Using COVID-19 as a teaching tool in a time of remote learning: A workflow for bioinformatic approaches to identifying candidates for therapeutic and vaccine development

Biochem Mol Biol Educ. 2020 Sep;48(5):492-498. doi: 10.1002/bmb.21413. Epub 2020 Jul 29.

Abstract

The COVID-19 pandemic has led to an urgent need for engaging computational alternatives to traditional laboratory exercises. Here we introduce a customizable and flexible workflow, designed with the SARS CoV-2 virus that causes COVID-19 in mind, as a means of reinforcing fundamental biology concepts using bioinformatics approaches. This workflow is accessible to a wide range of students in life science majors regardless of their prior bioinformatics knowledge, and all software is freely available, thus eliminating potential cost barriers. Using the workflow can thus provide a diverse group of students the opportunity to conduct inquiry-driven research. Here we demonstrate the utility of this workflow and outline the logical steps involved in the identification of therapeutic or vaccine targets against SARS CoV-2. We also provide an example of how the workflow may be adapted to other infectious microbes. Overall, our workflow anchors student understanding of viral biology and genomics and allows students to develop valuable bioinformatics expertise as well as to hone critical thinking and problem-solving skills, while also creating an opportunity to better understand emerging information surrounding the COVID-19 pandemic.

Keywords: active learning; cellular biology; computational biology; distance learning; immunology; inquiry‐based teaching; integration of research into undergraduate teaching; molecular biology; virology.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Antiviral Agents* / therapeutic use
  • Biological Science Disciplines
  • COVID-19 / immunology
  • COVID-19 / prevention & control*
  • COVID-19 Drug Treatment*
  • COVID-19 Vaccines*
  • Computational Biology / education*
  • Computational Biology / methods*
  • Education, Distance / methods*
  • Humans
  • Learning
  • Pandemics
  • SARS-CoV-2 / drug effects
  • SARS-CoV-2 / immunology
  • Students
  • Workflow*

Substances

  • Antiviral Agents
  • COVID-19 Vaccines