Conspectus
Structural elucidation is an important and challenging stage in
the discovery of new organic molecules. Single-crystal X-ray analysis
provides the most unquestionable results, though in practice the availability
of suitable crystals limits its broad use. On the other hand, NMR
spectroscopy has become the leading and universal technique to accomplish
the task. Despite continuous advances in the field, the misinterpretation
of NMR data is commonplace, evidenced by the large number of erroneous
structures being published in top journals. Quantum calculations of
NMR chemical shifts and scalar coupling constants emerged as ideal
complements to facilitate the elucidation process when experimental
NMR data is inconclusive. Since seminal reports demonstrated that
affordable DFT methods provide NMR predictions accurate enough to
differentiate among closely related isomers, the discipline has experienced
substantial growth. The impact has been felt in different areas, and
nowadays the results of such calculations are routinely seen in high
impact literature.
This Account describes our investigations
in the field of quantum NMR calculations, focusing on the development
of tools for structural elucidation and practical applications. We
pioneered the use of artificial intelligence methods in the development
of novel strategies of structural validation. Our first generation
of trained artificial neural networks (ANNs) showed excellent ability
to identify mistakes at the atom connectivity level, whereas the use
of multidimensional pattern recognition pushed the performance to
the stereochemical limit. In a conceptually different approach, we
developed DP4+, an updated version of the DP4 probability used to
determine the most likely structure among two or more candidates when
one set of experimental data is available. Increasing the level of
theory in NMR calculations and including unscaled data in the formalism
improved the performance of the method, further validated to settle
the configuration of challenging motifs such as spiroepoxides or Mosher’s
derivatives. One of the limitations of DP4+ is related to the relatively
large computational cost involved in obtaining DFT-optimized geometries,
which led to the development of a fast variant including the valuable
information provided by coupling constants (J-DP4
method).
These tools were explored to suggest the most probable
structure of controversial natural or unnatural products originally
misassigned, with some predictions further validated by synthesis
(as in the case of pseudorubriflordilactone B). The possibility of
predicting the structure of a natural product without requiring authentic
sample was investigated in collaboration with Prof. Pilli (UNICAMP,
Brazil) in the computer-guided total synthesis and stereochemical
revisions of several natural products. Despite these advances, there
remain considerable challenges, such as the case of configurational
assessment of polar systems featuring multiple intramolecular hydrogen
bonding interactions because of the po...