I have written quite a number of posts on using quantum mechanics computations to predict NMR spectra that can aid in identifying chemical structure. Perhaps the most robust technique is Goodman’s DP4 method (post), which has seen some recent revisions (updated DP4, DP4+). I have also posted on the use of computed coupling constants (posts).

Grimblat, Gavín, Daranas and Sarotti have now combined these two approaches, using computed ¹H and ¹³C chemical shifts and ³J_HH coupling constants with the DP4 framework to predict chemical structure.¹

They describe two different approaches to incorporate coupling constants:

• dJ-DP4 (direct method) incorporates the coupling constants into a new probability function, using the coupling constants in an analogous way as chemical shifts. This requires explicit computation of all chemical shifts and ³J_HH coupling constants for all low-energy conformations.
• iJ-DP4 (indirect method) uses the experimental coupling constants to set conformational constraints thereby reducing the number of total conformations that need be sampled. Thus, large values of the coupling constant (³J_HH > 8 Hz) selects conformations with coplanar hydrogens, while small values (³J_HH < 4 Hz) selects conformations with perpendicular hydrogens. Other values are ignored. Typically, only one or two coupling constants are used to select the viable conformations.

The authors test these two variants on 69 molecules. The original DP4 method predicted the correct stereoisomer for 75% of the examples, while dJ-DP4 correct identifies 96% of the cases. As a test of the indirect method, they examined marilzabicycloallenes A and B (1 and 2). DP4 predicts the correct stereoisomer with only 3.1% (1) or <0.1% (2) probability. dJ-DP4 predicts the correct isomer for 1 with 99.9% probability and 97.6% probability for 2. The advantage of iJ-DP4 is that using one coupling constant reduces the number of conformations that must be computed by 84%, yet maintains a probability of getting the correct assignment at 99.2% or better. Using two coupling constants to constrain conformations means that only 7% of all of the conformations need to be samples, and the predictive power is maintained.

1

2

Both of these new methods clearly deserve further application.

References

1. Grimblat, N.; Gavín, J. A.; Hernández Daranas, A.; Sarotti, A. M., “Combining the Power of J Coupling and DP4 Analysis on Stereochemical Assignments: The J-DP4 Methods.” Org. Letters 2019, 21, 4003-4007, DOI: 10.1021/acs.orglett.9b01193.

InChIs

1: InChI=1S/C15H21Br2ClO4/c1-8-15(20)14-6-10(17)12(19)7-11(18)13(22-14)5-9(21-8)3-2-4-16/h3-4,8-15,19-20H,5-7H2,1H3/t2-,8-,9+,10-,11+,12+,13+,14+,15-/m0/s1
InChIKey=APNVVMOUATXTFG-NTSAAJDMSA-N

2: InChI=1S/C15H21Br2ClO4/c1-8-15(20)14-6-10(17)12(19)7-11(18)13(22-14)5-9(21-8)3-2-4-16/h3-4,8-15,19-20H,5-7H2,1H3/t2-,8-,9-,10-,11+,12+,13+,14+,15-/m0/s1
InChIKey=APNVVMOUATXTFG-SSBNIETDSA-N

Can vibrational spectroscopy be used to identify stereoisomers? Medel, Stelbrink, and Suhm have examined the vibrational spectra of (+)- and (-)-α-pinene, (±)-1, in the presence of four different chiral terpenes 2-5.¹ They recorded gas phase spectra by thermal expansion of a chiral α-pinene with each chiral terpene.

For the complex of 4 with (+)-1 or (-)-1 and 5 with (+)-1 or (-)-1, the OH vibrational frequency is identical for the two different stereoisomers. However, the OH vibrational frequencies differ by 2 cm^-1 with 3, and the complex of 3/(+)-1 displays two different OH stretches that differ by 11 cm^-1. And in the case of the complex of α-pinene with 2, the OH vibrational frequencies of the two different stereoisomers differ by 11 cm^-1!

The B3LYP-D3(BJ)/def2-TZVP optimized geometry of the 2/(+)-1 and 2/(-)-1 complexes are shown in Figure 2, and some subtle differences in sterics and dispersion give rise to the different vibrational frequencies.

2/(+)-1

2/(-)-1

Figure 2. B3LYP-D3(BJ)/def2-TZVP optimized geometry of the 2/(+)-1 and 2/(-)-1

Of interest to readers of this blog will be the DFT study of these complexes. The authors used three different well-known methods – B3LYP-D3(BJ)/def2-TZVP, M06-2x/def2-TZVP, and ωB97X-D/def2-TZVP – to compute structures and (most importantly) predict the vibrational frequencies. Interestingly, M06-2x/def2-TZVP and ωB97X-D/ def2-TZVP both failed to predict the vibrational frequency difference between the complexes with the two stereoisomers of α-pinene. However, B3LYP-D3(BJ)/def2-TZVP performed extremely well, with a mean average error (MAE) of only 1.9 cm^-1 for the four different terpenes. Using this functional and the larger may-cc-pvtz basis set reduced the MAE to 1.5 cm^-1 with the largest error of only 2.5 cm^-1.

As the authors note, these complexes provide some fertile ground for further experimental and computational study and benchmarking.

Reference

1. Medel, R.; Stelbrink, C.; Suhm, M. A., “Vibrational Signatures of Chirality Recognition Between α-Pinene and Alcohols for Theory Benchmarking.” Angew. Chem. Int. Ed. 2019, 58, 8177-8181, DOI: 10.1002/anie.201901687.

InChIs

(-)-1, (-)-α-pinene: InChI=1S/C10H16/c1-7-4-5-8-6-9(7)10(8,2)3/h4,8-9H,5-6H2,1-3H3/t8-,9-/m0/s1
InChIKey=GRWFGVWFFZKLTI-IUCAKERBSA-N

(+)-1, (-)-α-pinene: InChI=1S/C10H16/c1-7-4-5-8-6-9(7)10(8,2)3/h4,8-9H,5-6H2,1-3H3/t8-,9-/m1/s1
InChIKey=GRWFGVWFFZKLTI-RKDXNWHRSA-N

2, (-)borneol: InChI=1S/C10H18O/c1-9(2)7-4-5-10(9,3)8(11)6-7/h7-8,11H,4-6H2,1-3H3/t7-,8+,10+/m0/s1
InChiKey=DTGKSKDOIYIVQL-QXFUBDJGSA-N

3, (+)-fenchol: InChI=1S/C10H18O/c1-9(2)7-4-5-10(3,6-7)8(9)11/h7-8,11H,4-6H2,1-3H3/t7-,8-,10+/m0/s1
InChIKey=IAIHUHQCLTYTSF-OYNCUSHFSA-N

4, (-1)-isopinocampheol: InChI=1S/C10H18O/c1-6-8-4-7(5-9(6)11)10(8,2)3/h6-9,11H,4-5H2,1-3H3/t6-,7+,8-,9-/m1/s1
InChIKey=REPVLJRCJUVQFA-BZNPZCIMSA-N

5, (1S)-1-phenylethanol: InChI=1S/C8H10O/c1-7(9)8-5-3-2-4-6-8/h2-7,9H,1H3/t7-/m0/s1
InChIKey=WAPNOHKVXSQRPX-ZETCQYMHSA-N