14 research outputs found

    ComplexViewer: visualization of curated macromolecular complexes.

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    SUMMARY: Proteins frequently function as parts of complexes, assemblages of multiple proteins and other biomolecules, yet network visualizations usually only show proteins as parts of binary interactions. ComplexViewer visualizes interactions with more than two participants and thereby avoids the need to first expand these into multiple binary interactions. Furthermore, if binding regions between molecules are known then these can be displayed in the context of the larger complex. AVAILABILITY AND IMPLEMENTATION: freely available under Apache version 2 license; EMBL-EBI Complex Portal: http://www.ebi.ac.uk/complexportal; Source code: https://github.com/MICommunity/ComplexViewer; Package: https://www.npmjs.com/package/complexviewer; http://biojs.io/d/complexviewer. Language: JavaScript; Web technology: Scalable Vector Graphics; Libraries: D3.js. CONTACT: [email protected] or [email protected]

    Complex Portal 2022:New curation frontiers

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    International audienceThe Complex Portal (www.ebi.ac.uk/complexportal) is a manually curated, encyclopaedic database of macromolecular complexes with known function from a range of model organisms. It summarizes complex composition, topology and function along with links to a large range of domain-specific resources (i.e. wwPDB, EMDB and Reactome). Since the last update in 2019, we have produced a first draft complexome for Escherichia coli, maintained and updated that of Saccharomyces cerevisiae, added over 40 coronavirus complexes and increased the human complexome to over 1100 complexes that include approximately 200 complexes that act as targets for viral proteins or are part of the immune system. The display of protein features in ComplexViewer has been improved and the participant table is now colour-coordinated with the nodes in ComplexViewer. Community collaboration has expanded, for example by contributing to an analysis of putative transcription cofactors and providing data accessible to semantic web tools through Wikidata which is now populated with manually curated Complex Portal content through a new bot. Our data license is now CC0 to encourage data reuse. Users are encouraged to get in touch, provide us with feedback and send curation requests through the ‘Support’ link

    The IntAct database:Efficient access to fine-grained molecular interaction data

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    The IntAct molecular interaction database (https://www.ebi.ac.uk/intact) is a curated resource of molecular interactions, derived from the scientific literature and from direct data depositions. As of August 2021, IntAct provides more than one million binary interactions, curated by twelve global partners of the International Molecular Exchange consortium, for which the IntAct database provides a shared curation and dissemination platform. The IMEx curation policy has always emphasised a fine-grained data and curation model, aiming to capture the relevant experimental detail essential for the interpretation of the provided molecular interaction data. Here, we present recent curation focus and progress, as well as a completely redeveloped website which presents IntAct data in a much more user-friendly and detailed way

    The MIntAct project—IntAct as a common curation platform for 11 molecular interaction databases

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    IntAct (freely available at http://www.ebi.ac.uk/intact) is an open-source, open data molecular interaction database populated by data either curated from the literature or from direct data depositions. IntAct has developed a sophisticated web-based curation tool, capable of supporting both IMEx- and MIMIx-level curation. This tool is now utilized by multiple additional curation teams, all of whom annotate data directly into the IntAct database. Members of the IntAct team supply appropriate levels of training, perform quality control on entries and take responsibility for long-term data maintenance. Recently, the MINT and IntAct databases decided to merge their separate efforts to make optimal use of limited developer resources and maximize the curation output. All data manually curated by the MINT curators have been moved into the IntAct database at EMBL-EBI and are merged with the existing IntAct dataset. Both IntAct and MINT are active contributors to the IMEx consortium (http://www.imexconsortium.org

    Performance Analysis of Orthogonal Pairs Designed for an Expanded Eukaryotic Genetic Code

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    Background: The suppression of amber stop codons with non-canonical amino acids (ncAAs) is used for the site-specific introduction of many unusual functions into proteins. Specific orthogonal aminoacyl-tRNA synthetase (o-aaRS)/amber suppressor tRNA CUA pairs (o-pairs) for the incorporation of ncAAs in S. cerevisiae were previously selected from an E. coli tyrosyl-tRNA synthetase/tRNACUA mutant library. Incorporation fidelity relies on the specificity of the o-aaRSs for their ncAAs and the ability to effectively discriminate against their natural substrate Tyr or any other canonical amino acid. Methodology/Principal Findings: We used o-pairs previously developed for ncAAs carrying reactive alkyne-, azido-, or photocrosslinker side chains to suppress an amber mutant of human superoxide dismutase 1 in S. cerevisiae. We found worse incorporation efficiencies of the alkyne- and the photocrosslinker ncAAs than reported earlier. In our hands, amber suppression with the ncAA containing the azido group did not occur at all. In addition to the incorporation experiments in S. cerevisiae, we analyzed the catalytic properties of the o-aaRSs in vitro. Surprisingly, all o-aaRSs showed much higher preference for their natural substrate Tyr than for any of the tested ncAAs. While it is unclear why efficiently recognized Tyr is not inserted at amber codons, we speculate that metabolically inert ncAAs accumulate in the cell, and for this reason they are incorporated despite being weak substrates for the o-aaRSs. Conclusions/Significance: O-pairs have been developed for a whole plethora of ncAAs. However, a systematic and detaile

    Improving the Gene Ontology Resource to Facilitate More Informative Analysis and Interpretation of Alzheimer’s Disease Data

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    The analysis and interpretation of high-throughput datasets relies on access to high-quality bioinformatics resources, as well as processing pipelines and analysis tools. Gene Ontology (GO, geneontology.org) is a major resource for gene enrichment analysis. The aim of this project, funded by the Alzheimer’s Research United Kingdom (ARUK) foundation and led by the University College London (UCL) biocuration team, was to enhance the GO resource by developing new neurological GO terms, and use GO terms to annotate gene products associated with dementia. Specifically, proteins and protein complexes relevant to processes involving amyloid-beta and tau have been annotated and the resulting annotations are denoted in GO databases as ‘ARUK-UCL’. Biological knowledge presented in the scientific literature was captured through the association of GO terms with dementia-relevant protein records; GO itself was revised, and new GO terms were added. This literature biocuration increased the number of Alzheimer’s-relevant gene products that were being associated with neurological GO terms, such as ‘amyloid-beta clearance’ or ‘learning or memory’, as well as neuronal structures and their compartments. Of the total 2055 annotations that we contributed for the prioritised gene products, 526 have associated proteins and complexes with neurological GO terms. To ensure that these descriptive annotations could be provided for Alzheimer’s-relevant gene products, over 70 new GO terms were created. Here, we describe how the improvements in ontology development and biocuration resulting from this initiative can benefit the scientific community and enhance the interpretation of dementia data
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