Cell-Based Drug Discovery: Identification and Optimization of Small Molecules that Reduce c-MYC Protein Levels in

Jesús R Medina1, Xinrong Tian1, William H Li1

  • 1Medicinal Science and Technology, GlaxoSmithKline, Collegeville, Pennsylvania 19426, United States.

Insights

Researchers developed new compounds that effectively reduce c-MYC oncoprotein levels, offering a promising indirect therapeutic strategy for cancers driven by MYC overexpression. This approach bypasses the challenge of directly targeting the MYC protein.

Area of Science:

  • Oncology
  • Molecular Biology
  • Medicinal Chemistry

Background:

  • Elevated c-MYC oncoprotein is a frequent abnormality in human cancers.
  • Directly inhibiting MYC is challenging due to the absence of a druggable binding pocket.
  • Previous work established an indirect strategy to reduce endogenous c-MYC protein levels.

Purpose of the Study:

  • To detail the medicinal chemistry efforts focused on discovering potent, orally bioavailable compounds that reduce c-MYC levels.
  • To present the development of a minimum pharmacophore model derived from structure-activity relationships.
  • To highlight the property-based approach used for optimizing pharmacokinetic profiles.

Main Methods:

  • Screening of compounds to identify those decreasing endogenous c-MYC protein levels in a MYC-amplified cell line.
  • Medicinal chemistry optimization guided by structure-activity relationships (SAR).
  • Pharmacokinetic property modulation using a property-based approach.

Main Results:

  • Discovery of a novel series of compounds that phenocopy c-MYC knockdown by siRNA.
  • Identification of potent, orally bioavailable compounds capable of reducing c-MYC levels.
  • Development of a minimum pharmacophore model for guiding further drug design.

Conclusions:

  • The study successfully identified and optimized compounds for indirect MYC inhibition.
  • These orally bioavailable compounds represent a promising new therapeutic avenue for MYC-driven cancers.
  • The developed pharmacophore model and optimization strategies can inform future drug discovery efforts.