Evidence map›Paper›PMID 35460633›Full record

ArticleEnvironmental research2022

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

Open access · greenAbstract read
In one paragraph

Article in Environmental research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Artificial intelligence directed computational protein design: lessons from COVID-19 for pandemic-ready vaccines and antibody therapeutics.Journal of pharmacy & pharmaceutical sciences : a publication of the Canadian Society for Pharmaceutical Sciences, Societe canadienne des sciences pharmaceutiques · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 2 countries.

Rahul KaushikLaboratory for Structural Bioinformatics, Center for Biosystems Dynamics Research, RIKEN, 1-7-22 Suehiro, Yokohama, Kanagawa, 230-0045, Japan.
Naveen KumarZoonotic Diseases Group, ICAR- National Institute of High Security Animal Diseases, Bhopal, 462022, India.
Kam Y J ZhangLaboratory for Structural Bioinformatics, Center for Biosystems Dynamics Research, RIKEN, 1-7-22 Suehiro, Yokohama, Kanagawa, 230-0045, Japan.
Pratiksha SrivastavaZoonotic Diseases Group, ICAR- National Institute of High Security Animal Diseases, Bhopal, 462022, India.
Sandeep BhatiaZoonotic Diseases Group, ICAR- National Institute of High Security Animal Diseases, Bhopal, 462022, India.
Yashpal Singh MalikCollege of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Science University (GADVASU), Ludhiana, 141004, Punjab, India. Electronic address: malikyps@gmail.com.
National Institute of High Security Animal Diseases · INRIKEN Center for Biosystems Dynamics Research · JPGuru Angad Dev Veterinary and Animal Sciences University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the origin of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a highly debatable and unresolved issue for scientific communities all over the world. Understanding the mechanism of virus entry to the host cells is crucial to deciphering the susceptibility profiles of animal species to SARS-CoV-2. The interaction of SARS-CoV-2 ligands (receptor-binding domain 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 SARS-CoV-2 spike protein can bind to a wide range of 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. Furthermore, the current study facilitated the identification of genetic determinants that may differentiate susceptible from 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 bat species' susceptibility to SARS-CoV-2. The current study's findings highlight the importance of intensive surveillance programmes aimed at identifying susceptible hosts, especially those with the potential to transmit zoonotic pathogens, in order to prevent future outbreaks.

Indexed as

COVID-19Spike Glycoprotein, CoronavirusAngiotensin-Converting Enzyme 2AnimalsHumansPeptidyl-Dipeptidase ASARS-CoV-2VertebratesAngiotensin-Converting Enzyme 2Peptidyl-Dipeptidase ASpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2ACE2Binding affinityDissociation constantHost rangeSARS-CoV-2Spike proteinVertebrate species

Identifiers

PMID35460633
PMCPMC9020514
OpenAlexW4225606090

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.