Artificial intelligence for the discovery of novel antimicrobial agents for emerging infectious diseases.

Journal: Drug discovery today
Published Date: Apr 1, 2022

Abstract

The search for effective drugs to treat new and existing diseases is a laborious one requiring a large investment of capital, resources, and time. The coronavirus 2019 (COVID-19) pandemic has been a painful reminder of the lack of development of new antimicrobial agents to treat emerging infectious diseases. Artificial intelligence (AI) and other in silico techniques can drive a more efficient, cost-friendly approach to drug discovery by helping move potential candidates with better clinical tolerance forward in the pipeline. Several research teams have developed successful AI platforms for hit identification, lead generation, and lead optimization. In this review, we investigate the technologies at the forefront of spearheading an AI revolution in drug discovery and pharmaceutical sciences.

Authors

  • Adam Bess
    Department of Computer Sciences, Louisiana State University, Baton Rouge, LA, United States.
  • Frej Berglind
    Department of Computer Sciences, Louisiana State University, Baton Rouge, LA, United States.
  • Supratik Mukhopadhyay
    Department of Environmental Sciences, Center for Computation & Technology, Coastal Studies Institute, Louisiana State University, Baton Rouge, LA, United States.
  • Michal Brylinski
    Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, United States.
  • Nicholas Griggs
    Trinity Consultants Inc., Mountain View, CA, USA.
  • Tiffany Cho
    Trinity Consultants Inc., Mountain View, CA, USA.
  • Chris Galliano
    Skymount Medical US Inc, New Orleans, LA, USA.
  • Kishor M Wasan
    Department of Urologic Sciences, Faculty of Medicine and the Neglected Global Diseases Initiative, University of British Columbia, Vancouver, BC, Canada.

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