December 21, 2022
by Mikhail Elyashberg, Leading Researcher, ACD/Labs
Furaquinocin L
A large class of natural products are the Meroterpenoids. They are produced by polyketide or nonpolyketide and terpenoid biosynthesis. A large number of meroterpenoids have been isolated from streptomycete bacteria.
Tistechok et al. [1] described the isolation, purification, and structure elucidation of a new naphthoquinone-based meroterpenoid, Furaquinocin L (1) from Streptomyces sp. Je 1-369, which expands the structural diversity of the furaquinocin family of natural products.
1
To elucidate the structure of compound 1, authors utilized 1H, 13C , COSY, H-C HSQC, H-C HMBC, H-N HSQC and H-N HMBC NMR spectra. The spectroscopic data are presented in Table 1.
Table 1. NMR spectroscopic data of compound 1
C/X Label | δC | δC Calc (HOSE) | XHn | δH | M(H) | COSY | H to C HMBC | δN | H to N HMBC |
C 1 | 91.4 | 90.19 | CH | 4.99 | q | 1.5 | C 4, C 17, C 16 | ||
C 2 | 15.8 | 15.7 | CH3 | 1.5 | d | 4.99 | C 3, C 1 | ||
C 3 | 46.4 | 46.47 | C | ||||||
C 4 | 19.2 | 17.53 | CH3 | 1.32 | s | C 17, C 3, C 1, C 5 | |||
C 5 | 118.7 | 116.6 | C | ||||||
C 6 | 179.2 | 183.56 | C | ||||||
C 7 | 139.9 | 137.82 | C | ||||||
C 8 | 110 | 107.33 | C | ||||||
C 9 | 147.8 | 145.4 | C | ||||||
C 10 | 153.1 | 147.72 | C | ||||||
C 11 | 60.8 | 61.24 | CH3 | 3.99 | s | C 10 | |||
C 12 | 123.2 | 115.86 | C | ||||||
C 13 | 9 | 8.94 | CH3 | 2.22 | s | C 12, C 14, C 10 | |||
C 14 | 149 | 146.88 | C | ||||||
C 15 | 101.4 | 98.6 | C | ||||||
C 16 | 169.1 | 161.92 | C | ||||||
C 17 | 37.9 | 36.43 | CH2 | 1.72 | u | 1.87 | C 18, C 3 | ||
C 17 | 37.9 | 36.43 | CH2 | 1.94 | u | ||||
C 18 | 23.5 | 23.01 | CH2 | 1.87 | u | 1.72, 5.09 | |||
C 18 | 23.5 | 23.01 | CH2 | 2.01 | u | ||||
C 19 | 123.5 | 125.78 | CH | 5.09 | t | 1.56, 1.66, 1.87 | C 22, C 21, C 17 | ||
C 20 | 132.2 | 131.79 | C | ||||||
C 21 | 25.7 | 25.7 | CH3 | 1.66 | s | 1.56, 5.09 | C 22, C 19 | ||
C 22 | 17.7 | 17.5 | CH3 | 1.56 | s | 1.66, 5.09 | C 21, C 19 | ||
C 23 | 167 | 169.71 | C | ||||||
C 24 | 22.1 | 20.37 | CH3 | 2.25 | s | C 23 | 171.7 | ||
N 1 | N | 301.9 | |||||||
N 2 | NH | 14.9 | s | C 7, C 23 | 171.7 | ||||
O 1 | OH | 12.89 | s | C 8, C 9, C 10 | 301.9 | ||||
O 2 | OH | 8.1 | s | C 15, C 12, C 14, C 10 |
These data were entered into ACD/Structure Elucidator (ACD/SE), and the program created the Molecular Connectivity Diagram (MCD) which is shown in Figure 1.
Figure 1. Molecular connectivity diagram. Hybridizations of carbon atoms are marked by corresponding colors: sp2 – violet, sp3 – blue, not sp (sp2 or sp3) – light blue. Labels “ob” and “fb” are set by the program to carbon atoms for which neighboring with heteroatom is either obligatory (ob) or forbidden (fb). The HMBC connectivities are marked by green arrows.
The MCD contains two light blue carbon atoms (91.4 and 101.4) with ambiguous hybridizations and two carbons without any correlations (132.2 and 179.2). This may increase the elucidation time. Checking the MCD for existing contradictions in the 2D NMR data showed that the minimum number of nonstandard correlations (NSC) is equal to two. Therefore, Fuzzy Structure Generation (FSG) together with 13C chemical shift prediction using incremental and neural network approaches and structure filtering was initiated. FSG options were defined by the program automatically. Results: k = 854306 → (structural filtering) → 260 → (duplicate removal) → 258, tg=22 m 40 s. 13C chemical shift prediction was further carried out by the HOSE code-based method and the structures were ranked in increasing order of average deviations. The six top ranked structures are shown in Figure 2:
Figure 2. The top structures of the ranked output file. 13C chemical shift prediction was carried out using the HOSE code-based method, the neural networks, and the incremental approach. Average deviations of 13C chemical shifts determined by these methods are denoted as dA, dN and dI correspondingly. Red arrows indicate nonstandard HMBC correlations (NSC), i.e, those whose lengths exceeds three chemical bonds (nJCH, n>3).
Figure 2 shows that the published structure of Furaquinocin L coincides with structure #2 of the ranked file, while the difference between dA (#2) and dA (#1) is small (0.094). At the same time, the neural network and incremental methods favor structure #2. In this case, the selection of the most probable structure can be accomplished by taking into account the lengths of NSCs.
Figure 3 shows the important fragments of structures #1 and #2, in order to ease analyzing these structures.
Figure 3. Fragments of structures #1 – #3.
We see that the length of the correlation of OH 12.89 to N 301.9 is of 6 chemical bonds in structure # 1. Meanwhile, as was shown by Buevich and Elyashberg [2], HMBC correlations of such large length can hardly be observable. Therefore structure #1 can be eliminated, along with structures #4 – #6 which also containing too long HMBC correlations. The length of the correlation of OH 12.89 to N 301.9 is of five chemical bonds in structures #2 and #3, which allows considering them realistic ones. Calculation of the DP4 probabilities for structures #1- #3 confirmed the priority of structure #2 (see Figure 4).
Figure 4. DP4 probabilities calculated for structures #1 – #3.
It is interesting to note that the authors [1] considered structure #4 as an alternative to structure #2 and rejected it on the basis of 13C chemical shift prediction using ACD/Labs Predictors. Other possible structures suggested by ACD/SE could not be proposed as this would be too difficult a problem for a human expert.
Thus, utilizing ACD/SE allowed us to determine the right structure of Furaquinocin L using Fuzzy Structure Generation (options were set by program automatically) in the presence of two nonstandard correlations, one of which was of five chemical bonds length.
[1] S.Tistechok, M. Stierhof , M. Myronovskyi, J. Zapp, O.Gromyko, A. Luzhetskyy. (2002). Furaquinocins K and L: Novel Naphthoquinone-Based Meroterpenoids from Streptomyces sp. Je 1-369. Antibiotics, 11, 1587, https://doi.org/10.3390/antibiotics11111587 [2] A.V. Buevich, M.E. Elyashberg. (2020). Enhancing Computer Assisted Structure Elucidation with DFT analysis of J-couplings. Magn. Reson. Chem., 58(6), 594-606, DOI: 10.1002/mrc.4996