A convenient determination of .sigma.+ values

Cornélis, André; Lambert, Stephane; Laszlo, Pierre

doi:10.1021/jo00422a059

Cited by 13 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The relationship between chemical shift values and the moieties on a scaffold has been widely investigated. SCS increments have been determined for many species, including the classes of compounds examined here. ,− A related approach is to correlate chemical shift values to chemometric descriptors such as electronegativity, , π-electron density, and Hammett constants. , NMRscape is distinct from these studies in that (i) the chemical features of the moieties are not explicitly used for determination of their functional relationship to the shift value and that (ii) the presence of possibly complex cooperativity between moieties is taken into account, guided by the principles of OptiChem theory with reordering of the moieties and multivariate polynomial fitting of the landscape.…”

Section: Extracting Rules From the Chemical Shift Landscapesmentioning

confidence: 99%

NMR Landscapes for Chemical Shift Prediction

Moore

Pelczer

et al. 2012

J. Phys. Chem. A

View full text Add to dashboard Cite

The ability to reliably predict NMR chemical shifts plays an important role in elucidating the structure of organic molecules. Additionally, an intriguing question is how the multitude of variable factors (structural, electronic, and environmental) correlate with the actual electromagnetic shielding effect that determines the chemical shift value. This work presents NMRscape as a new tool for understanding these correlations by constructing the landscape that describes the relationship between the chemical shift value and the moieties bonded to a molecular scaffold. The scaffold may be as small as a single atom probed by NMR or a larger molecular framework containing the probed atom. NMRscape operates with only a list of the chemical moieties bonded to the scaffold, without utilizing any potentially biasing chemometric descriptors. The corresponding chemical shift landscape is constructed based on fundamental physical principles, which makes NMRscape a credible chemical shift prediction and analysis tool. As an illustration, we demonstrate that NMRscape can predict (13)C chemical shifts with an accuracy exceeding the substituent chemical shift (SCS) increment, hierarchical organization of spherical environments (HOSE), and neural networks (NN), methods for three distinct families of molecules sharing a common scaffold structure with moieties placed at two variable sites. The constructed NMR landscapes confirmed known empirical rules relating chemical shift values to the variation of chemical moieties on a scaffold, as well as uncovered hitherto hidden relationships. The practical importance of NMRscape is discussed.

show abstract