Compound Set Enrichment: A Novel Approach to Analysis of Primary HTS Data

Abstract

The main goal of high-throughput screening (HTS) is to identify active chemical series rather than just individual active compounds. In light of this goal, a new method (called compound set enrichment) to identify active chemical series from primary screening data is proposed. The method employs the scaffold tree compound classification in conjunction with the Kolmogorov-Smirnov statistic to assess the overall activity of a compound scaffold. The application of this method to seven PubChem data sets (containing between 9389 and 263679 molecules) is presented, and the ability of this method to identify compound classes with only weakly active compounds (potentially latent hits) is demonstrated. The analysis presented here shows how methods based on an activity cutoff can distort activity information, leading to the incorrect activity assignment of compound series. These results suggest that this method might have utility in the rational selection of active classes of compounds (and not just individual active compounds) for followup and validation.

Probabilistic Substructure Mining From Small‐Molecule Screens

“…Furthermore, our finding that noisy primary screening data can yield valuable information is consistent with other research in the field that successfully mine primary screening data while ignoring the data from confirmatory experiments 29. 9 For example, compound set enrichment (CSE) identifies statistically significant distributions of scaffolds in the primary screening data, enabling the detection of groups of active molecules that were initially missed 29. In a similar manner, local hit rate analysis (LHR) identifies clusters of molecules whose distribution is statistically significant in the primary screening data 9…”

Application of Titration-Based Screening for the Rapid Pilot Testing of High-Throughput Assays

“…Such actives could possibly be rescued with post-HTS data-mining techniques aimed at identifying latent hits. 23,24 Both compounds 5 and 6 were annotated as weak TP at the 8.3 µM screening concentration but found as FN at all other doses (Fig. 4b, c).…”

Recent Trends and Observations in the Design of High-Quality Screening Collections

“…Further investigations of identified scaffolds with a higher propensity for 'activity cliffs' and 'selectivity cliffs' [119], which might also serve as particular interesting starting points for library design. A strategy to identify latent privileged scaffolds for a particular target from primary future science group screening data was proposed by Varin et al [120]. The approach identifies scaffolds generated by the scaffold tree that are statistically more active than the background according to the primary screening data.…”