The discovery of potential tubulin inhibitors: A combination of pharmacophore modeling, virtual screening, and molecular docking studies

Abstract

The microtubules play a significant role in the growth and functions of cells, and hence, inhibition of microtubule assembly has emerged as one of the most promising strategies for the treatment of cancer. To clarify the essential structure-activity relationship of tubulin inhibitors as well as identify novel leads, three-dimensional pharmacophore models were established on the basis of known tubulin inhibitors. The model (Hypo1) that had the highest correlation coefficient (0.9330), the largest cost difference (66.911) and the lowest RMSD value (0.70258) was chosen as the best pharmacophore model. Hypo1 was validated using test set, Fischer randomization and leave-one-out methods and a decoy set. Then, the model was used as a 3D structural query to search the Specs database. We subsequently refined the retrieved hit compounds by subjecting them to drug-like filtrations and molecular docking studies. Finally, we selected 10 compounds on the basis of the necessary interactions with the key residues to be experimentally validated in a bioassay. We showed that all compounds had some level of inhibitory effect on MCF-7 breast cancer cell line where the most promising three candidates exhibited an inhibition rate of more than 80% at a concentration of 100μmol/L.