Repository logo
  • English
  • Deutsch
  • Español
  • Français
  • Log In
    New user? Click here to register.Have you forgotten your password?
Universidad Panamericana
  • Communities & Collections
  • Research Outputs
  • Fundings & Projects
  • Researchers
  • Statistics
  • Feedback
  • English
  • Deutsch
  • Español
  • Français
  1. Home
  2. CRIS
  3. Publications
  4. Unlocking Antimicrobial Peptides: In Silico Proteolysis and Artificial Intelligence-Driven Discovery from Cnidarian Omics
 
  • Details
Options

Unlocking Antimicrobial Peptides: In Silico Proteolysis and Artificial Intelligence-Driven Discovery from Cnidarian Omics

Journal
Molecules
ISSN
1420-3049
Publisher
MDPI
Date Issued
2025
Author(s)
Barroso, Ricardo Alexandre
Agüero-Chapin, Guillermin
Sousa, Rita
Marrero Ponce, Yovani  
Facultad de Ingeniería - CampCM  
Antunes, Agostinho
Type
Resource Types::text::journal::journal article
DOI
10.3390/molecules30030550
URL
https://scripta.up.edu.mx/handle/20.500.12552/11912
Abstract
Overcoming the growing challenge of antimicrobial resistance (AMR), which affects millions of people worldwide, has driven attention for the exploration of marine-derived antimicrobial peptides (AMPs) for innovative solutions. Cnidarians, such as corals, sea anemones, and jellyfish, are a promising valuable resource of these bioactive peptides due to their robust innate immune systems yet are still poorly explored. Hence, we employed an in silico proteolysis strategy to search for novel AMPs from omics data of 111 Cnidaria species. Millions of peptides were retrieved and screened using shallow- and deep-learning models, prioritizing AMPs with a reduced toxicity and with a structural distinctiveness from characterized AMPs. After complex network analysis, a final dataset of 3130 Cnidaria singular non-haemolytic and non-toxic AMPs were identified. Such unique AMPs were mined for their putative antibacterial activity, revealing 20 favourable candidates for in vitro testing against important ESKAPEE pathogens, offering potential new avenues for antibiotic development. ©The authors. ©MDPI.
Subjects

Cnidaria

Antimicrobial

Omics

Artificial intelligen...

Complex networks

License
Acceso Abierto
URL License
https://creativecommons.org/licenses/by-nc-sa/4.0/
How to cite
Barroso, R. A., Agüero-Chapin, G., Sousa, R., Marrero-Ponce, Y., & Antunes, A. (2025). Unlocking Antimicrobial Peptides: In Silico Proteolysis and Artificial Intelligence-Driven Discovery from Cnidarian Omics. Molecules, 30(3), 550. https://doi.org/10.3390/molecules30030550

Copyright 2024 Universidad Panamericana
Términos y condiciones | Política de privacidad | Reglamento General

Built with DSpace-CRIS software - Extension maintained and optimized by - Hosting & support SCImago Lab

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback