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Biased Complement Diversity Selection for Effective Exploration of Chemical Space in Hit-Finding Campaigns

Jansen, Hanneke and De Pascale, Gianfranco and Lindvall, Mika and Moser, Heinz and Pfister, Keith and Wartchow, Charles and Fong, Susan and Warne, Bob (2019) Biased Complement Diversity Selection for Effective Exploration of Chemical Space in Hit-Finding Campaigns. Journal of chemical information and modeling, 59 (5). pp. 1709-1714. ISSN 1549960X

Abstract

The success of hit-finding campaigns relies on many factors, including the quality and diversity of the set of compounds that is selected for screening. This paper presents a generalized workflow that guides compound selections from large compound archives with opportunities to bias the selections with available knowledge in order to improve hit quality while still effectively sampling the accessible chemical space. An optional flag in the workflow supports an explicit complement design function where diversity selections complement a given core set of compounds. Results from three project applications as well as a literature case study exemplify the effectiveness of the approach, which is available as a KNIME workflow named Biased Complement Diversity (BCD).

Item Type: Article
Date Deposited: 25 Sep 2019 00:45
Last Modified: 25 Sep 2019 00:45
URI: https://oak.novartis.com/id/eprint/38753

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