At the very heart of the role of a medicinal chemist or drug designer is the ability to link chemical structure to molecular properties.  The traditional approach to deriving these structure-property relationships (SPR) has been to encode known compounds in the form of molecular 'descriptors' and link them to experimentally determined properties in a quantitative fashion. At AstraZeneca, we have been at the forefront of the emerging field of matched molecular pairs analysis (MMPA) or inverse-QSAR, with a number of recent publications in the area1,2. As the name implies, this turns the traditional approach of investigating these relationships on its head in the identification of changes in structure that correspond to a desirable changes in properties3. The presentation will attempt to summarize the current state-of-the-art with respect to the literature, AstraZeneca's in-house system for MMPA, and how we can use it to expedite the multi-objective optimization of chemical leads. 

Rational, data-driven approach to lead optimization

243rd National Meeting (2012)

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