Stranger uses open-source AI to model ALK resistance and design backup cancer drug for free
anshulkundaje · x · 2026-11-06
Cancer patient @kevinace shared that Jan Domanski, who runs science at OpenFold — an open-source AI model predicting how proteins and drugs fit together — DM'd him offering to help design his backup cancer drug for free.
His cancer is driven by a broken ALK protein; Lorlatinib keeps it in check but resistance mutations are inevitable. Domanski ran AI models on his own compute to map where known escape mutations land relative to the drug pocket.
Key finding: most mutations hit inside the drug's binding pocket, swapping small residues for bulkier ones that physically block the drug — a "pocket problem" that's designable around. Renders show lorlatinib locked in the ALK kinase domain (PDB 4CLI) with 11 resistance sites, seven touching the drug directly; analysis used ESMFold2, OpenBind-0, and Protenix-v2 co-folding predictions.
More from AGI Musings
- Model value as conditional entropy removed: why rising world entropy hurts model companies — xiaosun86 · 2026-11-06
- The most valuable secrets in AI are no-go theorems, not new tricks — fkasummer · 2026-11-06
- GitHub commits hit 275M/week as AI-generated tokens commoditize frontier labs' edge — DimitrisPapail · 2026-11-06
- Argument: AGI's value lies in the long tail, not a few frontier pockets — kevinsurace · 2026-11-06
- Researchers clash over Anthropic report: conclusions rest on subjective staff assessments — danielrock · 2026-11-06
- Reddit essay argues the case against AI consciousness is one-sided and empirically weak — nate1212 · 2026-11-06