GalaxyDock: protein-ligand docking with flexible protein side-chains

Area of Science:

• Computational biology
• Structural bioinformatics
• Drug discovery

Background:

• Protein-ligand docking is crucial for drug discovery.
• Incorporating receptor flexibility is a key challenge in docking.
• Current methods for receptor flexibility are computationally intensive.

Purpose of the Study:

• To develop a novel protein-ligand docking program, GalaxyDock.
• To account for receptor flexibility through global optimization of side-chain conformations.
• To improve the accuracy of binding conformation prediction.

Main Methods:

• Developed GalaxyDock, a program utilizing global optimization for flexible side-chain docking.
• Employed an AutoDock-based energy function trained for flexible side-chain interactions.
• Validated the method on HIV-PR, LXRβ, cAPK, and 16 diverse protein-ligand complexes.

Main Results:

• GalaxyDock demonstrated higher or comparable performance to existing flexible docking methods.
• Achieved a 10%-60% increase in binding conformation prediction accuracy over rigid-receptor docking.
• Successfully predicted binding conformations for proteins with ligand-induced side-chain changes.

Conclusions:

• GalaxyDock offers an effective approach to incorporate receptor flexibility in docking.
• The global energy optimization method shows promise for future extensions to larger receptor flexibility.
• GalaxyDock is available for public use, facilitating further research.