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

A collection of designed peptides to target SARS-Cov-2 – ACE2 interaction: PepI-Covid19 database

Ruben Molina, Baldo Oliva, View ORCID ProfileNarcis Fernandez-Fuentes
doi: https://doi.org/10.1101/2020.04.28.051789
Ruben Molina
1Structural Bioinformatics Lab, Department of Experimental and Health Science, Universitat Pompeu Fabra, Barcelona 08003, Catalonia, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Baldo Oliva
1Structural Bioinformatics Lab, Department of Experimental and Health Science, Universitat Pompeu Fabra, Barcelona 08003, Catalonia, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: naf4@aber.ac.uk
Narcis Fernandez-Fuentes
2Department of Biosciences, U Science Tech, Universitat de Vic-Universitat Central de Catalunya, Vic 08500, Catalonia, Spain
3Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth SY23 3EB, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Narcis Fernandez-Fuentes
  • For correspondence: naf4@aber.ac.uk
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Data/Code
  • Preview PDF
Loading

Abstract

The angiotensin-converting enzyme 2 is the cellular receptor used by SARS coronavirus SARS-CoV and SARS-CoV-2 to enter the cell. Both coronavirus use the receptor-binding domain (RBD) of their viral spike protein to interact with ACE2. The structural basis of these interactions are already known, forming a dimer of ACE2 with a trimer of the spike protein, opening the door to target them to prevent the infection. Here we present PepI-Cov19 database, a repository of peptides designed to target the interaction between the RDB of SARS-CoV-2 and ACE2 as well as the dimerization of ACE2 monomers. The peptides were modelled using our method PiPreD that uses native elements of the interaction between the targeted protein and cognate partner that are subsequently included in the designed peptides. These peptides recapitulate stretches of residues present in the native interface plus novel and highly diverse conformations that preserve the key interactions on the interface. PepI-Covid19 database provides an easy and convenient access to this wealth of information to the scientific community with the view of maximizing its potential impact in the development of novel therapeutic agents.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • http://aleph.upf.edu/pepicovid19

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted April 29, 2020.
Download PDF
Data/Code
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 collection of designed peptides to target SARS-Cov-2 – ACE2 interaction: PepI-Covid19 database
(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 collection of designed peptides to target SARS-Cov-2 – ACE2 interaction: PepI-Covid19 database
Ruben Molina, Baldo Oliva, Narcis Fernandez-Fuentes
bioRxiv 2020.04.28.051789; doi: https://doi.org/10.1101/2020.04.28.051789
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
A collection of designed peptides to target SARS-Cov-2 – ACE2 interaction: PepI-Covid19 database
Ruben Molina, Baldo Oliva, Narcis Fernandez-Fuentes
bioRxiv 2020.04.28.051789; doi: https://doi.org/10.1101/2020.04.28.051789

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 (3579)
  • Biochemistry (7526)
  • Bioengineering (5486)
  • Bioinformatics (20703)
  • Biophysics (10261)
  • Cancer Biology (7939)
  • Cell Biology (11585)
  • Clinical Trials (138)
  • Developmental Biology (6574)
  • Ecology (10145)
  • Epidemiology (2065)
  • Evolutionary Biology (13556)
  • Genetics (9502)
  • Genomics (12796)
  • Immunology (7888)
  • Microbiology (19460)
  • Molecular Biology (7618)
  • Neuroscience (41917)
  • Paleontology (307)
  • Pathology (1253)
  • Pharmacology and Toxicology (2182)
  • Physiology (3253)
  • Plant Biology (7011)
  • Scientific Communication and Education (1291)
  • Synthetic Biology (1942)
  • Systems Biology (5410)
  • Zoology (1108)