Free energy along drug-protein binding pathways interactively sampled in virtual reality

Area of Science:

• Computational Biology
• Biophysics
• Molecular Dynamics

Background:

• Understanding protein-ligand interactions is crucial for drug discovery.
• Exploring molecular dynamics and binding pathways requires advanced computational methods.

Purpose of the Study:

• To present a novel two-step approach, iMD-VR-FE, combining interactive molecular dynamics in virtual reality (iMD-VR) with free energy (FE) calculations.
• To explore biological processes at the molecular level, focusing on protein-ligand unbinding pathways.

Main Methods:

• Stage one: Utilizes a human-in-the-loop iMD-VR framework to generate diverse protein-ligand unbinding pathways.
• Stage two: Employs iMD-VR-sampled pathways to define reaction coordinates for free energy (FE) calculations.
• Applies the iMD-VR-FE method to study benzamidine ligand unbinding from trypsin.

Main Results:

• The iMD-VR-FE approach yields consistent binding free energy values across different pathways.
• Free energy profiles effectively distinguish energetic differences between various protein-ligand conformations.
• Identifies metastable states along the unbinding pathways, providing detailed mechanistic insights.

Conclusions:

• The iMD-VR-FE method offers an intuitive and efficient way to test hypotheses for biomolecular pathways.
• Researchers can gain both qualitative and quantitative insights into molecular dynamics and binding processes.
• This approach enhances the exploration of complex biological systems at the molecular level.