Improved Alchemical Free Energy Calculations with Optimized Smoothstep Softcore Potentials

Area of Science:

• Computational chemistry
• Molecular modeling
• Biophysics

Background:

• GPU-accelerated simulations enable complex biological system analysis.
• Concerted alchemical transformations are key for hydration and relative binding free energy predictions.
• Existing methods face challenges like particle collapse and large gradient jumps.

Purpose of the Study:

• To address limitations in current softcore potentials for alchemical free energy calculations.
• To develop a more robust and consistent method for predicting free energies.
• To improve the reliability of simulations for drug discovery.

Main Methods:

• Classification of challenges in alchemical transformations: endpoint catastrophes, particle collapse, and large gradient-jumps.
• Development of a new family of smoothstep softcore (SSC) potentials.
• Testing SSC potentials on pathological cases and comparing with conventional and stepwise methods.

Main Results:

• SSC potentials effectively address particle collapse and large gradient-jump problems.
• A second-order SSC(2) potential matches conventional method performance while significantly improving consistency.
• Concerted SSC(2) shows promise compared to stepwise methods in relative binding free energy calculations.

Conclusions:

• The novel SSC potentials offer a more stable and consistent approach to alchemical free energy simulations.
• This advancement has significant implications for accurate molecular modeling in drug discovery.
• The SSC framework provides a generalized solution for previously intractable simulation problems.