A survey on computational methods in discovering protein inhibitors of SARS-CoV-2

Abstract The outbreak of acute respiratory disease in 2019, namely Coronavirus Disease-2019 (COVID-19), has become an unprecedented healthcare crisis. To mitigate the pandemic, there are a lot of collective and multidisciplinary efforts in facilitating the rapid discovery of protein inhibitors or dr...

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Bibliographic Details
Published in:Briefings in bioinformatics 2022-01, Vol.23 (1)
Main Authors: Liu, Qiaoming, Wan, Jun, Wang, Guohua
Format: Article
Language:English
Subjects:
Algorithms
Antiviral Agents - chemistry
Antiviral Agents - therapeutic use
Computational Biology
Computer applications
Coronaviruses
COVID-19
COVID-19 - drug therapy
COVID-19 - epidemiology
Databases, Factual
Humans
Inhibitors
Molecular Docking Simulation
Pandemics
Proteins
Respiratory diseases
Review
Reviews
SARS-CoV-2 - metabolism
Severe acute respiratory syndrome
Severe acute respiratory syndrome coronavirus 2
Viral diseases
Viruses
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Summary:Abstract The outbreak of acute respiratory disease in 2019, namely Coronavirus Disease-2019 (COVID-19), has become an unprecedented healthcare crisis. To mitigate the pandemic, there are a lot of collective and multidisciplinary efforts in facilitating the rapid discovery of protein inhibitors or drugs against COVID-19. Although many computational methods to predict protein inhibitors have been developed [ 1– 5], few systematic reviews on these methods have been published. Here, we provide a comprehensive overview of the existing methods to discover potential inhibitors of COVID-19 virus, so-called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). First, we briefly categorize and describe computational approaches by the basic algorithms involved in. Then we review the related biological datasets used in such predictions. Furthermore, we emphatically discuss current knowledge on SARS-CoV-2 inhibitors with the latest findings and development of computational methods in uncovering protein inhibitors against COVID-19.
ISSN:1467-5463
1477-4054
DOI:10.1093/bib/bbab416