RadicalSAM.org: A Resource to Interpret Sequence-Function Space and Discover New Radical SAM Enzyme Chemistry

Nils Oberg, Timothy W. Precord, Douglas A. Mitchell, John A. Gerlt

Research output: Contribution to journalReview articlepeer-review

Abstract

The radical SAM superfamily (RSS), arguably the most functionally diverse enzyme superfamily, is also one of the largest with ∼700 K members currently in the UniProt database. The vast majority of the members have uncharacterized enzymatic activities and metabolic functions. In this Perspective, we describe RadicalSAM.org, a new web-based resource that enables a user-friendly genomic enzymology strategy to explore sequence-function space in the RSS. The resource attempts to enable identification of isofunctional groups of radical SAM enzymes using sequence similarity networks (SSNs) and the genome context of the bacterial, archaeal, and fungal members provided by genome neighborhood diagrams (GNDs). Enzymatic activities and in vivo functions frequently can be inferred from genome context given the tendency for genes of related function to be clustered. We invite the scientific community to use RadicalSAM.org to (i) guide their experimental studies to discover new enzymatic activities and metabolic functions, (ii) contribute experimentally verified annotations to RadicalSAM.org to enhance the ability to predict novel activities and functions, and (iii) provide suggestions for improving this resource.

Original languageEnglish (US)
Pages (from-to)22-35
Number of pages14
JournalACS Bio and Med Chem Au
Volume2
Issue number1
DOIs
StatePublished - Feb 16 2022

Keywords

  • Radical SAM superfamily
  • functional assignment
  • genome neighborhood diagrams
  • genomic enzymology
  • isofunctional families
  • protein sequence similarity networks
  • web tools

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Pharmaceutical Science
  • Drug Discovery

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