13C-15N Correlation via Unsymmetrical Indirect Covariance NMR: Application to Vinblastine
Gary E. Martin,*,† Bruce D. Hilton,† Kirill A. Blinov,‡ and Antony J. Williams§,⊥
Schering-Plough Research Institute, Summit, New Jersey 07901, AdVanced Chemistry DeVelopment, Moscow DiVision, Moscow, 117504,
Russian Federation, and AdVanced Chemistry DeVelopment, Toronto, Ontario M5C 1T4, Canada
ReceiVed July 24, 2007
Unsymmetrical indirect covariance processing methods allow the derivation of hyphenated 2D NMR data from the
component 2D spectra, potentially circumventing the acquisition of the much lower sensitivity hyphenated 2D NMR
experimental data. Calculation of HSQC-COSY and HSQC-NOESY spectra from GHSQC, COSY, and NOESY spectra,
respectively, has been reported. The use of unsymmetrical indirect covariance processing has also been applied to the
combination of 1H-13C GHSQC and 1H-15N long-range correlation data (GHMBC, IMPEACH, or CIGAR-HMBC).
The application of unsymmetrical indirect covariance processing to spectra of vinblastine is now reported, specifically
the algorithmic extraction of 13C-15N correlations via the unsymmetrical indirect covariance processing of the combination
of 1H-13C GHSQC and long-range 1H-15N GHMBC to produce the equivalent of a 13C-15N HSQC-HMBC correlation
spectrum. The elimination of artifact responses with aromatic solvent-induced shifts (ASIS) is shown in addition to a
method of forecasting potential artifact responses through the indirect covariance processing of the GHSQC spectrum
used in the unsymmetrical indirect covariance processing.
Long-range 1H-15N heteronuclear shift correlation NMR experi-
ments at natural abundance have become progressively more
important in natural product structure elucidation since the first
reports appeared a little over a decade ago. There have been several
reviews1–5 and two recent publications that have described the
simultaneous acquisition of 1H-13C and 1H-15N long-range het-
eronuclear chemical shift correlation spectra.6,7 Recently, there has
also been considerable interest in a relatively new area of investiga-
tion known as covariance NMR. A communication that described
indirect covariance NMR processing of hyphenated HSQC-TOCSY
data8 spurred our interest in the potential capabilities of indirect
covariance spectroscopy, which in turn led to the development of
unsymmetrical indirect covariance NMR processing methods.9 In
an extension of our initial investigation, unsymmetrical indirect
covariance NMR processing has been used to coprocess discretely
acquired 2D NMR spectra to afford the equivalent of hyphenated
2D NMR spectra. Examples have included the coprocessing of
GHSQC and GHMBC spectra to provide the equivalent of m,n-
ADEQUATE spectra.10 Coprocessing GHSQC and COSY spectra
offers a covariance spectrum equivalent to a GHSQC-COSY
spectrum.11,12 GHSQC and NOESY spectra have also been
coprocessed to afford correlation data equivalent to the very
insensitive GHSQC-NOESY experiment.13 Müller and co-workers14
have also described the generation of 13C-13C correlation plots from
HMBC spectra using covariance processing methods.
Carrying the utilization of unsymmetrical indirect covariance
processing methods a step further, given two coherence transfer
experiments of the type
A f B (1)
and
A f C (2)
it is possible to indirectly determine the coherence spectrum for
B T C (3)
Using this approach, we have recently shown that it is possible
to mathematically combine 1H-13C GHSQC and long-range
1H-15N GHMBC or a similar long-range correlation experiment,
e.g., IMPEACH-MBC or CIGAR-HMBC, to determine 13C-15N
heteronuclear chemical shift correlation spectra.15,16 In parallel
work, Kupcˇe and Freeman have shown it is possible to establish
13C-15N heteronuclear shift correlation using an unrelated technique
known as projection reconstruction NMR.7 We now wish to
demonstrate the application of unsymmetrical indirect covariance
processing methods to the mathematical combination of the 1H-13C
GHSQC and long-range 1H-15N GHMBC spectra of vinblastine
(1).
Results and Discussion
Vinblastine, 1, is a complex bis-indole alkaloid containing four
15N resonances. The 1H-15N GHMBC spectrum of the alkaloid
was acquired with the long-range delay optimized for 5 Hz, giving
the correlations shown in the structure in Figure 1. The four nitrogen
resonances were observed via long-range correlations to various
protons at 43.3, 64.1, 67.0, and 136.0 ppm. The latter is readily
assigned on the basis of its 15N shift as the N-16′ indole nitrogen.
15N chemical shifts for all of the nitrogens were calculated (ACD/
Labs Nitrogen NMR chemical shift prediction software, v 10.2)
using both HOSE-code and neural network calculations, which are
summarized in Table 1. On the basis of the calculated 15N chemical
shifts, N-6′ was assigned as the 15N resonance at 43.3 ppm. Long-
range heteronuclear correlations were necessary to differentiate and
assign unequivocally the nitrogen resonances at 64.1 and 67.0 ppm,
as N-1 and N-9, respectively.
Figure 2 shows the 1H-15N GHMBC and multiplicity-edited
1H-13C GHSQC spectra flanking the 13C-15N HSQC-HMBC
* To whom correspondence should be addressed. Tel: +908.473-5398.
Fax: +908.473-6559. E-mail: gary.martin@spcorp.com.
† Schering-Plough Research Institute.
‡ Advanced Chemistry Development, Moscow Division.
§ Advanced Chemistry Development, Toronto.
⊥ Present address: ChemZoo, Wake Forest, NC 27587.
Table 1. Calculated (ACDLabs, Nitrogen NMR Chemical
Shift Prediction Software, v10.2) versus Observed 15N Chemical
Shifts for Vinblastine (1)a
position
15N HOSE
code (ppm)
15N neural
network (ppm)
15N observed
(ppm)
N-1 66.0 66.7 64.1
N-9 55.3 56.0 67.0
N-6′ 43.0 34.4 43.3
N-16′ 138.2 138.9 136.0
a Observed data are taken from the 5 Hz optimized 1H-15N GHMBC
assignments shown in Figure 1 and the spectrum shown in Figure 2.
J. Nat. Prod. 2007, 70, 1966–19701966
10.1021/np070361t CCC: $37.00  2007 American Chemical Society and American Society of Pharmacognosy
Published on Web 11/29/2007

correlation spectrum calculated using unsymmetrical indirect co-
variance processing. The GHSQC spectrum has been transposed
to reflect the orientation of this spectrum used by the algorithm
during the unsymmetrical indirect covariance processing, which
gives 13C chemical shift information in the F2 dimension of the
13C-15N HSQC-HMBC correlation spectrum; 15N chemical shift
information is presented in the F1 dimension of the spectrum. The
fully assigned 13C-15N HSQC-HMBC spectrum is shown in Figure
3. With the sole exception of the apparent correlation response from
the C-24 O-methyl resonance to N1, all of the responses are
Figure 1. Structure of vinblastine (1) showing long-range 1H-15N correlations observed in the 5 Hz optimized 1H-15N GHMBC spectrum
in d6-DMSO at 26 oC. Dashed arrow denotes weak correlation. Red arrows are correlations from methylenes to 15N and are color coded to
correspond to responses from methylene carbons in the 13C-15N HSQC-HMBC spectrum shown in Figure 3. The NH correlation to N-16′
is not observed in the 13C-15N HSQC-HMBC spectrum since the H-16′ proton is not on a 13C and the experiment did not sample 1JNH
heteronuclear coupling information despite the fact that these correlations can be observed in a 1H-15N GHMBC or equivalent long-range
heteronuclear shift correlation spectrum.
Figure 2. Composite plot showing the 5 Hz optimized 1H-15N GHMBC spectrum (top left panel) and the transposed, multiplicity-
edited 1H-13C GHSQC (bottom right panel) spectra of vinblastine (1) used in the calculation of the 13C-15N HSQC-HMBC heteronuclear
correlation spectrum shown in the top right panel. Methylene responses are inverted in the multiplicity-edited 1H-13C GHSQC spectrum
and plotted in red; methine and methyl correlations have positive phase and are plotted in black. The carbon multiplicity information
from the GHSQC spectrum is carried forward into the 13C-15N HSQC-HMBC spectrum. Methylene carbons correlated to 15N appear
in red; methine and methyl carbons correlated to 15N are plotted in black. The fully annotated 13C-15N HSQC-HMBC correlation
spectrum is shown in Figure 3.
13C-15N Correlation Via Unsymmetrical Indirect CoVariance NMR Journal of Natural Products, 2007, Vol. 70, No. 12 1967

reasonable (Figure 1). The apparent C-24 O-methyl correlation
response arises because of an overlap of the H-2 methine and 24-
O-methyl resonances in the 1H spectrum (red-boxed region in the
multiplicity-edited 1H-13C GHSQC spectrum shown in the bottom
right panel of Figure 2; red-boxed response in the 13C-15N HSQC-
HMBC spectrum shown in Figure 3).8,9 As even partial overlap of
the bases of Lorentzian peaks can potentially give rise to artifact
responses, there is little likelihood that extensive linear prediction
will eliminate artifact responses.17
To confirm the origin of the C-24 O-methyl-N-1 correlation
response as an artifact, the 20 mg vinblastine sample used for this
study was diluted by the addition of 50 µL of d6-benzene, inducing
an aromatic solvent-induced shift (ASIS) that shifted the H-2
resonance slightly downfield and between the 16- and 24-O-methyl
Figure 3. 13C-15N HSQC-HMBC spectrum from Figure 2 showing response assignments. The correlation response from the C24 O-methyl
group to N-1 is obviously an artifact. Examination of the transposed, multiplicity-edited 1H-13C GHSQC panel in Figure 2 (red-boxed
region, lower right panel) illustrates the overlap of the H-2 methine and the C24 O-methyl resonances. This type of overlap can give rise
to artifact responses in unsymmetrical indirect covariance processed heteronuclear correlation data matrices.8,9
Figure 4. Slice at the N-1 chemical shift (64.1 ppm) from (black trace) the 13C-15N HSQC–HMBC spectrum in d6-DMSO shown in
Figures 2 and 3; slice from the 13C-15N HSQC-HMBC spectrum following the addition of 50 µL of d6-benzene to the initial d6-DMSO
sample (red trace). The aromatic solvent-induced shift caused by the addition of d6-benzene shifted the H-2 resonance slightly downfield
between the C-16 and C-24 O-methyl resonances so that only the base of these resonances is overlapped in the 600 MHz 1H spectrum (red
trace). As a consequence of shifting the H-2 resonance, the C-24 O-methyl response went from being the largest response in the trace
shown in the black trace to a much smaller response in the red trace. Simultaneously, the now slightly greater overlap of the base of the
H-2 resonance and that of the C-16 O-methyl resonance led to some increase in the intensity of an artifact response for this resonance as
would be expected with the increasing overlap of the pair of resonances.
1968 Journal of Natural Products, 2007, Vol. 70, No. 12 Martin et al.

singlets. Reacquisition of both the multiplicity-edited 1H-13C
GHSQC and 1H-15N GHMBC spectra was followed again by
unsymmetrical indirect covariance processing of the resulting 2D
spectra. The N-1 slices at 64.1 from both 13C-15N HSQC-HMBC
correlation spectra are shown in Figure 4.
The addition of the d6-benzene to the sample provided an ASIS
of the H-2 resonance downfield to a position between the flanking
C-16 and C-24 O-methyl resonances. The C-24 O-methyl response
was the most intense correlation response in the N-1 slice at 64.1
ppm, shown in Figure 4 by the black trace. When the H-2 resonance
with which it was overlapped (Figure 2, GHSQC spectrum, lower
right panel) was shifted downfield by the addition of d6-benzene,
the intensity of the C-24 O-methyl artifact response significantly
diminished, as shown by the N-1 slice in Figure 4 by the red trace.
Commensurate with the downfield shift of the H-2 resonance, the
overlap of the bases of the Lorentzian lines for the H-2 and H-16
O-methyl resonance began to increase. The new H-16 O-methyl
H-2 partial overlap caused an increase above the t1 tracking noise
at the shift of the C-16 O-methyl resonance in the black trace shown
in Figure 4 to the level of the diminished C-24 O-methyl response
in the red trace shown in Figure 4. These observations confirm
that the response observed at the 13C chemical shift of the C-24
O-methyl resonance in Figure 3 was indeed a consequence of the
overlap of the H-2 and H-24 O-methyl resonances in the F2
dimension of the 1H-13C GHSQC spectra used in the calculation
of the 13C-15N HSQC-HMBC spectra.
A way of further enhancing the utility of 13C-15N HSQC-HMBC
experiments without having to resort to further experimental work
is available through the use of simple covariance processing. A
GHSQC experiment would not normally be subjected to covariance
processing, as there is no correlation information to be gained from
this type of data manipulation. However, the specific case of a
GHSQC spectrum with resonance overlaps of the type represented
by the H-2 methine and H-24 O-methyl resonances may be
considered. In this case, covariance processing of the GHSQC
spectrum will give rise to a covariance spectrum in which the off-
diagonal responses observed in the spectrum arise from proton
resonance overlap. Figure 5A shows the result of covariance
processing the GHSQC spectrum of vinblastine (1) prior to the
addition of d6-benzene. There are several sets of off-diagonal
responses in the covariance spectrum, which is not surprising for
a molecule of the complexity of 1. The most prominent pair of
off-diagonal responses were observed at the 13C chemical shifts of
the C-2 and C-24 O-methyl resonances. In this eventuality, if either
of the pair of resonances with the off-diagonal responses has a
directly bound proton that is long-range coupled to 15N in the
1H-15N GHMBC spectrum, an artifact response can be anticipated
at the 13C chemical shift of the other member of the pair. In the
case of vinblastine, there is a prominent C-2-N-1 correlation
response, as expected. In addition, as has already been discussed,
there is also a very strong artifact response at the C-24 13C and
N-1 15N chemical shifts in the 13C-15N correlation spectrum shown
Figure 5. Panel A shows the conventional indirect covariance processed result from the multiplicity-edited GHSQC spectrum of vinblastine
(1). Normally, this processing would not be done, as it does not provide useful correlation information. However, there are some correlation
responses that need to be considered. Because of the nature of the indirect covariance processing algorithms, correlation responses in the
indirect covariance processed result from a GHSQC spectrum can only occur due to resonance overlap. In the expansion shown in panel
B the off-diagonal responses arising from the overlap of the H-2 and H-24 O-methyl resonances are labeled. Responses of this type are a
predictor of potential artifact responses in the 13C-15N HSQC-HMBC correlation spectrum calculated by unsymmetrical indirect covariance
processing shown in Figures 2 and 3. If one of the overlapped proton resonances exhibits a long-range correlation response to 15N in the
GHMBC spectrum used in the unsymmetrical indirect covariance processing, an artifact response can be observed at the corresponding 13C
chemical shift of the proton overlapped with the proton that is legitimately long-range correlated to 15N. The artifact response will be
observed at the 15N shift of the nitrogen to which the legitimate correlation is observed. In the present case, H-2 is long-range coupled to
N1, giving a correlation response for C-2-N-1 (Figure 3). The overlap of the H-2 and H-24 O-methyl resonances leads to a C-2-N-1
correlation response via the 2JNH correlation of H-2 to N-1 and consequently to the C-24-N-1 artifact response observed in Figure 3, as
predicted in panel B.
13C-15N Correlation Via Unsymmetrical Indirect CoVariance NMR Journal of Natural Products, 2007, Vol. 70, No. 12 1969

in Figure 3. Applying conventional covariance processing to the
1H-13C GHSQC spectrum of a molecule of interest prior to using
unsymmetrical indirect covariance processing to generate a 13C-15N
HSQC-HMBC heteronuclear shift correlation spectrum provides a
convenient means of forecasting the possibility of artifact correlation
responses in the unsymmetrical indirect covariance processed data.
Furthermore, since a GHSQC spectrum will always be available
when unsymmetrical indirect covariance processing is being done,
the cost of this step is inconsequential and the interpretation of the
covariance spectrum is a facile process.
As has been shown previously for simpler molecules,15,16
multiplicity-edited 1H-13C GHSQC and 1H-15N long-range het-
eronuclear shift correlation spectra can be used successfully for
unsymmetrical indirect covariance processing for molecules of the
molecular complexity of vinblastine (1) with a relative minimum
of artifacts. Further, by subjecting the initial multiplicity-edited
1H-13C GHSQC spectrum to covariance processing, the possibility
of artifacts can be forecast on the basis of off-diagonal correlation
responses in the covariance spectrum. We are currently exploring
the potential benefits and impact of the availability of 13C-15N
heteronuclear chemical shift correlation data on the computer-
assisted structure elucidation of a group of model alkaloids, which
will be the subject of a future report. We are also exploring the
potential of covariance processing of GHSQC spectra for the
prediction of artifacts in other unsymmetrical indirect covariance
processing applications.
It should be noted that covariance8,13 and unsymmetrical indirect
covariance methods10–13,15,16 do not create new connectivity
information that is not already present in the spectra from which
they are derived. Rather, these methods provide an alternative and
potentially very efficient way to extract the connectivity information
contained in the spectra being processed. In a sense, covariance
processing methods are analogous to the Fourier transform.
The interpretation of time domain data is essentially impossible,
while the information content of a spectrum following conversion
to the frequency domain is much more readily interpreted.
Experimental Section
General Experimental Procedures. A sample of 20 mg of
vinblastine (1) (Sigma Aldrich) was prepared for NMR data acquisition
by dissolving the material in ∼180 µL of d6-DMSO (CIL). The resulting
solution was transferred to a 3 mm NMR tube (Wilmad) using a flexible
Teflon needle and a gastight syringe (Hamilton). All NMR spectra were
recorded using a Varian three-channel NMR spectrometer operating at
a proton observation frequency of 599.75 MHz and equipped with a 5
mm Varian ColdProbe operating at an rf coil temperature of 20 K.
The sample temperature was regulated at 26 oC. The GHSQC and
GHMBC pulse sequences were used directly from the vendor-supplied
pulse sequence library without modification. The one-bond delay in
the HSQC experiment was optimized for 145 Hz. The long-range delay
in the 1H-15N GHMBC experiment was optimized for 5 Hz. Gradient
1H-13C HSQC data were acquired, but nongradient data could be
employed; gradient 1H-15N data are necessary to sufficiently flatten
the noise floor of the 2D data matrix when data are acquired at natural
abundance. The 1H-13C GHSQC data were acquired in ∼30 min; the
1H-15N GHMBC data were acquired in 6.8 h. Spectral widths for both
experiments in the F2 frequency domain were 7225 Hz; F1 spectral
windows were optimized independently. All 2D NMR spectra were
acquired with 1024 points in t2 and were zero-filled to 2048 points
prior to the first Fourier transform. The second frequency domain of
both experiments was digitized using 128 increments of the evolution
time, t1, after which the data were linear predicted to 256 points and
then zero-filled to 512 points prior to the second Fourier transform.
The 1H-13C GHSQC spectrum was acquired with 8 transients/t1
increment. The 1H-15N GHMBC data were acquired with 128
transients/t1 increment. All NMR data processing was done using the
ACD/Labs SpecManager v10.02 software. Unsymmetrical indirect
covariance calculations took ∼4 s using a laptop computer with 1 Gbyte
of RAM and a 1.8 GHz processor. For the ASIS experiments, 50 µL
of d6-benzene (CIL) was added to the sample.
References and Notes
(1) Martin, G. E.; Hadden, C. E. J. Nat. Prod. 2000, 65, 543–585.
(2) Marek, R.; Lycka, A. Curr. Org. Chem. 2002, 6, 35–66.
(3) Martin, G. E.; Williams, A. J. Annu. Rep. NMR Spectrosc. Webb, G. A.,
Ed.; Elsevier: Amsterdam, 2005; Vol. 18, pp 1–119.
(4) Forgo, P.; Homann, J.; Dombi, G.; Máthé, L. In Poisonous Plants
and Related Toxins; Acamovic, T., Steward, S., Pennycott, T. W.,
Eds.; CABI Publishing: Wallingford, UK, 2004; pp 322–328.
(5) Martin, G. E.; Solntseva, M.; Williams, A. J. In Modern Alkaloids,,
Fattorusso, E., Taglialatela-Scafati, O., Eds.; Wiley-VCH: New York,
2007, in press.
(6) Pérez-Trujillo, M.; Nolis, P.; Parella, T. Org. Lett. 2007, 9, 29–32.
(7) Kupcˇe, E.; Freeman, R. Magn. Reson. Chem. 2007, 45, 103–105.
(8) Zhang, Z.; Brüschweiler, R. J. Am. Chem. Soc. 2004, 126, 13180–
13181.
(9) Blinov, K. A.; Larin, N. I.; Kvasha, M. P.; Moser, A.; Williams, A. J.;
Martin, G. E. Magn. Reson. Chem. 2005, 43, 999–1007.
(10) Blinov, K. A.; Larin, N. I.; Williams, A. J.; Zell, M.; Martin, G. E.
Magn. Reson. Chem. 2006, 44, 107–109.
(11) Blinov, K. A.; Larin, N. I.; Williams, A. J.; Mills, K. A.; Martin, G. E.
J. Heterocycl. Chem. 2006, 43, 163–166.
(12) Martin, G. E.; Hilton, B. D.; Irish, P. A.; Blinov, K. A.; Williams,
A. J. J. Nat. Prod. 2007, 70, 1393–1397.
(13) Blinov, K. A.; Williams, A. J.; Hilton, B. D.; Irish, P. A.; Martin,
G. E. Magn. Reson. Chem. 2007, 45, 544–546.
(14) Schoeflberger, W.; Smrecˇki, V.; Vikic´-Topic´, D.; Müller, N. Magn.
Reson. Chem. 2007, 45, 583–589.
(15) Martin, G. E.; Hilton, B. D.; Irish, P. A.; Blinov, K. A.; Williams,
A. J. Magn. Reson. Chem. 2007, 45, 624–627.
(16) Martin, G. E.; Hilton, B. D.; Irish, P. A.; Blinov, K. A.; Williams,
A. J. J. Heterocycl. Chem. 2007, 44, 1219–1222.
(17) Martin, G. E.; Hilton, B. D.; Blinov, K. A.; Williams, A. J. Magn.
Reson. Chem. 2008, in press.
NP070361T
1970 Journal of Natural Products, 2007, Vol. 70, No. 12 Martin et al.