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    This study introduces a pH-dependent binding free energy calculation method, accounting for protonation changes. The approach accurately predicts binding free energies and pKa shifts in host-guest systems.

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    Area of Science:

    • Computational Chemistry
    • Molecular Modeling
    • Physical Chemistry

    Background:

    • Protonation state changes during binding affect electrostatic environments.
    • pH-dependent binding free energy is crucial but often ignored in fixed protonation state models.
    • Accurate modeling requires considering the dynamic nature of protonation.

    Purpose of the Study:

    • To develop and validate a method for calculating pH-dependent binding free energies.
    • To model proton uptake/release in host-guest systems.
    • To accurately predict experimental binding free energies across different pH conditions.

    Main Methods:

    • A two-step approach using lambda-dynamics with enhanced sampling.
    • Adaptive landscape flattening to determine pKa shifts and reference binding free energies.
    • Application to a model cucurbit[7]uril host/guest system.

    Main Results:

    • Successfully constructed pH-dependent binding profiles.
    • Accurately captured experimental pKa shifts and binding free energies.
    • Identified limitations in CGenFF for molecular charge distribution, improved by minor charge modifications.

    Conclusions:

    • The developed framework enables accurate computation of pH-dependent binding free energies.
    • Minor force field adjustments significantly improve pKa shift predictions.
    • Highlights the importance of considering protonation dynamics in molecular binding.