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High-Throughput Screening of Drug−Brain Tissue Binding and in Silico Prediction for Assessment of Central Nervous System Drug Delivery

Hong Wan,*^† Mikael Rehngren,^‡ Fabrizio Giordanetto,^§ Fredrik Bergström,^† and Anders Tunek^‡

Lead Generation DMPK & Physical Chemistry, Lead Generation Computational Chemistry, Discovery DMPK and Bioanalytical Chemistry, AstraZeneca R&D, Mlndal, SE-431 88, Mlndal, Sweden

J. Med. Chem., 2007, 50 (19), pp 4606–4615

DOI: 10.1021/jm070375w

Publication Date (Web): August 29, 2007

To whom correspondence should be addressed. Phone: +46 31 776 4801. Fax: +46 31 776 3748. E-mail: hong.wan@astrazeneca.com.

†

Lead Generation DMPK & Physical Chemistry.

‡

Discovery DMPK and Bioanalytical Chemistry.

Lead Generation Computational Chemistry.

Abstract

A high-throughput method for rapid screening of in vitro drug−brain homogenate binding is presented. The method is based on a straightforward sample pooling approach combining equilibrium dialysis with liquid chromatography mass spectrometry (LCMS). A strong correlation of fraction unbound in brain (f_u) between single compound measurements and 25-pooled compounds (R² = 0.906) was obtained for a selection of structurally diverse CNS compounds with a wide range of fractions unbound. Effects of brain homogenate dilution and dialysis time were investigated. To the best of our knowledge, it was the first time that we have demonstrated consistent fraction unbound in mouse and rat brain homogenate, revealing the drug−tissue partitioning mechanism predominated by hydrophobic interaction. On the basis of this finding, a generic approach to estimate drug binding to various tissues is proposed. A robust and interpretable QSAR for f_u prediction is also presented by statistical modeling.

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