WizePairZ: a novel algorithm to identify, encode, and exploit matched molecular pairs with unspecified cores in medicinal chemistry
| Autor: | Stephen A. St-Gallay, Edward Jolyon Griffen, Daniel J. Warner |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: |
Exploit
Computer science Chemistry Pharmaceutical General Chemical Engineering Library and Information Sciences computer.software_genre ENCODE Notation Medicinal chemistry Histone Deacetylases lcsh:Chemistry Knowledge extraction Enumeration Physical and Theoretical Chemistry Information retrieval Molecular Structure lcsh:T58.5-58.64 Drug discovery lcsh:Information technology General Chemistry Computer Graphics and Computer-Aided Design Computer Science Applications Histone Deacetylase Inhibitors Data set Transformation (function) lcsh:QD1-999 Drug Design Oral Presentation Data mining Matched molecular pair analysis computer Algorithm Algorithms |
| Zdroj: | Journal of Cheminformatics Journal of Cheminformatics, Vol 3, Iss Suppl 1, p O9 (2011) |
| ISSN: | 1758-2946 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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