SPAG11B experimental anticancer peptide
A lab-made peptide being studied for its potential to fight cancer cells; experimental, not 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)
Fork this card to add platform evidence →
Activity measured in linked reference(s) — IC50/MIC/cytotoxicity data
Fork this card to add platform evidence →
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 the same molecule that attacks tumor cells also kill harmful bacteria, at doses lower than the ones used against cancer?
If this holds, a single peptide could help oncology patients on two fronts: fighting their cancer and protecting them from bacterial infections at the same time. That would be especially valuable for cancers already linked to bacteria, like certain stomach cancers tied to H. pylori.
If the two ends of this molecule each do their own job independently, could we keep just one end and still keep the benefits?
Long peptides are expensive and difficult to manufacture. If the cancer-killing activity lives mostly in one end of this molecule, chemists could potentially build a shorter version that is cheaper to produce and still just as effective, making it more practical to develop as a therapy.
Does this molecule destroy cancer cells by physically disrupting their outer membrane, the way soap dissolves grease?
If the killing comes from physically disrupting the membrane rather than binding one specific protein, then what matters most is how well it tells cancer cells apart from healthy ones. It would also change how researchers improve it: the focus would shift to fine-tuning its electrical charge and shape rather than hunting for a molecular target.
▸full evidence table1 metrics
| metric | value | tool |
|---|---|---|
| ranking score | 0.5337924361228943 | 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{pep05263,
sequence = {DLLPPRTPPYQEPASDLKVVDFRRSEGFCQEYCNYMETQVGYCPKKKDACCLH},
target = {anticancer},
author = {peptidemodel},
year = {2026},
status = {bioassayed}
}