This protocol is intended to provide chemists who discover or make new organic compounds with a valuable tool for validating the structural assignments of those new chemical entities. Experimental 1 H and/or 13 C NMR spectral data and its proper interpretation for the compound of interest is required as a starting point. The approach involves the following steps: (i) using molecular mechanics calculations (with, e.g., MacroModel) to generate a library of conformers; (ii) using density functional theory (DFT) calculations (with, e.g., Gaussian 09) to determine optimal geometry, free energies and chemical shifts for each conformer; (iii) determining Boltzmann-weighted proton and carbon chemical shifts; and (iv) comparing the computed chemical shifts for two or more candidate structures with experimental data to determine the best fit. For a typical structure assignment of a small organic molecule (e.g., fewer than ∼10 non-H atoms or up to ∼180 a.m.u. and ∼20 conformers), this protocol can be completed in ∼2 h of active effort over a 2-d period; for more complex molecules (e.g., fewer than ∼30 non-H atoms or up to ∼500 a.m.u. and ∼50 conformers), the protocol requires ∼3-6 h of active effort over a 2-week period. To demonstrate the method, we have chosen the analysis of the cis- versus the trans-diastereoisomers of 3-methylcyclohexanol (1-cis versus 1-trans). The protocol is written in a manner that makes the computation of chemical shifts tractable for chemists who may otherwise have only rudimentary computational experience.
Bibliographical noteFunding Information:
acknoWleDGMents We thank T.A. Bedell and N.P. Labello for their contributions to the scripting efforts. We thank C.J. Cramer, A.N. Garr, A.M. Harned, S.S. Humble, K.A. Kalstabakken, J.C. Lo, D.J. Marell, K.W. Wiitala and B.P. Woods for helpful input, feedback and comments at various stages of the protocol development and manuscript preparation. This work was carried out in part using software and hardware resources made available through the University of Minnesota Supercomputing Institute (MSI). The research was supported by a grant awarded by the US National Science Foundation (NSF, CHE-0911696). P.H.W. was supported by an NSF Graduate Research Fellowship.