@{MTMT:33286659, title = {Prediction of protein structure and intrinsic disorder in the era of deep learning}, url = {https://m2.mtmt.hu/api/publication/33286659}, author = {Erdős, Gábor and Dosztányi, Zsuzsanna}, booktitle = {Structure and Intrinsic Disorder in Enzymology}, doi = {10.1016/B978-0-323-99533-7.00007-8}, unique-id = {33286659}, year = {2023}, pages = {199-224}, orcid-numbers = {Erdős, Gábor/0000-0001-6218-5192; Dosztányi, Zsuzsanna/0000-0002-3624-5937} } @article{MTMT:32009587, title = {Critical assessment of protein intrinsic disorder prediction}, url = {https://m2.mtmt.hu/api/publication/32009587}, author = {Necci, M. and Piovesan, D. and Hoque, M.T. and Walsh, I. and Iqbal, S. and Vendruscolo, M. and Sormanni, P. and Wang, C. and Raimondi, D. and Sharma, R. and Zhou, Y. and Litfin, T. and Galzitskaya, O.V. and Lobanov, M.Y. and Vranken, W. and Wallner, B. and Mirabello, C. and Malhis, N. and Dosztányi, Zsuzsanna and Erdős, Gábor and Mészáros, B. and Gao, J. and Wang, K. and Hu, G. and Wu, Z. and Sharma, A. and Hanson, J. and Paliwal, K. and Callebaut, I. and Bitard-Feildel, T. and Orlando, G. and Peng, Z. and Xu, J. and Wang, S. and Jones, D.T. and Cozzetto, D. and Meng, F. and Yan, J. and Gsponer, J. and Cheng, J. and Wu, T. and Kurgan, L. and Promponas, V.J. and Tamana, S. and Marino-Buslje, C. and Martínez-Pérez, E. and Chasapi, A. and Ouzounis, C. and Dunker, A.K. and Kajava, A.V. and Leclercq, J.Y. and Aykac-Fas, B. and Lambrughi, M. and Maiani, E. and Papaleo, E. and Chemes, L.B. and Álvarez, L. and González-Foutel, N.S. and Iglesias, V. and Pujols, J. and Ventura, S. and Palopoli, N. and Benítez, G.I. and Parisi, G. and Bassot, C. and Elofsson, A. and Govindarajan, S. and Lamb, J. and Salvatore, M. and Hatos, András and Monzon, A.M. and Bevilacqua, M. and Mičetić, I. and Minervini, G. and Paladin, L. and Quaglia, F. and Leonardi, E. and Davey, N. and Horváth, Tamás and Kovacs, O.P. and Murvai, Nikoletta and Pancsa, Rita and Schád, Éva and Szabó, Beáta and Tantos, Ágnes and Macedo-Ribeiro, S. and Manso, J.A. and Pereira, P.J.B. and Davidović, R. and Veljkovic, N. and Hajdu-Soltész, B. and Pajkos, M. and Szaniszló, Tamás and Guharoy, M. and Lazar, T. and Macossay-Castillo, M. and Tompa, Péter and Tosatto, S.C.E.}, doi = {10.1038/s41592-021-01117-3}, journal-iso = {NAT METHODS}, journal = {NATURE METHODS}, volume = {18}, unique-id = {32009587}, issn = {1548-7091}, 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 Fmax = 0.483 on the full dataset and Fmax = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with Fmax = 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.}, year = {2021}, eissn = {1548-7105}, pages = {472-481}, orcid-numbers = {Dosztányi, Zsuzsanna/0000-0002-3624-5937; Erdős, Gábor/0000-0001-6218-5192; Hatos, András/0000-0001-9224-9820; Pancsa, Rita/0000-0003-0849-9312; Szaniszló, Tamás/0000-0002-3130-9284} } @article{MTMT:31992673, title = {MobiDB-lite 3.0: fast consensus annotation of intrinsic disorder flavors in proteins}, url = {https://m2.mtmt.hu/api/publication/31992673}, author = {Necci, Marco and Piovesan, Damiano and Clementel, Damiano and Dosztányi, Zsuzsanna and Tosatto, Silvio C E}, doi = {10.1093/bioinformatics/btaa1045}, journal-iso = {BIOINFORMATICS}, journal = {BIOINFORMATICS}, volume = {36}, unique-id = {31992673}, issn = {1367-4803}, year = {2020}, eissn = {1460-2059}, pages = {5533-5534}, orcid-numbers = {Dosztányi, Zsuzsanna/0000-0002-3624-5937; Tosatto, Silvio C E/0000-0003-4525-7793} } @article{MTMT:31641470, title = {The MemMoRF database for recognizing disordered protein regions interacting with cellular membranes}, url = {https://m2.mtmt.hu/api/publication/31641470}, author = {Gáspárné Csizmadia, Georgina and Erdős, Gábor and Tordai, Hedvig and Padányi, Rita and Tosatto, Silvio and Dosztányi, Zsuzsanna and Hegedűs, Tamás}, doi = {10.1093/nar/gkaa954}, journal-iso = {NUCLEIC ACIDS RES}, journal = {NUCLEIC ACIDS RESEARCH}, volume = {49}, unique-id = {31641470}, issn = {0305-1048}, year = {2020}, eissn = {1362-4962}, pages = {D355-D360}, orcid-numbers = {Gáspárné Csizmadia, Georgina/0000-0003-4321-9670; Erdős, Gábor/0000-0001-6218-5192; Tordai, Hedvig/0000-0002-0875-5569; Padányi, Rita/0000-0001-7798-0463; Dosztányi, Zsuzsanna/0000-0002-3624-5937; Hegedűs, Tamás/0000-0002-0331-9629} } @article{MTMT:31634342, title = {Evolutionary Study of Disorder in Protein Sequences}, url = {https://m2.mtmt.hu/api/publication/31634342}, author = {Kastano, Kristina and Erdős, Gábor and Mier, Pablo and Alanis-Lobato, Gregorio and Promponas, Vasilis J. and Dosztányi, Zsuzsanna and Andrade-Navarro, Miguel A.}, doi = {10.3390/biom10101413}, journal-iso = {BIOMOLECULES}, journal = {BIOMOLECULES}, volume = {10}, unique-id = {31634342}, issn = {2218-273X}, year = {2020}, eissn = {2218-273X}, orcid-numbers = {Erdős, Gábor/0000-0001-6218-5192; Dosztányi, Zsuzsanna/0000-0002-3624-5937} } @article{MTMT:31277690, title = {Analyzing Protein Disorder with IUPred2A}, url = {https://m2.mtmt.hu/api/publication/31277690}, author = {Erdős, Gábor and Dosztányi, Zsuzsanna}, doi = {10.1002/cpbi.99}, journal-iso = {CURR PROTOC BIOINFORMATICS}, journal = {CURRENT PROTOCOLS IN BIOINFORMATICS}, volume = {70}, unique-id = {31277690}, issn = {1934-3396}, year = {2020}, eissn = {1934-340X}, orcid-numbers = {Erdős, Gábor/0000-0001-6218-5192; Dosztányi, Zsuzsanna/0000-0002-3624-5937} } @article{MTMT:30922925, title = {PhaSePro. the database of proteins driving liquid-liquid phase separation.}, url = {https://m2.mtmt.hu/api/publication/30922925}, author = {Mészáros, Bálint and Erdős, Gábor and Szabó, Beáta and Schád, Éva and Tantos, Ágnes and Horváth, Tamás and Horváth, Tamás and Murvai, Nikoletta and Kovács, Orsolya P and Kovács, Márton and Tosatto, Silvio C E and Tompa, Péter and Dosztányi, Zsuzsanna and Pancsa, Rita}, doi = {10.1093/nar/gkz848}, journal-iso = {NUCLEIC ACIDS RES}, journal = {NUCLEIC ACIDS RESEARCH}, volume = {48}, unique-id = {30922925}, issn = {0305-1048}, abstract = {Membraneless organelles (MOs) are dynamic liquid condensates that host a variety of specific cellular processes, such as ribosome biogenesis or RNA degradation. MOs form through liquid-liquid phase separation (LLPS), a process that relies on multivalent weak interactions of the constituent proteins and other macromolecules. Since the first discoveries of certain proteins being able to drive LLPS, it emerged as a general mechanism for the effective organization of cellular space that is exploited in all kingdoms of life. While numerous experimental studies report novel cases, the computational identification of LLPS drivers is lagging behind, and many open questions remain about the sequence determinants, composition, regulation and biological relevance of the resulting condensates. Our limited ability to overcome these issues is largely due to the lack of a dedicated LLPS database. Therefore, here we introduce PhaSePro (https://phasepro.elte.hu), an openly accessible, comprehensive, manually curated database of experimentally validated LLPS driver proteins/protein regions. It not only provides a wealth of information on such systems, but improves the standardization of data by introducing novel LLPS-specific controlled vocabularies. PhaSePro can be accessed through an appealing, user-friendly interface and thus has definite potential to become the central resource in this dynamically developing field.}, year = {2020}, eissn = {1362-4962}, pages = {D360-D367}, orcid-numbers = {Erdős, Gábor/0000-0001-6218-5192; Dosztányi, Zsuzsanna/0000-0002-3624-5937; Pancsa, Rita/0000-0003-0849-9312} } @article{MTMT:30922910, title = {DisProt: intrinsic protein disorder annotation in 2020}, url = {https://m2.mtmt.hu/api/publication/30922910}, author = {Hatos, András and Hajdu-Soltész, Borbála and Monzon, Alexander M and Palopoli, Nicolas and Álvarez, Lucía and Aykac-Fas, Burcu and Bassot, Claudio and Benítez, Guillermo I and Bevilacqua, Martina and Chasapi, Anastasia and Chemes, Lucia and Davey, Norman E and Davidović, Radoslav and Dunker, A Keith and Elofsson, Arne and Gobeill, Julien and Foutel, Nicolás S González and Sudha, Govindarajan and Guharoy, Mainak and Horváth, Tamás and Iglesias, Valentin and Kajava, Andrey V and Kovacs, Orsolya P and Lamb, John and Lambrughi, Matteo and Lazar, Tamas and Leclercq, Jeremy Y and Leonardi, Emanuela and Macedo-Ribeiro, Sandra and Macossay-Castillo, Mauricio and Maiani, Emiliano and Manso, José A and Marino-Buslje, Cristina and Martínez-Pérez, Elizabeth and Mészáros, Bálint and Mičetić, Ivan and Minervini, Giovanni and Murvai, Nikoletta and Necci, Marco and Ouzounis, Christos A and Pajkos, Mátyás and Paladin, Lisanna and Pancsa, Rita and Papaleo, Elena and Parisi, Gustavo and Pasche, Emilie and Barbosa Pereira, Pedro J and Promponas, Vasilis J and Pujols, Jordi and Quaglia, Federica and Ruch, Patrick and Salvatore, Marco and Schád, Éva and Szabó, Beáta and Szaniszló, Tamás and Tamana, Stella and Tantos, Ágnes and Veljkovic, Nevena and Ventura, Salvador and Vranken, Wim and Dosztányi, Zsuzsanna and Tompa, Péter and Tosatto, Silvio C E and Piovesan, Damiano}, doi = {10.1093/nar/gkz975}, journal-iso = {NUCLEIC ACIDS RES}, journal = {NUCLEIC ACIDS RESEARCH}, volume = {48}, unique-id = {30922910}, issn = {0305-1048}, abstract = {The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the 'dark' proteome.}, year = {2020}, eissn = {1362-4962}, pages = {D269-D276}, orcid-numbers = {Hatos, András/0000-0001-9224-9820; Pancsa, Rita/0000-0003-0849-9312; Szaniszló, Tamás/0000-0002-3130-9284; Dosztányi, Zsuzsanna/0000-0002-3624-5937} } @article{MTMT:30418509, title = {Disentangling the complexity of low complexity proteins}, url = {https://m2.mtmt.hu/api/publication/30418509}, author = {Pablo, Mier and Lisanna, Paladin and Stella, Tamana and Sophia, Petrosian and Hajdu-Soltész, Borbála and Annika, Urbanek and Aleksandra, Gruca and Dariusz, Plewczynski and Marcin, Grynberg and Pau, Bernadó and Gáspári, Zoltán and Christos, A. Ouzounis and Vasilis, J. Promponas and Andrey, V. Kajava and John, M. Hancock and Silvio, C. E. Tosatto and Dosztányi, Zsuzsanna and Miguel, A. Andrade-Navarro}, doi = {10.1093/bib/bbz007}, journal-iso = {BRIEF BIOINFORM}, journal = {BRIEFINGS IN BIOINFORMATICS}, volume = {21}, unique-id = {30418509}, issn = {1467-5463}, year = {2020}, eissn = {1477-4054}, pages = {458-472}, orcid-numbers = {Dosztányi, Zsuzsanna/0000-0002-3624-5937} } @article{MTMT:30875480, title = {Sequence and Structure Properties Uncover the Natural Classification of Protein Complexes Formed by Intrinsically Disordered Proteins via Mutual Synergistic Folding}, url = {https://m2.mtmt.hu/api/publication/30875480}, author = {Mészáros, Bálint and Dobson, László and Fichó, Erzsébet and Simon, István}, doi = {10.3390/ijms20215460}, journal-iso = {INT J MOL SCI}, journal = {INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES}, volume = {20}, unique-id = {30875480}, issn = {1661-6596}, year = {2019}, eissn = {1422-0067}, orcid-numbers = {Fichó, Erzsébet/0000-0002-3965-8438} }