Unlocking Antimicrobial Peptides: In Silico Proteolysis and Artificial Intelligence-Driven Discovery from Cnidarian Omics.
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| Format: | Artículo científico |
| Sprache: | en |
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Molecules (Basel, Switzerland)
2025
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| author | Barroso, Ricardo Alexandre Agüero-Chapin, Guillermin Sousa, Rita Marrero-Ponce, Yovani Antunes, Agostinho |
| author_facet | Barroso, Ricardo Alexandre Agüero-Chapin, Guillermin Sousa, Rita Marrero-Ponce, Yovani Antunes, Agostinho Barroso, Ricardo Alexandre Agüero-Chapin, Guillermin Sousa, Rita Marrero-Ponce, Yovani Antunes, Agostinho |
| collection | PubMed - marine biology |
| contents | Unlocking Antimicrobial Peptides: In Silico Proteolysis and Artificial Intelligence-Driven Discovery from Cnidarian Omics. Barroso, Ricardo Alexandre Agüero-Chapin, Guillermin Sousa, Rita Marrero-Ponce, Yovani Antunes, Agostinho Animals Antimicrobial Peptides Proteolysis Artificial Intelligence Cnidaria Computer Simulation Anti-Bacterial Agents Drug Discovery 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. |
| format | Artículo científico |
| id | pubmed_39942653 |
| institution | PubMed |
| language | en |
| publishDate | 2025 |
| publisher | Molecules (Basel, Switzerland) |
| record_format | pubmed |
| spellingShingle | Unlocking Antimicrobial Peptides: In Silico Proteolysis and Artificial Intelligence-Driven Discovery from Cnidarian Omics. Barroso, Ricardo Alexandre Agüero-Chapin, Guillermin Sousa, Rita Marrero-Ponce, Yovani Antunes, Agostinho Animals Antimicrobial Peptides Proteolysis Artificial Intelligence Cnidaria Computer Simulation Anti-Bacterial Agents Drug Discovery Unlocking Antimicrobial Peptides: In Silico Proteolysis and Artificial Intelligence-Driven Discovery from Cnidarian Omics. Barroso, Ricardo Alexandre Agüero-Chapin, Guillermin Sousa, Rita Marrero-Ponce, Yovani Antunes, Agostinho Animals Antimicrobial Peptides Proteolysis Artificial Intelligence Cnidaria Computer Simulation Anti-Bacterial Agents Drug Discovery 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. |
| title | Unlocking Antimicrobial Peptides: In Silico Proteolysis and Artificial Intelligence-Driven Discovery from Cnidarian Omics. |
| topic | Animals Antimicrobial Peptides Proteolysis Artificial Intelligence Cnidaria Computer Simulation Anti-Bacterial Agents Drug Discovery |
| url | https://pubmed.ncbi.nlm.nih.gov/39942653/ |