Lactacin-F LafX anticancer peptide
A peptide studied for its ability to 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.
A chemistry service or a researcher ordered the sequence, it was manufactured, and mass spectrometry confirmed the right molecule was produced.
A binding or activity measurement confirmed that it actually does what the computer predicted — or didn't.
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 a peptide that looks promising against cancer cells actually be useless on its own?
If this holds, researchers testing LafX by itself in cancer screens would get false negatives and miss its real potential. The practical upside: any drug built on LafX would need to deliver two peptides together, which changes how it is formulated and tested from day one.
Is there a specific structural feature that locks two peptides together to form a pore, and could we tune it?
If those two glycine positions really are the contact point, scientists could dial the pairing tighter or looser just by swapping in a slightly bulkier amino acid, giving a precise knob to adjust potency without redesigning the whole molecule.
Can you take the useful half of a two-part peptide, clip it shorter, and chemically staple it so it works on its own?
If it works, this approach could turn a complicated two-ingredient system into a single, well-defined drug, which is far easier and cheaper to manufacture and much simpler to get through regulatory review.
Does this peptide recognize and attack a membrane fat that cancer cells expose unusually, instead of locking onto a protein?
If the target is that lipid signature, it would help predict which cancer types are most vulnerable and explain why healthy cells might be spared. It would also reveal the most likely way tumors could develop resistance, pointing researchers toward what to watch for early.
Could a peptide from a common probiotic bacterium help suppress the gut pathogen responsible for C. difficile infections?
C. difficile causes severe, sometimes life-threatening gut infections that are notoriously hard to treat. If the LafA/LafX pair targets these bacteria, it might open a path to a narrow-spectrum gut therapeutic that works with the microbiome rather than wiping it out, and this use case is better supported by existing evidence than the cancer angle.
▸full evidence table1 metrics
| metric | value | tool |
|---|---|---|
| ranking score | 0.8813088536262512 | 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{pep05335,
sequence = {NKWGNAVIGAATGATRGVSWCRGFGPWGMTACALGGAAIGGYLGYKSN},
target = {anticancer},
author = {peptidemodel},
year = {2026},
status = {computed}
}