Evolutionary Analysis of Mammalian ACE۲ and the Key Residues Involved in Binding to the Spike Protein Revealed Potential SARS-CoV-۲ Hosts

سال انتشار: 1400
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 32

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شناسه ملی سند علمی:

JR_JMMI-10-1_001

تاریخ نمایه سازی: 29 بهمن 1402

چکیده مقاله:

Introduction: Severe acute respiratory syndrome coronavirus ۲ (SARS-CoV-۲) spilled over to humans via wild mammals, entering the host cell using angiotensin-converting enzyme ۲ (ACE۲) as receptor through Spike (S) protein binding. While SARS-CoV-۲ became fully adapted to humans and globally spread, some mammal species were infected back. The present study evaluated the potential risk of mammals becoming hosts for SARS-CoV-۲ through bioinformatics prediction based on ACE۲ receptors. Methods: We used evolutionary bioinformatic approaches and comparative analysis of ACE۲ critical residues that bind SARS-CoV-۲ S-protein and predicted potential SARS-CoV-۲ hosts among mammals and assessed their risk. Results: ACE۲ phylogenetic tree placed primates close to rodents and rabbits. Felines, rodents, and rabbits had higher ACE۲ similarities than human ACE۲ (hACE۲). Farmed animals, such as bovids, swine, and equids, had similar ACE۲ compared to hACE۲; however, these animals showed low SARS-CoV-۲ susceptibility. Some cetaceans also presented high similarities in ACE۲ key residues with hACE۲. Conclusion: Here, we showed wild and domestic mammals with a low divergence of ACE۲ compared to humans, discussing their possible chance of being infected, especially those animals kept as livestock or pets. Regarding the feasible transmission through contaminated water, cetaceans can be at risk of SARS-CoV-۲ infection. Extensive surveillance of SARS-CoV-۲ should be applied to prevent new coronavirus outbreaks and preserve mammals from infectious threats.

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نویسندگان

Luciano Rodrigo Lopes

Bioinformatics and Bio-Data Science Division, Health Informatics Department, Universidade Federal de São Paulo, UNIFESP, São Paulo, SP, Brazil

Natália Carvalho de Lucca Pina

Bioinformatics and Bio-Data Science Division, Health Informatics Department, Universidade Federal de São Paulo, UNIFESP, São Paulo, SP, Brazil

Antonio Carlos Da Silva Junior

Bioinformatics and Bio-Data Science Division, Health Informatics Department, Universidade Federal de São Paulo, UNIFESP, São Paulo, SP, Brazil

Paulo Bandiera-Paiva

Bioinformatics and Bio-Data Science Division, Health Informatics Department, Universidade Federal de São Paulo, UNIFESP, São Paulo, SP, Brazil

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