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   Evolutionary Analysis of Mammalian ACE2 and the Key Residues Involved in Binding to the Spike Protein Revealed Potential SARS-CoV-2 Hosts  
   
نویسنده lopes luciano rodrigo ,lucca pina natália carvalho de ,silva junior antonio carlos da ,paiva paulo-bandiera
منبع journal of medical microbiology and infectious diseases - 2022 - دوره : 10 - شماره : 1 - صفحه:1 -9
چکیده    Introduction: severe acute respiratory syndrome coronavirus 2 (sars-cov-2) spilled over to humans via wild mammals, entering the host cell using angiotensin-converting enzyme 2 (ace2) as receptor through spike (s) protein binding. while sars-cov-2 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-2 through bioinformatics prediction based on ace2 receptors. methods: we usedevolutionary bioinformatic approaches and comparative analysis of ace2 critical residues that bind sars-cov-2 s-protein and predicted potential sars-cov-2 hosts among mammals and assessed their risk. results: ace2 phylogenetic tree placed primates close to rodents and rabbits. felines, rodents, and rabbits had higher ace2 similarities than human ace2 (hace2). farmed animals, such as bovids, swine, and equids, had similar ace2 compared to hace2; however, these animals showed low sars-cov-2 susceptibility. some cetaceans also presented high similarities in ace2 key residues with hace2. conclusion: here, we showed wild and domestic mammals with a low divergence of ace2 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-2 infection. extensive surveillance of sars-cov-2 should be applied to prevent new coronavirus outbreaks and preserve mammals from infectious threats.
کلیدواژه SARS-CoV-2 ,Coronavirus ,ACE2 ,Mammals ,Wildlife
آدرس universidade federal de são paulo, bioinformatics and bio-data science division, health informatics department, Brazil, universidade federal de são paulo, bioinformatics and bio-data science division, health informatics department, Brazil, universidade federal de são paulo, bioinformatics and bio-data science division, health informatics department, Brazil, universidade federal de são paulo, bioinformatics and bio-data science division, health informatics department, Brazil
 
     
   
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