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Microtubules, investigated extensively in past few decades as a potential pharmaceutical target for cancer treatment, because of their important role in the mitotic process. However, agents that target microtubules frequently have limitations on the development of resistance. Microtubules, αβ-tubulin dimers have mainly four different interaction sites, including the colchicine binding site, a potential target for establishing new tubulin inhibitors. Numerous drugs in this domain are less likely to develop multidrug resistance, which limits the effectiveness of several inhibitors. In this study a virtual screening strategy was used with structure-based followed by QSAR model-based screening. First, a docking-based approach used to select high interacting compounds from the natural compound database, thereafter a QSAR model, built using literature data on anticancer activity of heterogeneous compounds used to screen the molecules from zinc natural databases. Following that, Lipinski's rule of five was used to filter the resulting hit compounds. The ADMET and DFT-based analyses were done to refine the retrieved hits and reduce the rate of false positives. Finally, molecular dynamics simulation and MMPBSA were performed to check the stability of selected leads with tubulin.

Identification of anti-cancer natural compounds against colchicine binding site of tubulin: a combined structure and QSAR-based approach