Molecular Insights into Phage-Hydrogel Polymer Interactions Through Docking, Molecular Dynamics, and Machine Learning

Area of Science:

• Biomaterials Science
• Computational Biology
• Drug Delivery Systems

Background:

• Bacteriophage (phage) therapy faces challenges with phage instability, diffusion, and infectivity loss at target sites.
• Hydrogels are promising carriers for phage delivery due to biocompatibility and controlled release properties.
• Molecular mechanisms governing phage-hydrogel interactions are not well understood.

Purpose of the Study:

• To investigate phage-hydrogel interactions at a molecular level using an in silico framework.
• To evaluate the binding affinities and stability of phage proteins with various hydrogel polymers.
• To identify key factors for designing effective hydrogel-based phage delivery systems.

Main Methods:

• Utilized molecular docking, molecular dynamics (MD) simulations, and MM/PBSA calculations.
• Employed machine learning for adhesion prediction and diffusion modeling.
• Assessed interactions between bacteriophage capsid and tail proteins and eight hydrogel polymers.

Main Results:

• Identified solvent-accessible pockets on phage proteins capable of interacting with hydrogel polymers.
• Hyaluronic acid and GelMA hydrogels demonstrated strong binding affinities to specific phage proteins.
• MD simulations confirmed the stability of phage-hydrogel complexes, supported by MM/PBSA energies.
• Machine learning identified hydrogen bonding and electrostatic interactions as crucial for phage retention.

Conclusions:

• Hydrogels with charged and polar functional groups promote stable, reversible phage binding for controlled release.
• This study provides mechanistic insights for rational hydrogel design in phage delivery.
• High-throughput computational strategies can accelerate the development of optimized phage therapeutics.