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Experimental validation of an affinity energy distribution calculated with the expectation maximization method
Gustaf Götmar1, Georges Guiochon
1Department of Chemistry, University of Tennessee, Knoxville, Tennessee 37996-1600, USA.
Langmuir : the ACS Journal of Surfaces and Colloids
|July 28, 2004
Summary
The study found that computational methods accurately predict the adsorption energy differences between (S)-alprenolol and (R)-alprenolol enantiomers on chiral stationary phases, matching experimental results.
Area of Science:
- Chiral chromatography
- Computational chemistry
- Physical chemistry
Background:
- Chiral stationary phases (CSPs) are crucial for separating enantiomers.
- Understanding enantioselective adsorption is key to optimizing chromatographic separations.
- Computational modeling offers a potential route to predict enantioselective interactions.
Purpose of the Study:
- To compare computational predictions of enantioselective adsorption energies with experimental measurements.
- To validate the expectation maximization method for calculating adsorption energy distributions in chiral chromatography.
Main Methods:
- Calculation of high-energy adsorption modes using the expectation maximization method.
- Measurement of adsorption energies via isothermal titration calorimetry.
- Comparison of calculated and experimentally determined energy differences between (S)-alprenolol and (R)-alprenolol enantiomers.
Main Results:
- The difference in average high-energy mode adsorption energies calculated via expectation maximization closely matched the experimentally measured adsorption energy difference.
- This agreement validates the computational approach for predicting enantioselective adsorption.
Conclusions:
- The expectation maximization method is a reliable tool for predicting enantioselective adsorption energies in chiral chromatography.
- Computational modeling can accurately guide the selection and optimization of chiral stationary phases.