Archive for the 'NMR' Category

More examples of structure determination with computed NMR chemical shifts

Use of computed NMR chemical shifts in structure determination is really growing fast. Presented here are a couple of recent examples.

Nguyen and Tantillo used computed chemical shifts with the DP4 analysis to identify the structure of three terpenes 1-3.1 They optimized the geometries of all of the diastereomers of each compound, along with multiple conformations of each diastereomer, at B3LYP/6-31+G(d,p) and then computed the chemical shifts at SMD(CHCl3)–mPW1PW91/6-311+G(2d,p). The chemical shifts were Boltzmann weighted including all conformations within 3 kcal mol-1 of the lowest energy structure.

For 1, the DP4 analysis using just the proton shifts predicted a different isomer than using the carbon shifts, but when combined, DP4 predicted the structure, with 98.8% confidence, shown in the scheme above, and in Figure 1. For 2, the combined proton and carbon shift analysis with DP4 indicated a 100% confidence of the structure shown in the scheme and Figure 1. Lastly, for 3, which is more complicated due to the conformations of the 9-member ring, DP4 predicts with 100% confidence the structure shown in the scheme and Figure 1.




Figure 1. Optimized geometries of 1-3.

Feng, Davis and coworkers have examined a series of anthroquionones from Australian marine sponges.2 The structure of one compound was a choice of two options: 4 or 5. Initial geometries were obtain by molecular mechanics and the low energy isomers were then reoptimized at B3LYP/6-31+G(d,p). The chemical shifts were computed using PCM/MPW1PW91/6-311+G(2d,p). Application of the DP4 method indicate the structure to be 4 with a 100% confidence level. The lowest energy conformer of 4 is shown in Figure 2.

Figure 2. Optimized geometry of 4.


1) Nguyen, Q. N. N.; Tantillo, D. J. “Using quantum chemical computations of NMR chemical shifts to assign relative configurations of terpenes from an engineered Streptomyces host,” J. Antibiotics 2016, 69, 534–540, DOI: 10.1038/ja.2016.51.

2) Khokhar, S.; Pierens, G. K.; Hooper, J. N. A.; Ekins, M. G.; Feng, Y.; Rohan A. Davis, R. A. “Rhodocomatulin-Type Anthraquinones from the Australian Marine Invertebrates Clathria hirsuta and Comatula rotalaria,” J. Nat. Prod., 2016, 79, 946–953, DOI: 10.1021/acs.jnatprod.5b01029.


1: InChI=1S/C15H24/c1-10-5-6-15(4)8-11-7-14(2,3)9-12(11)13(10)15/h9-11,13H,5-8H2,1-4H3/t10-,11+,13-,15+/m1/s1

2: InChI=1S/C15H24/c1-10-5-6-15(4)8-11-7-14(2,3)9-12(11)13(10)15/h5,11-13H,6-9H2,1-4H3/t11-,12-,13+,15-/m0/s1

3: InChI=1S/C20H32/c1-14-6-9-18-19(3,4)10-11-20(18,5)13-17-15(2)7-8-16(17)12-14/h6,13,15-16,18H,7-12H2,1-5H3/b14-6-,17-13-/t15-,16-,18-,20+/m0/s1

4: InChI=1S/C18H14O7/c1-7(19)13-10(20)6-11(21)15-16(13)17(22)9-4-8(24-2)5-12(25-3)14(9)18(15)23/h4-6,20-21H,1-3H3

5: InChI=1S/C18H14O7/c1-7(19)13-10(20)6-11(21)15-16(13)14-9(17(22)18(15)23)4-8(24-2)5-12(14)25-3/h4-6,20-21H,1-3H3

NMR &terpenes Steven Bachrach 25 Oct 2016 No Comments

Further development of DP4 for NMR structure determination

Computational chemistry has had a remarkable impact on the field of structure determination by NMR spectroscopy. The ability to efficiently compute 13C and 1H chemical shifts allows for comparison of the computed chemical shifts of potential structures against the experimental values, a tremendous aid in structure determination (see some examples in previous posts). Goodman and Smith developed the DP4 method1 (see this post) to assist in identifying proper structures by means of statistical distribution of errors and Bayes Theorem.

The Goodman group now reports on workflow solutions to structure prediction using DP4.2 They explore the use of open source computational tools both for predicting conformations and for computing the chemical shifts. They use a set of 10 drugs to test the performance. In general, the original DP4 method works very well in predicting drug structure, despite the fact that DP4 parameters were developed for natural products. The only failure is for simvastatin, where the large number of diastereomers and conformational flexibility prove to be too complex. The open source tools perform just slightly less effectively than the commercial packages, but are certainly a viable route for those with limited resources. The authors also provide a series of python scripts that allow users to create a seamless workflow; these should prove most helpful to the structure determination community.



1) Smith, S. G.; Goodman, J. M. "Assigning Stereochemistry to Single Diastereoisomers by GIAO
NMR Calculation: The DP4 Probability," J. Am. Chem. Soc. 2010, 132, 12946-12959, DOI: 10.1021/ja105035r.

2) Ermanis, K.; Parkes, K. E. B.; Agback, T.; Goodman, J. M. “Expanding DP4: application to drug compounds and automation,” Org. Biomol. Chem., 2016, 14, 3943-3949, DOI: 10.1039/c6ob00015k.


Simvastatin: InChI=1S/C25H38O5/c1-6-25(4,5)24(28)30-21-12-15(2)11-17-8-7-16(3)20(23(17)21)10-9-19-13-18(26)14-22(27)29-19/h7-8,11,15-16,18-21,23,26H,6,9-10,12-14H2,1-5H3/t15-,16-,18+,19+,20-,21-,23-/m0/s1

NMR Steven Bachrach 11 Oct 2016 No Comments

Predicting chemical structure using DP4+

Structure determination has been greatly facilitated by the use of computed NMR spectra to compare with experimental spectra. Perhaps the best method for doing this is the DP4 procedure developed by Smith and Goodman.1 (I have a previous post on their paper.) The basic idea is that if you have an experimental NMR spectrum and a number of potential structures, the computed spectra for each possibility are ranked by a statistical treatment based on the Student t-test.

Grimblat, Zanardi, and Sarotti question a couple of the assumptions embedded within the DP4 method, and offer a revision that they call DP4+.2 The two assumptions are (1) that the chemical shifts are computed at B3LYP/6-31G**//MMFF and (2) that the chemical shifts are scaled and then utilized in the analysis.

To test these assumptions, they examine a set of 72 organic compounds comprising 1219 13C shifts and 1123 1H shifts. They optimized the structures at B3LYP/6-31G* and computed the chemical shifts of these compounds using the B3LYP and mPW1PW91 functionals with 6 basis sets (6-31G*, 6-31G**, 6-31+G**, 6-311G*, 6-311G**, and 6-311+G**). With all of the combinations, the standard deviation of both the proton and carbon chemical shifts were significantly smaller than with the originally proposed method.

With regards to the second assumption, they define a new probability functions that multiplies the error using scaled chemical shifts with the error using unscaled chemical shifts, and this they call DP4+. Again with all of the computational methods, the DP4+ prediction outperforms the DP4 prediction.

As a test case, they looked at cryptomoscatone D1 and D2 (1), for which the structures were determined with traditional methods. DP4 predicts that both cryptomoscatone D1 and D2 are structure 1d. However, DP4+ correctly predicts that cryptomoscatone D1 is 1b and cryptomoscatone D2 is 1a.

Lin and Tagliatatela-Scafati have reported the use of DP4+ to aid in the structure determination of plakdiepoxide 2.3 ROESY NMR could not provide definitive judgement of the stereochemical relationship about the bond between the two epoxide rings. They computed a number of conformers of the model compounds 2a and 2b at B3LYP/6-31G(d). The computed chemical shifts were then used with the DP4+ procedure to determine that the structure has the stereochemistry of 2b.


(1) Smith, S. G.; Goodman, J. M. "Assigning Stereochemistry to Single Diastereoisomers by GIAO NMR Calculation: The DP4 Probability," J. Am. Chem. Soc. 2010, 132, 12946-12959, DOI: 10.1021/ja105035r.

(2) Grimblat, N.; Zanardi, M. M.; Sarotti, A. M. "Beyond DP4: an Improved Probability
for the Stereochemical Assignment of Isomeric Compounds using Quantum Chemical Calculations of NMR Shifts," J. Org. Chem. 2015, 80, 12526-12534, DOI: 10.1021/acs.joc.5b02396.

(3) Chianese, G.; Yu, H.-B.; Yang, F.; Sirignano, C.; Luciano, P.; Han, B.-N.; Khan, S.; Lin, H.-W.; Taglialatela-Scafati, O. "PPAR Modulating Polyketides from a Chinese Plakortis simplex and Clues on the Origin of Their Chemodiversity," J. Org. Chem. 2016, 81 (12), 5135–5143, DOI: 10.1021/acs.joc.6b00695.


Cryptomoscatone D1: InChI=1S/C17H20O4/c18-14(10-9-13-5-2-1-3-6-13)11-15(19)12-16-7-4-8-17(20)21-16/h1-6,8-10,14-16,18-19H,7,11-12H2/b10-9+/t14-,15-,16-/m1/s1

Cryptomoscatone D2: InChI=1S/C17H20O4/c18-14(10-9-13-5-2-1-3-6-13)11-15(19)12-16-7-4-8-17(20)21-16/h1-6,8-10,14-16,18-19H,7,11-12H2/b10-9+/t14-,15+,16+/m0/s1

plakdiepoxide: InChI=1S/C18H32O4/c1-6-9-10-13(4)12-17(7-2)16(22-17)18(8-3)14(21-18)11-15(19)20-5/h13-14,16H,6-12H2,1-5H3/t13?,14-,16-,17+,18-/m0/s1

NMR Steven Bachrach 20 Jun 2016 1 Comment

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.


(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.


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-

NMR Steven Bachrach 11 Jan 2016 3 Comments

Structure revision: Vescalagin and Castalagin

Vescalagin 1 and castalagin 2 are found in plants and also in wine and whisky. They possess some intriguing stereochemistry and the topic of interest in the paper by Tanaka and coworkers is the stereochemistry of the triphenyl fragment.1 The original proposed structure indicated a (S,S) (1a and 2a) configuration, yet a molecular mechanics study suggest the (S,R) (1b and 2b) configuration would be lower in energy.

1a: R1 = OH, R2 = H
2a: R1 = H, R2 = OH

1b: R1 = OH, R2 = H
2b: R1 = H, R2 = OH

Recognizing the power of DFT computations in resolving this type of structural problem, Tanaka measured the ECD spectrum of the hydrolyzed forms of 1 and 2, namely 3 and 4. The (S,S) and (S,R) isomers of 3 and 4 were subjected to a Monte Carlo search using MM. Low-lying conformers were reoptimized at B3LYP/6-31G(d,p) including PCM, modeling methanol as the solvent. The ECD spectrum was then predicted using all conformations with a population over 1%. The computed spectrum for the (S,R) isomer reproduced the negative Cotton effect at 218 nm observed in the experiment.

3a: R1 = OH, R2 = H
4a: R1 = H, R2 = OH

3b: R1 = OH, R2 = H
3b: R1 = H, R2 = OH

The structures of 1 and 2 of both stereoisomers were next optimized at B3LYP/6-31G(d,p) including PCM. The lowest energy conformation of each is shown in Figure 1. The 1H and 13C chemical shifts were computed at this level, again using all conformations with a population greater than 1%. The correlation coefficient for the fit between the experimental values of the chemical shifts and 1a and 2a are significantly lower for both proton and carbon, while the correlation coefficients compared to 1b and 2b are larger, 0.93 or better. Therefore, the structures of vescalagin is 1b and castalagin is 2b.



Figure 1. B3LYP/6-31G(d,p) optimized geometries of the lowest energy conformers of 1b and 2b.


(1) Matsuo, Y.; Wakamatsu, H.; Omar, M.; Tanaka, T. "Reinvestigation of the Stereochemistry of the C-Glycosidic Ellagitannins, Vescalagin and Castalagin," Org. Lett. 2014, 17, 46-49, DOI: 10.1021/ol503212v.


1: InChI=1S/C41H26O26/c42-8-1-5-12(24(48)21(8)45)13-6(2-9(43)22(46)25(13)49)39(60)65-34-11(4-63-37(5)58)64-38(59)7-3-10(44)23(47)26(50)14(7)15-18-16(28(52)32(56)27(15)51)17-19-20(30(54)33(57)29(17)53)31(55)35(66-41(19)62)36(34)67-40(18)61/h1-3,11,31,34-36,42-57H,4H2/t11-,31-,34+,35+,36-/m0/s1

2: InChI=1S/C41H26O26/c42-8-1-5-12(24(48)21(8)45)13-6(2-9(43)22(46)25(13)49)39(60)65-34-11(4-63-37(5)58)64-38(59)7-3-10(44)23(47)26(50)14(7)15-18-16(28(52)32(56)27(15)51)17-19-20(30(54)33(57)29(17)53)31(55)35(66-41(19)62)36(34)67-40(18)61/h1-3,11,31,34-36,42-57H,4H2/t11-,31+,34+,35+,36-/m0/s1

NMR Steven Bachrach 09 Mar 2015 No Comments

Structures of cephalosporolide C, J, and bassianolone

Here is a story that must drive chemical database quality control personnel nuts. Song, et al. noticed that the reported 13C NMR of the natural products cephalosporolide C 1, cephalosporolide J 2 and bassianolone 3 are identical.1 Given that it is highly unlikely that two diastereomers would have identical NMR spectra, the likelihood that these three have identical spectra seemed remote at best.

Compounds 1 and 2 were synthesized and their structures confirmed by x-ray crystallography. Their 13C NMR spectra show clear distinctions, indicating that the isolated “2” is actually 1. Experimental support for the notion that 1 and 3 are actually the same was provided by preparing the diacetylide of 1 and comparing its NMR spectra to that of natural “3”.

Quantum computations confirmed that in fact the natural product thought to be 3 is actually 1. The structures of 1 and 3 were optimized at B3LYP/6-311+G(2d,p) and 13C chemical shifts were computed with these geometries at mPW1PW91/6-311+G(2d,p)/CPCM(chloroform). (The computed structures are shown in Figure 1.) The mean absolute deviation (MAD) between the computed and experimental spectra for 1 is 0.97 ppm, while the MAD for the computed spectrum of 3 compared with the experimental values is 2.44 ppm, with a maximum error of 5.13ppm, more than twice the maximum error with structure 1. The authors attribute the misassignments to a faulty initial spectra of authentic cephalosporolide C 1.



Figure 1. B3LYP/6-311+G(2d,p) optimized geometries of 1 and 3.


(1) Song, L.; Lee, K.-H.; Lin, Z.; Tong, R. "Structural Revision of Cephalosporolide J and Bassianolone," J. Org. Chem. 2014, 79, 1493-1497, DOI: 10.1021/jo402602h.


1: InChI=1S/C10H16O5/c1-6-2-3-7(11)4-8(12)9(13)5-10(14)15-6/h6,8-9,12-13H,2-5H2,1H3/t6-,8+,9+/m1/s1

2: InChI=1S/C10H16O5/c1-6-2-3-7(11)4-8(12)9(13)5-10(14)15-6/h6,8-9,12-13H,2-5H2,1H3/t6-,8+,9-/m1/s1

3: InChI=1S/C10H16O5/c1-6(11)2-3-7(12)4-9-8(13)5-10(14)15-9/h6,8-9,11,13H,2-5H2,1H3/t6-,8+,9+/m1/s1

NMR Steven Bachrach 16 Feb 2015 No Comments

Protocol for computing NMR chemical shifts

I have posted on the use of computed NMR chemical shifts and coupling constants to help aid in structure identification. The second edition of my book Computational Organic Chemistry has a largely all-new chapter on structure identification aided by computed spectra, especially NMR spectra. In my recent opinion piece speculating on challenges in computational organic chemistry,1 the first area I highlight is encouraging the larger use of computed spectra as an essential component of structure determination.

While more and more non-traditional computational users are employing quantum computations towards these problems, I suspect that many non-users are a bit wary about stepping into an arena they are not expert in, an arena chock-filled with acronyms and methods and potentially little guidance. While some very nice papers2-6 and web sites (Chemical Shift Repository (Cheshire) and DP4) do outline procedures for using computations in this fashion, they are not truly designed for the non-specialist.

Well, fear not any longer. Hoye and coworkers, synthetic chemists who have utilized computational approaches in structure determinations for a number of years, have written a detailed step-by-step protocol for using a standard computational approach towards structure determination.7 The article is written with the synthetic chemist in mind, and includes a number of scripts to automate many of the steps.

For the specialist, the overall outline of the protocol is fairly routine:

  1. Utilize MacroModel to perform a conformational search for each proposed structure, retaining the geometries within 5 kcal mol-1 of the global minimum.
  2. Optimize these conformations for each structure at M06-2x/6-31+G(d).
  3. For each conformation of each structure, compute the 1H and 13C chemical shifts, scale them, and determine the Boltzmann weighted chemical shifts
  4. Compare these chemical shifts with the experimental values using Mean Absolute Error

The article is straightforward and easily guides the novice user through these steps. Anyone unsure of how to utilize quantum chemical computations in structure determination is well advised to start with this article.


(1) Bachrach, S. M. "Challenges in computational organic chemistry," WIRES: Comput. Mol. Sci. 2014, 4, 482-487, DOI: 10.1002/wcms.1185.

(2) Lodewyk, M. W.; Siebert, M. R.; Tantillo, D. J. "Computational Prediction of 1H and 13C Chemical Shifts: A Useful Tool for Natural Product, Mechanistic, and Synthetic Organic Chemistry," Chem. Rev. 2012, 112, 1839–1862, DOI: 10.1021/cr200106v.

(3) 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.>

(4) 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.

(5) Smith, S. G.; Goodman, J. M. "Assigning the Stereochemistry of Pairs of Diastereoisomers Using GIAO NMR Shift Calculation," J. Org. Chem. 2009, 74, 4597-4607, DOI: 10.1021/jo900408d.

(6) Smith, S. G.; Goodman, J. M. "Assigning Stereochemistry to Single Diastereoisomers by GIAO NMR Calculation: The DP4 Probability," J. Am. Chem. Soc. 2010, 132, 12946-12959, DOI: 10.1021/ja105035r.

(7) Willoughby, P. H.; Jansma, M. J.; Hoye, T. R. "A guide to small-molecule structure assignment through computation of (1H and 13C) NMR chemical shifts," Nat. Protocols 2014, 9, 643-660, DOI: 10.1038/nprot.2014.042.

NMR Steven Bachrach 09 Feb 2015 No Comments

Structure of Citrinalin B

Here is another nice example of the partnership between experiment and computation in ascertaining molecular structure. The Sarpong, Tantillo, Andersen, Berlinck, and Miller groups collaborated on the synthesis, characterization and biosynthesis of some metabolites from Penniculium strains.1 I will focus here on just the structural identification component of this paper; the synthesis and the biosynthesis are very interesting too!

Cyclopiamine A 1 and cyclopiamine B 2 interconvert through an intermediate that allows for the epimerization at carbon bearing the nitro group.2



Citrinalin A 3 might also seem to undergo the same type of ring opening-ring closing reaction to produce citrinalin B. However, the original proposed structure3 of citrinalin B 4 implies an epimerization at a different carbon (at the ring fusion to the terminal 5 member ring). These authors suggested that perhaps the proper structure of citrinalin B is 5, which differs from citrinalin A only at the carbon bearing the nitro group, analogous to the relationship between 1 and 2.




The low energy conformations of both 4 and 5 (actually the trifluoroacetic acid salts) were optimized at B3LYP/6-31+G(d,p) and the chemical shifts for both 1H and 13C were computed, Boltzmann-weighted and scaled, and then compared with the NMR spectra of authentic citrinalin B. (The lowest energy conformations of 4 and 5 are shown in Figure 1.) The corrected mean absolute deviations for the 1H and 13C chemical shift for the original structure 4 are 0.45 ppm and 2.0 ppm, respectively (with the largest outliers of 2.3 ppm for H and 9.6 ppm for C). These errors are about twice what is observed in comparing the experimental and computed 1H and 13C chemical shifts of 3. The agreement between the computed and experimental values using 5 are much improved, with mean deviations of 0.12 and 1.6ppm, and largest deviations of 0.38 ppm for 1H and 4.4 ppm for 13C. Use of Goodman’s DP4 method indicates a 100% probability that the structure of citrinalin B is 5. This prediction is confirmed by the x-ray structure.



Figure 1. B3LYP/6-31+G(d,p) optimized lowest energy conformers of 4 and 5.


(1) Mercado-Marin, E. V.; Garcia-Reynaga, P.; Romminger, S.; Pimenta, E. F.; Romney, D. K.; Lodewyk, M. W.; Williams, D. E.; Andersen, R. J.; Miller, S. J.; Tantillo, D. J.; Berlinck, R. G. S.; Sarpong, R. "Total synthesis and isolation of citrinalin and cyclopiamine congeners," Nature 2014, 509, 318-324, DOI: 10.1038/nature13273.

(2) Bond, R. F.; Boeyens, J. C. A.; Holzapfel, C. W.; Steyn, P. S. "Cyclopiamines A and B, novel oxindole metabolites of Penicillium cyclopium westling," J. Chem. Soc., Perkin Trans I 1979, 1751-1761, DOI: 10.1039/P19790001751.

(3) Pimenta, E. F.; Vita-Marques, A. M.; Tininis, A.; Seleghim, M. H. R.; Sette, L. D.; Veloso, K.; Ferreira, A. G.; Williams, D. E.; Patrick, B. O.; Dalisay, D. S.; Andersen, R. J.; Berlinck, R. G. S. "Use of Experimental Design for the Optimization of the Production of New Secondary Metabolites by Two Penicillium Species," J. Nat. Prod. 2010, 73, 1821-1832, DOI: 10.1021/np100470h.


1: InChI=1S/C26H33N3O5/c1-23(2)12-17(30)20-18(34-5)9-8-16-21(20)28(23)22(31)26(16)13-25(29(32)33)14-27-10-6-7-15(27)11-19(25)24(26,3)4/h8-9,15,19H,6-7,10-14H2,1-5H3/t15-,19+,25+,26-/m1/s1

2: InChI=1S/C26H33N3O5/c1-23(2)12-17(30)20-18(34-5)9-8-16-21(20)28(23)22(31)26(16)13-25(29(32)33)14-27-10-6-7-15(27)11-19(25)24(26,3)4/h8-9,15,19H,6-7,10-14H2,1-5H3/t15-,19+,25-,26-/m1/s1

3: InChI=1S/C25H31N3O5/c1-22(2)11-16(29)19-17(33-22)8-7-15-20(19)26-21(30)25(15)12-24(28(31)32)13-27-9-5-6-14(27)10-18(24)23(25,3)4/h7-8,14,18H,5-6,9-13H2,1-4H3,(H,26,30)/t14-,18+,24+,25-/m0/s1

4: InChI=1S/C25H31N3O5/c1-22(2)11-16(29)19-17(33-22)8-7-15-20(19)26-21(30)25(15)12-24(28(31)32)13-27-9-5-6-14(27)10-18(24)23(25,3)4/h7-8,14,18H,5-6,9-13H2,1-4H3,(H,26,30)/t14-,18-,24-,25+/m1/s1

5: InChI=1S/C25H31N3O5/c1-22(2)11-16(29)19-17(33-22)8-7-15-20(19)26-21(30)25(15)12-24(28(31)32)13-27-9-5-6-14(27)10-18(24)23(25,3)4/h7-8,14,18H,5-6,9-13H2,1-4H3,(H,26,30)/t14-,18+,24-,25-/m0/s1

NMR Steven Bachrach 24 Jun 2014 4 Comments

Structure determination: Quercusnin A

Here’s another nice example of the use of computed NMR spectra to aid in structure identification. Quercusnin A was identified in an extract of dried sapwood from the oak tree Quercus crispula. The NMR sectrum along with structural comparison to the previously determined extract vescalagin, led the authors to the structure 1.1


To aid in determining the absolute stereochemistry as centers 1’ and A8, the authors employed a computational approach. Conformers of the four diastereomers (RR, RS, SR, SS) were optimized first with molecular mechanics, then the low energy conformers were reoptimized at AM1, and then finally all of the conformers within 6 kcal mol-1 of the lowest energy structure were reoptimized at PCM(acetone)/B3LYP/6-31G(d,p). The 1H and 13C NMR chemical shifts for all of the structures that contribute greater than 1% to the Boltzmann population were computed at PCM(acetone)mPW1PW91/6-311+G(2d,p)//B3LYP/6-31G(d,p). The DP4 probability (see this post) identified the (1’S,A8R) isomer with 100% probability for matching up with the experimental NMR spectrum. Additionally, the computed ECD spectrum matches nicely with the experimental spectra for this same stereoisomer. The lowest energy conformer of 1 is shown in Figure 1.


Figure 1. PCM(acetone)/B3LYP/6-31G(d,p) structure of the lowest energy conformer of 1.


(1) Omar, M.; Matsuo, Y.; Maeda, H.; Saito, Y.; Tanaka, T. "New Metabolites of C-Glycosidic Ellagitannin from Japanese Oak Sapwood," Org. Lett. 2014, 16, 1378–1381, DOI: 10.1021/ol500146a.


1: InChI=1S/C36H24O22/c37-11-2-8-15(24(44)20(11)40)16-9(3-12(38)21(41)25(16)45)36(53)56-29-14(5-54-32(8)49)55-33(50)10-4-13(39)22(42)26(46)19(10)30-17-6(34(51)57-30)1-7-18(23(17)43)31(58-35(7)52)28(48)27(29)47/h1-4,14,27-31,37-48H,5H2/t14-,27-,28-,29-,30-,31+/m1/s1

NMR Steven Bachrach 01 Apr 2014 No Comments

Computation-aided structure determination

I have not discussed any papers that utilize computations to confirm chemical structure in a while, so here are two recent examples.

Grabow has utilized MP2 and M06-2x computations to confirm the lowest energy conformation of (-)-lupinine 1.1 The interesting structural aspect of this compound is the possibility of an intramolecular hydrogen bond linking the hydroxyl group with the amine.


Using molecular mechanics, the authors identified 57 structures within 50 kJ mol-1 of each other. These geometries were reoptimized at MP2/6-311++G(d,p) and M06-2x/6-311++G(d,p).
The lowest energy structures had the expected trans ring fusion, with a trans relationship between the hydrogen on the bridgehead carbon (C9) and the hydroxymethyl group. This corresponds to either the (R,R) or (S,S) isomer. The three lowest energy structures are shown in Figure 1. Unfortunately, the geometry for the lowest energy isomer provided in the Supporting Materials is wrong, and the authors did not supply the geometries of the other isomers. This situation is unacceptable! Reviewers and editors must do a better job in policing the Supporting Materials; there is no excuse for not including all of the optimized structures, and better yet, in a more usable format that what has been done here. I have reoptimized these structures at M06-2x/6-31G(d). The lowest energy conformer 1a does possess the expected internal hydrogen bond.




Figure 1. M06-2x/6-31G(d) optimized structures of the three lowest energy conformers of 1, with relative free energies in kJ mol-1.

Table 1 provides a comparison of the MP2 computed values of important structural parameters along with the experimental values obtained from a microwave experiment. The agreement with the computed values for 1a provides strong evidence that this is the structure of (-)-lupinine.

Table 1. Comparison of MP2 and experimental structural parameters of 1.a


Expt. (1)

MP2 (1a)




























aRotational constants (A, B, C) in MHz, centrifugal distortion constants (ΔJ, ΔJK, ΔK) in kHz, and nuclear quadrupole coupling tensor elements (χaa, χbb, χcc) in MHz.

The second study utilizes computed NMR chemical shifts to discriminate potential diastereomeric structures. Laurefurenyne A was first assigned the structure 2 based on 1D and 2D NMR experiments. However, based on potential biochemical analogy to other compounds, Paton and Burton2 had doubts about this structure. In addition to synthesizing the natural material, they performed an extensive computational study of the chemical shifts of the diastereomers. For each of the 32 possible diastereomers, they performed a Monte Carlo search of the conformational space using molecular mechanics. The structures of all isomers within 10 kJ mol-1 of the lowest energy structure were reoptimized at ωB97X-D/6-31G(d) with PCM (CHCl3) and chemical shifts obtained at mPW1PW91/6-311G(d,p). Final chemical shifts were obtained using a Boltzmann weighting. The computed values for 2 were quite off from the experimental values, with a mean unsigned error of 1.5 ppm. A better assessment was provided with the DP4 method, which indicated that 3 has the highest probability of being the correct structure, a structure consistent with the likely biosynthetic pathway.




(1) Jahn, M. K.; Dewald, D.; Vallejo-López, M.; Cocinero, E. J.; Lesarri, A.; Grabow, J.-U. "Rotational Spectra of Bicyclic Decanes: The Trans Conformation of (-)-Lupinine," J. Phys. Chem. A 2013, DOI: 10.1021/jp407671m.

(2) Shepherd, D. J.; Broadwith, P. A.; Dyson, B. S.; Paton, R. S.; Burton, J. W. "Structure Reassignment of Laurefurenynes A and B by Computation and Total Synthesis," Chem. Eur. J. 2013, 19, 12644-12648, DOI: 10.1002/chem.201302349.


(-)-Lupinine 1: InChI=1S/C11H21NO/c1-11-6-2-3-7-12(11)8-4-5-10(11)9-13/h10,13H,2-9H2,1H3/t10-,11+/m0/s1

Laurefurenyne A 3: InChI=1S/C14H20O4.C2H6/c1-3-4-5-6-12-11(16)8-14(18-12)13-7-10(15)9(2)17-13;1-2/h1,4-5,9-16H,6-8H2,2H3;1-2H3/b5-4-;/t9-,10-,11-,12+,13-,14+;/m1./s1

NMR Steven Bachrach 09 Dec 2013 2 Comments

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