Pandemic strategies with computational and structural biology against COVID-19: A retrospective

Ching Hsuan Liu, Cheng Hua Lu, Liang Tzung Lin

Research output: Contribution to journalReview articlepeer-review

Abstract

The emergence of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which is the etiologic agent of the coronavirus disease 2019 (COVID-19) pandemic, has dominated all aspects of life since of 2020. Research studies on the virus and exploration of therapeutic and preventive strategies has been moving at rapid rates to control the pandemic. In the field of bioinformatics or computational and structural biology, recent research strategies have used multiple disciplines to compile large datasets to uncover statistical correlations and significance, visualize and model proteins, perform molecular dynamics simulations, and employ the help of artificial intelligence and machine learning to harness computational processing power to further the research on COVID-19, including drug screening, drug design, vaccine development, prognosis prediction, and outbreak prediction. These recent developments should help us better understand the viral disease and develop the much-needed therapies and strategies for the management of COVID-19.

Original languageEnglish
Pages (from-to)187-192
Number of pages6
JournalComputational and Structural Biotechnology Journal
Volume20
DOIs
Publication statusPublished - Jan 2022

Keywords

  • Artificial intelligence
  • COVID-19
  • Disease prediction
  • Drug design
  • Drug screening
  • Machine learning
  • SARS-CoV-2
  • Vaccine development

ASJC Scopus subject areas

  • Biotechnology
  • Biophysics
  • Structural Biology
  • Biochemistry
  • Genetics
  • Computer Science Applications

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