An in silico approach for screening flavonoids as P-glycoprotein inhibitors based on a Bayesian-regularized neural network

@article{Wang2005AnIS,
  title={An in silico approach for screening flavonoids as P-glycoprotein inhibitors based on a Bayesian-regularized neural network},
  author={Yong-Hua Wang and Yan Li and Sheng-Li Yang and Ling Yang},
  journal={Journal of computer-aided molecular design},
  year={2005},
  volume={19 3},
  pages={137-47}
}
P-glycoprotein (P-gp), an ATP-binding cassette (ABC) transporter, functions as a biological barrier by extruding cytotoxic agents out of cells, resulting in an obstacle in chemotherapeutic treatment of cancer. In order to aid in the development of potential P-gp inhibitors, we constructed a quantitative structure-activity relationship (QSAR) model of flavonoids as P-gp inhibitors based on Bayesian-regularized neural network (BRNN). A dataset of 57 flavonoids collected from a literature binding… CONTINUE READING