Abstract

In recent years computational power has continued to increase dramatically, which has enabled more routine access to a range of complex computational approaches in drug discovery. This has not only created an opportunity to revisit known approaches in a discovery setting but is also driving the development of the next wave of novel approaches to further exploit this power. This chapter reports on the recent progress of computational modelling in the kinase field including some successes in terms of potency predictions and longer-term challenges highlighted with example case studies. The kinase field appears to be a particularly attractive opportunity for computational approaches, likely driven by the significant ongoing interest in drug discovery and enabled by the wealth of high quality X-ray crystal structures and activity/affinity data.

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