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Subtimizer: Computational Workflow for Structure-Guided Design of Potent and Selective Kinase Peptide Substrates.

Abeeb A Yekeen1,2, Cynthia J Meyer1,2, Melissa McCoy1

  • 1Department of Biochemistry, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, Texas 75390-9038, United States.

Journal of Chemical Information and Modeling
|February 7, 2026
PubMed
Summary

We developed Subtimizer, an AI pipeline for designing kinase peptide substrates. This tool enhances substrate activity and specificity, aiding kinase research and drug discovery.

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Area of Science:

  • Biochemistry
  • Computational Biology
  • Drug Discovery

Background:

  • Kinases are crucial for cell signaling and are key drug targets.
  • Short peptide substrates are vital for kinase assays but challenging to design effectively.
  • Current methods for substrate design lack sufficient activity and specificity.

Purpose of the Study:

  • To present Subtimizer, a computational pipeline for structure-guided kinase peptide substrate design.
  • To improve kinase substrate activity, specificity, and affinity using AI-driven design.
  • To facilitate kinase research and accelerate drug discovery through enhanced assay development.

Main Methods:

  • Utilized AlphaFold-Multimer for protein structure modeling.
  • Employed ProteinMPNN for de novo protein sequence design.
  • Incorporated AlphaFold2 for structure-based interface evaluation.
  • Applied the Subtimizer pipeline to design peptide substrates for five kinases.

Main Results:

  • Four out of five tested kinases showed significantly enhanced activity (up to 350%) with designed substrates.
  • Michaelis constant (Km) decreased by over 2-fold, indicating improved enzyme-substrate affinity.
  • Designed peptides for MET and ROS1 kinases demonstrated enhanced target selectivity (4-fold and 11-fold, respectively).

Conclusions:

  • AI-driven, structure-guided protein design is effective for creating potent and selective kinase substrates.
  • Subtimizer pipeline offers a streamlined approach for optimizing kinase peptide substrates.
  • This technology advances kinase functional studies and aids in drug discovery efforts.