Use of shape similarities for the classification of P-glycoprotein substrates and nonsubstrates.

Background: The multidrug transporter P-glycoprotein (P-gp) ATP-binding cassette B1 (ABCB1) is one of the key proteins influencing bioavailability and uptake of drugs in the brain. In addition, it is one of the main factors contributing to multidrug resistance in tumor therapy. Due to its promiscuous substrate recognition, prediction of substrate properties for the multidrug transporter P-gp represents a challenging task.

In silico prediction of substrate properties for ABC-multidrug transporters.

Overexpression of ABC (ATP-binding cassette)-type drug efflux pumps, such as ABCB1, ABCC1 and ABCG2 in cancer cells confers multi-drug resistance (MDR) and represents a major cause of treatment failures in cancer therapy. Furthermore, there is increasing evidence for the important contribution of ABC-transporters to bioavailability, distribution, elimination and blood-brain barrier permeation of drug candidates. This review presents an overview on the different computational methods and models pursued to predict ABC-transporter substrate properties of drug-like compounds.