In-silico Analysis of Angiotensin-converting Enzyme 2 (ACE2) of Livestock, Pet and Poultry Animals to Determine its Susceptibility to SARS–CoV- 2 Infection

(E-pub Ahead of Print)

Author(s): Aman Kumar*, Anil Panwar, Kanisht Batra, Sachinandan Dey, Sushila Maan

Journal Name: Combinatorial Chemistry & High Throughput Screening
Accelerated Technologies for Biotechnology, Bioassays, Medicinal Chemistry and Natural Products Research

Become EABM
Become Reviewer
Call for Editor


Background: Novel coronavirus SARS-CoV-2 is responsible of COVID-19 pandemic. It was first reported in Wuhan, China in December, 2019 and despite the tremendous efforts to control the disease, it has now spread almost all over the world.The interaction of SARS-CoV-2spike protein and its acceptor protein ACE2 is an important issue in determining viralhost range and cross-species infection, while the binding capacity of spike protein toACE2 of different species is unknown.

Objective: The present study has been conducted to determine the susceptibility of livestock, poultry and pets to SARSCoV-2.

Methods: We evaluated the receptor-utilizing capability of ACE2sfrom various species by sequence alignment,phylogenetic clustering and protein-ligand interaction studies with the currently knownACE2s utilized by SARS-CoV-2.

Result:In-silico study predicted that SARS-CoV-2 tends to utilize ACE2s ofvarious animal species with varied possible interactions and theprobability ofthe receptor utilization will be greater in horse and poor in chicken followed by ruminants.

Conclusion: Present studypredicted that SARS-CoV-2 tends to utilize ACE2s ofvarious livestock and poultry species with greater probability in equine and poor in chicken. Study may provide important insights into the animal models for SARSCoV-2 and animal management for COVID-19 control.

Keywords: : COVID-19, pandemic, SARS, ACE-2, domestic animal, protein docking

Rights & PermissionsPrintExport Cite as

Article Details

(E-pub Ahead of Print)
DOI: 10.2174/1386207323666201110144542
Price: $95

Article Metrics

PDF: 39