Anionic antimicrobial peptide 2 anticancer peptide
A lab-studied peptide that may help fight cancer cells; experimental, 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.
If only one end of a long molecule does the actual work, could we just use that end?
If the short tail of this peptide turns out to be all that matters for killing cancer cells, researchers could manufacture it at a fraction of the current cost. That could make it far more practical to develop as a drug candidate.
Most cancer-targeting peptides are positively charged, so how could a negatively charged one still find tumor cells?
Many cancer cells wear a specific fat molecule (phosphatidylserine) on their outer surface that healthy cells keep hidden inside. If this negatively charged peptide latches on to that instead of using charge attraction, it could open a whole new way to target tumors selectively, for people who need treatments that spare healthy tissue.
Can you build a peptide drug that stays switched off in healthy tissue but switches on inside a tumor?
Tumors have a distinct chemical environment, including enzymes and acidity not found in healthy tissue. If a neutralizing cap can be designed to fall off only in that environment, it could allow a potent cancer-killing peptide to travel through the body safely and activate only where it is needed, reducing side effects for patients.
Some molecules only become dangerous to cells after several copies lock together, so could that be what makes this peptide work?
If the peptide needs to cluster before it can punch holes in cancer cell membranes, understanding that step could help researchers design more potent versions that assemble faster, or dial back activity in healthy tissue. It would also explain why a negatively charged peptide can kill cancer cells at all, a puzzle that currently limits confidence in this class of molecules.
▸full evidence table1 metrics
| metric | value | tool |
|---|---|---|
| ranking score | 0.6690128445625305 | 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{pep05202,
sequence = {ETESTPDYLKNIQQQLEEYTKNFNTQVQNAFDSDKIKSEVNNFIESLGKILNTEKKEAPK},
target = {anticancer},
author = {peptidemodel},
year = {2026},
status = {bioassayed}
}