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A buffer can prevent a sudden drop or increase in the pH of a solution after the addition of a strong acid or base up to its buffering capacity; however, such addition of a strong acid or base does result in the slight pH change of the solution. The small pH change can be calculated by determining the resulting change in the concentration of buffer components, i.e., a weak acid and its conjugate base or vice versa. The concentrations obtained using these stoichiometric calculations can be used...
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Toward Validated Quantum Mechanical Workflows Predicting pH-Dependent Properties: Benchmarking Protocols for

Donatus A Agbaglo1, Minh T N Ho1, Michael J Frisch2

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This study validates numerous quantum mechanical workflows for predicting molecular pH properties. Standard density functionals with triple-ζ basis sets and linear corrections achieve reliable pKa predictions, advancing computational chemistry.

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Area of Science:

  • Computational Chemistry
  • Physical Chemistry
  • Molecular Modeling

Background:

  • Accurate prediction of pH-dependent molecular properties is crucial in chemistry and drug discovery.
  • Existing computational methods require validation for predicting pKa values of flexible molecules.

Purpose of the Study:

  • To validate a comprehensive set of quantum-mechanical workflows for predicting pH-dependent properties.
  • To assess the performance of various computational components, including sampling, solvent models, basis sets, and density functionals.

Main Methods:

  • Tested 3076 distinct workflows combining different conformational sampling protocols, continuum solvent models, atomic orbital basis sets, and density functional approximations (DFAs).
  • Included geometry optimization, thermal effects, and empirical correction schemes.
  • Benchmarked predictions against experimental pKa data for 20 N-acylsulfonamides from the SAMPL7 challenge.

Main Results:

  • Workflows using standard density functionals, triple-ζ basis sets, and linear empirical corrections yielded root-mean-square deviations (RMSD) of 0.6-1.2 log units for pKa.
  • Identified reliable combinations of computational methods for pKa prediction.

Conclusions:

  • The study provides a validated framework for predicting pH-dependent properties of flexible molecules.
  • Advances the development of reliable, physics-based, black-box prediction tools for molecular properties.