Esculentin-1SIa antiviral peptide
A short protein fragment that fights viruses; studied as a potential antiviral treatment but not yet an approved drug.
A researcher, an agent, or an algorithm wrote down the sequence and picked a target to hit.
An AI model like OpenFold3 or AlphaFold built a 3D structure and scored how well it fits the binding site.
A second contributor repeated the computation on their own hardware and the scores matched.
Literature-extracted sequence peptide — synthesized for bioassay as documented in linked reference(s)
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Activity measured in linked reference(s) — IC50/MIC/cytotoxicity data
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Research directions for this peptide, selected from the current sources — hypotheses you can explore and model. None of it is proven yet; tap any one to see the full thinking.
Does this peptide destroy viruses by shredding their fatty outer shell, rather than blocking them from latching onto your cells?
If it works by ripping open the virus membrane itself, it could potentially fight a wide range of enveloped viruses (flu, herpes, HIV) regardless of which strain they are. The catch: that same tearing ability might also irritate human cells, so researchers would need to tune it carefully before it could be used as a treatment.
Could a frog-skin peptide discovered for antiviral activity also work against the stubborn bacterial films that cause chronic wounds and lung infections?
Biofilms, the slimy shields bacteria hide inside, make infections like infected surgical implants or cystic fibrosis lung disease very hard to treat. If this peptide disrupts those shields, it could open up a new use in an area where patients currently have very few options.
If you swap out the unremarkable first stretch of this peptide for a tiny fat molecule that anchors it to virus membranes, could it become far more potent?
A peptide that lingers near the virus surface instead of drifting away could need far less drug to do the same job. If this modification works as hypothesized, it would give researchers a practical starting point for a stronger, more efficient antiviral without having to design a brand new molecule from scratch.
Could a peptide that attacks the flu virus in a completely different way than current drugs stay effective even as the virus mutates?
Flu viruses develop resistance to drugs like Tamiflu by changing the exact proteins those drugs target. A peptide that attacks the virus membrane rather than those proteins would not be fooled by those mutations. If this holds up, it could matter a great deal during outbreaks where existing drugs are losing effectiveness.
Could spreading positive charges evenly along a peptide make it attack virus membranes while leaving your own cells mostly unharmed?
One of the biggest problems with membrane-attacking peptides is that they can hurt human red blood cells too. If the spacing of positive charges along this peptide naturally spares human cell membranes while still targeting the negatively charged surface of enveloped viruses, it would suggest a design rule that could make a whole class of antiviral peptides safer.
Could the unusual number of flexibility points in this peptide be a feature rather than a flaw, letting it wrap around the tiny, tightly curved surface of a virus?
Most antiviral peptide engineering tries to make peptides more rigid and rod-like. But if the flexible hinges in this peptide are what allows it to grip a spherical virus particle, then the standard engineering playbook would actually make it worse. If confirmed, this would be a useful counter-intuitive rule for designing better antivirals from similar peptides.
▸full evidence table1 metrics
| metric | value | tool |
|---|---|---|
| ranking score | 0.6569241881370544 | boltz-2 |
▸3-letter notation
▸recipeboltz-2 2.2.1
| parameter | value |
|---|---|
| model | boltz-2 2.2.1 |
| weights | — |
| hardware | vast_v100_32gb |
| mlx version | — |
| python | — |
| random seed | 1 |
| msa strategy | none_monomer |
| runtime | — |
| predicted by | — |
| predicted at | 2026-05-23 |
▸citationbibtex
@peptide{pep05421,
sequence = {GIFSKFAGKGIKNLLVKGVKNIGKEVGMDVIRTGIDIAGCKIKGEC},
target = {antimicrobial},
author = {peptidemodel},
year = {2026},
status = {bioassayed}
}