On Outliers and Activity Cliffs-Why QSAR Often Disappoints

By G. Maggiora. Journal of Chemical Information and Modeling, 2006

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Enabling future drug discovery by de novo design (2011, background): “83 Although it has been shown that this is not generally the case in arbitrary chemical spaces and associated activity landscapes, 85 , 108 search algorithms relying on local optimization have proven to deliver results of practical relevance and sufﬁcient quality for many complicated optimization…”
PubChem3D: Biologically relevant 3-D similarity (2011, background): “This suggests that single conformer per compound 3-D similarity is showing some of the anticipated effect of the “similarity principle”, which states that structurally similar molecules are likely to have similar biological activities [33-36], such that the “active/active” space is separated from th”
Machine learning methods in chemoinformatics (2014, neutral): “15”
Comparing structural fingerprints using a literature-based similarity benchmark (2016, background): “As with any guiding principle, there are exceptions; in drug discovery these are referred to as activity cliffs [2] where small changes in the structure cause large changes in biological activity.”