Abstract
Pharmacophore modeling of large, drug-like molecules, such as the dopamine reuptake inhibitor GBR 12909, is complicated by their flexibility. A comprehensive hierarchical clustering study of two GBR 12909 analogs was performed to identify representative conformers for input to three-dimensional quantitative structure–activity relationship studies of closely-related analogs. Two data sets of more than 700 conformers each produced by random search conformational analysis of a piperazine and a piperidine GBR 12909 analog were studied. Several clustering studies were carried out based on different feature sets that include the important pharmacophore elements. The distance maps, the plot of the effective number of clusters versus actual number of clusters, and the novel derived clustering statistic, percentage change in the effective number of clusters, were shown to be useful in determining the appropriate clustering level.
Six clusters were chosen for each analog, each representing a different region of the torsional angle space that determines the relative orientation of the pharmacophore elements. Conformers of each cluster that are representative of these regions were identified and compared for each analog. This study illustrates the utility of using hierarchical clustering for the classification of conformers of highly flexible molecules in terms of the three-dimensional spatial orientation of key pharmacophore elements.
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Abbreviations
- %ΔEff:
-
percentage change in the effective number of clusters
- 3D-QSAR:
-
three-dimensional quantitative structure–activity relationship
- CoMFA:
-
Comparative Molecular Field Analysis
- DA:
-
dopamine
- DAT:
-
dopamine transporter
- FRC:
-
fuzzy relational clustering
- QSAR:
-
quantitative structure-activity relationship
- RMSD:
-
root mean square deviation
- RTB:
-
number of rotatable bonds
- SAR:
-
structure–activity relationship
- SERT:
-
serotonin transporter
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Acknowledgements
This work was supported in part by NIH grant DA018153 (C.A.V.). K.M.G. acknowledges the support of Ruth L. Kirschstein National Research Service Award Individual Predoctoral Fellowship DA015555.
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Gilbert, K.M., Venanzi, C.A. Hierarchical clustering analysis of flexible GBR 12909 dialkyl piperazine and piperidine analogs. J Comput Aided Mol Des 20, 209–225 (2006). https://doi.org/10.1007/s10822-006-9046-2
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DOI: https://doi.org/10.1007/s10822-006-9046-2