Unambiguous Identification of Natural Products Using a Mass Spectrometer

One of the main objectives and problems in the discovery of new secondary metabolites is the identification of an exact molecular formula for natural products.^[1] Molecular formulas can be employed as a benchmark for dereplication of established natural products from current compound databases, which avoids unwanted wastage of time and decreases labor cost.

Furthermore, the quick confirmation of molecular formula would offer important information for structural exposition of unknown compounds and speed up the entire discovery process of natural products.

Mass spectrometry is a well-known method for measuring the exact mass to charge (m/z) ratios of various ions. This method has been extensively employed in determining the molecular formulas of both natural products and synthetic compounds. In mass spectrometry, the resolution could be given by the formula:^[2]

Resolution = R = M/∆M

Where M is the m/z ratio of the chosen peak and ∆M is typically defined as the peak width at its half-maximum peak height. Increasing the resolving power of the mass spectrometers could enhance the resolution of the measurement. As a result, the monoisotopic mass peak could be identified accurately and result in an exact molecular weight of the compound. However, just the accurate mass is not enough for determining the definite molecular formula of natural products because of the combinatorial explosion.^[3] It has been shown that even with 0.1 ppm mass accuracy for the MS instrument, it was not possible to determine a unique molecular formula if C, H, N, S, O, P atoms were involved in the search list for molecules with molecular weight beyond 185.9760 Da.^[3] Therefore, additional information, such as isotope abundance ratio, would be needed for the determination.

Table 1. Mass defects and natural abundance of common isotopes in organic compounds

The mass defect concept is the consequence of the different nuclear binding energies of various elements and their nuclides.^[4] Traditionally, ¹²C was described as the element with zero mass defect, while other nuclides have different mass defect based on their relative nuclear binding energy to ¹²C. Furthermore, each element would have a specific ratio for different isotopes depending on their natural abundance. As a result, compounds with different elemental makeup would possess different exact masses and also unique Isotopic Fine Structure (IFS). Table 1 shows mass defects and natural abundance of common elements in organic compounds and their isotopes.^[4]

This article reveals the unambiguous molecular formula determination of a natural product echinomycin A using the IFS concept described earlier. This technique would possibly be used as a powerful tool for quick discovery of new compounds and fast dereplication of established compounds in natural product libraries. It was recently discovered that IFS was important for determining a precise molecular formula for the unambiguous molecular formula determination of keyicin, an antibiotic synthesized by marine bacterial co-culture.^[5] The determination of the correct formula played a key role in the structural elucidation process of keyicin since an exact carbon count cannot be achieved by NMR without ¹³C isotopic enrichment.

Experiment

The examined compound, echinomycin, was isolated from the marine Streptomyces sp. WMMC-592 following the usual routine involves the natural product isolation and purification process.^[6] HPLC purification was carried out using a Shimadzu LC-20AP system with a Luna 5 μm C18 100 Å 250*10 mm column. Linear gradient from 25:75 MeCN/H₂O (with 0.1% acetic acid) to 50:50 MeCN/H₂O (with 0.1% acetic acid) over 35 minutes was employed.

A Bruker 12T MRMS (Magnetic Resonance Mass Spectrometry) instrument and a Bruker QTOF MS instrument were used to carry out mass spectrometry detection. The instruments were operated under ESI positive mode to obtain complete scan MS spectra. The instrument calibrations were done using Bruker ESI-MS tuning mix. The compound was dissolved in LC/MS grade MeOH (2 μg/mL). The obtained data were analyzed using Bruker Compass DataAnalysis 4.4 SR1. Molecular formula determination was performed using SmartFormula and the isotopic patterns were simulated using Simulate Pattern.

Results and Discussion

Assignment of the Molecular Ion and SmartFormula Prediction of Possible Molecular Formulas

Direct infusion MRMS data acquired under ESI (electrospray ionization) positive mode exhibited an intense [M+H]⁺ adduct peak with m/z ratio of 1101.4275. Isotopologues were completely resolved in the spectra for [MH+1]⁺, [MH+2]⁺, and [MH+3]⁺ ions (Figure 1a). Alternatively, data obtained on a QTOF did not exhibit resolved isotopologues (Figure 1b). SmartFormula was used to offer an array of reasonable formulas. The search was configured to be C48S1N6O6 and the upper formula C54 based on preliminary NMR data. The MS error tolerance was configured to be 2 ppm, and seven possible molecular formulas were provided by SmartFormula analysis (Figure 1c): [C₅₁H₇₃N₈O₁₁S₄]⁺, [C₅₁H₆₅N₁₂O₁₂S₂]⁺, [C₅₀H₆₉N₈O₁₆S₂]⁺, [C₄₈H₅₇N₂₂O₆S₂]⁺, [C₅₂H₇₇N₈O₆S₆]⁺, [C₅₂H₆₉N₁₂O₇S₄]⁺, and [C₅₁H₆₁N₁₆O₈S₂]⁺.

Figure 1. (a) Bruker 12T MRMS spectra and (b) Bruker QTOF MS spectra of tested compounds. [MH+1]⁺, [MH+2]⁺, [MH+3]⁺ ions were displayed. (c) SmartFormula analysis of possible adducts formulas.

Determination of the Exact Molecular Formula

Different element makeup of the molecules would exhibit their unique IFS, and these fine structures could be seen with the enhanced resolution of the MRMS instrument (Figure 1a). For [MH+1]⁺ ion, the difference between the two peaks was 0.0066 u, which was in accordance with the mass defect difference of ¹⁵N¹²C and ¹⁴N¹³C (0.0063 u). Similar calculations were carried out and the different peaks observed in [MH+2]⁺ and [MH+3]⁺ ions were assigned to the combinations of ³⁴S¹²C₂/³²S¹³C₂ and ³⁴S¹³C¹²C₂/³²S¹³C₃, respectively. On the contrary, the spectra acquired from the QTOF instrument were unable to exhibit similar fine structures (Figure 1b). Therefore, the exact molecular formula could be identified from a range of possibilities by comparing its unique IFS to the acquired spectra.

The IFS of three possible species — [C₅₁H₇₃N₈O₁₁S₄]⁺, [C₄₈H₅₇N₂₂O₆S₂]⁺, and [C₅₁H₆₅N₁₂O₁₂S₂]⁺ — were simulated by Simulate Pattern function and the simulated MS peaks were superimposed with the actual spectra (Figure 2). For [MH+2]⁺ ion, the relative abundance of [¹²C₅₁H₇₃N₈O₁₁³²S₃ ³⁴S]⁺ was considerably higher when compared to the actual molecule (Figure 2a), which signified that the tested compound must have fewer sulfur atoms than [C₅₁H₇₃N₈O₁₁S₄]⁺. A similar trend was found in the [MH+3]⁺ ion overlaid spectra. The tested compound was suggested to contain two sulfur atoms because the sulfur-related peaks in [MH+2]⁺ and [MH+3]⁺ overlaid spectra matched the simulated IFS of [C₄₈H₅₇N₂₂O₆S₂]⁺ (Figure 2b).

Figure 2. Overlaid IFS of the actual tested compound spectra: (a) [C₅₁H₇₃N₈O₁₁S₄]⁺; (b) [C₄₈H₅₇N₂₂O₆S₂]⁺; (c) [C₅₁H₆₅N₁₂O₂S₂]⁺.

However, the simulated [C₄₈H₅₇¹⁴N₂₁¹⁵NO₆S₂]⁺ ion abundance and [¹²C₄₇¹³CH₅₇¹⁴N₂₁¹⁵NO₆S₂]⁺ ion abundance were more when compared to the corresponding ion abundance in the actual spectra, implying that this adduct formula was a mismatch. Similar evaluations were carried out on [C₅₁H₆₅N₁₂O₂S₂]⁺ and the simulated fine structure could match the actual spectra (Figure 2c), meaning that the molecular formula of the tested compound was C₅₁H₆₄N₁₂O₂S₂. This compound was identified as echinomycin A by comprehensive NMR analysis.

Conclusion

The unambiguous identification of the tested compound molecular formula among a range of potentials was realized by obtaining data from Bruker 12T MRMS system and analyzing the IFS of the obtained MS spectra. This method features efficient and quick molecular formula identification for further dereplication and new natural products discovery attempts.

The SmartFormula and Simulate Pattern functions of Bruker Compass DataAnalysis 4.4 SR1 software were important for this analysis. When configuring appropriate limitations in SmartFormula search, the potential molecular formulas of the tested sample could be cut down and the Simulate Pattern process could be made easy. The identified accurate molecular formula would potentially be employed as one of the key elements for metabolites database analyses.

References

[1] Dührkop, K.; Hufsky, F.; Böcker, S., Mass Spectrom (Tokyo) 2014, 3(3): S0037; DOI: 10.5702/massspectrometry.S0037

[2] Guan, S.; Marshall, A. G., Anal. Chem. 1996, 68(1), 46–71.

[3] Kind, T.; Fiehn, O. BMC Bioinformatics 2006, 7:234.

[4] Sleno, L., J. Mass. Spectrom. 2012, 47, 226–236.

[5] Adnani, N.; Chevrette, M. G.; Adibhatla, S. N.; Zhang, F.; Yu, Q.; Braun, D. R.; Nelson, J.; Simpkins, S. W.; McDonald, B. R.; Myers, C. L.; Piotrowski, J. S.; Thompson, C. J.; Currie, C. R.; Li, L.; Rajski, S. R.; Bugni, T. S. ACS Chem. Biol. 2017, 12, 3093–3102.

[6] Zhang, F.; Adnani, N.; Vazquez-Rivera, E.; Braun, D.R.; Tonelli, M.; Andes, D.R.; Bugni, T.S. J. Org. Chem. 2015, 80, 8713–8719.

[7] Dell, A.; Williams, D. H.; Morris, H. R.; Smith, G. A.; Feeney, J.; Roberts, G. C., J. Am. Chem. Soc. 1975, 97(9), 2497–2502.

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