Tubulin is a validated anticancer target and a core structural protein whose inhibition can block tubulin polymerization, making it important in cancer drug discovery. In the cited machine learning-driven repurposing workflow, autoqsar models were trained on curated tubulin inhibitors and glide docking was used to screen compounds against the colchicine-binding site, with biochemical assays confirming inhibition. The study identified omeprazole and podofilox as stable colchicine-site binders that inhibit tubulin polymerization, while sulfadoxine and trimethoprim were also predicted to bind the same site. Overall, this supports tubulin as a mechanistically defined anticancer target for inhibitor discovery, especially through colchicine-site binding and polymerization blockade. A 2026 Bioorganic & Medicinal Chemistry study (PMID:41689974) highlights how machine learning can accelerate repurposing toward new tubulin inhibitors.
Cancer
- Tubulin was used as the focus of a machine learning-driven drug repurposing workflow to identify new anticancer inhibitors. (PMID:41689974)
- autoqsar models trained on curated tubulin inhibitors supported inhibitor discovery against this target. (PMID:41689974)
- glide docking screened compounds against the tubulin colchicine-binding site, linking computational screening to a defined binding pocket. (PMID:41689974)
- omeprazole and podofilox were identified as stable colchicine-site tubulin binders and confirmed to inhibit tubulin polymerization. (PMID:41689974)
- sulfadoxine and trimethoprim were also identified as stable colchicine-site tubulin binders in the same repurposing study. (PMID:41689974)