Illuminating Dark Proteins using Reactome Pathways Article Swipe
Lisa Matthews
,
Guanming Wu
,
Robin Haw
,
Timothy Brunson
,
Nasim Sanati
,
Solomon I. Shorser
,
Deidre Beavers
,
Patrick T. Conley
,
Lincoln Stein
,
Peter D’Eustachio
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3180/poster/20221027matthews
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3180/poster/20221027matthews
Diseases are often the consequence of proteins or protein complexes that are non-functional or that function improperly. An active area of research has focused on the identification of molecules that can interact with defective proteins and restore their function. While 22% percent of human proteins are estimated to be druggable, less than fifteen percent are targeted by FDA-approved drugs, and the vast majority of untargeted proteins are understudied or so-called "dark" proteins. Elucidation of the function of these dark proteins, particularly those in commonly drug-targeted protein families, may offer therapeutic opportunities for many diseases. Reactome is the most comprehensive, open-access pathway knowledgebase covering 2585 pathways and including 14246 reactions, 11088 proteins, 13984 complexes, and 1093 drugs. Placing dark proteins in the context of Reactome pathways provides a framework of reference for these proteins facilitating the generation of hypotheses for experimental biologists to develop targeted experiments, unravel the potential functions of these proteins, and then design drugs to manipulate them. To this end, we have trained a random forest with 106 protein/gene pairwise features collected from multiple resources to predict functional interactions between dark proteins and proteins annotated in Reactome and then developed three scores to measure the interactions between dark proteins and Reactome pathways based on enrichment analysis and fuzzy logic simulations. Literature evidence via manual checking and systematic NLP-based analysis support predicted interacting pathways for dark proteins. To visualize dark proteins in the context of Reactome pathways, we have also developed a new website, idg.reactome.org, by extending the Reactome web application with new features illustrating these proteins together with tissue-specific protein and gene expression levels and drug interactions.
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Metadata
- Type
- report
- Language
- en
- Landing Page
- http://doi.org/10.3180/poster/20221027matthews
- https://doi.org/10.3180/poster/20221027matthews
- OA Status
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- Cited By
- 2
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
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https://doi.org/10.3180/poster/20221027matthewsDigital Object Identifier
- Title
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Illuminating Dark Proteins using Reactome PathwaysWork title
- Type
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reportOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-10-26Full publication date if available
- Authors
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Lisa Matthews, Guanming Wu, Robin Haw, Timothy Brunson, Nasim Sanati, Solomon I. Shorser, Deidre Beavers, Patrick T. Conley, Lincoln Stein, Peter D’EustachioList of authors in order
- Landing page
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https://doi.org/10.3180/poster/20221027matthewsPublisher landing page
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https://doi.org/10.3180/poster/20221027matthewsDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.3180/poster/20221027matthewsDirect OA link when available
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Human proteins, Computational biology, Context (archaeology), Druggability, Function (biology), Biology, Gene ontology, Gene, Bioinformatics, Genetics, Gene expression, PaleontologyTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
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2024: 2Per-year citation counts (last 5 years)
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