title: De novo prediction of p-glycoprotein-mediated efflux liability for druglike compounds.
abstract: P-glycoprotein (Pgp) is capable of recognizing and transporting a wide range of chemically diverse compounds in vivo. Overcoming Pgp-mediated efflux can represent a significant challenge when penetration into the central nervous system is required or within the context of developing anticancer therapies. While numerous in silico models have been developed to predict Pgp-mediated efflux, these models rely on training sets and are best suited to make interpolations. Therefore, it is desirable to develop ab initio models that can be used to predict efflux liabilities. Herein, we present a de novo method that can be used to predict Pgp-mediated efflux potential for druglike compounds. A model, which correlates the computed solvation free energy differences obtained in water and chloroform with Pgp-mediated efflux (in logarithmic scale), was successful in predicting Pgp efflux ratios for a wide range of chemically diverse compounds with a R(2) and root-mean-square error of 0.65 and 0.29, respectively.
authors.affiliation: Department of Molecular Structure and Department of Medicinal Chemistry, Amgen Inc. , 360 Binney Street, Cambridge, Massachusetts 02142, United States.
authors.forename: Hakan
authors.initials: H
authors.lastname: Gunaydin
authors.affiliation: Department of Molecular Structure and Department of Medicinal Chemistry, Amgen Inc. , 360 Binney Street, Cambridge, Massachusetts 02142, United States.
authors.forename: Matthew M
authors.initials: MM
authors.lastname: Weiss
authors.affiliation: Department of Molecular Structure, Amgen Inc. , One Amgen Center Drive, Thousand Oaks, California 91320, United States.
authors.forename: Yaxiong
authors.initials: Y
authors.lastname: Sun
keywords: P-glycoprotein; efflux ratio; prediction