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Automated identification of structurally heterogeneous and patentable antiproliferative hits as potential tubulin inhibitors.

Giuseppe Felice MangiatordiDaniela TrisciuzziRosamaria IacobazziNunzio DenoraLeonardo PisaniMarco CattoFrancesco LeonettiDomenico AlbergaNicolotti Orazio
Published in: Chemical biology & drug design (2018)
By employing a recently developed hierarchical computational platform, we identified 37 novel and structurally diverse tubulin targeting compounds. In particular, hierarchical molecular filters, based on molecular shape similarity, structure-based pharmacophore, and molecular docking, were applied on a large chemical collection of commercial compounds to identify unexplored and patentable microtubule-destabilizing candidates. The herein proposed 37 novel hits, showing new molecular scaffolds (such as 1,3,3a,4-tetraaza-1,2,3,4,5,6,7,7a-octahydroindene or dihydropyrrolidin-2-one fused to a chromen-4-one), are provided with antiproliferative activity in the μm range toward MCF-7 (human breast cancer lines). Importantly, there is a likely causative relationship between cytotoxicity and the inhibition of tubulin polymerization at the colchicine binding site, assessed through fluorescence polymerization assays.
Keyphrases
  • molecular docking
  • high throughput
  • single molecule
  • molecular dynamics simulations
  • endothelial cells
  • deep learning
  • molecular dynamics
  • drug delivery
  • breast cancer cells