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2. Aggrescan4D: A comprehensive tool for pH‐dependent analysis and engineering of protein aggregation propensity.

Author

Zalewski, Mateusz, Iglesias, Valentin, Bárcenas, Oriol, Ventura, Salvador, and Kmiecik, Sebastian

Abstract

Aggrescan4D (A4D) is an advanced computational tool designed for predicting protein aggregation, leveraging structural information and the influence of pH. Building upon its predecessor, Aggrescan3D (A3D), A4D has undergone numerous enhancements aimed at assisting the improvement of protein solubility. This manuscript reviews A4D's updated functionalities and explains the fundamental principles behind its pH‐dependent calculations. Additionally, it presents an antibody case study to evaluate its performance in comparison with other structure‐based predictors. Notably, A4D integrates advanced protein engineering protocols with pH‐dependent calculations, enhancing its utility in advising solubility‐enhancing mutations. A4D considers the impact of structural flexibility on aggregation propensities, and includes a large set of precalculated predictions. These capabilities should help to open new avenues for both understanding and managing protein aggregation. A4D is accessible through a dedicated web server at https://biocomp.chem.uw.edu.pl/a4d/. [ABSTRACT FROM AUTHOR]

Published
2024
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8. Selection of an Aptamer against the Enzyme 1-deoxy-D-xylulose-5-phosphate Reductoisomerase from Plasmodium falciparum

Author

Enginyeria Electrònica, Elèctrica i Automàtica, Universitat Rovira i Virgili, Roca, Carlota; Avalos-Padilla, Yunuen; Prieto-Simon, Beatriz; Iglesias, Valentin; Ramirez, Miriam; Imperial, Santiago; Fernandez-Busquets, Xavier, Enginyeria Electrònica, Elèctrica i Automàtica, Universitat Rovira i Virgili, and Roca, Carlota; Avalos-Padilla, Yunuen; Prieto-Simon, Beatriz; Iglesias, Valentin; Ramirez, Miriam; Imperial, Santiago; Fernandez-Busquets, Xavier

Abstract

The methyl erythritol phosphate (MEP) pathway of isoprenoid biosynthesis is essential for malaria parasites and also for several human pathogenic bacteria, thus representing an interesting target for future antimalarials and antibiotics and for diagnostic strategies. We have developed a DNA aptamer (D10) against Plasmodium falciparum 1-deoxy-D-xylulose-5-phosphate reductoisomerase (DXR), the second enzyme of this metabolic route. D10 binds in vitro to recombinant DXR from P. falciparum and Escherichia coli, showing at 10 mu M a ca. 50% inhibition of the bacterial enzyme. In silico docking analysis indicates that D10 associates with DXR in solvent-exposed regions outside the active center pocket. According to fluorescence confocal microscopy data, this aptamer specifically targets in P. falciparum in vitro cultures the apicoplast organelle where the MEP pathway is localized and is, therefore, a highly specific marker of red blood cells parasitized by Plasmodium vs. naive erythrocytes. D10 is also selective for the detection of MEP+ bacteria (e.g., E. coli and Pseudomonas aeruginosa) vs. those lacking DXR (e.g., Enterococcus faecalis). Based on these results, we discuss the potential of DNA aptamers in the development of ligands that can outcompete the performance of the well-established antibody technology for future therapeutic and diagnostic approaches.

Published
2022

9. Critical assessment of protein intrinsic disorder prediction

Author

Necci, Marco, Piovesan, Damiano, Hoque Md, Tamjidul, Walsh, Ian, Iqbal, Sumaiya, Vendruscolo, Michele, Sormanni, Pietro, Wang, Chen, Raimondi, Daniele, Sharma, Ronesh, Zhou, Yaoqi, Litfin, Thomas, Galzitskaya Oxana, Valerianovna, Lobanov Michail, Yu, Vranken, Wim, Wallner, Björn, Mirabello, Claudio, Malhis, Nawar, Dosztányi, Zsuzsanna, Erdős, Gábor, Mészáros, Bálint, Gao, Jianzhao, Wang, Kui, Hu, Gang, Wu, Zhonghua, Sharma, Alok, Hanson, Jack, Paliwal, Kuldip, Callebaut, Isabelle, Bitard-Feildel, Tristan, Orlando, Gabriele, Peng, Zhenling, Xu, Jinbo, Wang, Sheng, Jones David, T., Cozzetto, Domenico, Meng, Fanchi, Yan, Jing, Gsponer, Jörg, Cheng, Jianlin, Wu, Tianqi, Kurgan, Lukasz, Promponas Vasilis, J., Tamana, Stella, Marino-Buslje, Cristina, Martínez-Pérez, Elizabeth, Chasapi, Anastasia, Ouzounis, Christos, Dunker A., Keith, Kajava Andrey, V., Leclercq Jeremy, Y., Aykac-Fas, Burcu, Lambrughi, Matteo, Maiani, Emiliano, Papaleo, Elena, Chemes Lucia, Beatriz, Álvarez, Lucía, González-Foutel Nicolás, S., Iglesias, Valentin, Pujols, Jordi, Ventura, Salvador, Palopoli, Nicolás, Benítez Guillermo, Ignacio, Parisi, Gustavo, Bassot, Claudio, Elofsson, Arne, Govindarajan, Sudha, Lamb, John, Salvatore, Marco, Hatos, András, Monzon Alexander, Miguel, Bevilacqua, Martina, Mičetić, Ivan, Minervini, Giovanni, Paladin, Lisanna, Quaglia, Federica, Leonardi, Emanuela, Davey, Norman, Horvath, Tamas, Kovacs Orsolya, Panna, Murvai, Nikoletta, Pancsa, Rita, Schad, Eva, Szabo, Beata, Tantos, Agnes, Macedo-Ribeiro, Sandra, Manso Jose, Antonio, Pereira Pedro José, Barbosa, Davidović, Radoslav, Veljkovic, Nevena, Hajdu-Soltész, Borbála, Pajkos, Mátyás, Szaniszló, Tamás, Guharoy, Mainak, Lazar, Tamas, Macossay-Castillo, Mauricio, Tompa, Peter, Tosatto Silvio C., E., Caid, Predictors, DisProt, Curators, Università degli Studi di Padova = University of Padua (Unipd), Institut de minéralogie, de physique des matériaux et de cosmochimie (IMPMC), Muséum national d'Histoire naturelle (MNHN)-Institut de recherche pour le développement [IRD] : UR206-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Necci, Marco [0000-0001-9377-482X], Piovesan, Damiano [0000-0001-8210-2390], Tosatto, Silvio C. E. [0000-0003-4525-7793], Apollo - University of Cambridge Repository, Informatics and Applied Informatics, Chemistry, Basic (bio-) Medical Sciences, Department of Bio-engineering Sciences, Faculty of Sciences and Bioengineering Sciences, Structural Biology Brussels, Tosatto, Silvio CE [0000-0003-4525-7793], ANR-17-CE12-0016,FUNBRCA2,Caractérisation d'un nouveau site de liaison à l'ADN dans la protéine BRCA2(2017), Universita degli Studi di Padova, CAID Predictors, and DisProt Curators

Subjects
Protein Folding, Protein Conformation, Computer science, 631/45/612, analysis, [SDV]Life Sciences [q-bio], purl.org/becyt/ford/1.7 [https], MESH: Amino Acid Sequence, Biochemistry, purl.org/becyt/ford/1 [https], Protein structure, MESH: Protein Conformation, 631/114/2398, Databases, Protein, Biological sciences, ComputingMilieux_MISCELLANEOUS, MESH: Intrinsically Disordered Proteins, 0303 health sciences, 030302 biochemistry & molecular biology, disorder, Critical assessment, Protein folding, Protein Binding, Biotechnology, MESH: Computational Biology, MESH: Databases, Protein, disorder prediction, MESH: Protein Folding, Computational biology, Intrinsically disordered proteins, Orders of magnitude (entropy), 03 medical and health sciences, MESH: Software, Computational platforms and environments, 631/114/2411, Machine learning, Molecule, MESH: Protein Binding, [INFO]Computer Science [cs], Amino Acid Sequence, Molecular Biology, 030304 developmental biology, business.industry, Deep learning, Computational Biology, Proteins, Cell Biology, 631/114/1305, Intrinsically Disordered Proteins, CAID, 631/114/794, Protein structure predictions, Artificial intelligence, business, Software
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., Results are presented from the first Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment, a community-based blind test to determine the state of the art in predicting intrinsically disordered regions in proteins.

Published
2021
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10. MED15 prion-like domain forms a coiled-coil responsible for its amyloid conversion and propagation

Author

Batlle Carreras, Cristina, Calvo, Isabel, Iglesias, Valentin, J. Lynch, Cian, Gil-Garcia, Marcos, Serrano, Manuel, Ventura, Salvador, and Universitat Autònoma de Barcelona. Departament de Bioquímica i de Biologia Molecular

Subjects
Prions, Protein aggregation
Abstract

Altres ajuts: "la Caixa" Foundation i ICREA-Academia 2016 A disordered to β-sheet transition was thought to drive the functional switch of Q/N-rich prions, similar to pathogenic amyloids. However, recent evidence indicates a critical role for coiled-coil (CC) regions within yeast prion domains in amyloid formation. We show that many human prion-like domains (PrLDs) contain CC regions that overlap with polyQ tracts. Most of the proteins bearing these domains are transcriptional coactivators, including the Mediator complex subunit 15 (MED15) involved in bridging enhancers and promoters. We demonstrate that the human MED15-PrLD forms homodimers in solution sustained by CC interactions and that it is this CC fold that mediates the transition towards a β-sheet amyloid state, its chemical or genetic disruption abolishing aggregation. As in functional yeast prions, a GFP globular domain adjacent to MED15-PrLD retains its structural integrity in the amyloid state. Expression of MED15-PrLD in human cells promotes the formation of cytoplasmic and perinuclear inclusions, kidnapping endogenous full-length MED15 to these aggregates in a prion-like manner. The prion-like properties of MED15 are conserved, suggesting novel mechanisms for the function and malfunction of this transcription coactivator.

Published
2021

12. Anatomía Neuroquirúrgica del By-Pass temporo-silviano: De la disección al procedimiento quirúrgico.

Author

Dodaro, Fabián, Rubino, Pablo, Cicler, Julián, Colombo, Axel, and Iglesias, Valentin

Abstract

Copyright of Revista Argentina de Anatomia Online is the property of Asociacion Argentina de Anatomia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2022

13. DisProt: intrinsic protein disorder annotation in 2020

Author

Hatos, András, Hajdu-Soltész, Borbála, Monzon, Alexander M., Palopoli, Nicolas, Álvarez, Lucía, Aykac-Fas, Burcu, Bassot, Claudio, Benítez, Guillermo I., Bevilacqua, Martina, Chasapi, Anastasia, Chemes, Lucia, Davey, Norman E., Davidović, Radoslav, Dunker, A. Keith, Elofsson, Arne, Gobeill, Julien, Foutel, Nicolás S. González, Sudha, Govindarajan, Guharoy, Mainak, Horvath, Tamas, Iglesias, Valentin, Kajava, Andrey V., Kovacs, Orsolya P., Lamb, John, Lambrughi, Matteo, Lazar, Tamas, Leclercq, Jeremy Y., Leonardi, Emanuela, Macedo-Ribeiro, Sandra, Macossay-Castillo, Mauricio, Maiani, Emiliano, Manso, José A., Marino-Buslje, Cristina, Martínez-Pérez, Elizabeth, Mészáros, Bálint, Mičetić, Ivan, Minervini, Giovanni, Murvai, Nikoletta, Necci, Marco, Ouzounis, Christos A., Pajkos, Mátyás, Paladin, Lisanna, Pancsa, Rita, Papaleo, Elena, Parisi, Gustavo, Pasche, Emilie, Barbosa Pereira, Pedro J., Promponas, Vasilis J., Pujols, Jordi, Quaglia, Federica, Ruch, Patrick, Salvatore, Marco, Schad, Eva, Szabo, Beata, Szaniszló, Tamás, Tamana, Stella, Tantos, Agnes, Veljkovic, Nevena, Ventura, Salvador, Vranken, Wim, Dosztányi, Zsuzsanna, Tompa, Peter, Tosatto, Silvio C. E., Piovesan, Damiano, Promponas, Vasilis J. [0000-0003-3352-4831], Universita degli Studi di Padova, Vinča Institute of Nuclear Sciences, University of Belgrade [Belgrade], Stockholm University, Laboratoire Leibniz (Leibniz - IMAG), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Université Joseph Fourier - Grenoble 1 (UJF), Laboratoire de biochimie théorique [Paris] (LBT (UPR_9080)), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Institut de biologie physico-chimique (IBPC (FR_550)), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC), Reproductive Neuroscience Unit, Department of Obstetrics and Gynecology and Department of Neurobiology, Yale University School of Medicine, Centre de recherche en Biologie Cellulaire (CRBM), Université Montpellier 1 (UM1)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Università degli Studi di Modena e Reggio Emilia (UNIMORE), Structural Biology Brussels (SBB), Vrije Universiteit Brussel (VUB), Instituto de Biologia Molecular e Celular (IBMC), Hungarian Academy of Sciences (MTA), Institute of Agrobiotechnology, National Center for Research and Technology, Universidad Nacional de Quilmes (UNQ), Université de Genève et Hôpitaux Universitaires de Genève (SIM), Hôpitaux Universitaires de Genève (HUG), Biophysics and Bioinformatics Laboratory, Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona (UAB), Service d'informatique médicale (SIM), Hôpitaux de Genève, Department of Structural Biology, Biophysics Research Group [Budapest] (ELTE-MTA 'Lendület'), Department of Bio-engineering Sciences, Structural Biology Brussels, Faculty of Sciences and Bioengineering Sciences, Informatics and Applied Informatics, Chemistry, Basic (bio-) Medical Sciences, Instituto de Investigação e Inovação em Saúde, Université Joseph Fourier - Grenoble 1 (UJF)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), Université Paris Diderot - Paris 7 (UPD7)-Institut de biologie physico-chimique (IBPC), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université Montpellier 2 - Sciences et Techniques (UM2)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Université Montpellier 1 (UM1), Vrije Universiteit [Brussels] (VUB), Universitat Autònoma de Barcelona [Barcelona] (UAB), Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Institut de biologie physico-chimique (IBPC (FR_550)), and Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Disordered proteins, Interface (Java), Disorder Ontology, [SDV]Life Sciences [q-bio], Interoperability, [SDV.BC]Life Sciences [q-bio]/Cellular Biology, Ontology (information science), Biology, 03 medical and health sciences, Annotation, Genetics, Database Issue, Databases, Protein, ComputingMilieux_MISCELLANEOUS, Data Curation, 030304 developmental biology, Graphical user interface, Structure (mathematical logic), 0303 health sciences, Intrinsically Disordered Proteins / chemistry, Information retrieval, Intrinsically disordered proteins, Data curation, Molecular sequence annotation, business.industry, 030302 biochemistry & molecular biology, Intrinsic protein, Biological Ontologies, Molecular Sequence Annotation, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Intrinsically Disordered Proteins, Dark proteome, Ontology, Intrisic protein disorder, Literature curation, business, Biological ontologies
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. Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT) of Argentina [PICT-2015/3367, PICT-2017/1924]; Ministry of Education, Science and Technological Development of the Republic of Serbia [ON173001]; Vetenskapsrådet [2016-03798]; Hungarian National Research, Development, and Innovation Office (NKFIH) [FK-128133]; Italian Ministry of Health Young Investigator Grant [GR-2011-02347754]; Ministerio de Economía y Competitividad (MINECO) [BIO2016-78310-R]; ICREA (ICREA-Academia 2015); Fundac¸ão para a Ciência e a Tecnologia (FCT, Portugal); European Regional Development Fund [POCI-01-0145-FEDER-031173, POCI-01-0145-FEDER-029221]; Mexican National Council of Science and Technology (CONACYT) [215503]; Elixir-GR, Action ‘Reinforcement of the Research and Innovation Infrastructure’, Operational Programme ‘Competitiveness, Entrepreneurship and Innovation’ [NSRF 2014-2020]. co-financed by Greece and the European Union (European Regional Development Fund); Hungarian Academy of Sciences [PREMIUM-2017-48]; Carlsberg Distinguished Fellowship [CF18-0314]; Danmarks Grundforskningsfond [DNRF125]; National Research, Development and Innovation Office [K-125340]; Research Foundation Flanders (FWO) [G.0328.16N]; Hungarian Academy of Sciences [LP2014-18]; OTKA [K108798 and K124670]. This project has received funding from the European Union’s Horizon 2020 research and innovation programme [778247]. Funding for open access charge: European Union’s Horizon 2020 research and innovation programme [778247]. Conflict of interest statement. None declared.

Published
2020
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14. DispHred : a server to predict pH-dependent order-disorder transitions in intrinsically disordered proteins

Author

Santos, Jaime, Iglesias, Valentin, Pintado Grima, Carlos, Santos-Suárez, Juan, Ventura, Salvador, and Universitat Autònoma de Barcelona. Departament de Bioquímica i de Biologia Molecular

Subjects
0301 basic medicine, disorder prediction, PH, Bioinformatics, Ph dependent, Conditional folding, Intrinsically disordered proteins, Article, Catalysis, Inorganic Chemistry, lcsh:Chemistry, User-Computer Interface, 03 medical and health sciences, Machine learning, Physical and Theoretical Chemistry, conditional folding, Molecular Biology, lcsh:QH301-705.5, Spectroscopy, Disorder prediction, Sequence (medicine), Internet, 030102 biochemistry & molecular biology, Basis (linear algebra), Chemistry, pH, Organic Chemistry, Reproducibility of Results, General Medicine, Function (mathematics), bioinformatics, Hydrogen-Ion Concentration, Net (mathematics), Disorder predictors, Computer Science Applications, 030104 developmental biology, Order (biology), machine learning, lcsh:Biology (General), lcsh:QD1-999, intrinsically disordered proteins, Biological system, Hydrophobic and Hydrophilic Interactions, Algorithms
Abstract

The natively unfolded nature of intrinsically disordered proteins (IDPs) relies on several physicochemical principles, of which the balance between a low sequence hydrophobicity and a high net charge appears to be critical. Under this premise, it is well-known that disordered proteins populate a defined region of the charge&ndash, hydropathy (C&ndash, H) space and that a linear boundary condition is sufficient to distinguish between folded and disordered proteins, an approach widely applied for the prediction of protein disorder. Nevertheless, it is evident that the C&ndash, H relation of a protein is not unalterable but can be modulated by factors extrinsic to its sequence. Here, we applied a C&ndash, H-based analysis to develop a computational approach that evaluates sequence disorder as a function of pH, assuming that both protein net charge and hydrophobicity are dependent on pH solution. On that basis, we developed DispHred, the first pH-dependent predictor of protein disorder. Despite its simplicity, DispHred displays very high accuracy in identifying pH-induced order/disorder protein transitions. DispHred might be useful for diverse applications, from the analysis of conditionally disordered segments to the synthetic design of disorder tags for biotechnological applications. Importantly, since many disorder predictors use hydrophobicity as an input, the here developed framework can be implemented in other state-of-the-art algorithms.

Published
2020

15. DisProt:Intrinsic protein disorder annotation in 2020

Author

Hatos, András, Hajdu-Soltész, Borbála, Monzon, Alexander M., Palopoli, Nicolas, Álvarez, Lucía, Aykac-Fas, Burcu, Bassot, Claudio, Benítez, Guillermo I., Bevilacqua, Martina, Chasapi, Anastasia, Chemes, Lucia, Davey, Norman E., Davidović, Radoslav, Dunker, A. Keith, Elofsson, Arne, Gobeill, Julien, Foutel, Nicolás S.González, Sudha, Govindarajan, Guharoy, Mainak, Horvath, Tamas, Iglesias, Valentin, Kajava, Andrey V., Kovacs, Orsolya P., Lamb, John, Lambrughi, Matteo, Lazar, Tamas, Leclercq, Jeremy Y., Leonardi, Emanuela, MacEdo-Ribeiro, Sandra, MacOssay-Castillo, Mauricio, Maiani, Emiliano, Manso, José A., Marino-Buslje, Cristina, Martínez-Pérez, Elizabeth, Mészáros, Bálint, Mičetić, Ivan, Minervini, Giovanni, Murvai, Nikoletta, Necci, Marco, Ouzounis, Christos A., Pajkos, Mátyás, Paladin, Lisanna, Pancsa, Rita, Papaleo, Elena, Parisi, Gustavo, Pasche, Emilie, Barbosa Pereira, Pedro J., Promponas, Vasilis J., Pujols, Jordi, Quaglia, Federica, Ruch, Patrick, Salvatore, Marco, Schad, Eva, Szabo, Beata, Szaniszló, Tamás, Tamana, Stella, Tantos, Agnes, Veljkovic, Nevena, Ventura, Salvador, Vranken, Wim, Dosztányi, Zsuzsanna, Tompa, Peter, Tosatto, Silvio C.E., Piovesan, Damiano, Hatos, András, Hajdu-Soltész, Borbála, Monzon, Alexander M., Palopoli, Nicolas, Álvarez, Lucía, Aykac-Fas, Burcu, Bassot, Claudio, Benítez, Guillermo I., Bevilacqua, Martina, Chasapi, Anastasia, Chemes, Lucia, Davey, Norman E., Davidović, Radoslav, Dunker, A. Keith, Elofsson, Arne, Gobeill, Julien, Foutel, Nicolás S.González, Sudha, Govindarajan, Guharoy, Mainak, Horvath, Tamas, Iglesias, Valentin, Kajava, Andrey V., Kovacs, Orsolya P., Lamb, John, Lambrughi, Matteo, Lazar, Tamas, Leclercq, Jeremy Y., Leonardi, Emanuela, MacEdo-Ribeiro, Sandra, MacOssay-Castillo, Mauricio, Maiani, Emiliano, Manso, José A., Marino-Buslje, Cristina, Martínez-Pérez, Elizabeth, Mészáros, Bálint, Mičetić, Ivan, Minervini, Giovanni, Murvai, Nikoletta, Necci, Marco, Ouzounis, Christos A., Pajkos, Mátyás, Paladin, Lisanna, Pancsa, Rita, Papaleo, Elena, Parisi, Gustavo, Pasche, Emilie, Barbosa Pereira, Pedro J., Promponas, Vasilis J., Pujols, Jordi, Quaglia, Federica, Ruch, Patrick, Salvatore, Marco, Schad, Eva, Szabo, Beata, Szaniszló, Tamás, Tamana, Stella, Tantos, Agnes, Veljkovic, Nevena, Ventura, Salvador, Vranken, Wim, Dosztányi, Zsuzsanna, Tompa, Peter, Tosatto, Silvio C.E., and Piovesan, Damiano

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.

Published
2020

17. DisProt: intrinsic protein disorder annotation in 2020

Author

Hatos, András, Hajdu-Soltész, Borbála, Monzon, Alexander M, Palopoli, Nicolas, Álvarez, Lucía, Aykac-Fas, Burcu, Bassot, Claudio, Benítez, Guillermo I, Bevilacqua, Martina, Chasapi, Anastasia, Chemes, Lucia, Davey, Norman E, Davidović, Radoslav S., Dunker, A Keith, Elofsson, Arne, Gobeill, Julien, Foutel, Nicolás S González, Sudha, Govindarajan, Guharoy, Mainak, Horvath, Tamas, Iglesias, Valentin, Kajava, Andrey V., Kovacs, Orsolya P, Lamb, John, Lambrughi, Matteo, Lazar, Tamas, Leclercq, Jeremy Y, Leonardi, Emanuela, Macedo-Ribeiro, Sandra, Macossay-Castillo, Mauricio, Maiani, Emiliano, Manso, José A, Marino-Buslje, Cristina, Martínez-Pérez, Elizabeth, Mészáros, Bálint, Mičetić, Ivan, Minervini, Giovanni, Murvai, Nikoletta, Necci, Marco, Ouzounis, Christos A, Pajkos, Mátyás, Paladin, Lisanna, Pancsa, Rita, Papaleo, Elena, Parisi, Gustavo, Pasche, Emilie, Barbosa Pereira, Pedro J, Promponas, Vasilis J, Pujols, Jordi, Quaglia, Federica, Ruch, Patrick, Salvatore, Marco, Schad, Eva, Szabo, Beata, Szaniszló, Tamás, Tamana, Stella, Tantos, Agnes, Veljković, Nevena V., Ventura, Salvador, Vranken, Wim, Dosztányi, Zsuzsanna, Tompa, Peter, Tosatto, Silvio C E, Piovesan, Damiano, Hatos, András, Hajdu-Soltész, Borbála, Monzon, Alexander M, Palopoli, Nicolas, Álvarez, Lucía, Aykac-Fas, Burcu, Bassot, Claudio, Benítez, Guillermo I, Bevilacqua, Martina, Chasapi, Anastasia, Chemes, Lucia, Davey, Norman E, Davidović, Radoslav S., Dunker, A Keith, Elofsson, Arne, Gobeill, Julien, Foutel, Nicolás S González, Sudha, Govindarajan, Guharoy, Mainak, Horvath, Tamas, Iglesias, Valentin, Kajava, Andrey V., Kovacs, Orsolya P, Lamb, John, Lambrughi, Matteo, Lazar, Tamas, Leclercq, Jeremy Y, Leonardi, Emanuela, Macedo-Ribeiro, Sandra, Macossay-Castillo, Mauricio, Maiani, Emiliano, Manso, José A, Marino-Buslje, Cristina, Martínez-Pérez, Elizabeth, Mészáros, Bálint, Mičetić, Ivan, Minervini, Giovanni, Murvai, Nikoletta, Necci, Marco, Ouzounis, Christos A, Pajkos, Mátyás, Paladin, Lisanna, Pancsa, Rita, Papaleo, Elena, Parisi, Gustavo, Pasche, Emilie, Barbosa Pereira, Pedro J, Promponas, Vasilis J, Pujols, Jordi, Quaglia, Federica, Ruch, Patrick, Salvatore, Marco, Schad, Eva, Szabo, Beata, Szaniszló, Tamás, Tamana, Stella, Tantos, Agnes, Veljković, Nevena V., Ventura, Salvador, Vranken, Wim, Dosztányi, Zsuzsanna, Tompa, Peter, Tosatto, Silvio C E, and Piovesan, Damiano

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.

Published
2019

18. DisProt: intrinsic protein disorder annotation in 2020

Author

Hatos, András, primary, Hajdu-Soltész, Borbála, additional, Monzon, Alexander M, additional, Palopoli, Nicolas, additional, Álvarez, Lucía, additional, Aykac-Fas, Burcu, additional, Bassot, Claudio, additional, Benítez, Guillermo I, additional, Bevilacqua, Martina, additional, Chasapi, Anastasia, additional, Chemes, Lucia, additional, Davey, Norman E, additional, Davidović, Radoslav, additional, Dunker, A Keith, additional, Elofsson, Arne, additional, Gobeill, Julien, additional, Foutel, Nicolás S González, additional, Sudha, Govindarajan, additional, Guharoy, Mainak, additional, Horvath, Tamas, additional, Iglesias, Valentin, additional, Kajava, Andrey V, additional, Kovacs, Orsolya P, additional, Lamb, John, additional, Lambrughi, Matteo, additional, Lazar, Tamas, additional, Leclercq, Jeremy Y, additional, Leonardi, Emanuela, additional, Macedo-Ribeiro, Sandra, additional, Macossay-Castillo, Mauricio, additional, Maiani, Emiliano, additional, Manso, José A, additional, Marino-Buslje, Cristina, additional, Martínez-Pérez, Elizabeth, additional, Mészáros, Bálint, additional, Mičetić, Ivan, additional, Minervini, Giovanni, additional, Murvai, Nikoletta, additional, Necci, Marco, additional, Ouzounis, Christos A, additional, Pajkos, Mátyás, additional, Paladin, Lisanna, additional, Pancsa, Rita, additional, Papaleo, Elena, additional, Parisi, Gustavo, additional, Pasche, Emilie, additional, Barbosa Pereira, Pedro J, additional, Promponas, Vasilis J, additional, Pujols, Jordi, additional, Quaglia, Federica, additional, Ruch, Patrick, additional, Salvatore, Marco, additional, Schad, Eva, additional, Szabo, Beata, additional, Szaniszló, Tamás, additional, Tamana, Stella, additional, Tantos, Agnes, additional, Veljkovic, Nevena, additional, Ventura, Salvador, additional, Vranken, Wim, additional, Dosztányi, Zsuzsanna, additional, Tompa, Peter, additional, Tosatto, Silvio C E, additional, and Piovesan, Damiano, additional

Published
2019
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28. Perfecting prediction of mutational impact on the aggregation propensity of the ALS-associated hn RNPA2 prion-like protein.

Author

Batlle, Cristina, Fernández, María Rosario, Iglesias, Valentin, and Ventura, Salvador

Subjects
PRIONS, LIQUID-liquid interfaces, AMYLOID beta-protein, GENETIC mutation, AMINO acid sequence
Abstract

An increasing number of human proteins are being found to bear a prion-like domain (Pr LD) driving the formation of membraneless compartments through liquid-liquid phase separation. Point mutations in these Pr LDs promote the transition to an amyloid-like state. There has been much debate on whether this aberrant aggregation is caused by compositional or sequential changes. A recent extensive mutational study of the ALS-associated prion-like hn RNPA2 protein provides a framework to discriminate the molecular determinants behind pathogenic Pr LDs aggregation. The effect of mutations on the aggregation propensity of hn RNPA2 is best predicted by combining their impact on Pr LD amino acid composition and sequence-based amyloid propensity. This opens an avenue for the prediction of disease causing mutations in other human prion-like proteins. [ABSTRACT FROM AUTHOR]

Published
2017
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29. Computational Assessment of Bacterial Protein Structures Indicates a Selection Against Aggregation.

Author

Carija, Anita, Pinheiro, Francisca, Iglesias, Valentin, and Ventura, Salvador

Subjects
BACTERIAL proteins, PROTEIN structure, QUATERNARY structure, GLOBULAR proteins, CYTOSKELETAL proteins
Abstract

The aggregation of proteins compromises cell fitness, either because it titrates functional proteins into non-productive inclusions or because it results in the formation of toxic assemblies. Accordingly, computational proteome-wide analyses suggest that prevention of aggregation upon misfolding plays a key role in sequence evolution. Most proteins spend their lifetimes in a folded state; therefore, it is conceivable that, in addition to sequences, protein structures would have also evolved to minimize the risk of aggregation in their natural environments. By exploiting the AGGRESCAN3D structure-based approach to predict the aggregation propensity of >600 Escherichia coli proteins, we show that the structural aggregation propensity of globular proteins is connected with their abundance, length, essentiality, subcellular location and quaternary structure. These data suggest that the avoidance of protein aggregation has contributed to shape the structural properties of proteins in bacterial cells. [ABSTRACT FROM AUTHOR]

Published
2019
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30. Aggrescan4D: A comprehensive tool for pH-dependent analysis and engineering of protein aggregation propensity.

Author

Zalewski M, Iglesias V, Bárcenas O, Ventura S, and Kmiecik S

Subjects
Hydrogen-Ion Concentration, Software, Proteins chemistry, Proteins genetics, Proteins metabolism, Solubility, Protein Aggregates, Protein Engineering methods
Abstract

Aggrescan4D (A4D) is an advanced computational tool designed for predicting protein aggregation, leveraging structural information and the influence of pH. Building upon its predecessor, Aggrescan3D (A3D), A4D has undergone numerous enhancements aimed at assisting the improvement of protein solubility. This manuscript reviews A4D's updated functionalities and explains the fundamental principles behind its pH-dependent calculations. Additionally, it presents an antibody case study to evaluate its performance in comparison with other structure-based predictors. Notably, A4D integrates advanced protein engineering protocols with pH-dependent calculations, enhancing its utility in advising solubility-enhancing mutations. A4D considers the impact of structural flexibility on aggregation propensities, and includes a large set of precalculated predictions. These capabilities should help to open new avenues for both understanding and managing protein aggregation. A4D is accessible through a dedicated web server at https://biocomp.chem.uw.edu.pl/a4d/., (© 2024 The Author(s). Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.)

Published
2024
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31. DisProt: intrinsic protein disorder annotation in 2020.

Author

Hatos A, Hajdu-Soltész B, Monzon AM, Palopoli N, Álvarez L, Aykac-Fas B, Bassot C, Benítez GI, Bevilacqua M, Chasapi A, Chemes L, Davey NE, Davidović R, Dunker AK, Elofsson A, Gobeill J, Foutel NSG, Sudha G, Guharoy M, Horvath T, Iglesias V, Kajava AV, Kovacs OP, Lamb J, Lambrughi M, Lazar T, Leclercq JY, Leonardi E, Macedo-Ribeiro S, Macossay-Castillo M, Maiani E, Manso JA, Marino-Buslje C, Martínez-Pérez E, Mészáros B, Mičetić I, Minervini G, Murvai N, Necci M, Ouzounis CA, Pajkos M, Paladin L, Pancsa R, Papaleo E, Parisi G, Pasche E, Barbosa Pereira PJ, Promponas VJ, Pujols J, Quaglia F, Ruch P, Salvatore M, Schad E, Szabo B, Szaniszló T, Tamana S, Tantos A, Veljkovic N, Ventura S, Vranken W, Dosztányi Z, Tompa P, Tosatto SCE, and Piovesan D

Subjects
Biological Ontologies, Data Curation, Molecular Sequence Annotation, Databases, Protein, Intrinsically Disordered Proteins chemistry
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., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Published
2020
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