Distributions of compounds, scaffolds, and cyclic skeletons.

<p>The percentage of targets with increasing numbers of (<b>A</b>) compounds, (<b>B</b>) scaffolds, and (<b>C</b>) CSKs is reported for the K_i (red) and IC₅₀ (blue) data sets.</p

Calculation of first- and second-order target promiscuity indices.

<p>Shown is a workflow that illustrates how first- and second-order target promiscuity indices are calculated. On the basis of compound activity data, the activity profile of a compound is generated by collecting all available target annotations (top). Accordingly, for each compound, the number of targets it is active against is counted to yield the <i>compound promiscuity index</i> (CPI). Then, all compounds active against the same target are grouped (bottom). For each target, the number of unique scaffolds contained in its ligands is determined as the <i>first-order target promiscuity index</i> (TPI_1). Furthermore, CPI values of all compounds interacting with a given target are summed and the average CPI value is calculated as the <i>second-order target promiscuity index</i> (TPI_2).</p

Target family promiscuity.

<p>The distribution of targets with varying TPI_2 values is reported in pie charts for (<b>A</b>) 10 target families from the K_i set and (<b>B</b>) 14 families from the IC₅₀ set that contain at least 10 individual targets. Each color-coded pie chart segment reports the proportion of targets with TPI_2 values falling into a specific range. Seven value ranges are defined and colored-coded, as indicated on the right. For each family, an ID (bold) and the number of targets are provided. For example, “<b>59</b>: 12” means that family 59 contains 12 targets (K_i set). Target families are listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126838#pone.0126838.t004" target="_blank">Table 4</a>.</p

Target families.

<p>Listed are 15 target families that contain 10 or more targets. For each family, its ID according to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126838#pone.0126838.g006" target="_blank">Fig 6</a> is given and the number of targets in the K_i and IC₅₀ sets is reported. “-” indicates that there are fewer than 10 targets for the corresponding family in the K_i or IC₅₀ set. For these families, the distribution of TPI_2 values is reported in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126838#pone.0126838.g006" target="_blank">Fig 6</a>.</p><p>Target families.</p

Targets with comparable TPI_1 and different TPI_2 values (K_i set).

<p>Listed are 10 exemplary targets from the K_i set that yielded the same or very similar TPI_1 values (of varying magnitude) but significantly different TPI_2 values. For each target, its ChEMBL ID, name, and the number of active compounds (#Cpds) are provided together with TPI_1 and TPI_2 values. In addition, the percentage of compounds active against multiple targets (MT-Cpds) is given. “0%” means that all compounds only have reported activity against the given target but no others.</p><p>Targets with comparable TPI_1 and different TPI_2 values (K_i set).</p

Comparison of promiscuity indices for targets in the K_i set.

<p>(<b>A</b>) For 354 targets from the K_i set, their TPI_1 and TPI_2 values are compared. Each dot in the scatter plot represents a target. The correlation coefficient (R²) for TPI_1 and TPI_2 values is provided. (<b>B</b>) Relationships between TPI_1 and TPI_2 values are captured in a heat map in which cells are colored according to the population density of targets. In addition, the number of targets is reported for cells that were populated with more than 20 targets using white numbers.</p

Comparison of promiscuity indices for targets in the IC₅₀ set.

<p>For 649 targets from the IC₅₀ set, their TPI_1 and TPI_2 values are compared. The representation is according to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126838#pone.0126838.g004" target="_blank">Fig 4</a>.</p

Data sets.

<p>For the K_i and IC₅₀ value-based data sets, the number of compounds, targets, and compound-target interactions is reported. In addition, the number of unique scaffolds and cyclic skeletons (CSKs) obtained from active compounds is provided.</p><p>Data sets.</p

Introduction of Target Cliffs as a Concept To Identify and Describe Complex Molecular Selectivity Patterns

The study of target specificity or selectivity of small molecules is an important task in drug design. In an ideal situation, a compound would exclusively interact with an individual target and hence be target specific. However, such exclusive binding events are likely to be rare, as increasing evidence suggests. Because many compounds are active against more than one target, apparent selectivity often results from potency differences, i.e., a compound that is highly potent against a given target and weakly potent against one or more others displays target selectivity. In a simple case, a compound might have known activity against a pair of targets and be selective for one over the other. Then, selectivity is straightforward to rationalize. However, there are many more complex selectivity relationships associated with multi-target activities of compounds that are difficult to analyze and compare in a consistent manner. For this purpose, we introduce herein target cliffs as a concept to describe complex selectivity patterns. A target cliff is defined as a pair of targets against which at least one compound displays a large difference in potency. As such, target cliffs are distinct from activity cliffs. However, qualifying target pairs (target cliffs) and compound pairs (activity cliffs) can be systematically extracted from the same data structure termed target-compound matrices. Furthermore, these two types of cliffs can be compared to identify and prioritize compounds that are selective and reveal structure–activity relationship (SAR) information

Assay frequency vs. assay promiscuity.

<p>For increasing numbers of (<b>a</b>) primary and (<b>b</b>) confirmatory assays, the distribution of assay promiscuity is reported in a box plot format. The plot gives the smallest degree of assay promiscuity (bottom line), first quartile (lower boundary of the box), median value (thick line), third quartile (upper boundary of the box), and largest degree of assay promiscuity (top line).</p