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Compound Set Enrichment: A novel approach to analysis of primary HTS data.

Varin, Thibault and Gubler, Hanspeter and Parker, Christian and Zhang, Ji and Raman, Pichai and Ertl, Peter and Schuffenhauer, Ansgar (2010) Compound Set Enrichment: A novel approach to analysis of primary HTS data. Journal of Chemical Information and Modeling. ISSN 1549-960X

Abstract

The main goal of high-throughput screening (HTS) is to identify active chemical series rather than just individual active compounds. A new method (called Compound Set Enrichment) to identify active chemical series from primary screening data is proposed. The application of the Scaffold Tree compound classification method, in conjunction with the Kolmogorov-Smirnov statistic to assess the scaffold activity is described. 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 cut-off distort activity information leading to the incorrect assignment active series of compounds. These results suggest that this method may have utility in the rational selection of active classes of compounds (and not just individual active compounds) for follow-up and validation.

Item Type: Article
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Additional Information: archiving not formally supported by this publisher
Keywords: High throughput screening; activity cut-off; compound selection; compound classification; Scaffold Tree; Kolmogorov-Smirnov statistics; latent hit, hitlist triaging
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Date Deposited: 13 Oct 2015 13:16
Last Modified: 13 Oct 2015 13:16
URI: https://oak.novartis.com/id/eprint/2809

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