Group Leader
SOCIAL
CONTACTS
+39 049 827 6260
+39 049 827 6269
BIOGRAPHY
Silvio C. E. Tosatto is currently Full Professor of Bioinformatics and Head of the BioComputing UP lab at the Department of Biomedical Sciences of the University of Padua (Italy). Within ELIXIR, the European infrastructure for blife science data, he is deputy Head of Node of ELIXIR Italy, ExCo of the Data Platform, co-lead of the Cellular & Molecular Research priority area as well as co-lead of the Machine Learning focus group.
ACADEMIC POSITION
Full professor
since (10/2016)
DEGREES
- 2002 – PhD (Dr. rer. nat., Grade: Magna cum laude) in bioinformatics (computer science)
Universität Mannheim – Germany - 1998 – Graduate in Computer Science & Business Administration (Diplom Wirtschaftsinformatiker)
Universität Mannheim – Germany
LANGUAGES
English
Spanish
German
Italian
(Fluent)
(Fluent)
(Native)
(Native)
2024
Journal Articles
Alessio Del Conte; Giorgia F Camagni; Damiano Clementel; Giovanni Minervini; Alexander Miguel Monzon; Carlo Ferrari; Damiano Piovesan; Silvio C. E Tosatto
RING 4.0: Faster residue interaction networks with novel interaction types across over 35,000 different chemical structures Journal Article
In: 2024, ISSN: 03051048, (Cited by: 5; All Open Access, Gold Open Access).
@article{DelConte2024W306,
title = {RING 4.0: Faster residue interaction networks with novel interaction types across over 35,000 different chemical structures},
author = { Alessio Del Conte and Giorgia F Camagni and Damiano Clementel and Giovanni Minervini and Alexander Miguel Monzon and Carlo Ferrari and Damiano Piovesan and Silvio C. E Tosatto},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197788039\&doi=10.1093%2fnar%2fgkae337\&partnerID=40\&md5=bca70d16fbb39f5466a3957673ef9eef},
doi = {10.1093/nar/gkae337},
issn = {03051048},
year = {2024},
date = {2024-01-01},
abstract = {Residue interaction networks (RINs) are a valuable approach for representing contacts in protein structures. RINs have been widely used in various research areas, including the analysis of mutation effects, domain-domain communication, catalytic activity, and molecular dynamics simulations. The RING server is a powerful tool to calculate non-covalent molecular interactions based on geometrical parameters, providing high-quality and reliable results. Here, we introduce RING 4.0, which includes significant enhancements for identifying both covalent and non-covalent bonds in protein structures. It now encompasses seven different interaction types, with the addition of π-hydrogen, halogen bonds and metal ion coordination sites. The definitions of all available bond types have also been refined and RING can now process the complete PDB chemical component dictionary (over 35000 different molecules) which provides atom names and covalent connectivity information for all known ligands. Optimization of the software has improved execution time by an order of magnitude. The RING web server has been redesigned to provide a more engaging and interactive user experience, incorporating new visualization tools. Users can now visualize all types of interactions simultaneously in the structure viewer and network component. The web server, including extensive help and tutorials, is available from URL: https://ring.biocomputingup.it/. © 2024 The Author(s). Published by Oxford University Press on behalf of Nucleic Acids Research.},
note = {Cited by: 5; All Open Access, Gold Open Access},
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pubstate = {published},
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Massimo Bellanda; Milena Damulewicz; Barbara Zambelli; Elisa Costanzi; Francesco Gregoris; Stefano Mammi; Silvio C. E. Tosatto; Rodolfo Costa; Giovanni Minervini; Gabriella M. Mazzotta
A PDZ scaffolding/CaM-mediated pathway in Cryptochrome signaling Journal Article
In: 2024, ISSN: 09618368, (Cited by: 0).
@article{Bellanda2024,
title = {A PDZ scaffolding/CaM-mediated pathway in Cryptochrome signaling},
author = { Massimo Bellanda and Milena Damulewicz and Barbara Zambelli and Elisa Costanzi and Francesco Gregoris and Stefano Mammi and Silvio C. E. Tosatto and Rodolfo Costa and Giovanni Minervini and Gabriella M. Mazzotta},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185346556\&doi=10.1002%2fpro.4914\&partnerID=40\&md5=9d3ca7169c5c85e7e43289adbe2c3e24},
doi = {10.1002/pro.4914},
issn = {09618368},
year = {2024},
date = {2024-01-01},
abstract = {Cryptochromes are cardinal constituents of the circadian clock, which orchestrates daily physiological rhythms in living organisms. A growing body of evidence points to their participation in pathways that have not traditionally been associated with circadian clock regulation, implying that cryptochromes may be subject to modulation by multiple signaling mechanisms. In this study, we demonstrate that human CRY2 (hCRY2) forms a complex with the large, modular scaffolding protein known as Multi-PDZ Domain Protein 1 (MUPP1). This interaction is facilitated by the calcium-binding protein Calmodulin (CaM) in a calcium-dependent manner. Our findings suggest a novel cooperative mechanism for the regulation of mammalian cryptochromes, mediated by calcium ions (Ca2+) and CaM. We propose that this Ca2+/CaM-mediated signaling pathway may be an evolutionarily conserved mechanism that has been maintained from Drosophila to mammals, most likely in relation to its potential role in the broader context of cryptochrome function and regulation. Further, the understanding of cryptochrome interactions with other proteins and signaling pathways could lead to a better definition of its role within the intricate network of molecular interactions that govern circadian rhythms. © 2024 The Protein Society.},
note = {Cited by: 0},
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pubstate = {published},
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}
Hamidreza Ghafouri; Tamas Lazar; Alessio Del Conte; Luiggi G. Tenorio Ku; Peter Tompa; Silvio C.E. Tosatto; Alexander Miguel Monzon; Maria C. Aspromonte; Pau Bernadó; Belén Chaves-Arquero; Lucia Beatriz Chemes; Damiano Clementel; Tiago N. Cordeiro; Carlos A. Elena-Real; Michael Feig; Isabella C. Felli; Carlo Ferrari; Julie D. Forman-Kay; Tiago Gomes; Frank Gondelaud; Claudiu C. Gradinaru; Tâp Ha-Duong; Teresa Head-Gordon; Pétur O. Heidarsson; Giacomo Janson; Gunnar Jeschke; Emanuela Leonardi; Zi Hao Liu; Sonia Longhi; Xamuel L. Lund; Maria J. Macias; Pau Martin-Malpartida; Davide Mercadante; Assia Mouhand; Gabor Nagy; María Victoria Nugnes; José Manuel Pérez-Cañadillas; Giulia Pesce; Roberta Pierattelli; Damiano Piovesan; Federica Quaglia; Sylvie Ricard-Blum; Paul Robustelli; Amin Sagar; Edoardo Salladini; Lucile Sénicourt; Nathalie Sibille; João M.C. Teixeira; Thomas E. Tsangaris; Mihaly Varadi
PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins Journal Article
In: 2024, ISSN: 03051048, (Cited by: 10; All Open Access, Gold Open Access).
@article{Ghafouri2024D536,
title = {PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins},
author = { Hamidreza Ghafouri and Tamas Lazar and Alessio Del Conte and Luiggi G. Tenorio Ku and Peter Tompa and Silvio C.E. Tosatto and Alexander Miguel Monzon and Maria C. Aspromonte and Pau Bernad\'{o} and Bel\'{e}n Chaves-Arquero and Lucia Beatriz Chemes and Damiano Clementel and Tiago N. Cordeiro and Carlos A. Elena-Real and Michael Feig and Isabella C. Felli and Carlo Ferrari and Julie D. Forman-Kay and Tiago Gomes and Frank Gondelaud and Claudiu C. Gradinaru and T\^{a}p Ha-Duong and Teresa Head-Gordon and P\'{e}tur O. Heidarsson and Giacomo Janson and Gunnar Jeschke and Emanuela Leonardi and Zi Hao Liu and Sonia Longhi and Xamuel L. Lund and Maria J. Macias and Pau Martin-Malpartida and Davide Mercadante and Assia Mouhand and Gabor Nagy and Mar\'{i}a Victoria Nugnes and Jos\'{e} Manuel P\'{e}rez-Ca\~{n}adillas and Giulia Pesce and Roberta Pierattelli and Damiano Piovesan and Federica Quaglia and Sylvie Ricard-Blum and Paul Robustelli and Amin Sagar and Edoardo Salladini and Lucile S\'{e}nicourt and Nathalie Sibille and Jo\~{a}o M.C. Teixeira and Thomas E. Tsangaris and Mihaly Varadi},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181761325\&doi=10.1093%2fnar%2fgkad947\&partnerID=40\&md5=0ad51562357f3e5f603d744e02f8729a},
doi = {10.1093/nar/gkad947},
issn = {03051048},
year = {2024},
date = {2024-01-01},
abstract = {The Protein Ensemble Database (PED) (URL: https://proteinensemble.org) is the primary resource for depositing structural ensembles of intrinsically disordered proteins. This updated version of PED reflects advancements in the field, denoting a continual expansion with a total of 461 entries and 538 ensembles, including those generated without explicit experimental data through novel machine learning (ML) techniques. With this significant increment in the number of ensembles, a few yet-unprecedented new entries entered the database, including those also determined or refined by electron paramagnetic resonance or circular dichroism data. In addition, PED was enriched with several new features, including a novel deposition service, improved user interface, new database cross-referencing options and integration with the 3D-Beacons network\textemdashall representing efforts to improve the FAIRness of the database. Foreseeably, PED will keep growing in size and expanding with new types of ensembles generated by accurate and fast ML-based generative models and coarse-grained simulations. Therefore, among future efforts, priority will be given to further develop the database to be compatible with ensembles modeled at a coarse-grained level. © The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.},
note = {Cited by: 10; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Damiano Piovesan; Davide Zago; Parnal Joshi; M. Clara De Paolis Kaluza; Mahta Mehdiabadi; Rashika Ramola; Alexander Miguel Monzon; Walter Reade; Iddo Friedberg; Predrag Radivojac; Silvio C. E. Tosatto
CAFA-evaluator: a Python tool for benchmarking ontological classification methods Journal Article
In: 2024, ISSN: 26350041, (Cited by: 2; All Open Access, Gold Open Access).
@article{Piovesan2024,
title = {CAFA-evaluator: a Python tool for benchmarking ontological classification methods},
author = { Damiano Piovesan and Davide Zago and Parnal Joshi and M. Clara De Paolis Kaluza and Mahta Mehdiabadi and Rashika Ramola and Alexander Miguel Monzon and Walter Reade and Iddo Friedberg and Predrag Radivojac and Silvio C. E. Tosatto},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188993912\&doi=10.1093%2fbioadv%2fvbae043\&partnerID=40\&md5=b6e09ea188a60708097f5bc31ba115dd},
doi = {10.1093/bioadv/vbae043},
issn = {26350041},
year = {2024},
date = {2024-01-01},
abstract = {We present CAFA-evaluator, a powerful Python program designed to evaluate the performance of prediction methods on targets with hierarchical concept dependencies. It generalizes multi-label evaluation to modern ontologies where the prediction targets are drawn from a directed acyclic graph and achieves high efficiency by leveraging matrix computation and topological sorting. The program requirements include a small number of standard Python libraries, making CAFA-evaluator easy to maintain. The code replicates the Critical Assessment of protein Function Annotation (CAFA) benchmarking, which evaluates predictions of the consistent subgraphs in Gene Ontology. Owing to its reliability and accuracy, the organizers have selected CAFA-evaluator as the official CAFA evaluation software. © 2024 The Author(s). Published by Oxford University Press.},
note = {Cited by: 2; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Francesco Gregoris; Giovanni Minervini; Silvio C. E. Tosatto
In Silico Exploration of AHR-HIF Pathway Interplay: Implications for Therapeutic Targeting in ccRCC Journal Article
In: 2024, ISSN: 20734425, (Cited by: 0; All Open Access, Gold Open Access).
@article{Gregoris2024,
title = {In Silico Exploration of AHR-HIF Pathway Interplay: Implications for Therapeutic Targeting in ccRCC},
author = { Francesco Gregoris and Giovanni Minervini and Silvio C. E. Tosatto},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205114282\&doi=10.3390%2fgenes15091167\&partnerID=40\&md5=4358b236c257d898f6c44e2639ebbd9d},
doi = {10.3390/genes15091167},
issn = {20734425},
year = {2024},
date = {2024-01-01},
abstract = {The oxygen-sensing pathway is a crucial regulatory circuit that defines cellular conditions and is extensively exploited in cancer development. Pathogenic mutations in the von Hippel\textendashLindau (VHL) tumour suppressor impair its role as a master regulator of hypoxia-inducible factors (HIFs), leading to constitutive HIF activation and uncontrolled angiogenesis, increasing the risk of developing clear cell renal cell carcinoma (ccRCC). HIF hyperactivation can sequester HIF-1β, preventing the aryl hydrocarbon receptor (AHR) from correctly activating gene expression in response to endogenous and exogenous ligands such as TCDD (dioxins). In this study, we used protein\textendashprotein interaction networks and gene expression profiling to characterize the impact of VHL loss on AHR activity. Our findings reveal specific expression patterns of AHR interactors following exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and in ccRCC. We identified several AHR interactors significantly associated with poor survival rates in ccRCC patients. Notably, the upregulation of the androgen receptor (AR) and retinoblastoma-associated protein (RB1) by TCDD, coupled with their respective downregulation in ccRCC and association with poor survival rates, suggests novel therapeutic targets. The strategic activation of the AHR via selective AHR modulators (SAhRMs) could stimulate its anticancer activity, specifically targeting RB1 and AR to reduce cell cycle progression and metastasis formation in ccRCC. Our study provides comprehensive insights into the complex interplay between the AHR and HIF pathways in ccRCC pathogenesis, offering novel strategies for targeted therapeutic interventions. © 2024 by the authors.},
note = {Cited by: 0; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}