Design of the LifeArc Index Set and Retrospective Review of Its Performance: A Collection for Sharing. (March 2019)

• Record Type: Journal Article
• Authors: Birchall, Kristian; Merritt, Andy; Sattikar, Afrah; Kettleborough, Catherine; Saxty, Barbara
• Is Part Of: SLAS discovery. Volume 24:Number 3(2019)
• Page Start: 332
• Page End: 345
• Publication Date: 2019-03
• Subjects: high-throughput screening -- compound library design -- chemoinformatics; Drugs -- Analysis -- Periodicals; Drugs -- Testing -- Periodicals; Biomolecules -- Analysis -- Periodicals; Biomolecules -- Analysis; Drugs -- Analysis; Drugs -- Testing; Drug Evaluation, Preclinical; Molecular Biology -- methods; Periodicals; Periodicals; 615.1
• DOI: 10.1177/2472555218803696
• Languages: English
• ISSNs: 2472-5552

Abstract

Building, curating, and maintaining a compound collection is an expensive operation, beyond the scope of most academic organizations. Here we describe the selection criteria used to compile the LifeArc diversity set from commercial suppliers and the process we undertook to generate our representative LifeArc index set. The aim was to avoid a "junk in, junk out" screen collection to increase chemical tractability going forward, while maximizing diversity. Using historical LifeArc screening data, we demonstrate that the index set was predictive of ligandability and that progressable hits could be identified by mining associated clusters within our larger diversity set. Indeed, a higher percentage of index-derived hit clusters were found to have been progressed into hit-to-lead programs, reflecting better drug-likeness. In practice, the library has been shared widely with academic groups and used routinely within LifeArc to assess the ligandability of novel targets. Its small size is well suited to meet the needs of medium-throughput screening in labs with either limited automation, limited precious or expensive reagents, or complex cellular assays. The strategy of screening a small set in combination with rapid hit analog follow-up has demonstrated the utility of finding active clusters for potential development against challenging targets.