Ligand binding free energy evaluation by Monte Carlo Recursion.

Area of Science:

• Computational Chemistry
• Biophysics
• Drug Discovery

Background:

• Accurate calculation of ligand binding free energies is crucial but challenging.
• Existing methods include molecular docking, end-point calculations, alchemical methods, and biased simulations, each with trade-offs in accuracy and computational cost.

Purpose of the Study:

• To present and validate the Monte Carlo Recursion (MCR) method as an intermediate approach for ligand binding free energy calculations.
• To assess the performance of MCR using a dataset of guest-host systems and compare it with experimental data and end-point calculations.

Main Methods:

• The study employs the Monte Carlo Recursion (MCR) method, which samples systems at increasing effective temperatures.
• Free energy is calculated from Monte Carlo (MC) averages of terms W(b,T) at each iteration.
• Validation involved a dataset of 75 guest-host systems and comparison with experimental binding energies and equilibrium MC end-point calculations.

Main Results:

• MCR demonstrated a good correlation between computed binding energies and experimental data.
• Lower-energy terms in the MCR calculation were found to be most relevant for estimating binding energies.
• The MCR method provided insights into the binding energy funnel and potential connections to ligand binding kinetics.

Conclusions:

• The Monte Carlo Recursion (MCR) method offers a viable and accurate approach for evaluating ligand binding free energies.
• MCR provides a balance between computational efficiency and accuracy, complementing existing methods.
• The developed MCR codes are publicly available, facilitating further research in computational drug discovery.