Predicting Blood−Brain Barrier Permeation from Three-Dimensional Molecular Structure

Patrizia Crivori,† Gabriele Cruciani,*‡ Pierre-Alain Carrupt,† and Bernard Testa†
Institute of Medicinal Chemistry, BEP, University of Lausanne, CH-1015 Lausanne-Dorigny, Switzerland, and Laboratory for Chemometrics, University of Perugia, Via Elce di Sotto 10, I-06123 Perugia, Italy
J. Med. Chem., 2000, 43 (11), pp 2204–2216
DOI: 10.1021/jm990968+
Publication Date (Web): May 16, 2000
Copyright © 2000 American Chemical Society
†

 University of Lausanne.

,
*

 Correspondence author. Fax:  +39 075 45646. E-mail:  gabri@chemiome.chm.unipg.it.

,
‡

 University of Perugia.

Abstract

Abstract Image

Predicting blood−brain barrier (BBB) permeation remains a challenge in drug design. Since it is impossible to determine experimentally the BBB partitioning of large numbers of preclinical candidates, alternative evaluation methods based on computerized models are desirable. The present study was conducted to demonstrate the value of descriptors derived from 3D molecular fields in estimating the BBB permeation of a large set of compounds and to produce a simple mathematical model suitable for external prediction. The method used (VolSurf) transforms 3D fields into descriptors and correlates them to the experimental permeation by a discriminant partial least squares procedure. The model obtained here correctly predicts more than 90% of the BBB permeation data. By quantifying the favorable and unfavorable contributions of physicochemical and structural properties, it also offers valuable insights for drug design, pharmacological profiling, and screening. The computational procedure is fully automated and quite fast. The method thus appears as a valuable new tool in virtual screening where selection or prioritization of candidates is required from large collections of compounds.

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History

  • Published In Issue June 01, 2000
  • Received December 15, 1999

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