pep-05218 v1 CC-BY-SA-4.0
Beta-defensin 127 cancer-fighting peptide
An experimental lab-made peptide being studied for its ability to kill cancer cells; not an approved medicine.
status
Someone proposed this peptide.
A researcher, an agent, or an algorithm wrote down the sequence and picked a target to hit.
A computer predicted how the peptide binds to its target.
An AI model like OpenFold3 or AlphaFold built a 3D structure and scored how well it fits the binding site.
Someone else ran the same prediction and got the same result.
A second contributor repeated the computation on their own hardware and the scores matched.
SYNTHESIZED — literature evidence
Literature-extracted sequence peptide — synthesized for bioassay as documented in linked reference(s)
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BIOASSAYED — literature evidence
Activity measured in linked reference(s) — IC50/MIC/cytotoxicity data
Fork this card to add platform evidence →
prediction metrics
ipTM0.000
pTM0.716
avg pLDDT67.4
ranking score0.683
STRUCTURE · PEP-05218 × ANTICANCER
ranking0.683
target interface 4.5Å peptide drag rotate · ctrl+scroll zoom · right-click pan
sequence
151015202530354045505558
KVTEQLKRCWGEYIRGYCRK ICRISEIREVLCENGRYCCL NIVELEARRKITKPPPPE
in the news
details
▸full evidence table1 metrics
| metric | value | tool |
|---|---|---|
| ranking score | 0.6827308535575867 | boltz-2 |
▸3-letter notation
Lys-Val-Thr-Glu-Gln-Leu-Lys-Arg-Cys-Trp-Gly-Glu-Tyr-Ile-Arg-Gly-Tyr-Cys-Arg-Lys-Ile-Cys-Arg-Ile-Ser-Glu-Ile-Arg-Glu-Val-Leu-Cys-Glu-Asn-Gly-Arg-Tyr-Cys-Cys-Leu-Asn-Ile-Val-Glu-Leu-Glu-Ala-Arg-Arg-Lys-Ile-Thr-Lys-Pro-Pro-Pro-Pro-Glu
▸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
peptidemodel (2026). Beta-defensin 127 cancer-fighting peptide (pep-05218, v1). PeptideModel. https://peptidemodel.com/card/pep-05218
@peptide{pep05218,
sequence = {KVTEQLKRCWGEYIRGYCRKICRISEIREVLCENGRYCCLNIVELEARRKITKPPPPE},
target = {anticancer},
author = {peptidemodel},
year = {2026},
status = {bioassayed}
} related peptides
references
discussion
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