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Exploring Sequence Space to Identify Binding Sites for Regulatory RNA-Binding Proteins
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RadicalSAM.org: A Resource to Interpret Sequence-Function Space and Discover New Radical SAM Enzyme Chemistry
Nils Oberg1, Timothy W Precord1,2, Douglas A Mitchell1,2,3
1Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, 1206 West Gregory Drive, Urbana, Illinois 61801, United States.
ACS Bio & Med Chem Au
|September 19, 2022
Summary
Radical SAM enzymes are diverse, with most functions unknown. RadicalSAM.org aids discovery of new enzyme functions using genomic data and sequence similarity networks.
Area of Science:
- Biochemistry
- Bioinformatics
- Genomics
Background:
- The radical SAM superfamily (RSS) is a vast and functionally diverse enzyme group, with most members lacking characterized activities.
- Exploring the sequence-function space of RSS is crucial for understanding metabolic pathways and discovering novel biocatalysts.
Purpose of the Study:
- Introduce RadicalSAM.org, a novel web resource for exploring RSS.
- Enable identification of isofunctional enzyme groups within RSS using genomic enzymology.
- Facilitate the discovery of new enzymatic activities and metabolic functions.
Main Methods:
- Utilized sequence similarity networks (SSNs) to group related RSS enzymes.
- Employed genome neighborhood diagrams (GNDs) to analyze the genomic context of RSS members.
- Integrated sequence and genomic context data for functional inference.
Main Results:
- RadicalSAM.org provides a user-friendly platform for genomic enzymology.
- The resource facilitates the identification of potential isofunctional enzyme clusters.
- Genome context analysis aids in predicting enzymatic activities and in vivo functions.
Conclusions:
- RadicalSAM.org is a valuable tool for guiding experimental studies on RSS.
- Community contributions of verified annotations will enhance predictive capabilities.
- The resource aims to accelerate the discovery of novel enzyme functions within the RSS.
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