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Related Concept Videos

Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Cyclic Adenosine Monophosphate (cAMP) is an essential second messenger that activates protein kinase A (PKA) and regulates various biological processes. A single epinephrine molecule binds to GPCR and activates several heterotrimeric G proteins, each stimulating multiple adenylyl cyclase, amplifying the signal, and synthesizing large numbers of cAMP molecules. Small changes in cAMP concentration affect PKA activity. The binding of four cAMP molecules induces a conformational change in PKA,...
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Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification
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Illuminating Dark Proteins using Reactome Pathways.

Timothy Brunson1, Nasim Sanati1, Lisa Matthews2

  • 1Oregon Health & Science University, Portland, OR 97239, USA.

Biorxiv : the Preprint Server for Biology
|June 19, 2023
PubMed
Summary
This summary is machine-generated.

Researchers uncovered the functions of "dark" proteins, which have limited known roles. This study used pathway analysis and machine learning to predict interactions, aiding in understanding protein functions and potential drug development.

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Area of Science:

  • Genomics and Bioinformatics
  • Molecular Biology
  • Systems Biology

Background:

  • A significant portion of protein-coding genes, termed "dark" proteins, have poorly understood functions, limiting biological insights and therapeutic development.
  • Understanding these dark proteins is crucial for advancing our knowledge of cellular mechanisms and identifying new drug targets.

Approach:

  • Integrated multiple data resources and employed a random forest classifier with 106 features to predict functional interactions between dark proteins and known Reactome pathways.
  • Developed novel scoring systems using enrichment analysis and fuzzy logic simulations to quantify dark protein interactions with Reactome pathways.
  • Validated predictions using single-cell RNA sequencing data and natural language processing (NLP) on over 22 million PubMed abstracts.

Key Points:

  • Successfully predicted functional interactions for numerous dark proteins within biological pathways.
  • Developed a robust computational framework for contextualizing poorly characterized proteins.
  • Created the Reactome IDG portal (https://idg.reactome.org) for visualizing and exploring dark proteins, including tissue-specific expression and drug interactions.

Conclusions:

  • This integrated approach provides a valuable resource for elucidating the biological roles and therapeutic potential of dark proteins.
  • The Reactome IDG portal facilitates deeper investigation into uncharacterized proteins, accelerating biological discovery.
  • Advances in understanding dark proteins can lead to novel therapeutic strategies and improved disease treatment.