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Virginia Tech

A Bioinformatics Approach to Identifying Radical SAM (S-Adenosyl-L-Methionine) Enzymes

Abstract

dc:description.abstract

Radical SAM enzymes are ancient, essential enzymes. They perform radical chemical reactions in virtually all living organisms and are involved in producing antibiotics, generating greenhouse gases, human health, and likely many other essential roles that have yet to be established. A wide variety of reactions have been characterized from this group of enzymes, including hydrogen abstractions, the transferring of methylthio groups, complex cyclization and rearrangement reactions, and others. However, many radical SAM enzymes have yet to be identified or characterized. There have been great leaps forward in the amount of enzyme sequences that are available in public databases, but experiments to investigate what chemical reactions the enzymes perform take a great deal of time. In our work, we utilize Hidden Markov Models to identify possible radical SAM enzymes and predict their possible functions through BLAST alignments and homology modelling. We also explore their distribution across the tree of life and determine how it is correlated with organism oxygen tolerances, because the core iron-sulfur cluster is oxygen sensitive. Trends in the abundances of radical SAM enzymes depending on oxygen tolerances were more apparent in prokaryotes than in eukaryotes. Although eukaryotes tend to have fewer radical SAM enzymes than prokaryotes, we were able to analyze uncharacterized radical SAM enzymes from both an aerobic eukaryote (Entamoeba histolytica) and a eukaryote capable of oxygenic photosynthesis (Gossypium barbadense), and predict the reactions they catalyze. This work sets the stage for the functional characterization of these essential yet elusive enzymes in future laboratory experiments.

Degree

thesis:*
Name thesis:degree_name
Master of Science in Life Sciences
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Biochemistry
Department dc:contributor.department
Biochemistry
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2020

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Gagliano, Elisa
Chair dc:contributor.committeechair
  • Brown, Anne M.
Committee members dc:contributor.committeemember
  • Allen, Kylie D.
  • Lemkul, Justin A.

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:26525
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/98736

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Gagliano, Elisa. A Bioinformatics Approach to Identifying Radical SAM (S-Adenosyl-L-Methionine) Enzymes. masters thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/98736