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

Ching Hsuan Liu, Cheng Hua Lu, Liang Tzung Lin

研究成果: 雜誌貢獻回顧型文獻同行評審

摘要

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.
原文英語
頁(從 - 到)187-192
頁數6
期刊Computational and Structural Biotechnology Journal
20
DOIs
出版狀態已發佈 - 1月 2022

ASJC Scopus subject areas

  • 生物技術
  • 生物物理學
  • 結構生物學
  • 生物化學
  • 遺傳學
  • 電腦科學應用

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