Pharmmaker: Pharmacophore modeling and hit identification based on druggability simulations

Area of Science:

• Computational chemistry
• Drug discovery
• Structural biology

Background:

• Druggability simulations characterize protein-drug binding.
• Pharmacophore models are crucial for virtual screening.
• A unified tool for simulation to screening is needed.

Purpose of the Study:

• To develop Pharmmaker, a novel computational tool.
• To integrate druggability simulations and pharmacophore modeling.
• To facilitate structure-based virtual screening for drug discovery.

Main Methods:

• Pharmmaker builds upon the ProDy application programming interface and DruGUI module.
• It involves identifying high-affinity residues and probe interactions.
• Top-ranked snapshots yield probe binding poses and protein conformations for pharmacophore model construction.

Main Results:

• Pharmmaker provides a systematic workflow from simulation to pharmacophore modeling.
• Pharmacophore models are generated using probe binding poses and protein conformations.
• These models serve as filters for identifying hits in virtual screening.

Conclusions:

• Pharmmaker addresses the lack of a comprehensive tool for drug discovery workflows.
• The tool enables efficient identification of potential drug candidates.
• Pharmmaker enhances computer-aided drug discovery by integrating multiple steps.