Combined in silico and in vitro approaches to identify P‐glycoprotein‐inhibiting pesticides

Abstract

AbstractThe P‐glycoprotein (P‐gp) efflux pump plays a major role in xenobiotic detoxification. The inhibition of its activity by environmental contaminants remains however rather little characterised. The present study was designed to develop a combination of different approaches to identify P‐gp inhibitors among a large number of pesticides using in silico and in vitro models. First, the prediction performance of four web tools was evaluated alone or in combination using a set of recently marketed drugs. The best combination of web tools—AdmetSAR2.0/PgpRules/pkCSM—was next used to predict P‐gp activity inhibition by 762 pesticides. Among the 187 pesticides predicted to be P‐gp inhibitors, 11 were tested in vitro for their ability to inhibit the efflux of reference substrates (rhodamine 123 and Hoechst 33342) in P‐gp overexpressing MCF7R cells and to inhibit the efflux of the reference substrate rhodamine 123 in the Caco‐2 cell monolayer. In MCF7R cell assays, ivermectin B1a, emamectin B1 benzoate, spinosad, dimethomorph and tralkoxydim inhibited P‐gp activity; ivermectin B1a, emamectin B1 benzoate and spinosad were determined to be stronger inhibitors (half‐maximal inhibitory concentration [IC50] of 3 ± 1, 5 ± 1 and 7 ± 1 µM, respectively) than dimethomorph and tralkoxydim (IC50 of 102 ± 7 and 88 ± 7 µM, respectively). Ivermectin B1a, emamectin B1 benzoate, spinosad and dimethomorph also inhibited P‐gp activity in Caco‐2 cell monolayer assays, with dimethomorph being a weaker P‐gp inhibitor. These combined approaches could be used to identify P‐gp inhibitors among food contaminants, but need to be optimised and adapted for high‐throughput screening.