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In-Depth Information
to 1. Thus, a unique cyclic skeleton covers multiple topologically equivalent scaffolds.
Following this structural hierarchy, Bemis and Murcko scaffolds and analog series
they represent might be regarded as structurally similar if they yield the same cyclic
skeleton (i.e., if they are topologically equivalent). This structural similarity criterion
has been applied, for example, in the exploration of coordinated activity cliffs [39].
The application of this criterion can also lead to ambiguities, for example, when the
heteroatom content of topologically equivalent scaffolds substantially differs. How-
ever, in many instances, this simple structural organization scheme has proven to be a
robust indicator of closely related analogs and otherwise similar compounds, leading
to a meaningful representation of activity cliffs [39].
16.5.2 Continuum of Activity Cliffs vs. Discrete States
If cliff partners are analogs or structurally related to the extent that their similarity
is evident on the basis of visual inspection, activity cliffs are defined in a meaning-
ful way. From molecular graph- or network-based activity landscape representations
presented herein, such cliffs can readily be selected. Importantly, the application of
local SAR analysis functions such as SALI or per-compound discontinuity scores will
consistently identify the most prominent cliffs that are present in a compound data
set for a chosen molecular representation, regardless of their potential significance
for medicinal chemistry. A characteristic feature of SALI is that it is designed to
detect a continuum of activity cliffs, which is appropriate for the characterization of
the activity cliff distribution in a data set. However, through continuous scoring, only
the ordering of cliffs is determined, not their absolute magnitude. Hence, it must be
investigated separately at which score threshold level activity cliffs become signif-
icant with respect to the potency distribution within a compound set. Alternatively,
chemical significance criteria can be predefined in order to focus the analysis exclu-
sively on activity cliffs meeting these requirements. Hence, activity cliffs might be
defined as discrete states, rather than a continuum, by specifying permitted potency
ranges, required potency differences, and similarity threshold values. A discrete def-
inition of activity cliffs is meaningful for applications such as data set comparisons
or frequency-of-occurrence analysis. For example, the following activity cliff defi-
nition has been proposed [40]: An activity cliff is formed between two compounds
if at least one of them is potent in the nanomolar range and if there is an at least a
100-fold difference in potency between them. Furthermore, cliff-forming compounds
must yield a Tanimoto similarity of 0.55 calculated with the extended connectivity
fingerprint with bond diameter 4 (ECFP4) [41], which corresponds approximately to
a value of 0.85 calculated with MACCS structural keys [42]. For many (but not all)
data-mining applications this is a meaningful definition of activity cliffs.
16.5.3 Experimental Data
In addition to the molecular representation dependence of activity landscapes and
cliffs, their characteristics are also influenced by experimental data variability.
However, this potential complication has thus far been investigated much less than
