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This article is part of the supplement: 3rd German Conference on Chemoinformatics: 21. CIC-Workshop

Poster presentation

The use of quantum chemistry in the prediction of ADME-Tox properties

S Van Damme and P Bultinck

Department of Inorganic and Physical Chemistry, University of Ghent, Krijgslaan 281 S3, B-9000 Gent, Belgium

corresponding author email

from 3rd German Conference on Chemoinformatics
Goslar, Germany. 11-13 November 2007

Chemistry Central Journal 2008, 2(Suppl 1):P16doi:10.1186/1752-153X-2-S1-P16

The electronic version of this abstract is the complete one and can be found online at: http://www.journal.chemistrycentral.com/content/2/S1/P16

Published:

26 March 2008

© 2008 Van Damme and Bultinck

Poster presentation

ADME-Tox properties are very important in pharmaceutical research, determining the fate of many molecules in the drug design sequence. Knowledge of ADME-Tox properties in the earliest stages of drug design is therefore highly desirable. The aim of this investigation is to construct low throughput in silico QSAR models in which ADME-Tox properties of single compounds are predicted with high accuracy based on Quantum Chemical information [1].

The possible role of quantum chemical information in chemoinformatics is discussed, with a closer look to the advantages, disadvantages and capabilities of quantum chemical descriptors in QSAR environments.

The use of quantum chemical information is explained by a worked-out example concerning the distribution of medicinal active molecules through the blood-brain barrier [2].

References

1. Karelson M: Quantum chemical descriptors in QSAR. In Computational Medicinal Chemistry for Drug Discovery. Edited by: Bultinck P, De Winter H, Langenaeker W, Tollenaere JP. Dekker Inc., NY; 2004:641-667.

2. Van Damme S, Langenaeker W, Bultinck P: Prediction of Blood-brain partitioning: a model based on ab initio calculated quantum chemical descriptors.

   Journal of Molecular graphics and modelling 2007, in press.

   in press. doi:10.1016/j.jmgm.2007.11.004.

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