2024
Journal Articles
1.
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: Nucleic Acids Research, vol. 52, no. W1, pp. W306 – W312, 2024, (Cited by: 1; 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},
year = {2024},
date = {2024-01-01},
journal = {Nucleic Acids Research},
volume = {52},
number = {W1},
pages = {W306 \textendash W312},
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: 1; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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.
2.
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: Protein Science, vol. 33, no. 3, 2024, (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},
year = {2024},
date = {2024-01-01},
journal = {Protein Science},
volume = {33},
number = {3},
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},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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.
3.
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: Bioinformatics Advances, vol. 4, no. 1, 2024, (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},
year = {2024},
date = {2024-01-01},
journal = {Bioinformatics Advances},
volume = {4},
number = {1},
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}
}
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.
4.
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: Nucleic Acids Research, vol. 52, no. D1, pp. D536 – D544, 2024, (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},
year = {2024},
date = {2024-01-01},
journal = {Nucleic Acids Research},
volume = {52},
number = {D1},
pages = {D536 \textendash D544},
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}
}
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—all 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.
5.
Federica Quaglia; Anastasia Chasapi; Maria Victoria Nugnes; Maria Cristina Aspromonte; Emanuela Leonardi; Damiano Piovesan; Silvio C.E. Tosatto
Best practices for the manual curation of intrinsically disordered proteins in DisProt Journal Article
In: Database, vol. 2024, 2024, (Cited by: 1; All Open Access, Gold Open Access).
@article{Quaglia2024,
title = {Best practices for the manual curation of intrinsically disordered proteins in DisProt},
author = { Federica Quaglia and Anastasia Chasapi and Maria Victoria Nugnes and Maria Cristina Aspromonte and Emanuela Leonardi and Damiano Piovesan and Silvio C.E. Tosatto},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188297172\&doi=10.1093%2fdatabase%2fbaae009\&partnerID=40\&md5=df4fca19479789139b3fd19bb35c817f},
doi = {10.1093/database/baae009},
year = {2024},
date = {2024-01-01},
journal = {Database},
volume = {2024},
abstract = {The DisProt database is a resource containing manually curated data on experimentally validated intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) from the literature. Developed in 2005, its primary goal was to collect structural and functional information into proteins that lack a fixed three-dimensional structure.Today, DisProt has evolved into a major repository that not only collects experimental data but also contributes to our understanding of the IDPs/IDRs roles in various biological processes, such as autophagy or the life cycle mechanisms in viruses or their involvement in diseases (such as cancer and neurodevelopmental disorders). DisProt offers detailed information on the structural states of IDPs/IDRs, including state transitions, interactions and their functions, all provided as curated annotations. One of the central activities of DisProt is the meticulous curation of experimental data from the literature. For this reason, to ensure that every expert and volunteer curator possesses the requisite knowledge for data evaluation, collection and integration, training courses and curation materials are available. However, biocuration guidelines concur on the importance of developing robust guidelines that not only provide critical information about data consistency but also ensure data acquisition.This guideline aims to provide both biocurators and external users with best practices for manually curating IDPs and IDRs in DisProt. It describes every step of the literature curation process and provides use cases of IDP curation within DisProt. © The Author(s) 2024. Published by Oxford University Press.},
note = {Cited by: 1; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The DisProt database is a resource containing manually curated data on experimentally validated intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) from the literature. Developed in 2005, its primary goal was to collect structural and functional information into proteins that lack a fixed three-dimensional structure.Today, DisProt has evolved into a major repository that not only collects experimental data but also contributes to our understanding of the IDPs/IDRs roles in various biological processes, such as autophagy or the life cycle mechanisms in viruses or their involvement in diseases (such as cancer and neurodevelopmental disorders). DisProt offers detailed information on the structural states of IDPs/IDRs, including state transitions, interactions and their functions, all provided as curated annotations. One of the central activities of DisProt is the meticulous curation of experimental data from the literature. For this reason, to ensure that every expert and volunteer curator possesses the requisite knowledge for data evaluation, collection and integration, training courses and curation materials are available. However, biocuration guidelines concur on the importance of developing robust guidelines that not only provide critical information about data consistency but also ensure data acquisition.This guideline aims to provide both biocurators and external users with best practices for manually curating IDPs and IDRs in DisProt. It describes every step of the literature curation process and provides use cases of IDP curation within DisProt. © The Author(s) 2024. Published by Oxford University Press.
6.
Maria Cristina Aspromonte; Maria Victoria Nugnes; Federica Quaglia; Adel Bouharoua; Silvio C.E. Tosatto; Damiano Piovesan; Vasileios Sagris; Vasilis J. Promponas; Anastasia Chasapi; Erzsébet Fichó; Galo E. Balatti; Gustavo Parisi; Martín González Buitrón; Gabor Erdos; Matyas Pajkos; Zsuzsanna Dosztányi; Laszlo Dobson; Alessio Del Conte; Damiano Clementel; Edoardo Salladini; Emanuela Leonardi; Fatemeh Kordevani; Hamidreza Ghafouri; Luiggi G. Tenorio Ku; Alexander Miguel Monzon; Carlo Ferrari; Zsófia Kálmán; Juliet F. Nilsson; Jaime Santos; Carlos Pintado-Grima; Salvador Ventura; Veronika Ács; Rita Pancsa; Mariane Goncalves Kulik; Miguel A. Andrade-Navarro; Pedro José Barbosa Pereira; Sonia Longhi; Philippe Le Mercier; Julian Bergier; Peter Tompa; Tamas Lazar
DisProt in 2024: improving function annotation of intrinsically disordered proteins Journal Article
In: Nucleic Acids Research, vol. 52, no. D1, pp. D434 – D441, 2024, (Cited by: 9; All Open Access, Gold Open Access).
@article{Aspromonte2024D434,
title = {DisProt in 2024: improving function annotation of intrinsically disordered proteins},
author = { Maria Cristina Aspromonte and Maria Victoria Nugnes and Federica Quaglia and Adel Bouharoua and Silvio C.E. Tosatto and Damiano Piovesan and Vasileios Sagris and Vasilis J. Promponas and Anastasia Chasapi and Erzs\'{e}bet Fich\'{o} and Galo E. Balatti and Gustavo Parisi and Mart\'{i}n Gonz\'{a}lez Buitr\'{o}n and Gabor Erdos and Matyas Pajkos and Zsuzsanna Doszt\'{a}nyi and Laszlo Dobson and Alessio Del Conte and Damiano Clementel and Edoardo Salladini and Emanuela Leonardi and Fatemeh Kordevani and Hamidreza Ghafouri and Luiggi G. Tenorio Ku and Alexander Miguel Monzon and Carlo Ferrari and Zs\'{o}fia K\'{a}lm\'{a}n and Juliet F. Nilsson and Jaime Santos and Carlos Pintado-Grima and Salvador Ventura and Veronika \'{A}cs and Rita Pancsa and Mariane Goncalves Kulik and Miguel A. Andrade-Navarro and Pedro Jos\'{e} Barbosa Pereira and Sonia Longhi and Philippe Le Mercier and Julian Bergier and Peter Tompa and Tamas Lazar},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176208048\&doi=10.1093%2fnar%2fgkad928\&partnerID=40\&md5=fc34ce08667ff42029fdb54d5142c08f},
doi = {10.1093/nar/gkad928},
year = {2024},
date = {2024-01-01},
journal = {Nucleic Acids Research},
volume = {52},
number = {D1},
pages = {D434 \textendash D441},
abstract = {DisProt (URL: https://disprot.org) is the gold standard database for intrinsically disordered proteins and regions, providing valuable information about their functions. The latest version of DisProt brings significant advancements, including a broader representation of functions and an enhanced curation process. These improvements aim to increase both the quality of annotations and their coverage at the sequence level. Higher coverage has been achieved by adopting additional evidence codes. Quality of annotations has been improved by systematically applying Minimum Information About Disorder Experiments (MIADE) principles and reporting all the details of the experimental setup that could potentially influence the structural state of a protein. The DisProt database now includes new thematic datasets and has expanded the adoption of Gene Ontology terms, resulting in an extensive functional repertoire which is automatically propagated to UniProtKB. Finally, we show that DisProt’s curated annotations strongly correlate with disorder predictions inferred from AlphaFold2 pLDDT (predicted Local Distance Difference Test) confidence scores. This comparison highlights the utility of DisProt in explaining apparent uncertainty of certain well-defined predicted structures, which often correspond to folding-upon-binding fragments. Overall, DisProt serves as a comprehensive resource, combining experimental evidence of disorder information to enhance our understanding of intrinsically disordered proteins and their functional implications. © The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.},
note = {Cited by: 9; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
DisProt (URL: https://disprot.org) is the gold standard database for intrinsically disordered proteins and regions, providing valuable information about their functions. The latest version of DisProt brings significant advancements, including a broader representation of functions and an enhanced curation process. These improvements aim to increase both the quality of annotations and their coverage at the sequence level. Higher coverage has been achieved by adopting additional evidence codes. Quality of annotations has been improved by systematically applying Minimum Information About Disorder Experiments (MIADE) principles and reporting all the details of the experimental setup that could potentially influence the structural state of a protein. The DisProt database now includes new thematic datasets and has expanded the adoption of Gene Ontology terms, resulting in an extensive functional repertoire which is automatically propagated to UniProtKB. Finally, we show that DisProt’s curated annotations strongly correlate with disorder predictions inferred from AlphaFold2 pLDDT (predicted Local Distance Difference Test) confidence scores. This comparison highlights the utility of DisProt in explaining apparent uncertainty of certain well-defined predicted structures, which often correspond to folding-upon-binding fragments. Overall, DisProt serves as a comprehensive resource, combining experimental evidence of disorder information to enhance our understanding of intrinsically disordered proteins and their functional implications. © The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.
2023
Journal Articles
7.
Paula Nazarena Arrías; Alexander Miguel Monzon; Damiano Clementel; Soroush Mozaffari; Damiano Piovesan; Andrey V. Kajava; Silvio C.E. Tosatto
The repetitive structure of DNA clamps: An overlooked protein tandem repeat Journal Article
In: Journal of Structural Biology, vol. 215, no. 3, 2023, (Cited by: 2; All Open Access, Hybrid Gold Open Access).
@article{Arr\'{i}as2023,
title = {The repetitive structure of DNA clamps: An overlooked protein tandem repeat},
author = { Paula Nazarena Arr\'{i}as 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/inward/record.uri?eid=2-s2.0-85165364940\&doi=10.1016%2fj.jsb.2023.108001\&partnerID=40\&md5=a32d9f45912f167f7d63dd4ecf4c4758},
doi = {10.1016/j.jsb.2023.108001},
year = {2023},
date = {2023-01-01},
journal = {Journal of Structural Biology},
volume = {215},
number = {3},
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: 2; All Open Access, Hybrid Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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
8.
Diana Piol; Laura Tosatto; Emanuela Zuccaro; Eric N. Anderson; Antonella Falconieri; Maria J. Polanco; Caterina Marchioretti; Federica Lia; Joseph White; Elisa Bregolin; Giovanni Minervini; Sara Parodi; Xavier Salvatella; Giorgio Arrigoni; Andrea Ballabio; Albert R. La Spada; Silvio C.E. Tosatto; Fabio Sambataro; Diego L. Medina; Udai B. Pandey; Manuela Basso; Maria Pennuto
In: Science Advances, vol. 9, no. 1, 2023, (Cited by: 6; All Open Access, Gold Open Access).
@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/inward/record.uri?eid=2-s2.0-85145870213\&doi=10.1126%2fsciadv.ade1694\&partnerID=40\&md5=47b819a09fd41c1bb6bde30c1401e4f7},
doi = {10.1126/sciadv.ade1694},
year = {2023},
date = {2023-01-01},
journal = {Science Advances},
volume = {9},
number = {1},
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\textendashregulated kinase plays more than a bystander role in SBMA-vulnerable postmitotic cells. Copyright © 2023 The Authors, some rights reserved;},
note = {Cited by: 6; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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;
9.
Alessio Del Conte; Alexander Miguel Monzon; Damiano Clementel; Giorgia F. Camagni; Giovanni Minervini; Silvio C.E. Tosatto; Damiano Piovesan
RING-PyMOL: residue interaction networks of structural ensembles and molecular dynamics Journal Article
In: Bioinformatics, vol. 39, no. 5, 2023, (Cited by: 6; All Open Access, Gold Open Access, Green Open Access).
@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/inward/record.uri?eid=2-s2.0-85159553803\&doi=10.1093%2fbioinformatics%2fbtad260\&partnerID=40\&md5=39b2bf96d22ea0ee520b95f47b590984},
doi = {10.1093/bioinformatics/btad260},
year = {2023},
date = {2023-01-01},
journal = {Bioinformatics},
volume = {39},
number = {5},
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: 6; All Open Access, Gold Open Access, Green Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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.
10.
Alessio Del Conte; Adel Bouhraoua; Mahta Mehdiabadi; Damiano Clementel; Alexander Miguel Monzon; Silvio C.E. Tosatto; Damiano Piovesan; Alex S. Holehouse; Daniel Griffith; Ryan J. Emenecker; Ashwini Patil; Ronesh Sharma; Tatsuhiko Tsunoda; Alok Sharma; Yi Jun Tang; Bin Liu; Claudio Mirabello; Björn Wallner; Burkhard Rost; Dagmar Ilzhöfer; Maria Littmann; Michael Heinzinger; Lea I.M. Krautheimer; Michael Bernhofer; Liam J. McGuffin; Isabelle Callebaut; Tristan Bitard Feildel; Jian Liu; Jianlin Cheng; Zhiye Guo; Jinbo Xu; Sheng Wang; Nawar Malhis; Jörg Gsponer; Chol-Song Kim; Kun-Sop Han; Myong-Chol Ma; Lukasz Kurgan; Sina Ghadermarzi; Akila Katuwawala; Bi Zhao; Zhenling Peng; Zhonghua Wu; Gang Hu; Kui Wang; Md Tamjidul Hoque; Md Wasi Ul Kabir; Michele Vendruscolo; Pietro Sormanni; Min Li; Fuhao Zhang; Pengzhen Jia; Yida Wang; Michail Yu Lobanov; Oxana V. Galzitskaya; Wim Vranken; Adrián Díaz; Thomas Litfin; Yaoqi Zhou; Jack Hanson; Kuldip Paliwal; Zsuzsanna Dosztányi; Gábor Erdős
CAID prediction portal: A comprehensive service for predicting intrinsic disorder and binding regions in proteins Journal Article
In: Nucleic Acids Research, vol. 51, no. W1, pp. W62 – W69, 2023, (Cited by: 13; All Open Access, Gold Open Access).
@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 Bj\"{o}rn Wallner and Burkhard Rost and Dagmar Ilzh\"{o}fer 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 J\"{o}rg 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 Adri\'{a}n D\'{i}az and Thomas Litfin and Yaoqi Zhou and Jack Hanson and Kuldip Paliwal and Zsuzsanna Doszt\'{a}nyi and G\'{a}bor Erd\H{o}s},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163958831\&doi=10.1093%2fnar%2fgkad430\&partnerID=40\&md5=a458ba56037429c6a042f7610f3cb4bf},
doi = {10.1093/nar/gkad430},
year = {2023},
date = {2023-01-01},
journal = {Nucleic Acids Research},
volume = {51},
number = {W1},
pages = {W62 \textendash W69},
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: 13; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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.