A challenging system: free energy prediction for factor Xa.

Area of Science:

• Computational chemistry
• Molecular dynamics simulations
• Drug discovery

Background:

• Factor Xa (fXa) is a key target for developing antithrombotic drugs.
• Previous molecular dynamics (MD) studies emphasized the importance of precise system setup for stable fXa simulations.

Purpose of the Study:

• To evaluate the utility of MD simulations for predicting the binding free energy of fXa inhibitors.
• To compare different computational methods for free energy calculations in the context of fXa inhibitors.

Main Methods:

• Molecular dynamics (MD) simulations of the Factor Xa system.
• Application of three distinct free energy calculation methods: molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA), molecular mechanics/Generalized Born surface area (MM/GBSA), and linear interaction energy (LIE).
• Validation of computational predictions against experimental data for a set of fXa ligands.

Main Results:

• Continuum solvent approaches (MM/PBSA and MM/GBSA) required explicit inclusion of some water molecules for satisfactory correlation with experimental binding free energies.
• The linear interaction energy (LIE) method yielded reasonable predictions when applied to a sufficiently large dataset of fXa ligands.
• The established protocol for setting up the fXa simulation system proved effective in generating adequate molecular ensembles for reliable free energy calculations.

Conclusions:

• MD simulations, with careful system setup, are a viable approach for predicting the binding free energies of Factor Xa inhibitors.
• The choice of free energy calculation method and system setup (e.g., inclusion of explicit water) significantly impacts prediction accuracy.
• This work validates a computational strategy for accelerating the discovery of novel antithrombotic agents targeting Factor Xa.