Identification and Analysis of Activity Cliffs Using 3D Similarity Techniques
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The analysis of activity landscapes and activity cliffs is a widely used method to locate critical regions of SAR. Knowledge of what changes in a series of molecules caused unexpectedly large changes in affinity allows the chemist to focus on the molecular features which are crucial for activity. We examine the usefulness of activity cliff analysis with a metric based on 3D shape and electrostatic similarity, utilizing a ligand-based alignment method. We demonstrate that 3D activity cliff analysis is complementary to the more usual 2D fingerprint-based methods, in that each finds cliffs that the other misses. Moreover, we show that analysis of the activity landscape in the context of a consensus 3D alignment allows the source of the activity cliff to be investigated in terms of the effect that a structural change has on the steric and electrostatic properties of a molecule. The technique is illustrated with two set of compounds with activity against acetylcholinesterase and dipeptidyl peptidase.