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Computational scheme for pH-dependent binding free energy calculation with explicit solvent.

Juyong Lee1, Benjamin T Miller1, Bernard R Brooks1

  • 1Laboratory of Computational Biology, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Bethesda, Maryland, 20892.

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Summary
This summary is machine-generated.

This study introduces a new computational method to calculate pH-dependent binding free energy, accounting for protonation states. This approach accurately models how pH affects molecular interactions, crucial for drug design and biochemistry.

Keywords:
Bennett acceptance ratioEDS-HREMabsolute binding free energy calculationbinding affinityconstant-pH simulationhost-guest systempH-dependence

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Area of Science:

  • Computational chemistry
  • Biophysical chemistry
  • Molecular modeling

Background:

  • Accurate binding free energy calculations are vital in molecular modeling.
  • The influence of pH on binding free energy has been historically challenging to model computationally.
  • Existing methods often neglect the crucial role of pH in molecular interactions.

Purpose of the Study:

  • To develop and validate a computational scheme for calculating pH-dependent binding free energy with explicit solvent.
  • To address the limitation of neglecting pH effects in traditional binding free energy calculations.
  • To provide a robust method for analyzing the ensemble of protonation states in titratable systems.

Main Methods:

  • Utilized a constant-pH methodology combining enveloping distribution sampling (EDS) and Hamiltonian replica exchange (HREM) to generate semi-grand canonical ensembles.
  • Employed the Bennett acceptance ratio (BAR) method to analyze the ensembles and compute binding free energy profiles.
  • Performed benchmark simulations on a host-guest system (cucurbit[7]uril and benzimidazole) using different long-range interaction schemes (cutoff, PME, IPS).

Main Results:

  • The developed computational scheme successfully captured the pH-dependent behavior of binding free energy.
  • Binding free energy profiles were accurately obtained for the benchmark system.
  • Particle Mesh Ewald (PME) and Isotropic Periodic Sum (IPS) methods yielded consistent results, while the cutoff method showed significant deviation.

Conclusions:

  • The presented constant-pH methodology offers an accurate approach to compute pH-dependent binding free energies.
  • The choice of long-range interaction calculation scheme significantly impacts the accuracy of binding free energy results.
  • This method provides valuable insights into pH-sensitive molecular recognition processes.