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Leveraging AI to Explore Structural Contexts of Post-Translational Modifications in Drug Binding.

Kirill E Medvedev1, R Dustin Schaeffer1, Nick V Grishin1,2

  • 1Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.

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Post-translational modifications (PTMs) impact drug binding. AI tools like AlphaFold3 model PTM effects on protein structure and drug interactions, aiding drug discovery and understanding disease.

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Area of Science:

  • Computational Biology
  • Drug Discovery
  • Structural Bioinformatics

Background:

  • Post-translational modifications (PTMs) are crucial for protein function and cellular regulation.
  • PTM defects are linked to various diseases, including cancer and neurodegenerative disorders.
  • PTMs significantly influence drug interactions and binding affinity, making them key targets in drug discovery.

Purpose of the Study:

  • To identify small molecule binding-associated PTMs influencing drug binding across human proteins.
  • To leverage AI-driven methods for large-scale modeling of PTMs and their effects on drug interactions.
  • To provide structural context for PTMs impacting small molecule binding.

Main Methods:

  • Developed the DrugDomain database to identify small molecule binding-associated PTMs.
  • Mapped 6,131 identified PTMs to structural domains using the ECOD database.
  • Utilized AI-based protein structure prediction tools (AlphaFold3, RoseTTAFold All-Atom, Chai-1) to generate 14,178 models of PTM-modified proteins with docked ligands.

Main Results:

  • AI methods can predict PTM effects on small molecule binding, though larger benchmarking is needed for precise accuracy evaluation.
  • Phosphorylation of NADPH-Cytochrome P450 Reductase was found to cause significant structural disruption in the binding pocket, potentially impairing function.
  • All generated data and models are publicly available via the DrugDomain database and GitHub.

Conclusions:

  • AI-driven approaches enable large-scale structural analysis of PTMs and their impact on drug binding.
  • This study provides a novel resource for understanding the structural context of PTMs in drug discovery.
  • The findings highlight the potential of targeting PTMs for therapeutic interventions.