},

url = {https://www.scopus.com/pages/publications/85115828696?origin=resultslist},

doi = {10.3389/fcell.2021.690397},

issn = {2296634X},

year  = {2021},

date = {2021-01-01},

journal = {Frontiers in Cell and Developmental Biology},

volume = {9},

publisher = {Frontiers Media S.A.},

abstract = {We describe, for the first time, a new splice variant of the human TGF-β type II receptor (TβRII). The new transcript lacks 149 nucleotides, resulting in a frameshift and the emergence of an early stop codon, rendering a truncated mature protein of 57 amino acids. The predicted protein, lacking the transmembrane domain and with a distinctive 13-amino-acid stretch at its C-terminus, was named TβRII-Soluble Endogenous (TβRII-SE). Binding predictions indicate that the novel 13-amino-acid stretch interacts with all three TGF-β cognate ligands and generates a more extensive protein–protein interface than TβRII. TβRII-SE and human IgG1 Fc domain were fused in frame in a lentiviral vector (Lv) for further characterization. With this vector, we transduced 293T cells and purified TβRII-SE/Fc by A/G protein chromatography from conditioned medium. Immunoblotting revealed homogeneous bands of approximately 37 kDa (reduced) and 75 kDa (non-reduced), indicating that TβRII-SE/Fc is secreted as a disulfide-linked homodimer. Moreover, high-affinity binding of TβRII-SE to the three TGF-β isoforms was confirmed by surface plasmon resonance (SPR) analysis. Also, intrahepatic delivery of Lv.TβRII-SE/Fc in a carbon tetrachloride-induced liver fibrosis model revealed amelioration of liver injury and fibrosis. Our results indicate that TβRII-SE is a novel member of the TGF-β signaling pathway with distinctive characteristics. This novel protein offers an alternative for the prevention and treatment of pathologies caused by the overproduction of TGF-β ligands. © Copyright © 2021 Bertolio, La Colla, Carrea, Romo, Canziani, Echarte, Campisano, Barletta, Monzon, Rodríguez, Chisari and Dewey.},

note = {Cited by: 9; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Parisi2021146,

title = {“Protein” no longer means what it used to},

author = {Gustavo Parisi and Nicolas Palopoli and Silvio C. E. Tosatto and María Silvina Fornasari and Peter Tompa},

url = {https://www.scopus.com/pages/publications/85110173062?origin=resultslist},

doi = {10.1016/j.crstbi.2021.06.002},

issn = {2665928X},

year  = {2021},

date = {2021-01-01},

journal = {Current Research in Structural Biology},

volume = {3},

pages = {146 - 152},

publisher = {Elsevier B.V.},

abstract = {Every biologist knows that the word protein describes a group of macromolecules essential to sustain life on Earth. As biologists, we are invariably trained under a protein paradigm established since the early twentieth century. However, in recent years, the term protein unveiled itself as an euphemism to describe the overwhelming heterogeneity of these compounds. Most of our current studies are targeted on carefully selected subsets of proteins, but we tend to think and write about these as representative of the whole population. Here we discuss how seeking for universal definitions and general rules in any arbitrarily segmented study would be misleading about the conclusions. Of course, it is not our purpose to discourage the use of the word protein. Instead, we suggest to embrace the extended universe of proteins to reach a deeper understanding of their full potential, realizing that the term encompasses a group of molecules very heterogeneous in terms of size, shape, chemistry and functions, i.e. the term protein no longer means what it used to. © 2021 The Authors},

note = {Cited by: 6; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Palopoli2021,

title = {Intrinsically Disordered Protein Ensembles Shape Evolutionary Rates Revealing Conformational Patterns},

author = {Nicolas Palopoli and Julia Marchetti and Alexander M. Monzon and Diego J. Zea and Silvio C. E. Tosatto and Maria S. Fornasari and Gustavo Parisi},

url = {https://www.scopus.com/pages/publications/85098132673?origin=resultslist},

doi = {10.1016/j.jmb.2020.166751},

issn = {00222836},

year  = {2021},

date = {2021-01-01},

journal = {Journal of Molecular Biology},

volume = {433},

number = {3},

publisher = {Academic Press},

abstract = {Intrinsically disordered proteins (IDPs) lack stable tertiary structure under physiological conditions. The unique composition and complex dynamical behaviour of IDPs make them a challenge for structural biology and molecular evolution studies. Using NMR ensembles, we found that IDPs evolve under a strong site-specific evolutionary rate heterogeneity, mainly originated by different constraints derived from their inter-residue contacts. Evolutionary rate profiles correlate with the experimentally observed conformational diversity of the protein, allowing the description of different conformational patterns possibly related to their structure-function relationships. The correlation between evolutionary rates and contact information improves when structural information is taken not from any individual conformer or the whole ensemble, but from combining a limited number of conformers. Our results suggest that residue contacts in disordered regions constrain evolutionary rates to conserve the dynamic behaviour of the ensemble and that evolutionary rates can be used as a proxy for the conformational diversity of IDPs. © 2020 Elsevier Ltd},

note = {Cited by: 7; All Open Access; Bronze Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Hatos2021,

title = {APICURON: A database to credit and acknowledge the work of biocurators},

author = {András Hatos and Federica Quaglia and Damiano Piovesan and Silvio C. E Tosatto},

url = {https://www.scopus.com/pages/publications/85105906122?origin=resultslist},

doi = {10.1093/database/baab019},

issn = {17580463},

year  = {2021},

date = {2021-01-01},

journal = {Database},

volume = {2021},

publisher = {Oxford University Press},

abstract = {APICURON is an open and freely accessible resource that tracks and credits the work of biocurators across multiple participating knowledgebases. Biocuration is essential to extract knowledge from research data and make it available in a structured and standardized way to the scientific community. However, processing biological data - mainly from literature - requires a huge effort that is difficult to attribute and quantify. APICURON collects biocuration events from third-party resources and aggregates this information, spotlighting biocurator contributions. APICURON promotes biocurator engagement implementing gamification concepts like badges, medals and leaderboards and at the same time provides a monitoring service for registered resources and for biocurators themselves. APICURON adopts a data model that is flexible enough to represent and track the majority of biocuration activities. Biocurators are identified through their Open Researcher and Contributor ID. The definition of curation events, scoring systems and rules for assigning badges and medals are resource-specific and easily customizable. Registered resources can transfer curation activities on the fly through a secure and robust Application Programming Interface (API). Here, we show how simple and effective it is to connect a resource to APICURON, describing the DisProt database of intrinsically disordered proteins as a use case. We believe APICURON will provide biological knowledgebases with a service to recognize and credit the effort of their biocurators, monitor their activity and promote curator engagement. Database URL: https://apicuron.org © 2021 The Author(s). Published by Oxford University Press.},

note = {Cited by: 17; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Paladin2021D452,

title = {RepeatsDB in 2021: Improved data and extended classification for protein tandem repeat structures},

author = {Lisanna Paladin and Martina Bevilacqua and Sara Errigo and Damiano Piovesan and Ivan Mičetić and Marco Necci and Alexander Miguel Monzon and Maria Laura Fabre and Jose Luis Lopez and Juliet F. Nilsson and Javier Rios and Pablo Lorenzano Menna and Maia Cabrera and Martin Gonzalez Buitron and Mariane Gonçalves Kulik and Sebastian Fernandez-Alberti and Maria Silvina Fornasari and Gustavo Parisi and Antonio Lagares and Layla Hirsh and Miguel A. Andrade-Navarro and Andrey V. Kajava and Silvio C. E. Tosatto},

url = {https://www.scopus.com/pages/publications/85099429028?origin=resultslist},

doi = {10.1093/nar/gkaa1097},

issn = {03051048},

year  = {2021},

date = {2021-01-01},

journal = {Nucleic Acids Research},

volume = {49},

number = {D1},

pages = {D452 - D457},

publisher = {Oxford University Press},

abstract = {The RepeatsDB database (URL: https://repeatsdb.org/) provides annotations and classification for protein tandem repeat structures from the Protein Data Bank (PDB). Protein tandem repeats are ubiquitous in all branches of the tree of life. The accumulation of solved repeat structures provides new possibilities for classification and detection, but also increasing the need for annotation. Here we present RepeatsDB 3.0, which addresses these challenges and presents an extended classification scheme. The major conceptual change compared to the previous version is the hierarchical classification combining top levels based solely on structural similarity (Class > Topology > Fold) with two new levels (Clan > Family) requiring sequence similarity and describing repeat motifs in collaboration with Pfam. Data growth has been addressed with improved mechanisms for browsing the classification hierarchy. A new UniProt-centric view unifies the increasingly frequent annotation of structures from identical or similar sequences. This update of RepeatsDB aligns with our commitment to develop a resource that extracts, organizes and distributes specialized information on tandem repeat protein structures. © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.},

note = {Cited by: 42; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Walsh20211122,

title = {DOME: recommendations for supervised machine learning validation in biology},

author = {Ian Walsh and Dmytro Fishman and Dario Garcia-Gasulla and Tiina Titma and Gianluca Pollastri and Emidio Capriotti and Rita Casadio and Salvador Capella-Gutierrez and Davide Cirillo and Alessio Del Conte and Alexandros C. Dimopoulos and Victoria Dominguez Del Angel and Joaquin Dopazo and Piero Fariselli and José Maria Fernández and Florian Huber and Anna Kreshuk and Tom Lenaerts and Pier Luigi Martelli and Arcadi Navarro and Pilib Ó Broin and Janet Piñero and Damiano Piovesan and Martin Reczko and Francesco Ronzano and Venkata Satagopam and Castrense Savojardo and Vojtech Spiwok and Marco Antonio Tangaro and Giacomo Tartari and David Salgado and Alfonso Valencia and Federico Zambelli and Jennifer Harrow and Fotis E. Psomopoulos and Silvio C. E. Tosatto},

url = {https://www.scopus.com/pages/publications/85111967406?origin=resultslist},

doi = {10.1038/s41592-021-01205-4},

issn = {15487091},

year  = {2021},

date = {2021-01-01},

journal = {Nature Methods},

volume = {18},

number = {10},

pages = {1122 - 1127},

publisher = {Nature Research},

note = {Cited by: 226; All Open Access; Green Open Access; Hybrid Gold Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Necci2021472,

title = {Critical assessment of protein intrinsic disorder prediction},

author = {Marco Necci and Damiano Piovesan and Md Tamjidul Hoque and Ian Walsh and Sumaiya Iqbal and Michele Vendruscolo and Pietro Sormanni and Chen Wang and Daniele Raimondi and Ronesh Sharma and Yaoqi Zhou and Thomas Litfin and Oxana Valerianovna Galzitskaya and Michail Yu. Lobanov and Wim Vranken and Björn Wallner and Claudio Mirabello and Nawar Malhis and Zsuzsanna Dosztányi and Gábor Erdős and Bálint Mészáros and Jianzhao Gao and Kui Wang and Gang Hu and Zhonghua Wu and Alok Sharma and Jack Hanson and Kuldip Paliwal and Isabelle Callebaut and Tristan Bitard-Feildel and Gabriele Orlando and Zhenling Peng and Jinbo Xu and Sheng Wang and David T. Jones and Domenico Cozzetto and Fanchi Meng and Jing Yan and Jörg Gsponer and Jianlin Cheng and Tianqi Wu and Lukasz Kurgan and Vasilis J. Promponas and Stella Tamana and Cristina Marino-Buslje and Elizabeth Martínez-Pérez and Anastasia Chasapi and Christos Ouzounis and A. Keith Dunker and Andrey V. Kajava and Jeremy Y. Leclercq and Burcu Aykac-Fas and Matteo Lambrughi and Emiliano Maiani and Elena Papaleo and Lucia Beatriz Chemes and Lucía Álvarez and Nicolás S. González-Foutel and Valentin Iglesias and Jordi Pujols and Salvador Ventura and Nicolás Palopoli and Guillermo Ignacio Benítez and Gustavo Parisi and Claudio Bassot and Arne Elofsson and Sudha Govindarajan and John Lamb and Marco Salvatore and András Hatos and Alexander Miguel Monzon and Martina Bevilacqua and Ivan Mičetić and Giovanni Minervini and Lisanna Paladin and Federica Quaglia and Emanuela Leonardi and Norman Davey and Tamas Horvath and Orsolya Panna Kovacs and Nikoletta Murvai and Rita Pancsa and Eva Schad and Beata Szabo and Agnes Tantos and Sandra Macedo-Ribeiro and Jose Antonio Manso and Pedro José Barbosa Pereira and Radoslav Davidović and Nevena Veljkovic and Borbála Hajdu-Soltész and Mátyás Pajkos and Tamás Szaniszló and Mainak Guharoy and Tamas Lazar and Mauricio Macossay-Castillo and Peter Tompa and Silvio C. E. Tosatto},

url = {https://www.scopus.com/pages/publications/85104988931?origin=resultslist},

doi = {10.1038/s41592-021-01117-3},

issn = {15487091},

year  = {2021},

date = {2021-01-01},

journal = {Nature Methods},

volume = {18},

number = {5},

pages = {472 - 481},

publisher = {Nature Research},

abstract = {Intrinsically disordered proteins, defying the traditional protein structure–function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has F_{max} = 0.483 on the full dataset and F_{max} = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with F_{max} = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude. © 2021, The Author(s), under exclusive licence to Springer Nature America, Inc.},

note = {Cited by: 287; All Open Access; Green Open Access; Hybrid Gold Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lazar2021D404,

title = {PED in 2021: A major update of the protein ensemble database for intrinsically disordered proteins},

author = {Tamas Lazar and Elizabeth Martínez-Pérez and Federica Quaglia and András Hatos and Lucía B. Chemes and Javier A. Iserte and Nicolás A. Méndez and Nicolás A. Garrone and Tadeo E. Saldaño and Julia Marchetti and Ana Julia Velez Rueda and Pau Bernadó and Martin Blackledge and Tiago N. Cordeiro and Eric Fagerberg and Julie D. Forman-Kay and Maria S. Fornasari and Toby J. Gibson and Gregory-Neal W. Gomes and Claudiu C. Gradinaru and Teresa Head-Gordon and Malene Ringkjøbing Jensen and Edward A. Lemke and Sonia Longhi and Cristina Marino-Buslje and Giovanni Minervini and Tanja Mittag and Alexander Miguel Monzon and Rohit V. Pappu and Gustavo Parisi and Sylvie Ricard-Blum and Kiersten M. Ruff and Edoardo Salladini and Marie Skepö and Dmitri Svergun and Sylvain D. Vallet and Mihaly Varadi and Peter Tompa and Silvio C. E. Tosatto and Damiano Piovesan},

url = {https://www.scopus.com/pages/publications/85095859724?origin=resultslist},

doi = {10.1093/nar/gkaa1021},

issn = {03051048},

year  = {2021},

date = {2021-01-01},

journal = {Nucleic Acids Research},

volume = {49},

number = {D1},

pages = {D404 - D411},

publisher = {Oxford University Press},

abstract = {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. © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited.},

note = {Cited by: 123; All Open Access; Gold Open Access; Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}