Search Results for "coupling"

dJ-DP4 and iJ-DP4: including coupling constants

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 3JHH 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 3JHH 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 (3JHH > 8 Hz) selects conformations with coplanar hydrogens, while small values (3JHH < 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

NMR Steven Bachrach 26 Jun 2019 No Comments

New Procedure for computing NMR spectra with spin-spin coupling

Computed NMR spectra have become a very useful tool in identifying chemical structures. I have blogged on this multiple times. A recent trend has been the development of computational procedures that lead to computed spectra (again, see that above link). Now, Grimme, Neese and coworkers have offered their approach to computed NMR spectra, including spin-spin splitting.1

Their procedure involves four distinct steps.

  1. Generation of the conformer and rotamer space. This is a critical distinctive element of their method in that they take a number of different tacks for sampling conformational space to insure that they have identified all low-energy structures. This involves a combination of normal mode following, genetic structure crossing (based on genetic algorithms for optimization), and molecular dynamics. Making this all work is their choice of using the computational efficient GFN-xTB2 quantum mechanical method.
  2. The low-energy structures are then subjected to re-optimization at PBEh-3c and then single-point energies obtained at DSD-BLYP-D3/def2-TZVPP including treatment of solvation by COSMO-RS. The low-energy structures that contribute 4% or more of the Boltzmann-weighted population are then carried forward.
  3. Chemical shifts and spin-spin coupling constants are then computed with the PBE0 method and the pcS and pcJ basis sets developed by Jensen for computing NMR shifts.3
  4. Lastly, the chemical shifts and coupling constants are averaged and the spin Hamiltonian is solved.

The paper provides a number of examples of the application of the methodology, all with quite good success. The computer codes to run this method are available for academic use from xtb@thch.uni-bonn.de.

References

1) Grimme, S.; Bannwarth, C.; Dohm, S.; Hansen, A.; Pisarek, J.; Pracht, P.; Seibert, J.; Neese, F., "Fully Automated Quantum-Chemistry-Based Computation of Spin–Spin-Coupled Nuclear Magnetic Resonance Spectra." Angew. Chem. Int. Ed. 2017, 56, 14763-14769, DOI: 10.1002/anie.201708266.

2) Grimme, S.; Bannwarth, C.; Shushkov, P., "A Robust and Accurate Tight-Binding Quantum Chemical Method for Structures, Vibrational Frequencies, and Noncovalent Interactions of Large Molecular Systems Parametrized for All spd-Block Elements (Z = 1–86)." J. Chem. Theory Comput. 2017, 13, 1989-2009, DOI: 10.1021/acs.jctc.7b00118.

3) Jensen, F., "Basis Set Convergence of Nuclear Magnetic Shielding Constants Calculated by Density Functional Methods." J. Chem. Theory Comput. 2008, 4, 719-727, DOI: 10.1021/ct800013z.

Grimme &NMR Steven Bachrach 05 Feb 2018 No Comments

NMR coupling constants of strychnine

Helgaker, Jaszunski, and Swider1 have examined the use of B3LYP with four different basis sets to compute the spin-spin coupling constants in strychnine 1.


1

They used previously optimized coordinates of the two major conformations of strychnine, shown in Figure 1.

Conformer A

Conformer B

Figure 1. Confrmations of strychnine 1.

They tested four basis sets designed for NMR computations: pcJ-0,2 pcJ-1,2 6-31G-J,3 and 6-311G-J.3 pCJ-0 and 6-31G-J are relatively small basis sets, while the other two are considerably larger.

All four basis sets provide values of the 122 J(C-H) with a root mean square deviation of less than 0.6 Hz. J(HH) and J(CC) coupling constants are also well predicted, especially with the larger pcJ-1 basis set. They also examined the four Ramsey terms in the coupling model. The Fermi contact term dominates, and if the large pcJ-1 basis set is used to calculate it, and the smaller pcJ-0 basis set is used for the other three terms, the RMS error only increases from 0.18 to 0.20 Hz. Taking this to the extreme, they omitted calculating any of the non-Fermi contact terms, with again only small increases in the RMS – even with the small pcJ-0 basis set. Considering the computational costs, one should seriously consider whether the non-Fermi contact terms and a small basis set might be satisfactory for your own problem(s) at hand.

References

1) Helgaker, T.; Jaszuński, M.; Świder, P., "Calculation of NMR Spin–Spin Coupling Constants in Strychnine." J. Org. Chem. 2016, ASAP, DOI: 10.1021/acs.joc.6b02157.

2) Jensen, F., "The Basis Set Convergence of Spin−Spin Coupling Constants Calculated by Density Functional Methods." J. Chem. Theor. Comput. 2006, 2, 1360-1369, DOI: 10.1021/ct600166u.

3) Kjær, H.; Sauer, S. P. A., "Pople Style Basis Sets for the Calculation of NMR Spin–Spin Coupling Constants: the 6-31G-J and 6-311G-J Basis Sets." J. Chem. Theor. Comput. 2011, 7, 4070-4076, DOI: 10.1021/ct200546q.

InChIs

Strychnine 1: InChI=1S/C21H22N2O2/c24-18-10-16-19-13-9-17-21(6-7-22(17)11-12(13)5-8-25-16)14-3-1-2-4-15(14)23(18)20(19)21/h1-5,13,16-17,19-20H,6-11H2/t13-,16-,17-,19-,20-,21+/m0/s1
InChIKey=QMGVPVSNSZLJIA-FVWCLLPLSA-N

NMR Steven Bachrach 15 Nov 2016 No Comments

Computed C-C NMR coupling constants

The use of computed NMR coupling constants is starting to grow. In a previous post I discussed a general study by Rablen and Bally on methods for computing JHH coupling constants. Now Williamson reports methods to experimentally obtain 1 JCC and 3JCC coupling constants.1 These were obtained for strychnine. He then computed the coupling constants in two steps. Using the B3LYP/6-31G(d) optimized geometry, first the Fermi contact contribution was computed at B3LYP/6-31+G(d,p) by uncontracting the basis set and adding an additional tighter set of polarization functions. Second, the remaining terms (spin-dipolar, paramagnetic spin-orbit and diamagnetic spin-orbit coupling) were computed with the 6-31+Gd,p) set without modifications. The two computed terms were added to give the final estimate.

A plot of the experimental vs. the DFT computed 1 JCC and 3JCC coupling constants shows
an excellent linear relation, with correlation coefficient of 0.9986 and a slope of 0.98. The mean absolute deviation for the computed and experimental 1 JCC and 3JCC coupling constants is 1.0
Hz and 0.4 Hz, respectively, both well within the experimental error.

I expect that computed NMR spectra will continue to be a growth area, especially for structural identification.

References

(1) Williamson, R. T.; Buevich, A. V.; Martin, G. E. "Experimental and Theoretical Investigation of 1JCC and nJCC Coupling Constants in Strychnine," Org. Letters 2012, 14, 5098-5101, DOI: 10.1021/ol302366s

InChIs

strychnine:
InChI=1S/C21H22N2O2/c24-18-10-16-19-13-9-17-21(6-7-22(17)11-12(13)5-8-25-16)14-3-1-2-4-15(14)23(18)20(19)21/h1-5,13,16-17,19-20H,6-11H2/t13-,16-,17-,19-,20-,21+/m0/s1
InChIKey=QMGVPVSNSZLJIA-FVWCLLPLSA-N

NMR Steven Bachrach 14 Nov 2012 3 Comments

Calculating NMR proton-proton coupling constants

Bally and Rablen have followed up their important study of the appropriate basis sets and density functional needed to compute NMR chemical shifts1 (see this post) with this great examination of procedures for computing proton-proton coupling constants.2

They performed a comparison of 165 experimental coupling constants from 66 small, rigid molecules with computed proton-proton coupling constants. They use a variety of basis sets and functionals. They also test whether all four components that lead to nuclear-nuclear spin coupling constants are need, or if just the Fermi contact term would suffice.

The computationally most efficient procedure, one that still provides excellent agreement with the experimental coupling constants is the following:

  1. optimize the geometry at B3LYP/6-31G(d)
  2. Calculate only the proton-proton Fermi contact terms at B3LYP/6-31G(d,p)u+1s[H]. The basis set used for computing the Fermi contact terms is unusual. The basis set for hydrogen (denoted as “u+1s[H]”) uncontracts the core functions and adds one more very compact 1s function.
  3. Scale the Fermi contact terms by 0.9155 to obtain the proton-proton coupling constants.

This methodology provides coupling constants with a mean error of 0.51 Hz, and when applied to a probe set of 61 coupling constants in 37 different molecules (including a few that require a number of conformers and thus a Boltzmann-weighted averaging of the coupling constants) the mean error is only 0.56 Hz.

Bally and Rablen supply a set of scripts to automate the computation of the coupling constants according to this prescription; these scripts are available in the supporting materials and also on the Cheshire web site. It should also be noted that the procedure described above can be performed with Gaussian-09; no other software is needed. Thus, these computations are amenable to synthetic chemists with a basic understanding of quantum chemistry.

References

(1) Jain, R.; Bally, T.; Rablen, P. R., "Calculating Accurate Proton Chemical Shifts of Organic Molecules with Density Functional Methods and Modest Basis Sets," J. Org. Chem., 2009, 74, 4017-4023, DOI: 10.1021/jo900482q.

(2) Bally, T.; Rablen, P. R., "Quantum-Chemical Simulation of 1H NMR Spectra. 2. Comparison of DFT-Based Procedures for Computing Proton-Proton Coupling Constants in Organic Molecules," J. Org. Chem., 2011, 76, 4818-4830, DOI: 10.1021/jo200513q

NMR Steven Bachrach 13 Dec 2011 6 Comments

An even shorter non-bonding HH distance

The competition for finding molecules with ever-closer non-bonding HH interactions is heating up. I have previously blogged about 1, a in,in-Bis(hydrosilane) designed by Pascal,1 with an HH distance of 1.57 Å, and also blogged about 2, the dimer of tri(di-t-butylphenyl)methane,2 where the distance between methine hydrogens on adjacent molecules is 1.566 Å.

Now Pascal reports on 3, which shows an even closer HH approach.3

The x-ray structure of 3 shows the in,in relationship of the two critical hydrogens, HA and HB. Though the positions of these hydrogens were refined, the C-H distance are artificially foreshortened. A variety of computed structures are reported, and these all support a very short HH non-bonding distance of about 1.52 Å. The B3PW91-D3/cc-pVTZ optimized structure is shown in Figure 1.

Figure 1. B3PW91-D3/cc-pVTZ optimized structure of 3.

The authors also note an unusual feature of the 1H NMR spectrum of 3: the HB signal appears as a double with JAB= 2.0 Hz. B3LYP/6–311++G(2df,2pd) NMR computations indicated a coupling of 3.1 Hz. This is the largest through-space coupling recorded.

References

1. Zong, J.; Mague, J. T.; Pascal, R. A., "Exceptional Steric Congestion in an in,in-Bis(hydrosilane)." J. Am. Chem. Soc. 2013, 135, 13235-13237, DOI: 10.1021/ja407398w.

2. Rösel, S.; Quanz, H.; Logemann, C.; Becker, J.; Mossou, E.; Cañadillas-Delgado, L.; Caldeweyher, E.; Grimme, S.; Schreiner, P. R., "London Dispersion Enables the Shortest Intermolecular Hydrocarbon H···H Contact." J. Am. Chem. Soc. 2017, 139, 7428–7431, DOI: 10.1021/jacs.7b01879.

3. Xiao, Y.; Mague, J. T.; Pascal, R. A., "An Exceptionally Close, Non-Bonded Hydrogen–Hydrogen Contact with Strong Through-Space Spin–Spin Coupling." Angew. Chem. Int. Ed. 2018, 57, 2244-2247, DOI: 10.1002/anie.201712304.

InChI

3: InChI=1S/C27H24S3/c1-4-17-13-28-10-16-11-29-14-18-5-2-8-21-24(18)27-23(17)20(7-1)26(21)22-9-3-6-19(25(22)27)15-30-12-16/h1-9,16,26-27H,10-15H2
InChIKey=NJBHGDPNFALCTL-UHFFFAOYSA-N

Uncategorized Steven Bachrach 22 May 2018 1 Comment

Computed spectra and the structure of (+)-frondosin B

The structure of (+)-frondosin B 1 has been the subject of some concern. The compound has been synthesized by a number of research groups with the expected R isomer as the target. However, the Danishefsky1 and MacMillan2 synthesis led to a molecule with [α]D of about +16°, while Trauner3 reports a value of -16.8° and Ovaska4 prepared the S isomer with [α]D = -17.3°. Something is amiss here.

Joyce and coworkers have looked into this structure problem through a combination of advanced analytical techniques and computational chemistry.5 They utilize optical activity, electronic circular dichroism (ECD) and vibrational circular dichroism (VCD) and compare the experiments with computational results. IR and VCD were computed at B3LYP/6-31G** using a Boltzmann-weighted set of low-energy conformations. ECD computations were done at CAM-B3LYP/6-31++G**//B3LYP/6-31G**.

Basically, they found that (+)-frondosin B does have the R stereocenter. The different synthetic schemes did actually all lead to the same isomer, tested by looking at key intermediates along the way. The discrepancy in the optical activity is due to a small impurity, 2, that has the opposite rotation and a magnitude 10 times greater than that of authentic 1.

This paper is another nice example demonstrating the power of modern computational approaches to spectra that can be extremely valuable in structure determination. Organic chemists of all stripes should certainly be aware of how this tool can complement experiments.

My thanks to Derek Lowe who posted on this paper in his In The Pipeline blog.

References

1) Inoue, M.; Carson, M. W.; Frontier, A. J.; Danishefsky, S. J., "Total Synthesis and Determination of the Absolute Configuration of Frondosin B." J. Am. Chem. Soc.
2001, 123, 1878-1889, DOI: 10.1021/ja0021060.

2) Reiter, M.; Torssell, S.; Lee, S.; MacMillan, D. W. C., "The organocatalytic three-step total synthesis of (+)-frondosin B." Chem. Sci. 2010, 1, 37-42, DOI: 10.1039/C0SC00204F.

3) Hughes, C. C.; Trauner, D., "Palladium-catalyzed couplings to nucleophilic heteroarenes: the total synthesis of (−)-frondosin B." Tetrahedron 2004, 60, 9675-9686, DOI: 10.1016/j.tet.2004.07.041.

4) Ovaska, T. V.; Sullivan, J. A.; Ovaska, S. I.; Winegrad, J. B.; Fair, J. D., "Asymmetric Synthesis of Seven-Membered Carbocyclic Rings via a Sequential Oxyanionic 5-Exo-Dig Cyclization/Claisen Rearrangement Process. Total Synthesis of (−)-Frondosin B." Org. Letters 2009, 11, 2715-2718, DOI: 10.1021/ol900967j.

5) Joyce, L. A.; Nawrat, C. C.; Sherer, E. C.; Biba, M.; Brunskill, A.; Martin, G. E.; Cohen, R. D.; Davies, I. W., "Beyond optical rotation: what’s left is not always right in total synthesis." Chem. Sci. 2018, 9, 415-424, DOI: 10.1039/C7SC04249C.

InChIs

1: InChI=1S/C20H24O2/c1-12-6-8-16-14(5-4-10-20(16,2)3)18-15-11-13(21)7-9-17(15)22-19(12)18/h7,9,11-12,21H,4-6,8,10H2,1-3H3/t12-/m1/s1
InChIKey=LSPMJSWSYGOLFD-GFCCVEGCSA-N

2: InChI=1S/C20H24O2/c1-12-5-4-10-20(3)16(12)8-6-13(2)19-18(20)15-11-14(21)7-9-17(15)22-19/h7,9,11,13,21H,4-6,8,10H2,1-3H3/t13-,20-/m1/s1
InChIKey=ZBXZDKMLFIJFHG-ZUOKHONESA-N

Optical Rotation Steven Bachrach 26 Mar 2018 No Comments

More applications of computed NMR spectra

In this post I cover two papers discussing application of computed NMR chemical shifts to structure identification and (yet) another review of computational techniques towards NMR structure prediction.

Grimblat, Kaufman, and Sarotti1 take up the structure of rubriflordilactone B 1, which was isolated from Schisandra rubriflora. The compound was then synthesized and its x-ray structure reported, however its NMR did not match with the natural extract. It was suggested that there were actually two compounds in the extract, the minor one was less soluble and is the crystallized 1, and a second compound responsible for the NMR signal.

The authors looked at all stereoisomers of this molecule keeping the three left-most rings intact. The low energy rotamers of these 32 stereoisomers were then optimized at B3LYP/6-31G* and the chemical shifts computed at PCM(pyridine)/mPW1PW91/6-31+G**. To benchmark the method, DP4+ was used to identify which stereoisomer best matches with the observed NMR of authentic 1; the top fit (92.6% probability) was the correct structure.

The 32 stereoisomers were then tested against the experimental NMR of the natural extract. DP4+ with just the proton shifts suggested structure 2 (99.8% probability); however, the 13C chemical shifts predicted a different structure. Re-examination of the reported chemical shifts identifies some mis-assigned signals, which led to a higher C-DP4+ prediction. When all 128 stereoisomers were tested, structure 2 had the highest DP4+ prediction (99.5%), but the C-DP4+ prediction remained problematic (10.8%). Analyzing the geometries of all reasonable alternative for agreement with the NOESY spectrum confirmed 2. These results underscore the importance of using all data sources.

Reddy and Kutateladze point out the importance of using coupling constants along with chemical shifts in structure identification.2 They examined cordycepol A 3, obtained from Cordyceps ophioglossoides. They noted that the computed chemical shifts and coupling constants of originally proposed structure 3a differed dramatically from the experimental values.

They first proposed that the compound has structure 3b. The computed coupling constants using their relativistic force field.3 The experimental coupling constants for the proton H1 are 13.4 and 7.1 Hz. The computed values for 3a are 8.9 and 1.6 Hz, and this structure is clearly incorrect. The coupling constants are improved with 3b, but the 13C chemical shifts are in poor agreement with experiment. So, they proposed structure 3c, the epimer at both C1 and C11 of the original structure.

They optimized four conformations of 3c at B3LYP/6-31G(d) and obtained Boltzmann-weighted chemical shifts at mPW1PW91/6-311+G(d,p). The RMS deviation of the computed 13C chemical shifts relative to the experiment is only 1.54 ppm, and more importantly, the computed coupling constants of 13.54 and 6.90 Hz are in excellent agreement with the experiment values.

Lastly, Grimblat and Sarotti present a review of a number of methods for using computed NMR chemical shifts towards structure prediction.4 These methods include CP3, DP4, DP4+ (all of which I have posted on in the past) and an artificial neural network approach of their own design. They discuss a number of interesting cases where each of these methods has been crucial in identifying the correct chemical structure.

References

1. Grimblat, N.; Kaufman, T. S.; Sarotti, A. M., "Computational Chemistry Driven Solution to Rubriflordilactone B." Org. Letters 2016, 18, 6420-6423, DOI: 10.1021/acs.orglett.6b03318.

2. Reddy, D. S.; Kutateladze, A. G., "Structure Revision of an Acorane Sesquiterpene Cordycepol A." Org. Letters 2016, 18, 4860-4863, DOI: 10.1021/acs.orglett.6b02341.

3. (a) Kutateladze, A. G.; Mukhina, O. A., "Minimalist Relativistic Force Field: Prediction of Proton–Proton Coupling Constants in 1H NMR Spectra Is Perfected with NBO Hybridization Parameters." J. Org. Chem. 2015, 80, 5218-5225, DOI: 10.1021/acs.joc.5b00619; (b) Kutateladze, A. G.; Mukhina, O. A., "Relativistic Force Field: Parametrization of 13C–1H Nuclear Spin–Spin Coupling Constants." J. Org. Chem. 2015, 80, 10838-10848, DOI: 10.1021/acs.joc.5b02001.

4. Grimblat, N.; Sarotti, A. M., "Computational Chemistry to the Rescue: Modern Toolboxes for the Assignment of Complex Molecules by GIAO NMR Calculations." Chem. Eur. J. 2016, 22, 12246-12261, DOI: h10.1002/chem.201601150.

InChIs

1: InChI=1S/C28H30O6/c1-13-9-20(32-26(13)30)25-14(2)24-17-6-5-15-12-28-21(8-7-16(15)18(17)10-19(24)31-25)27(3,4)33-22(28)11-23(29)34-28/h5-9,14,19-22,24-25H,10-12H2,1-4H3/t14-,19+,20-,21-,22+,24-,25-,28+/m0/s1
InChIKey=JGSLSHOXBXVVTQ-NEUKEVNNSA-N

2: InChI=1S/C28H30O6/c1-13-9-20(32-26(13)30)25-14(2)24-17-6-5-15-12-28-21(8-7-16(15)18(17)10-19(24)31-25)27(3,4)33-22(28)11-23(29)34-28/h5-9,14,19-22,24-25H,10-12H2,1-4H3/t14-,19-,20-,21-,22+,24+,25-,28+/m0/s1
InChIKey=JGSLSHOXBXVVTQ-WQIRXNRDSA-N

3c: InChI=1S/C16H28O2/c1-6-11(2)9-14-16(5)12(3)7-8-13(16)15(4,17)10-18-14/h9,12-14,17H,6-8,10H2,1-5H3/b11-9-/t12-,13-,14-,15-,16+/m0/s1
InChIKey=WPQIVUHVYBQTBG-AWEVENECSA-N

NMR Steven Bachrach 04 Oct 2017 No Comments

Nanobelt

The synthesis of components of nanostructures (like fullerenes and nanotubes) has dramatically matured over the past few years. I have blogged about nanohoops before, and this post presents the recent work of the Itami group in preparing the nanobelt 1.1


1

The synthesis is accomplished through a series of Wittig reactions with an aryl-aryl coupling to stitch together the final rings. The molecule is characterized by NMR and x-ray crystallography. The authors have also computed the structure of 1 at B3LYP/6-31G(d), shown in Figure 1. The computed C-C distances match up very well with the experimental distances. The strain energy of 1, presumably estimated by Reaction 1,2 is computed to be about 119 kcal mol-1.

1

Figure 1. B3LYP/6-31G(d) optimized structure of 1.

Rxn 1

NICS(0) values were obtained at B3LYP/6-311+G(2d,p)//B3LYP/6-31G(d); the rings along the middle of the belt have values of -7.44ppm and are indicative of normal aromatic 6-member rings, while the other rings have values of -2.00ppm. This suggests the dominant resonance structure shown below:

References

1) Povie, G.; Segawa, Y.; Nishihara, T.; Miyauchi, Y.; Itami, K., "Synthesis of a carbon nanobelt." Science 2017, 356, 172-175, DOI: 10.1126/science.aam8158.

2) Segawa, Y.; Yagi, A.; Ito, H.; Itami, K., "A Theoretical Study on the Strain Energy of Carbon Nanobelts." Org. Letters 2016, 18, 1430-1433, DOI: 10.1021/acs.orglett.6b00365.

InChIs:

1: InChI=1S/C48H24/c1-2-26-14-40-28-5-6-31-20-44-32(19-42(31)40)9-10-34-24-48-36(23-46(34)44)12-11-35-21-45-33(22-47(35)48)8-7-30-17-41-29(18-43(30)45)4-3-27-15-37(39(26)16-28)25(1)13-38(27)41/h1-24H
InChIKey=KJWRWEMHJRCQKK-UHFFFAOYSA-N

Aromaticity &nanohoops Steven Bachrach 22 May 2017 No Comments

Dynamic effects in computing NMR (and a patent issue?)

The prediction of NMR chemical shifts and coupling constants through ab initio computation is a major development of the past decade in computational organic chemistry. I have written about many developments on this blog. An oft-used method is a linear scaling of the computed chemical shifts to match those of some test set. Kwan and Liu wondered if the dynamics of molecular motions might be why we need this correction.1

They suggest that the chemical shift can be computed as

<σ> = σ(static molecule using high level computation) + error

where the error is the obtained by using a low level computation taking the difference between the chemical shifts obtained on a dynamic molecule less that obtained with a static molecule. The dynamic system is obtained by performing molecular dynamics of the molecule, following 25 trajectories and sampling every eighth point.

They find outstanding agreement for the proton chemical shift of 12 simple molecules (mean error of 0.02 ppm) and the carbon chemical shift of 19 simple molecules (mean error of 0.5 ppm) without any scaling. Similar excellent agreement is found for a test set of natural products.

They finish up with a discussion of [18]annulene 1. The structure of 1 is controversial. X-ray crystallography indicates a near D6h geometry, but the computed NMR shifts using a D6h geometry are in dramatic disagreement with the experimental values, leading Schleyer to suggest a C2  geometry. Kwan and Liu applied their dynamic NMR method to the D6h, D3h, and C2 structures, and find the best agreement with the experimental chemical shifts are from the dynamic NMR initiated from the D6h geometry. Dynamic effects thus make up for the gross error found with the static geometry, and now bring the experimental and computational data into accord.

One final note on this paper. The authors indicate that they have filed a provisional patent on their method. I am disturbed by this concept of patenting a computational methodology, especially in light of the fact that many other methods have been made available to the world without any legal restriction. For example, full details including scripts to apply Tantillo’s correction method are available through the Cheshire site and a web app to implement Goodman’s DP4 method are available for free. Provisional patents are not available for review from the US Patent Office so I cannot assess just what is being protected here. However, I believe that this action poses a real concern over the free and ready exchange of computational methodologies and ideas.

References

(1) Kwan, E. E.; Liu, R. Y. "Enhancing NMR Prediction for Organic Compounds Using Molecular Dynamics," J. Chem. Theor. Comput. 2015, 11, 5083-5089, DOI: 10.1021/acs.jctc.5b00856.

InChIs

1: InChI=1S/C18H18/c1-2-4-6-8-10-12-14-16-18-17-15-13-11-9-7-5-3-1/h1-18H/b2-1-,3-1+,4-2+,5-3+,6-4+,7-5-,8-6-,9-7+,10-8+,11-9+,12-10+,13-11-,14-12-,15-13+,16-14+,17-15+,18-16+,18-17-
InChIKey=STQWAGYDANTDNA-DWSNDWDZSA-N

NMR Steven Bachrach 11 Jan 2016 4 Comments

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