Binding affinity prediction with different force fields: examination of the linear interaction energy method.

Area of Science:

• Computational Chemistry
• Molecular Modeling
• Biophysics

Background:

• The linear interaction energy (LIE) method is a computational technique used to estimate binding free energies.
• Accurate prediction of binding affinities is crucial for drug discovery and understanding biological processes.
• The influence of force fields and system-specific properties on LIE method parameterization requires thorough investigation.

Purpose of the Study:

• To systematically evaluate the linear interaction energy (LIE) method's parameterization.
• To determine the dependence of LIE parameters on the force field and receptor binding site.
• To refine the LIE method for more accurate binding free energy calculations.

Main Methods:

• Calculated binding free energies for nine ligands complexed with P450cam.
• Employed three distinct molecular mechanics force fields: Amber95, Gromos87, and OPLS-AA.
• Investigated five LIE models, including a modified version with an additive constant (gamma).

Main Results:

• LIE calculations showed remarkable agreement with experimental relative binding free energies across all tested force fields.
• Absolute binding energies required an additional constant term (gamma) for accuracy.
• A consistent LIE model, including the gamma term, proved optimal for all three force fields, indicating force field independence of coefficients.
• The parameter gamma demonstrated a dependency on the binding site's hydrophobicity.

Conclusions:

• The coefficients of the LIE method are independent of the chosen force field.
• The additive constant (gamma) is essential for accurate absolute binding free energy calculations.
• The parameter gamma can be related to the hydrophobicity of the protein binding site, offering insights into ligand-protein interactions.