Drug discovery requires the design of molecules that modulate the activity of specific biological targets with minimal effects on other targets. To systematically predict pharmacologically relevant relationships between small molecules and protein targets, including undesirable off-targets, we have developed a probabilistic framework based on molecular similarity. Small molecules may be quantitatively compared based on 2D or 3D characteristics, the latter being directly related to binding. Given a new molecule along with a set of molecules sharing some biological effect, a single score based on the comparison to the known set is produced, reflecting either 2D similarity, 3D similarity or their combination. The results of a systematic application to a large set of drugs will be presented along with a critical analysis examining what can be learned about drug pharmacology based on different molecular similarity methods. The potential for association of phenotypic effects with specific biological targets will also be discussed.

Framework for systematic prediction of pharmacologically relevant targets of small molecules

243rd National Meeting (2012)

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