P-glycoprotein substrates

Combinatorial QSAR modeling of P-glycoprotein substrates. J. Chem. Inf. Model. 2006, 46, 1245-1254. 

J. E., Wring, S. A., Serabjit-Singh, C. S. Predicting P-glycoprotein substrates... 

Seelig, A., Landwojtowicz, E., Structure-activity relationship of P-glycoprotein substrates and modifiers, Eur. J. Pharm. Sci. 2000, 12, 31—40. 

Hitzl M, Drescher S, van der KH, SCHAFFELER E, FlSCHER J, SCHWAB M et al. The C3435T mutation in the human MDR1 gene is associated with altered efflux of the P-glycoprotein substrate rho-damine 123 from CD56+ natural killer cells. Pharmacogenetics 2001 11 (4) 293— 298. 

In a study of p-glycoprotein substrates vs. non-substrates, Varma et al. [48] concluded that substrate molecules with high passive permeability overwhelmed the transporter while substrate molecules with moderate passive permeability were more affected by p-glycoprotein. Approximately half of 63 p-glycoprotein substrates studied had MW >400 and PSA > 75 indicating that larger, more polar molecules are more likely to be p-glycoprotein substrates. 

Cabrera et al. [50] modeled a set of 163 drugs using TOPS-MODE descriptors with a linear discriminant model to predict p-glycoprotein efflux. Model accuracy was 81% for the training set and 77.5% for a validation set of 40 molecules. A "combinatorial QSAR" approach was used by de Lima et al. [51] to test multiple model types (kNN, decision tree, binary QSAR, SVM) with multiple descriptor sets from various software packages (MolconnZ, Atom Pair, VoSurf, MOE) for the prediction of p-glycoprotein substrates for a dataset of 192 molecules. Best overall performance on a test set of 51 molecules was achieved with an SVM and AP or VolSurf descriptors (81% accuracy each). 

Drescher, S., Schaeffeler, E., Hitzl, M., Hofmann, U., Schwab, M., Brinkmann, U., Eichelbaum, M. and Fromm, M.F. (2002) MDR1 gene polymorphisms and disposition of the P-glycoprotein substrate fexofenadine. British Journal of Clinical Pharmacology, 53, 526-534. 

Tiberghien, F. and Loor, F. (1996) Ranking of P-glycoprotein substrates and inhibitors by a calcein-AM fluorometry screening assay. Anti-Cancer Drugs, 7, 568-578. 

Gombar, V.K., Polli, J.W., Humphreys, J.E., Wring, S.A. and Serabjit-Singh, C. S. (2004) Predicting P-glycoprotein substrates by a quantitative structure-activity relationship model, fournal... 

M., Wildgoose, M., Giesing, D., Fravolini, A., Cruciani, G. and Vaz, R.J. (2005) A pharmacophore hypothesis for P-glycoprotein substrate recognition using GRIND-based 3D-QSAR. Journal of Medicinal Chemistry, 48, 2927-2935. 

Crivori, P., Reinach, B., Pezzetta, D. and Poggesi, I. (2006) Computational models for identifying potential P-glycoprotein substrates and inhibitors. Molecular Pharmaceutics, 3, 33 -4. 

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