In the past two decades of structure-based drug design we have seen several ups and downs of the field. With the first protein crystal structures rational drug design � mostly based on structure-based de novo design � emerged. It quickly became clear that the prediction of synthetic accessibility and binding affinity are the cornerstones of these methods. Today, we are still lacking reliable prediction methods resulting in the primary use of statistical learning approaches. Recent discussions on the predictivity of QSAR models and the existence of activity cliffs show that also these methods are no black-box tools. On the other hand, numerous examples of successful modeling applications can be found in the literature impressingly showing the relevance of structure-based modeling today. In our opinion, it is the mixture of computational search power and the medicinal chemist's intuition making structure-based modeling successful. In this talk, we will focus on computational tools supporting this interactive design process.

Pragmatic approaches to structure-based drug design

242nd National Meeting (2011)

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