ADMET evaluation in drug discovery. 20. Prediction of breast cancer resistance protein inhibition through machine learning.

ABSTRACT: Breast cancer resistance protein (BCRP/ABCG2), an ATP-binding cassette (ABC) efflux transporter, plays a critical role in multi-drug resistance (MDR) to anti-cancer drugs and drug-drug interactions. The prediction of BCRP inhibition can facilitate evaluating potential drug resistance and drug-drug interactions in early stage of drug discovery. Here we reported a structurally diverse dataset consisting of 1098 BCRP inhibitors and 1701 non-inhibitors. Analysis of various physicochemical properties illustrates that BCRP inhibitors are more hydrophobic and aromatic than non-inhibitors. We then developed a series of quantitative structure-activity relationship (QSAR) models to discriminate between BCRP inhibitors and non-inhibitors. The optimal feature subset was determined by a wrapper feature

SUBMITTER: Jiang D 

PROVIDER: S-EPMC7059329 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature