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Schnider B, M’Rad Y, el Ahmadie J, de Brevern AG, Imberty A, Lisacek F. HumanLectome, an update of UniLectin for the annotation and prediction of human lectins. Nucleic Acids Res 2024; 52:D1683-D1693. [PMID: 37889052 PMCID: PMC10767822 DOI: 10.1093/nar/gkad905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 10/03/2023] [Accepted: 10/06/2023] [Indexed: 10/28/2023] Open
Abstract
The UniLectin portal (https://unilectin.unige.ch/) was designed in 2019 with the goal of centralising curated and predicted data on carbohydrate-binding proteins known as lectins. UniLectin is also intended as a support for the study of lectomes (full lectin set) of organisms or tissues. The present update describes the inclusion of several new modules and details the latest (https://unilectin.unige.ch/humanLectome/), covering our knowledge of the human lectome and comprising 215 unevenly characterised lectins, particularly in terms of structural information. Each HumanLectome entry is protein-centric and compiles evidence of carbohydrate recognition domain(s), specificity, 3D-structure, tissue-based expression and related genomic data. Other recent improvements regarding interoperability and accessibility are outlined.
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Affiliation(s)
- Boris Schnider
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, CH-1211 Geneva, Switzerland
- Computer Science Department, University of Geneva, CH-1227 Geneva, Switzerland
| | - Yacine M’Rad
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, CH-1211 Geneva, Switzerland
- Computer Science Department, University of Geneva, CH-1227 Geneva, Switzerland
| | - Jalaa el Ahmadie
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, CH-1211 Geneva, Switzerland
- Computer Science Department, University of Geneva, CH-1227 Geneva, Switzerland
- University Grenoble Alpes, CNRS, CERMAV, F-38000 Grenoble, France
| | - Alexandre G de Brevern
- Université Paris Cité and Université de la Réunion and Université des Antilles, INSERM, BIGR, DSIMB Bioinformatics Team, F-75014 Paris, France
| | - Anne Imberty
- University Grenoble Alpes, CNRS, CERMAV, F-38000 Grenoble, France
| | - Frederique Lisacek
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, CH-1211 Geneva, Switzerland
- Computer Science Department, University of Geneva, CH-1227 Geneva, Switzerland
- Section of Biology, University of Geneva, CH-1205 Geneva, Switzerland
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2
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Aleksander SA, Balhoff J, Carbon S, Cherry JM, Drabkin HJ, Ebert D, Feuermann M, Gaudet P, Harris NL, Hill DP, Lee R, Mi H, Moxon S, Mungall CJ, Muruganugan A, Mushayahama T, Sternberg PW, Thomas PD, Van Auken K, Ramsey J, Siegele DA, Chisholm RL, Fey P, Aspromonte MC, Nugnes MV, Quaglia F, Tosatto S, Giglio M, Nadendla S, Antonazzo G, Attrill H, Dos Santos G, Marygold S, Strelets V, Tabone CJ, Thurmond J, Zhou P, Ahmed SH, Asanitthong P, Luna Buitrago D, Erdol MN, Gage MC, Ali Kadhum M, Li KYC, Long M, Michalak A, Pesala A, Pritazahra A, Saverimuttu SCC, Su R, Thurlow KE, Lovering RC, Logie C, Oliferenko S, Blake J, Christie K, Corbani L, Dolan ME, Drabkin HJ, Hill DP, Ni L, Sitnikov D, Smith C, Cuzick A, Seager J, Cooper L, Elser J, Jaiswal P, Gupta P, Jaiswal P, Naithani S, Lera-Ramirez M, Rutherford K, Wood V, De Pons JL, Dwinell MR, Hayman GT, Kaldunski ML, Kwitek AE, Laulederkind SJF, Tutaj MA, Vedi M, Wang SJ, D'Eustachio P, Aimo L, Axelsen K, Bridge A, Hyka-Nouspikel N, Morgat A, Aleksander SA, Cherry JM, Engel SR, Karra K, Miyasato SR, Nash RS, Skrzypek MS, Weng S, Wong ED, Bakker E, Berardini TZ, Reiser L, Auchincloss A, Axelsen K, Argoud-Puy G, Blatter MC, Boutet E, Breuza L, Bridge A, Casals-Casas C, Coudert E, Estreicher A, Livia Famiglietti M, Feuermann M, Gos A, Gruaz-Gumowski N, Hulo C, Hyka-Nouspikel N, Jungo F, Le Mercier P, Lieberherr D, Masson P, Morgat A, Pedruzzi I, Pourcel L, Poux S, Rivoire C, Sundaram S, Bateman A, Bowler-Barnett E, Bye-A-Jee H, Denny P, Ignatchenko A, Ishtiaq R, Lock A, Lussi Y, Magrane M, Martin MJ, Orchard S, Raposo P, Speretta E, Tyagi N, Warner K, Zaru R, Diehl AD, Lee R, Chan J, Diamantakis S, Raciti D, Zarowiecki M, Fisher M, James-Zorn C, Ponferrada V, Zorn A, Ramachandran S, Ruzicka L, Westerfield M. The Gene Ontology knowledgebase in 2023. Genetics 2023; 224:iyad031. [PMID: 36866529 PMCID: PMC10158837 DOI: 10.1093/genetics/iyad031] [Citation(s) in RCA: 218] [Impact Index Per Article: 218.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 02/10/2023] [Accepted: 02/11/2023] [Indexed: 03/04/2023] Open
Abstract
The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.
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3
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Bansal P, Morgat A, Axelsen KB, Muthukrishnan V, Coudert E, Aimo L, Hyka-Nouspikel N, Gasteiger E, Kerhornou A, Neto TB, Pozzato M, Blatter MC, Ignatchenko A, Redaschi N, Bridge A. Rhea, the reaction knowledgebase in 2022. Nucleic Acids Res 2022; 50:D693-D700. [PMID: 34755880 PMCID: PMC8728268 DOI: 10.1093/nar/gkab1016] [Citation(s) in RCA: 56] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 10/08/2021] [Accepted: 11/09/2021] [Indexed: 12/15/2022] Open
Abstract
Rhea (https://www.rhea-db.org) is an expert-curated knowledgebase of biochemical reactions based on the chemical ontology ChEBI (Chemical Entities of Biological Interest) (https://www.ebi.ac.uk/chebi). In this paper, we describe a number of key developments in Rhea since our last report in the database issue of Nucleic Acids Research in 2019. These include improved reaction coverage in Rhea, the adoption of Rhea as the reference vocabulary for enzyme annotation in the UniProt knowledgebase UniProtKB (https://www.uniprot.org), the development of a new Rhea website, and the designation of Rhea as an ELIXIR Core Data Resource. We hope that these and other developments will enhance the utility of Rhea as a reference resource to study and engineer enzymes and the metabolic systems in which they function.
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Affiliation(s)
- Parit Bansal
- Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, CH-1211 Geneva 4, Switzerland
| | - Anne Morgat
- Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, CH-1211 Geneva 4, Switzerland
| | - Kristian B Axelsen
- Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, CH-1211 Geneva 4, Switzerland
| | - Venkatesh Muthukrishnan
- Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, CH-1211 Geneva 4, Switzerland
| | - Elisabeth Coudert
- Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, CH-1211 Geneva 4, Switzerland
| | - Lucila Aimo
- Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, CH-1211 Geneva 4, Switzerland
| | - Nevila Hyka-Nouspikel
- Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, CH-1211 Geneva 4, Switzerland
| | - Elisabeth Gasteiger
- Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, CH-1211 Geneva 4, Switzerland
| | - Arnaud Kerhornou
- Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, CH-1211 Geneva 4, Switzerland
| | - Teresa Batista Neto
- Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, CH-1211 Geneva 4, Switzerland
| | - Monica Pozzato
- Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, CH-1211 Geneva 4, Switzerland
| | - Marie-Claude Blatter
- Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, CH-1211 Geneva 4, Switzerland
| | - Alex Ignatchenko
- EMBL-EBI European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Nicole Redaschi
- Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, CH-1211 Geneva 4, Switzerland
| | - Alan Bridge
- Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, CH-1211 Geneva 4, Switzerland
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Hufsky F, Lamkiewicz K, Almeida A, Aouacheria A, Arighi C, Bateman A, Baumbach J, Beerenwinkel N, Brandt C, Cacciabue M, Chuguransky S, Drechsel O, Finn RD, Fritz A, Fuchs S, Hattab G, Hauschild AC, Heider D, Hoffmann M, Hölzer M, Hoops S, Kaderali L, Kalvari I, von Kleist M, Kmiecinski R, Kühnert D, Lasso G, Libin P, List M, Löchel HF, Martin MJ, Martin R, Matschinske J, McHardy AC, Mendes P, Mistry J, Navratil V, Nawrocki EP, O’Toole ÁN, Ontiveros-Palacios N, Petrov AI, Rangel-Pineros G, Redaschi N, Reimering S, Reinert K, Reyes A, Richardson L, Robertson DL, Sadegh S, Singer JB, Theys K, Upton C, Welzel M, Williams L, Marz M. Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research. Brief Bioinform 2021; 22:642-663. [PMID: 33147627 PMCID: PMC7665365 DOI: 10.1093/bib/bbaa232] [Citation(s) in RCA: 81] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 07/28/2020] [Accepted: 08/26/2020] [Indexed: 12/16/2022] Open
Abstract
SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are free to use and available online, either through web applications or public code repositories. Contact:evbc@unj-jena.de.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Christian Brandt
- Institute of Infectious Disease and Infection Control at Jena University Hospital, Germany
| | - Marco Cacciabue
- Consejo Nacional de Investigaciones Científicas y Tócnicas (CONICET) working on FMDV virology at the Instituto de Agrobiotecnología y Biología Molecular (IABiMo, INTA-CONICET) and at the Departamento de Ciencias Básicas, Universidad Nacional de Luján (UNLu), Argentina
| | | | - Oliver Drechsel
- bioinformatics department at the Robert Koch-Institute, Germany
| | | | - Adrian Fritz
- Computational Biology of Infection Research group of Alice C. McHardy at the Helmholtz Centre for Infection Research, Germany
| | - Stephan Fuchs
- bioinformatics department at the Robert Koch-Institute, Germany
| | - Georges Hattab
- Bioinformatics Division at Philipps-University Marburg, Germany
| | | | - Dominik Heider
- Data Science in Biomedicine at the Philipps-University of Marburg, Germany
| | | | | | - Stefan Hoops
- Biocomplexity Institute and Initiative at the University of Virginia, USA
| | - Lars Kaderali
- Bioinformatics and head of the Institute of Bioinformatics at University Medicine Greifswald, Germany
| | | | - Max von Kleist
- bioinformatics department at the Robert Koch-Institute, Germany
| | - Renó Kmiecinski
- bioinformatics department at the Robert Koch-Institute, Germany
| | | | - Gorka Lasso
- Chandran Lab, Albert Einstein College of Medicine, USA
| | | | | | | | | | | | | | - Alice C McHardy
- Computational Biology of Infection Research Lab at the Helmholtz Centre for Infection Research in Braunschweig, Germany
| | - Pedro Mendes
- Center for Quantitative Medicine of the University of Connecticut School of Medicine, USA
| | | | - Vincent Navratil
- Bioinformatics and Systems Biology at the Rhône Alpes Bioinformatics core facility, Universitó de Lyon, France
| | | | | | | | | | | | - Nicole Redaschi
- Development of the Swiss-Prot group at the SIB for UniProt and SIB resources that cover viral biology (ViralZone)
| | - Susanne Reimering
- Computational Biology of Infection Research group of Alice C. McHardy at the Helmholtz Centre for Infection Research
| | | | | | | | | | - Sepideh Sadegh
- Chair of Experimental Bioinformatics at Technical University of Munich, Germany
| | - Joshua B Singer
- MRC-University of Glasgow Centre for Virus Research, Glasgow, Scotland, UK
| | | | - Chris Upton
- Department of Biochemistry and Microbiology, University of Victoria, Canada
| | | | | | - Manja Marz
- Friedrich Schiller University Jena, Germany
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5
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Gene Ontology Consortium. The Gene Ontology resource: enriching a GOld mine. Nucleic Acids Res 2021; 49:D325-34. [PMID: 33290552 DOI: 10.1093/nar/gkaa1113] [Citation(s) in RCA: 1756] [Impact Index Per Article: 585.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 10/22/2020] [Accepted: 12/02/2020] [Indexed: 12/28/2022] Open
Abstract
The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.
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Bateman A, Martin MJ, Orchard S, Magrane M, Agivetova R, Ahmad S, Alpi E, Bowler-Barnett EH, Britto R, Bursteinas B, Bye-A-Jee H, Coetzee R, Cukura A, Da Silva A, Denny P, Dogan T, Ebenezer T, Fan J, Castro LG, Garmiri P, Georghiou G, Gonzales L, Hatton-Ellis E, Hussein A, Ignatchenko A, Insana G, Ishtiaq R, Jokinen P, Joshi V, Jyothi D, Lock A, Lopez R, Luciani A, Luo J, Lussi Y, MacDougall A, Madeira F, Mahmoudy M, Menchi M, Mishra A, Moulang K, Nightingale A, Oliveira CS, Pundir S, Qi G, Raj S, Rice D, Lopez MR, Saidi R, Sampson J, Sawford T, Speretta E, Turner E, Tyagi N, Vasudev P, Volynkin V, Warner K, Watkins X, Zaru R, Zellner H, Bridge A, Poux S, Redaschi N, Aimo L, Argoud-Puy G, Auchincloss A, Axelsen K, Bansal P, Baratin D, Blatter MC, Bolleman J, Boutet E, Breuza L, Casals-Casas C, de Castro E, Echioukh KC, Coudert E, Cuche B, Doche M, Dornevil D, Estreicher A, Famiglietti ML, Feuermann M, Gasteiger E, Gehant S, Gerritsen V, Gos A, Gruaz-Gumowski N, Hinz U, Hulo C, Hyka-Nouspikel N, Jungo F, Keller G, Kerhornou A, Lara V, Le Mercier P, Lieberherr D, Lombardot T, Martin X, Masson P, Morgat A, Neto TB, Paesano S, Pedruzzi I, Pilbout S, Pourcel L, Pozzato M, Pruess M, Rivoire C, Sigrist C, Sonesson K, Stutz A, Sundaram S, Tognolli M, Verbregue L, Wu CH, Arighi CN, Arminski L, Chen C, Chen Y, Garavelli JS, Huang H, Laiho K, McGarvey P, Natale DA, Ross K, Vinayaka CR, Wang Q, Wang Y, Yeh LS, Zhang J, Ruch P, Teodoro D. UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Res 2021; 49:D480-D489. [PMID: 33237286 PMCID: PMC7778908 DOI: 10.1093/nar/gkaa1100] [Citation(s) in RCA: 3474] [Impact Index Per Article: 1158.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 10/21/2020] [Accepted: 11/02/2020] [Indexed: 02/07/2023] Open
Abstract
The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over the last two years to the resource. The number of sequences in UniProtKB has risen to approximately 190 million, despite continued work to reduce sequence redundancy at the proteome level. We have adopted new methods of assessing proteome completeness and quality. We continue to extract detailed annotations from the literature to add to reviewed entries and supplement these in unreviewed entries with annotations provided by automated systems such as the newly implemented Association-Rule-Based Annotator (ARBA). We have developed a credit-based publication submission interface to allow the community to contribute publications and annotations to UniProt entries. We describe how UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.
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Abstract
•Integrin may act as an alternative receptor for SARS-CoV-2 and could be implicated in its transmission and pathology. •The spike protein of SARS-CoV-2 acquired a RGD motif known to bind integrins. This motif is absent from other coronaviruses. •The integrin-binding motif is present at the surface of the spike protein, close to the ACE2 receptor-binding region. •Integrin binding may be a promising therapeutics target, and should be tested experimentally.
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Affiliation(s)
| | - Alan Bridge
- Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, Switzerland.
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Alocci D, Suchánková P, Costa R, Hory N, Mariethoz J, Vařeková RS, Toukach P, Lisacek F. SugarSketcher: Quick and Intuitive Online Glycan Drawing. Molecules 2018; 23:E3206. [PMID: 30563078 PMCID: PMC6320881 DOI: 10.3390/molecules23123206] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 11/23/2018] [Accepted: 11/29/2018] [Indexed: 01/24/2023] Open
Abstract
SugarSketcher is an intuitive and fast JavaScript interface module for online drawing of glycan structures in the popular Symbol Nomenclature for Glycans (SNFG) notation and exporting them to various commonly used formats encoding carbohydrate sequences (e.g., GlycoCT) or quality images (e.g., svg). It does not require a backend server or any specific browser plugins and can be integrated in any web glycoinformatics project. SugarSketcher allows drawing glycans both for glycobiologists and non-expert users. The "quick mode" allows a newcomer to build up a glycan structure having only a limited knowledge in carbohydrate chemistry. The "normal mode" integrates advanced options which enable glycobiologists to tailor complex carbohydrate structures. The source code is freely available on GitHub and glycoinformaticians are encouraged to participate in the development process while users are invited to test a prototype available on the ExPASY web-site and send feedback.
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Affiliation(s)
- Davide Alocci
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland.
- Computer Science Department, University of Geneva, 1211 Geneva, Switzerland.
| | - Pavla Suchánková
- CEITEC⁻Central European Institute of Technology, Masaryk University Brno, 625 00 Brno-Bohunice, Czech Republic.
- National Centre for Biomolecular Research, Faculty of Science, 625 00 Brno-Bohunice, Czech Republic.
| | - Renaud Costa
- Polytech Nice Sophia, Campus SophiaTech, 06903 Sophia-Antipolis, France.
| | - Nicolas Hory
- Polytech Nice Sophia, Campus SophiaTech, 06903 Sophia-Antipolis, France.
| | - Julien Mariethoz
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland.
- Computer Science Department, University of Geneva, 1211 Geneva, Switzerland.
| | - Radka Svobodová Vařeková
- CEITEC⁻Central European Institute of Technology, Masaryk University Brno, 625 00 Brno-Bohunice, Czech Republic.
- National Centre for Biomolecular Research, Faculty of Science, 625 00 Brno-Bohunice, Czech Republic.
| | - Philip Toukach
- Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Laboratory of Carbohydrate Chemistry, 119991 Moscow, Russia.
| | - Frédérique Lisacek
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland.
- Computer Science Department, University of Geneva, 1211 Geneva, Switzerland.
- Section of Biology, University of Geneva, 1211 Geneva, Switzerland.
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