pep-05207 v1 CC-BY-SA-4.0
CarS anticancer peptide
An experimental peptide studied in the lab for its potential to fight cancer cells; not yet an approved drug.
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)
Fork this card to add platform evidence →
BIOASSAYED — literature evidence
Activity measured in linked reference(s) — IC50/MIC/cytotoxicity data
Fork this card to add platform evidence →
prediction metrics
ipTM0.000
pTM0.752
avg pLDDT83.0
ranking score0.814
STRUCTURE · PEP-05207 × ANTICANCER
ranking0.814
target interface 4.5Å peptide drag rotate · ctrl+scroll zoom · right-click pan
sequence
151015202530354045505559
NIYWIADQFGIHLATGTARK LLDAVASGASLGTAFAAILG VTLPAWALAAAGALGATAA
in the news
details
▸full evidence table1 metrics
| metric | value | tool |
|---|---|---|
| ranking score | 0.8143728375434875 | boltz-2 |
▸3-letter notation
Asn-Ile-Tyr-Trp-Ile-Ala-Asp-Gln-Phe-Gly-Ile-His-Leu-Ala-Thr-Gly-Thr-Ala-Arg-Lys-Leu-Leu-Asp-Ala-Val-Ala-Ser-Gly-Ala-Ser-Leu-Gly-Thr-Ala-Phe-Ala-Ala-Ile-Leu-Gly-Val-Thr-Leu-Pro-Ala-Trp-Ala-Leu-Ala-Ala-Ala-Gly-Ala-Leu-Gly-Ala-Thr-Ala-Ala
▸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). CarS anticancer peptide (pep-05207, v1). PeptideModel. https://peptidemodel.com/card/pep-05207
@peptide{pep05207,
sequence = {NIYWIADQFGIHLATGTARKLLDAVASGASLGTAFAAILGVTLPAWALAAAGALGATAA},
target = {anticancer},
author = {peptidemodel},
year = {2026},
status = {bioassayed}
} related peptides
references
discussion
sign in to comment