De novo protein design enables targeting of intractable oncogenic interfaces

Varshika Ram Prakash1,2, Yusuf Najy1,2, Kalel Garrett1,2

  • 1Department of Oncology, Wayne State University School of Medicine, Detroit, MI, USA.

Insights

DesignForge, a new AI platform, creates novel miniproteins to target difficult cancer-driving protein-protein interactions (PPIs). This approach offers a new way to develop cancer therapies beyond traditional antibodies and small molecules.

Area of Science:

  • Computational biology
  • Protein engineering
  • Drug discovery

Background:

  • Protein-protein interactions (PPIs) involving oncogenic drivers are challenging cancer targets due to their complex nature and resistance to conventional drugs.
  • Existing therapies like antibodies face limitations in tissue penetration, intracellular delivery, and resistance, necessitating novel therapeutic modalities.

Purpose of the Study:

  • To develop an integrated computational framework, DesignForge, for *de novo* design of miniprotein binders targeting intractable oncogenic PPIs.
  • To demonstrate the platform's capability in designing binders for key cancer targets including PD-1/PD-L1, MYC/MAX, and KRAS/RAF interactions.

Main Methods:

  • Utilized deep learning for structure generation and sequence optimization.
  • Integrated energetic hotspot mapping to guide miniprotein design.
  • Employed AlphaFold2 for structural confidence assessment and MOE-based analyses for hotspot engagement.

Main Results:

  • Successfully engineered PD-1 mimetics to disrupt the PD-1/PD-L1 immune checkpoint.
  • Designed novel scaffolds targeting the MYC/MAX dimerization interface.
  • Generated KRAS binders predicted to inhibit RAF interaction, with high structural confidence and stability.

Conclusions:

  • DesignForge is a generalizable *in silico* platform for the rational design of therapeutic protein binders.
  • This approach enables the systematic targeting of previously intractable oncogenic PPIs, extending beyond antibody and small-molecule modalities.

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