Virtual combinatorial chemistry and in silico screening: Efficient tools for lead structure discovery?
T. Langer and G. Wolber
Institute of Pharmacy, University of Innsbruck Innrain
52, A-6020 Innsbruck,
Austria; Inte:Ligand GmbH Clemens-Maria Hofbauer-G.6, A-2344 Maria
Abstract: In this article, an overview of the most common ligand-based
in silico screening techniques is given together with an example on
the recent successful application of combined use of pharmacophore modeling,
database mining, and biological assays. Additionally, a new approach
for structure-based high-throughput pharmacophore model generation is
presented. The LigandScout program contains an automated method for
creating pharmacophore models from experimentally determined structure
data, e.g., publicly available from the Brookhaven Protein Databank
(PDB). In a first step, known algorithms were implemented and improved
to extract small-molecule ligands from the PDB including assignment
of hybridization states and bond orders. Second, from the interactions
of the interpreted ligands with relevant surrounding amino acids, pharmacophore
models reflecting functional interactions like H-bonds or ionic transfer
interactions were created. These models can be
used for screening molecular databases for similar modes of actions
on the one hand, or for screening one single compound for potential
side-effects (reversed screening) on the other hand. The implementation
was done using the ilib framework, which also formed the basis of the
software tool CombiGen, a fragment-based virtual combinatorial
library generation program enabling the user to obtain in silico compound
collections with high drug-likeness.
*Lecture presented at the Polish-Austrian-German-Hungarian-Italian Joint Meeting on Medicinal Chemistry, Kraków, Poland, 15-18 October 2003. Other presentations are published in this issue, pp. 907 -1032.
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