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Current and emerging tools of computational biology to improve the detoxification of mycotoxins.

Natalie SandlinDarius Russell KishJohn KimMarco ZaccariaBabak Momeni
Published in: Applied and environmental microbiology (2021)
Biological organisms carry a rich potential for removing toxins from our environment, but identifying suitable candidates and improving them remain challenging. We explore the use of computational tools to discover strains and enzymes that detoxify harmful compounds. In particular, we will focus on mycotoxins-fungi-produced toxins that contaminate food and feed-and biological enzymes that are capable of rendering them less harmful. We discuss the use of established and novel computational tools to complement existing empirical data in three directions: discovering the prospect of detoxification among underexplored organisms, finding important cellular processes that contribute to detoxification, and improving the performance of detoxifying enzymes. We hope to create a synergistic conversation between researchers in computational biology and those in the bioremediation field. We showcase open bioremediation questions where computational researchers can contribute and highlight relevant existing and emerging computational tools that could benefit bioremediation researchers.
Keyphrases
  • escherichia coli
  • minimally invasive
  • multidrug resistant
  • gram negative
  • human health
  • cancer therapy
  • machine learning
  • risk assessment
  • climate change
  • deep learning
  • artificial intelligence
  • data analysis