UniRule: a unified rule resource for automatic annotation in the UniProt Knowledgebase

MacDougall, Alistair J.; Volynkin, Vladimir; Saidi, Rabie; Poggioli, Diego; Zellner, Hermann; Hatton-Ellis, Emma; Joshi, Vishal; O′Donovan, Claire; Orchard, Sandra; Auchincloss, Andrea; Baratin, Delphine; Bolleman, Jerven; Coudert, Elisabeth; Castro, Edouard de; Hulo, Chantal; Masson, Patrick; Pedruzzi, Ivo; Rivoire, Catherine; Arighi, Cecilia N.; Wang, Qinghua; Chen, Chuming; Huang, Hongzhan; Garavelli, John S.; Vinayaka, C. R.; Yeh, Lai-Su L.; Natale, Darren A.; Laiho, Kati; Martin, Maria Jesus; Renaux, Alexandre; Pichler, Klemens

doi:10.1093/bioinformatics/btaa663

Cited by 15 publications

(14 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…As described in the preceding section, PANTHER trees are annotated with GO terms by the GO Consortium, and also by the PhyloGenes project (focusing on plant genes) 39 . The UniProt UniRule system 40 is starting to develop PANTHER tree‐based annotations for other protein properties such as protein names. Other resources, including UniProt 35 and the Alliance of Genome Resources, 41 have cross‐references and web links from gene or protein pages to PANTHER subfamilies and trees.…”

Section: The Panther Knowledgebasementioning

confidence: 99%

PANTHER: Making genome‐scale phylogenetics accessible to all

et al. 2021

View full text Add to dashboard Cite

Phylogenetics is a powerful tool for analyzing protein sequences, by inferring their evolutionary relationships to other proteins. However, phylogenetics analyses can be challenging: they are computationally expensive and must be performed carefully in order to avoid systematic errors and artifacts. Protein Analysis THrough Evolutionary Relationships (PANTHER; http://pantherdb.org) is a publicly available, user‐focused knowledgebase that stores the results of an extensive phylogenetic reconstruction pipeline that includes computational and manual processes and quality control steps. First, fully reconciled phylogenetic trees (including ancestral protein sequences) are reconstructed for a set of “reference” protein sequences obtained from fully sequenced genomes of organisms across the tree of life. Second, the resulting phylogenetic trees are manually reviewed and annotated with function evolution events: inferred gains and losses of protein function along branches of the phylogenetic tree. Here, we describe in detail the current contents of PANTHER, how those contents are generated, and how they can be used in a variety of applications. The PANTHER knowledgebase can be downloaded or accessed via an extensive API. In addition, PANTHER provides software tools to facilitate the application of the knowledgebase to common protein sequence analysis tasks: exploring an annotated genome by gene function; performing “enrichment analysis” of lists of genes; annotating a single sequence or large batch of sequences by homology; and assessing the likelihood that a genetic variant at a particular site in a protein will have deleterious effects.

show abstract

Section: The Panther Knowledgebasementioning

confidence: 99%

PANTHER: Making genome‐scale phylogenetics accessible to all

et al. 2021

View full text Add to dashboard Cite

show abstract

“…We also recurated all cognate ligand binding sites of interest found in features of the type "REGION", and moved them to "BINDING". Finally, we modified all UniRules (MacDougall, et al, 2020), including HAMAP (Pedruzzi, et al, 2015) and PROSITE (Sigrist, et al, 2013) rules, to provide binding site annotations using ChEBI identifiers in the new data model described here.…”

Section: Changes To the Uniprot Data Model And Formatsmentioning

confidence: 99%

Annotation of biologically relevant ligands in UniProtKB using ChEBI

Coudert

Géhant

Castro

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Motivation: To provide high quality, computationally tractable annotation of binding sites for biologically relevant (cognate) ligands in UniProtKB using the chemical ontology ChEBI (Chemical Entities of Biological Interest), to better support efforts to study and predict functionally relevant interactions between proteins and small molecule ligands. Results: We structured the data model for cognate ligand binding site annotations in UniProtKB and performed a complete reannotation of all cognate ligand binding sites using stable unique identifiers from ChEBI, which we now use as the reference vocabulary for all such annotations. We developed improved search and query facilities for cognate ligands in the UniProt website, REST API and SPARQL endpoint that leverage the chemical structure data, nomenclature, and classification that ChEBI provides. Availability: Binding site annotations for cognate ligands described using ChEBI are available for UniProtKB protein sequence records in several formats (text, XML, and RDF), and are freely available to query and download through the UniProt website (www.uniprot.org), REST API (www.uniprot.org/help/api), SPARQL endpoint (sparql.uniprot.org/), and FTP site (https://ftp.uniprot.org/pub/databases/uniprot/).

show abstract

“…Dazu gehörten z. B. aruH , eine Transaminase, die am Arginin‐Abbau beteiligt ist [41] ( PL10 ), ilvA2 , eine Threonin‐Dehydratase, die aus einer Homologie abgeleitet wurde [42] ( PL13 ), und PA0394 , das von UniRule [43] als PLP‐ Homöostaseprotein annotiert ist ( PL2, PL6 ), und dessen Homologe auch in E. coli ( yggS ) und S. aureus ( A0A0H2XHH8 ) stark angereichert waren. Interessanterweise konnte PL10 auch in diesem Experiment mutmaßliche Transkriptionsfaktoren anreichern (z.…”

Section: Ergebnisse Und Diskussionunclassified

Maßgeschneiderte Pyridoxal‐Sonden enthüllen neue Cofaktor‐abhängige Enzyme und antibiotische Treffer in kritischen bakteriellen Krankheitserregern

et al. 2022

View full text Add to dashboard Cite

Zur Überwindung der Antibiotika‐Resistenzkrise werden dringend neuartige bakterielle Angriffsziele benötigt. In diesem Artikel untersuchen wir systematisch Pyridoxalphosphat‐abhängige Enzyme (PLP‐DEs) in Bakterien, um uns auf Ziele zu konzentrieren, die an entscheidenden Stoffwechselprozessen beteiligt sind. Zu diesem Zweck haben wir acht Pyridoxal (PL)‐Sonden mit Modifikationen an verschiedenen Positionen entwickelt. Insgesamt übertrafen die Sonden die Leistung einer früheren Generation und lieferten detaillierte Informationen der PLP‐DEs in klinisch relevanten Krankheitserregern, einschließlich schwierig zu adressierender Gram‐negativer Stämme. Ausgewählte PLP‐DEs mit unbekannter Funktion wurden durch enzymatische Aktivitätsassays charakterisiert. Schließlich untersuchten wir eine Reihe von mutmaßlichen PLP‐Inhibitoren auf ihre antibiotische Aktivität und entschlüsselten die Zielenzyme aktiver Trefferverbindungen. Hier wurde ein kaum charakterisiertes Enzym, das für das bakterielle Wachstum unerlässlich ist, als PLP‐abhängige Cystein‐Desulfurase identifiziert und bestätigt, dass es durch das zugelassene Medikament Phenelzin gehemmt wird. Unser Ansatz bietet eine Grundlage für die Entschlüsselung neuartiger PLP‐DEs als essenzielle Antibiotikaziele sowie entsprechende Möglichkeiten zur Entschlüsselung kleiner Molekül‐Inhibitoren.

show abstract

UniRule: a unified rule resource for automatic annotation in the UniProt Knowledgebase

Cited by 15 publications

References 0 publications

PANTHER: Making genome‐scale phylogenetics accessible to all

PANTHER: Making genome‐scale phylogenetics accessible to all

Annotation of biologically relevant ligands in UniProtKB using ChEBI

Maßgeschneiderte Pyridoxal‐Sonden enthüllen neue Cofaktor‐abhängige Enzyme und antibiotische Treffer in kritischen bakteriellen Krankheitserregern

Contact Info

Product

Resources

About