Retrospective validation studies carried out on three benchmark databases containing a small fraction (that is 2.80%) of known tubulin binders permitted us to develop a computational platform very effective in selecting easier manageable subsets showing by far higher percentages of actives (about 25%). These studies relied on the hierarchical application of multilayer in silico screenings employing filters implying molecular shape similarity; a structure-based pharmacophore model and molecular docking campaigns. Building on this validated approach, we performed intensive prospective studies to screen a large chemical collection, including up to 3.7 millions of commercial compounds, to across an unexplored and patent space in the search of novel colchicine binding site inhibitors. Our investigation was successful in identifying a pool of 31 initial hits showing new molecular scaffolds (such as 4,5-dihydro-1H-pyrrolo[3,4-c]pyrazol-6-one and pyrazolo[1,5-a]pyrimidine). This panel of new hits resulted antiproliferative activity in the low μM range towards MCF-7 human breast cancer, HepG2 human liver cancer, HeLa human ovarian cancer and SHSY5Y human glioblastoma cell lines as well as interesting concentration-dependent inhibition of tubulin polymerization assessed through fluorescence polymerization assays. Unlike typical tubulin inhibitors, a satisfactorily low sensitivity towards P-gp was also measured in bi-directional transport studies across MDCKII-MDR1 cells for a selected subset of seven compounds.
Keywords: Docking; P-gp; Tubulin; Virtual screening.
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