Main Methods and Tools for Peptide Development Based on Protein-Protein Interactions (PPIs)

Protein-protein interactions (PPIs) play a fundamental role in numerous biological processes, including signaling pathways, immune responses, and disease mechanisms. Targeting PPIs with peptide-based therapeutics has emerged as a promising strategy for treating diseases such as cancer, neurodegenerative disorders, and viral infections.

Why Target PPIs with Peptides?

Peptides are short chains of amino acids that can mimic or disrupt PPIs, making them valuable for drug discovery. Unlike small molecules, which often struggle to bind the large, flat surfaces of PPIs, peptides offer high specificity and affinity, making them excellent candidates for therapeutic interventions.

                                                                      


Main Methods for Peptide-Based PPI Modulation

1. Rational Design and Computational Approaches

Computational tools have revolutionized peptide design by allowing researchers to model and predict peptide-PPI interactions before experimental validation.

  • Molecular Docking: Simulates peptide binding to a target protein to predict interaction strength.
  • Molecular Dynamics (MD) Simulations: Provides insights into peptide stability and conformational changes.
  • Machine Learning & AI: Predicts peptide sequences with optimal binding properties.

🛠 Tools Used:

  • HADDOCK (for docking simulations)
  • Rosetta (for protein design and modeling)
  • AlphaFold (for predicting protein-peptide interactions)

2. Phage Display Technology

Phage display is a high-throughput screening technique that allows researchers to identify peptides capable of binding to target PPIs. This method involves displaying peptide libraries on bacteriophages and selecting those with strong binding affinities.

🛠 Key Applications:

  • Identifying peptide inhibitors of oncogenic PPIs.
  • Developing high-affinity peptides for immune system modulation.

3. Structure-Based Drug Design (SBDD)

Structural biology techniques, such as X-ray crystallography and NMR spectroscopy, provide detailed 3D structures of PPIs. These structures guide the rational design of peptides that either disrupt or stabilize interactions.

🛠 Tools Used:

  • PDB (Protein Data Bank) – for structural reference
  • PyMOL – for molecular visualization
  • Chimera – for molecular docking and analysis

4. Peptide Stapling and Chemical Modifications

Peptide stapling enhances peptide stability, bioavailability, and cell permeability. This technique involves adding chemical cross-links (staples) to lock peptides into their bioactive conformations.

🛠 Common Modifications:

  • Stapled Peptides: Increase resistance to enzymatic degradation.
  • Cyclization: Improves binding affinity and structural rigidity.
  • Non-natural Amino Acids: Enhance selectivity and stability.

Experimental Validation Techniques

After designing potential PPI-targeting peptides, researchers use biophysical and biochemical assays to validate their effectiveness.

🔬 Common Validation Methods:

  • Surface Plasmon Resonance (SPR): Measures real-time peptide-protein interactions.
  • Isothermal Titration Calorimetry (ITC): Determines binding affinity and thermodynamics.
  • Cell-Based Assays: Tests peptide function in a biological context.

Conclusion

Peptide-based modulation of protein-protein interactions (PPIs) is a powerful approach for developing next-generation therapeutics. Advances in computational modeling, high-throughput screening, and structural biology have significantly accelerated peptide discovery. With the integration of machine learning and AI, the future of peptide therapeutics looks promising for tackling complex diseases.

30th Edition of International Research Conference on Science Health and Engineering | 28-29 March 2025 | San Francisco, United States

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