Computational insight into the interaction of oxaliplatin with insulin

Area of Science:

• Bioinorganic Chemistry
• Computational Chemistry
• Structural Biology

Background:

• Platinum-based drugs like cisplatin and oxaliplatin primarily target DNA but also interact with proteins.
• These off-target protein interactions, exemplified by insulin, contribute to drug side effects, reduced bioavailability, and cancer resistance.
• Structural data for metallodrug-protein adducts, such as oxaliplatin-insulin, are largely unavailable, hindering mechanistic understanding.

Purpose of the Study:

• To provide the first 3D structural insights into oxaliplatin-insulin adducts using computational methods.
• To elucidate the binding interactions and conformational changes upon oxaliplatin binding to insulin.
• To validate the computational approach against experimental data and explore its applicability to other metallodrug-protein systems.

Main Methods:

• Utilized a computational multiscale protocol optimized for bioinorganic interactions.
• Employed blind protein-metalloligand docking to predict initial binding structures.
• Refined structures using integrated Molecular Dynamics (MD) and Quantum Mechanics/Molecular Mechanics (QM/MM) simulations.

Main Results:

• Generated novel 3D structural models of oxaliplatin-insulin adducts.
• Identified specific conformational changes in insulin upon oxaliplatin binding.
• Results align with existing experimental fragment analysis data, confirming the model's validity.
• Provided potential insights into how these interactions may affect insulin's biological functions.

Conclusions:

• The computational multiscale protocol is effective for modeling metallodrug-protein interactions where experimental data is lacking.
• Structural insights into oxaliplatin-insulin adducts enhance understanding of platinum drug off-target effects.
• This strategy can be applied to study other metallodrug-protein/peptide systems, advancing drug design and therapeutic strategies.