General Quantum-Based NMR Method for the Assignment of Absolute Configuration by Single or Double Derivatization: Scope and Limitations.
María M ZanardiFranco A BiglioneMaximiliano A SortinoAriel M SarottiPublished in: The Journal of organic chemistry (2018)
The determination of the absolute configuration of chiral alcohols and amines is typically carried out with modified Mosher methods involving a double-derivatization strategy. On the other hand, the number of robust and reliable methods to accomplish that goal using a single derivatization approach is much less abundant and mainly limited to secondary alcohols or primary amines. Herein, we report a conceptually novel strategy to settle the most likely absolute configuration of a wide variety of substrates and chiral derivatizing agents following a single-derivatization experiment coupled with quantum calculations of NMR shifts and DP4+ analysis. Using an ambitious set of 114 examples, our methodology succeeded in setting the correct absolute configuration of the substrates in 96% of the cases. The classification achieved with secondary alcohols, secondary amines, and primary amines herein studied was excellent (100%), whereas more modest results (89%) were observed for primary and tertiary alcohols. Moreover, a new DP4+ integrated probability was built to strengthen the analysis when the NMR data of the two possible diastereoisomers are available. The suitability of these methods in solving the absolute configuration of two relevant cases of stereochemical misassignment ((+)- erythro-mefloquine and angiopterlactone B) is also provided.
Keyphrases
- ms ms
- high performance liquid chromatography
- liquid chromatography tandem mass spectrometry
- gas chromatography mass spectrometry
- solid phase extraction
- simultaneous determination
- magnetic resonance
- solid state
- liquid chromatography
- high resolution
- tandem mass spectrometry
- gas chromatography
- molecular dynamics
- mass spectrometry
- ultra high performance liquid chromatography
- machine learning
- ionic liquid
- deep learning
- electronic health record
- big data
- monte carlo
- molecular dynamics simulations
- artificial intelligence