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Colchicine effect on P-glycoprotein expression and activity: in silico and in vitro studies
Renata Silva1, Helena Carmo1, Vânia Vilas-Boas1
1REQUIMTE, Laboratório de Toxicologia, Departamento de Ciências Biológicas, Faculdade de Farmácia, Universidade do Porto, Rua de Jorge Viterbo Ferreira 228, 4050-313 Porto, Portugal.
Abstract:
Colchicine is a P-glycoprotein (P-gp) substrate that induces its expression, thus increasing the risk for unexpected pharmacokinetic interactions with this drug. Because increased P-gp expression does not always correlate with increased activity of this efflux pump, we evaluated the changes in both P-gp expression and activity induced by colchicine using an in vitro model. Caco-2 cells were incubated with 0.1-100 μM colchicine up to 96 h. Cytotoxicity was evaluated by the MTT and LDH leakage assays, P-gp expression and activity were evaluated by flow cytometry and P-gp ATPase activity was measured in MDR1-Sf9 membrane vesicles. Furthermore, colchicine fitting in P-gp induction and competitive inhibition pharmacophore hypothesis, and docking studies evaluating the interaction between colchicine and P-gp drug binding pocket were tested in silico. Significant cytotoxicity was noted after 48 h. At 24 h a significant increase in P-gp expression was observed, which was not accompanied by an increase in transport activity. Moreover, colchicine significantly increased P-gp ATPase activity, demonstrating to be actively transported by the pump. New pharmacophores were constructed to predict P-gp modulatory activity. Colchicine fitted both the P-gp induction and competitive inhibition models. In silico, colchicine was predicted to bind to the P-gp drug-binding pocket suggesting a competitive mechanism of transport. These results show that colchicine induced P-gp expression in Caco-2 cells but the activity of the protein remained unchanged, highlighting the need to simultaneously evaluate P-gp expression and activity. With the newly constructed pharmacophores, new drugs can be initially screened in silico to predict such potential pharmacokinetic interactions.
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