Integrating chemical and biological activity space is a principal requirement for the generation of activity landscape models. The activity landscape concept has been extended beyond single targets to design selectivity or multi-target landscapes. As long as activity against only a few targets is monitored, activity space representation is not a difficult task. However, the situation is more complicated if large numbers of targets are considered. For example, when compound collections are profiled against subsets of the kinome, often including hundreds of kinases, high-dimensional activity spaces are obtained that are difficult to de-convolute and represent in activity landscape models. In this case, further advanced design approaches must be investigated that depart from conventional activity landscape modeling. This contribution introduces new approaches to the design of high-dimensional activity landscape representations.

High-dimensional activity landscape representations

244th National Meeting (2012)

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