Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based...

Area of Science:

• Computational chemistry
• Structural biology
• Drug discovery

Background:

• Drug discovery is resource-intensive, necessitating efficient computational methods.
• Traditional docking methods often overlook protein flexibility, limiting accuracy.
• Ensemble-based docking offers a more dynamic approach to ligand-protein interactions.

Purpose of the Study:

• To demonstrate the application of ensemble-based docking for incorporating protein flexibility.
• To analyze the binding of Flovokawain B to lysozyme using this advanced technique.
• To improve the reliability of molecular docking predictions in drug discovery.

Main Methods:

• Molecular dynamics simulations of lysozyme to capture conformational dynamics.
• Conformation clustering based on molecular dynamics trajectories.
• Ligand-protein docking using selected protein conformations.

Main Results:

• Ensemble-based docking successfully introduced protein flexibility into the simulation.
• Cluster 2 of lysozyme conformations yielded the lowest binding energy with Flovokawain B (-29.37 kJ/mol).
• Molecular docking visualizations confirmed potential binding interactions.

Conclusions:

• Ensemble-based docking provides a more comprehensive understanding of dynamic protein behavior.
• This method enhances the accuracy of predicting ligand-protein binding outcomes.
• Incorporating protein dynamics is crucial for efficient and reliable drug discovery pipelines.