Benchmarking of Computational Methods for Creation of Retention Models in Quantitative Structure–Retention Relationships Studies

Quantitative
structure–retention relationship (QSRR) models
are powerful techniques for the prediction of retention times of analytes,
where chromatographic retention parameters are correlated with molecular
descriptors encoding chemical structures of analytes. Many QSRR models
contain geometrical descriptors derived from the three-dimensional
(3D) spatial coordinates of computationally predicted structures for
the analytes. Therefore, it is sensible to calculate these structures
correctly, as any error is likely to carry over to the resulting QSRR
models. This study compares molecular modeling, semiempirical, and
density functional methods (both B3LYP and M06) for structure optimization.
Each of the calculations was performed in a vacuum, then repeated
with solvent corrections for both acetonitrile and water. We also
compared Natural Bond Orbital analysis with the Mulliken charge calculation
method. The comparison of the examined computational methods for structure
calculation shows that, possibly due to the error inherent in descriptor
creation methods, a quick and inexpensive molecular modeling method
of structure determination gives similar results to experiments where
structures are optimized using an expensive and time-consuming level
of computational theory. Also, for structures with low flexibility,
vacuum or gas phase calculations are found to be as effective as those
calculations with solvent corrections added.