Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

A novel structure-based approach for identification of vertebrate susceptibility to SARS-CoV-2: implications for future surveillance programmes

Rahul Kaushik, Naveen Kumar, Kam Y. J. Zhang, Pratiksha Srivastava, Sandeep Bhatia, Yashpal Singh Malik
doi: https://doi.org/10.1101/2022.01.10.475752
Rahul Kaushik
1Laboratory for Structural Bioinformatics, Center for Biosystems Dynamics Research, RIKEN, 1-7-22 Suehiro, Yokohama, Kanagawa 230-0045, Japan
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Naveen Kumar
2Zoonotic Diseases Group, ICAR-National Institute of High Security Animal Diseases, Bhopal 462022, India
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kam Y. J. Zhang
1Laboratory for Structural Bioinformatics, Center for Biosystems Dynamics Research, RIKEN, 1-7-22 Suehiro, Yokohama, Kanagawa 230-0045, Japan
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Pratiksha Srivastava
2Zoonotic Diseases Group, ICAR-National Institute of High Security Animal Diseases, Bhopal 462022, India
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sandeep Bhatia
2Zoonotic Diseases Group, ICAR-National Institute of High Security Animal Diseases, Bhopal 462022, India
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yashpal Singh Malik
3College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Science University (GADVASU), Ludhiana 141004, Punjab, India
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: malikyps@gmail.com
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Understanding the origin of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a highly debatable and unsolved challenge for the scientific communities across the world. A key to dissect the susceptibility profiles of animal species to SARS-CoV-2 is to understand how virus enters into the cells. The interaction of SARS-CoV-2 ligands (RBD on spike protein) with its host cell receptor, angiotensin-converting enzyme 2 (ACE2), is a critical determinant of host range and cross-species transmission. In this study, we developed and implemented a rigorous computational approach for predicting binding affinity between 299 ACE2 orthologs from diverse vertebrate species and the SARS-CoV-2 spike protein. The findings show that the spike protein of SARS-CoV-2 can bind to many vertebrate species carrying evolutionary divergent ACE2, implying a broad host range at the virus entry level, which may contribute to cross-species transmission and further viral evolution. Additionally, the present study facilitated the identification of genetic determinants that may differentiate susceptible from the resistant host species based on the conservation of ACE2-spike protein interacting residues in vertebrate host species known to facilitate SARS-CoV-2 infection; however, these genetic determinants warrant in vivo experimental confirmation. The molecular interactions associated with varied binding affinity of distinct ACE2 isoforms in a specific bat species were identified using protein structure analysis, implying the existence of diversified susceptibility of bat species to SARS-CoV-2. The findings from current study highlight the importance of intensive surveillance programs aimed at identifying susceptible hosts, particularly those with the potential to transmit zoonotic pathogens, in order to prevent future outbreaks.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Back to top
PreviousNext
Posted January 12, 2022.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
A novel structure-based approach for identification of vertebrate susceptibility to SARS-CoV-2: implications for future surveillance programmes
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
A novel structure-based approach for identification of vertebrate susceptibility to SARS-CoV-2: implications for future surveillance programmes
Rahul Kaushik, Naveen Kumar, Kam Y. J. Zhang, Pratiksha Srivastava, Sandeep Bhatia, Yashpal Singh Malik
bioRxiv 2022.01.10.475752; doi: https://doi.org/10.1101/2022.01.10.475752
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
A novel structure-based approach for identification of vertebrate susceptibility to SARS-CoV-2: implications for future surveillance programmes
Rahul Kaushik, Naveen Kumar, Kam Y. J. Zhang, Pratiksha Srivastava, Sandeep Bhatia, Yashpal Singh Malik
bioRxiv 2022.01.10.475752; doi: https://doi.org/10.1101/2022.01.10.475752

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (3502)
  • Biochemistry (7343)
  • Bioengineering (5319)
  • Bioinformatics (20258)
  • Biophysics (10008)
  • Cancer Biology (7735)
  • Cell Biology (11293)
  • Clinical Trials (138)
  • Developmental Biology (6434)
  • Ecology (9947)
  • Epidemiology (2065)
  • Evolutionary Biology (13315)
  • Genetics (9359)
  • Genomics (12579)
  • Immunology (7696)
  • Microbiology (19008)
  • Molecular Biology (7437)
  • Neuroscience (41011)
  • Paleontology (300)
  • Pathology (1228)
  • Pharmacology and Toxicology (2134)
  • Physiology (3155)
  • Plant Biology (6858)
  • Scientific Communication and Education (1272)
  • Synthetic Biology (1895)
  • Systems Biology (5311)
  • Zoology (1087)