Literature DB >> 30290126

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

Kristian Birchall1, Andy Merritt1, Afrah Sattikar1, Catherine Kettleborough1, Barbara Saxty1.   

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.

Entities:  

Keywords:  chemoinformatics; compound library design; high-throughput screening

Mesh:

Year:  2018        PMID: 30290126     DOI: 10.1177/2472555218803696

Source DB:  PubMed          Journal:  SLAS Discov        ISSN: 2472-5552            Impact factor:   3.341


  2 in total

1.  The Academic Pill: How Academia Contributes to Curing Diseases.

Authors:  Marc Bickle
Journal:  SLAS Discov       Date:  2019-03       Impact factor: 3.341

2.  A "Target Class" Screen to Identify Activators of Two-Pore Domain Potassium (K2P) Channels.

Authors:  David McCoull; Emma Ococks; Jonathan M Large; David C Tickle; Alistair Mathie; Jeffrey Jerman; Paul D Wright
Journal:  SLAS Discov       Date:  2020-12-29       Impact factor: 3.341

  2 in total

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