NRGsuite: a PyMOL plugin to perform docking simulations in real time using FlexAID.

Area of Science:

• Computational Biology
• Structural Biology
• Drug Discovery

Background:

• Molecular recognition is crucial for biological processes.
• Understanding protein-ligand interactions is key in drug design.
• Existing tools may lack comprehensive features for binding site analysis.

Purpose of the Study:

• Introduce NRGsuite, a PyMOL plugin for protein surface cavity detection and refinement.
• Facilitate the use of identified cavities as target binding sites for docking simulations.
• Enhance control over docking simulation parameters and real-time visualization.

Main Methods:

• Developed NRGsuite as a PyMOL plugin using Python and C/C++.
• Integrated NRGsuite with the FlexAID docking software.
• Implemented features for cavity detection, refinement, volume calculation, and parameter control.

Main Results:

• NRGsuite enables precise identification and refinement of protein surface cavities.
• Users can define flexible side-chains and geometric constraints for docking.
• Real-time visualization of docking simulations is provided.

Conclusions:

• NRGsuite offers a powerful and user-friendly tool for molecular docking simulations.
• The plugin supports structure-guided drug design and serves as an educational resource.
• NRGsuite is compatible with Windows, Linux, and MacOS.