title: P-gp inhibition potential in cell-based models: which "calculation" method is the most accurate?
abstract: The objective was to directly compare the four different "calculation" methods of assessing P-gp inhibition potential using experimental data obtained from approximately 60 structurally diverse internal research and marketed compounds. Bidirectional studies for digoxin (probe for P-gp substrate) were performed with and without test compounds (at 10 microM). Four different calculation methods were applied to the same dataset (raw bidirectional permeability values) to obtain the "percent inhibition of P-gp" for these compounds using the different methods. Significantly different inhibition potential was obtained with the "exact" same experimental dataset depending on the calculation method used. Subsequently, entirely different conclusions regarding the "inhibition potential" of test compound was reached due to the different calculation methods. Based on the direct comparison of these methods, method no. 3 (i.e., inhibition of B to A permeability of digoxin) is recommended as the calculation method ideal during screening stages due to its high throughput amenability. The methodology is capable of rapidly screening compounds with adequate reliability for early stage drug discovery. Method no. 3 provides an abridged version of a bidirectional study that is fully capable of identifying all non-inhibitors (0-20%), moderate inhibitors (20-60%), and potent inhibitors (>60%) and demonstrates high correlation with method no. 1 (inhibition based on both A to B and B to A permeability of digoxin). Nevertheless, method no. 1 might be appropriate for more detailed mechanistic studies required in late stage discovery and development.
authors.affiliation: Metabolism and Pharmacokinetics, Bristol-Myers Squibb, P.O. Box # 4000, Mailstop: F.13-07, Route 206 & Province Line Road, Princeton, New Jersey 08543, USA. Praveen.balimane@bms.com
authors.forename: Praveen V
authors.initials: PV
authors.lastname: Balimane
authors.forename: Anthony
authors.initials: A
authors.lastname: Marino
authors.forename: Saeho
authors.initials: S
authors.lastname: Chong
mesh_terms: D020168:ATP Binding Cassette Transporter, Subfamily B, Member 1 / Q000037:antagonists & inhibitors*; D001692:Biological Transport / Q000187:drug effects; D018938:Caco-2 Cells / Q000187:drug effects / Q000378:metabolism*; D045744:Cell Line, Tumor; D002463:Cell Membrane Permeability / Q000187:drug effects / Q000502:physiology; D004077:Digoxin / Q000493:pharmacokinetics / Q000494:pharmacology; D004353:Drug Evaluation, Preclinical / Q000379:methods; D017320:HIV Protease Inhibitors / Q000494:pharmacology; D006801:Humans; D019469:Indinavir / Q000494:pharmacology; D007700:Kinetics; D011422:Propionates / Q000494:pharmacology; D011804:Quinolines / Q000494:pharmacology; D019258:Saquinavir / Q000494:pharmacology; D014700:Verapamil / Q000494:pharmacology
chemical_list: D020168:ATP Binding Cassette Transporter, Subfamily B, Member 1; D017320:HIV Protease Inhibitors; D011422:Propionates; D011804:Quinolines; C059141:verlukast; D019469:Indinavir; D004077:Digoxin; D014700:Verapamil; D019258:Saquinavir