Path-Based Nonequilibrium Binding Free Energy Estimation, from Protein-Ligand to RNA-Ligand Binding.

Area of Science:

• Computational chemistry
• Biophysics
• Drug discovery

Background:

• Estimating binding free energies is crucial for pharmaceutical research.
• Complex biological systems present significant computational challenges.

Purpose of the Study:

• To develop and validate a robust computational approach for binding free energy estimation.
• To investigate the binding of Gleevec to Abl-tyrosine kinase and ligands to preQ1 RNA.
• To compare water models for RNA-ligand binding free energy calculations.

Main Methods:

• Nonequilibrium steered molecular dynamics simulations.
• Path-based collective variables for enhanced sampling.
• Analysis of protein-ligand and RNA-ligand complexes.

Main Results:

• Accurate binding free energy estimates for the Abl-Gleevec system, aligning with experimental data.
• TIP3P water model showed better accuracy than TIP4P-D for RNA-ligand binding free energies.
• Demonstrated reliability in handling systems with large size and conformational flexibility.

Conclusions:

• The proposed path-based workflow effectively predicts binding free energies in complex biomolecular systems.
• Provides practical guidance on water model selection for RNA-ligand interactions.
• Highlights the potential for systematic binding free energy predictions across diverse targets.