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In order to derive design principles for multidimensional compound optimization of a given lead series. Databases containing descriptive pairs of molecules with steep SAR for several antitargets were generated as starting point for subsequent similarity-based comparisons to compounds of interest. Molecules suffering from an undesired antitarget activity are then compared to pairs of molecules in the antitarget database via 3D similarity-based methods. The corresponding alignment of a molecule of interest to a pair of (antitarget) reference compounds then yields hotspots for structural modification of that molecule to decrease antitarget activity which can be turned into new synthesis proposals.

Through Agglomerative Hierarchical Cluster analysis of the consensus RMSD matrix based on the common scaffold of the ligands, two clusters were identified. One of them contains only compounds of configuration (a) and the other one contains additionally one compound with configuration (b). Analysis of the protein-ligand interaction pattern showed different interaction behavior of the two types of stereoisomers, mainly related to amino acids Tyr 307 and Phe 343. This work was supported by the Austrian Science Fund, grant F03502 and by the Higher Education Commission Pakistan (HEC) References: 1.

Comput. Aided Mol. Des. 2001, 15, 497-520. 6. , Rarey, M. On the Art of Compiling and Using 'Drug-Like' Chemical Fragment Spaces. ChemMedChem 2008, 3, 1503-1507. 54 18th European Symposium on Quantitative Structure-Activity Relationships ORAL PRESENTATION 2 LigandScout: MORE ACCURACY FOR PHARMACOPHORE-BASED VIRTUAL SCREENING Gerhard Wolber1,2, Fabian Bendix2, Thomas Seidel2, Göhkan Ibis2 and Yasmin Aristei2 Freie Universität Berlin, Institut für Pharmazie, Königin-Luise-Str. 2+4, 14195 Berlin, Germany and 2 Inte:Ligand GmbH, Mariahilferstrasse 74B/11, 1070 Vienna, Austria 1 Virtual screening using three-dimensional arrangements of chemical features (3D pharmaco¬phores) has become a well-known and established method in computer-aided drug design.

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