Simple Entropy Terms for End-Point Binding Free Energy Calculations.

Area of Science:

• Computational Chemistry
• Molecular Modeling
• Biophysics

Background:

• Molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) and molecular mechanics/generalized Born surface area (MM/GBSA) are widely used for estimating binding free energies.
• These methods often struggle with accurately treating entropy and ligand pose stability in simulations of noncovalent complexes.
• Improving the accuracy of these estimators is crucial for drug discovery and understanding molecular interactions.

Purpose of the Study:

• To introduce computationally inexpensive modifications to MM/PBSA and MM/GBSA estimators to enhance the treatment of entropy.
• To evaluate the effectiveness of these modifications and a snapshot filtering approach on experimentally validated datasets.
• To improve the correlation between calculated and experimental binding free energies for noncovalent complexes.

Main Methods:

• Implemented second- and higher-order cumulant expansion terms to improve entropic calculations.
• Introduced a confining potential to restrain ligand external degrees of freedom.
• Applied a snapshot filtering method to remove ligand poses that have drifted significantly from the initial binding site (RMSD cutoff of 3 Å).

Main Results:

• Tested modified MM/PBSA and MM/GBSA estimators on six experimental datasets.
• For some datasets, no tested estimator showed significant correlation with experimental binding free energies.
• In datasets with existing correlation, a combination of a 3 Å ligand RMSD cutoff and second-order cumulant expansion showed comparable or superior performance to standard average interaction energy methods.

Conclusions:

• The proposed modifications, particularly the snapshot filtering and second-order cumulant expansion, offer a promising avenue for improving binding free energy predictions.
• These computationally inexpensive enhancements can lead to more accurate estimations of binding affinities, comparable or better than existing methods.
• Further validation across diverse systems is warranted to establish the general applicability of these improved MM/PBSA and MM/GBSA approaches.