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Evolution of Novartis' Small Molecule Screening Deck Design.

Ansgar Schuffenhauer1, Nadine Schneider1, Samuel Hintermann1

  • 1Novartis Institutes for BioMedical Research, Novartis Campus, CH-4002 Basel, Switzerland.

Journal of Medicinal Chemistry
|November 3, 2020
PubMed
Summary
This summary is machine-generated.

Novartis Institutes for BioMedical Research (NIBR) improved its compound screening decks. The 2019 deck prioritizes solubility and permeability over traditional criteria, enhancing drug discovery hit rates.

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Area of Science:

  • Drug Discovery
  • Medicinal Chemistry
  • Chemical Biology

Background:

  • Historically, screening decks comprised all available compounds.
  • The first NIBR screening deck (2015) utilized a 2D grid for diverse, property-optimized compound subsets.
  • Learnings from the 2015 deck informed the design of subsequent generations.

Purpose of the Study:

  • To summarize the evolution of screening deck design at NIBR.
  • To detail the transition from property-based ranking to solubility and permeability criteria.
  • To incorporate experimental assay data and biological activity profiles into deck design.

Main Methods:

  • Development of a 2015 screening deck with property-based ranking and structural redundancy.
  • Analysis of hit rates using traditional leadlikeness criteria (MW, clogP).
  • Design of a 2019 screening deck prioritizing solubility and permeability, incorporating assay data and biological activity profiles.

Main Results:

  • Traditional leadlikeness criteria (MW, clogP) were found to reduce hit rates for promising chemical starting points.
  • The 2019 screening deck demonstrated improved compound selection based on solubility and permeability.
  • Integration of experimental assay data and inferred biological activity enhanced compound set redundancy and diversity.

Conclusions:

  • Screening deck design has evolved at NIBR to optimize compound selection for drug discovery.
  • Prioritizing solubility and permeability over traditional leadlikeness criteria improves hit rates.
  • Utilizing experimental data and biological profiles leads to more effective screening libraries.