Abstract
High-throughput screening (HTS) often yields a list of compounds that requires prioritization before further work is performed. Prioritization criteria typically include activity, selectivity, physicochemical properties, and other absolute or calculated measurements of compound “value.” One critical method of compound prioritization is often not discussed in published accounts of HTS. We have referred to this oft-overlooked metric as “compound natural history.” These natural histories are observational evaluations of how a compound has been reported in the historical literature or compound databases. The purpose of this work was to develop a useful natural history visualization (NHV) that could form a standard, important part of hit reporting and evaluation. In this case report, we propose an efficient and effective NHV that will assist in the prioritization of active compounds and demonstrate its utility using a retrospective analysis of reported hits. We propose that this method of compound natural history evaluation be adopted in HTS triage and become an integral component of published reports of HTS outcomes.
Original language | English (US) |
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Pages (from-to) | 862-869 |
Number of pages | 8 |
Journal | SLAS Discovery |
Volume | 26 |
Issue number | 7 |
Early online date | Jun 11 2021 |
DOIs | |
State | Published - Aug 2021 |
Bibliographical note
Funding Information:We would like to acknowledge seminal discussions with Daniel Erlanson (VP of Chemistry at Frontier Medicines) and Jonathan Baell (Professor of Medicinal Chemistry, Monash University) throughout the past 10 years regarding high-throughput screening triage. The authors received no financial support for the research, authorship, and/or publication of this article.
Publisher Copyright:
© Society for Laboratory Automation and Screening 2021.
Keywords
- assays
- high-throughput screening
- triage
- visualization