Prediction of Blood-Βrain Partitioning and Human Serum Albumin Binding Based on COSMO-RS σ-Moments

• Published in: Journal of chemical information and modeling Vol. 47; no. 1; pp. 228 - 233
• Main Authors: Wichmann, Karin, Diedenhofen, Michael, Klamt, Andreas
• Format: Journal Article
• Language: English
• Published: American Chemical Society 22.01.2007
• ISSN: 1549-9596; 1549-960X
• DOI: 10.1021/ci600385w

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.