Brevinin-2GHb antimicrobial peptide
A short protein fragment that kills or slows the growth of bacteria and other microbes; used only as a lab research tool.
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.
Could trimming the inactive part of a natural peptide turn it into a useful weapon against one of the world's most dangerous drug-resistant bacteria?
Acinetobacter baumannii is on the WHO's most-critical list of superbugs, and doctors are running out of options. If this hypothesis holds, a stripped-down version of a frog-derived peptide could become a compact, synthesizable drug candidate that targets this pathogen, giving researchers a new starting point for antibiotic development.
Could the seemingly useless front half of this peptide actually be a built-in safety lock that keeps it dormant until the right environment unlocks it?
Many promising antimicrobial peptides cause side effects by attacking healthy tissue indiscriminately. If this peptide turns out to be activated only by proteases present at an infection site, it could mean a new class of antibiotic that stays inactive in the bloodstream and fires only where bacteria are actually present, which would be a meaningful step toward safer, more targeted treatments.
Does the acidic front section of this peptide electrostatically block its own business end from grabbing onto bacterial membranes, explaining why it performs far worse than close relatives?
Understanding exactly why a peptide underperforms matters because it tells engineers precisely what to fix. If confirmed, this finding would give drug designers a clear map: the structural anchor at the tip (the Rana box) is doing its job, and the problem is the antagonistic front section, meaning targeted edits to that region could convert a weak candidate into a potent one without starting from scratch.
▸full evidence table1 metrics
| metric | value | tool |
|---|---|---|
| ranking score | 0.5581293702125549 | 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{pep05595,
sequence = {GTISLLCQEDERGADEDDEGEMTEEQKRSLLGLLKGAGKTLLSAGLNKIACKLTGKC},
target = {antimicrobial},
author = {peptidemodel},
year = {2026},
status = {bioassayed}
}