Prediction of Blood-Βrain Partitioning and Human Serum Albumin Binding Based on COSMO-RS σ-Moments
Models for the prediction of blood-brain partitioning (logBB) and human serum albumin binding (logK(HSA)) of neutral molecules were developed using the set of 5 COSMO-RS σ-moments as descriptors. These σ-moments have already been introduced earlier as a general descriptor set for partition coefficie...
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Published in | Journal of chemical information and modeling Vol. 47; no. 1; pp. 228 - 233 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
American Chemical Society
22.01.2007
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Online Access | Get full text |
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Summary: | Models for the prediction of blood-brain partitioning (logBB) and human serum albumin binding (logK(HSA)) of neutral molecules were developed using the set of 5 COSMO-RS σ-moments as descriptors. These σ-moments have already been introduced earlier as a general descriptor set for partition coefficients. They are obtained from quantum chemical calculations using the continuum solvation model COSMO and a subsequent statistical decomposition of the resulting polarization charge densities. The model for blood-brain partitioning was built on a data set of 103 compounds and yielded a correlation coefficient of r 2 = 0.71 and an rms error of 0.40 log units. The human serum albumin binding model was built on a data set of 92 compounds and achieved an r 2 of 0.67 and an rms error of 0.33 log units. Both models were validated by leave-one-out cross-validation tests, which resulted in q 2 = 0.68 and a qms error of 0.42 for the logBB model and in q 2 = 0.63 and a qms error of 0.35 for the logK(HSA) model. Together with the previously published models for intestinal absorption and for drug solubility the presented two models complete the COSMO-RS based set of ADME prediction models. |
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Bibliography: | ark:/67375/TPS-LVZHWCB7-9 istex:C84CC3BC338FF33DB8F279C96C33CFECE5DD6955 |
ISSN: | 1549-9596 1549-960X |
DOI: | 10.1021/ci600385w |