This article is part of the supplement: 6th German Conference on Chemoinformatics, GCC 2010
Oral presentation
WizePairZ: a novel algorithm to identify, encode, and exploit matched molecular pairs with unspecified cores in medicinal chemistry
-
* Corresponding author: Stephen A St-Gallay steve.st-gallay@astrazeneca.com
1 AstraZeneca, Loughborough, UK
2 AstraZeneca, Alderly Park, UK
Journal of Cheminformatics 2011, 3(Suppl 1):O9 doi:10.1186/1758-2946-3-S1-O9
The electronic version of this article is the complete one and can be found online at: http://www.jcheminf.com/content/3/S1/O9
| Published: | 19 April 2011 |
© 2011 Warner et al; licensee BioMed Central Ltd.
Oral presentation
An algorithm to automatically identify and extract matched molecular pairs from a collection of compounds has been developed, allowing the learning associated with each molecular transformation to be readily exploited in drug discovery projects. Here, we present the application to an example data set of 11 histone deacetylase inhibitors. The matched pairs were identified, and corresponding differences in activity and lipophilicity were recorded. These property differences were associated with the chemical transformations encoded in the SMIRKS reaction notation. The transformations identified a subseries with the optimal balance of these two parameters. Enumeration of a virtual library of compounds using the extracted transformations identified two additional compounds initially excluded from the analysis with an accurate estimation of their biological activity. We describe how the WizePairZ system can be used to archive and apply medicinal chemistry knowledge from one drug discovery project to another as well as identify common bioisosteres.