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Integrating DNA-encoded chemical libraries with virtual combinatorial library screening: Optimizing a PARP10 inhibitor.

Authors
  • Lemke, Mike1
  • Ravenscroft, Hannah1
  • Rueb, Nicole J2
  • Kireev, Dmitri3
  • Ferraris, Dana4
  • Franzini, Raphael M5
  • 1 Department of Chemistry, McDaniel College, 2 College Hill, Westminster, MD 21157, USA.
  • 2 Department of Medicinal Chemistry, Skaggs College of Pharmacy, University of Utah, 30 S 2000 E, Salt Lake City, UT 84112, USA.
  • 3 Center for Integrative Chemical Biology and Drug Discovery, UNC Eshelman School of Pharmacy, 301 Pharmacy Lane, University of North Carolina, Chapel Hill, NC 27599, USA. Electronic address: [email protected]
  • 4 Department of Chemistry, McDaniel College, 2 College Hill, Westminster, MD 21157, USA. Electronic address: [email protected]
  • 5 Department of Medicinal Chemistry, Skaggs College of Pharmacy, University of Utah, 30 S 2000 E, Salt Lake City, UT 84112, USA. Electronic address: [email protected]
Type
Published Article
Journal
Bioorganic & medicinal chemistry letters
Publication Date
Aug 05, 2020
Volume
30
Issue
19
Pages
127464–127464
Identifiers
DOI: 10.1016/j.bmcl.2020.127464
PMID: 32768646
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Two critical steps in drug development are 1) the discovery of molecules that have the desired effects on a target, and 2) the optimization of such molecules into lead compounds with the required potency and pharmacokinetic properties for translation. DNA-encoded chemical libraries (DECLs) can nowadays yield hits with unprecedented ease, and lead-optimization is becoming the limiting step. Here we integrate DECL screening with structure-based computational methods to streamline the development of lead compounds. The presented workflow consists of enumerating a virtual combinatorial library (VCL) derived from a DECL screening hit and using computational binding prediction to identify molecules with enhanced properties relative to the original DECL hit. As proof-of-concept demonstration, we applied this approach to identify an inhibitor of PARP10 that is more potent and druglike than the original DECL screening hit. Copyright © 2020 Elsevier Ltd. All rights reserved.

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