Functional pathway pharmacology: chemical tools, pathway knowledge and mechanistic model-based interpretation of experimental data

Decades of signal transduction research have elucidated a complex and dynamic architecture of signaling pathways and networks that are associated with cellular responses, physiological responses as well as various pathologies. Consequently, there is great interest in pharmacological manipulation of these pathways for therapeutic purposes. Pathway complexity brings forth two distinct challenges, one in the systematic generation of pathway-level datasets under multiple conditions and one in the interpretation of such complex data. Mechanistic model-based analysis has been used to aid in drug discovery and development, specifically in understanding and predicting the interaction of small molecule inhibitors with pathways. Examples including the quantitative comparison of multiple compounds and mechanisms of action, target selection and the elucidation of clinical findings are reviewed.