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Predicting Chromatographic Retention Times from Quantum-Chemical Solvation Free Energies: A Pilot Study of Oxysterols
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DOI：10.1021/acs.jpca.5c08150.png)
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Abstract
En 中文
High-performance liquid chromatography (HPLC) is a key component of analytical chemistry workflows. In HPLC, analytes are separated by retention times (RTs), which depend on analyte partitioning between a column stationary phase and a solvent mobile phase. Measured RT depends on the details of the chromatographic method: solvent and stationary phase composition, solvent gradient, pH, temperature, and more. Predicting RT remains a challenge across different chromatographic conditions. We present a pilot study using quantum chemistry and continuum solvent models to predict analyte transfer between stationary and mobile phases. Simulations of a set of oxysterols suggest that computed solvation free energies can complement machine-learned models and potentially advance de novo prediction of RT.
Keywords:
LIQUID-CHROMATOGRAPHY
COSMO-RS
PHASE
IDENTIFICATION
ADSORPTION
SEPARATION
BEHAVIOR
VOLUME
MODEL
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