ProPose: steered virtual screening by simultaneous protein-ligand docking and ligand-ligand alignment

Area of Science:

• Computational chemistry
• Drug discovery
• Structural biology

Background:

• Virtual screening is crucial for identifying drug candidates.
• Incorporating prior knowledge (a priori information) can improve screening efficiency.
• Handling multiple target structures and protein flexibility remains a challenge in docking.

Purpose of the Study:

• To evaluate ProPose, a model-free screening engine, for simultaneous protein-ligand docking and alignment.
• To assess the utility of incorporating multiple target structures as a priori information.
• To improve virtual screening enrichment and accuracy for antiviral drug targets.

Main Methods:

• Utilized the ProPose screening engine for simultaneous docking and alignment.
• Employed multiple structures of herpes simplex virus thymidine kinase as a priori information.
• Combined ligand- and receptor-based methods, including interaction and docking constraints.

Main Results:

• Simultaneous alignment to two target structures improved enrichment of compatible chemical substructures.
• Ensured better steric fit of ligands into the target protein active site.
• Effectively handled target flexibility and improved ranking compared to simple scoring functions.

Conclusions:

• Simultaneous alignment using multiple target structures is an effective strategy for virtual screening.
• ProPose integrates diverse a priori information to enhance drug discovery protocols.
• Combining ligand and receptor-based approaches compensates for scoring function limitations.