Liang Et Al-2010-Journal of Separation Science
Liang Et Al-2010-Journal of Separation Science
Liang Et Al-2010-Journal of Separation Science
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J. Sep. Sci. 2010, 33, 410–421 Other Techniques 411
chemically represent the TCM investigated [12–15]. Thus, obtained, some types of variation sources are likely confused
the CF technique has been extensively accepted for quality from one chromatogram to another. One of the variations is
control of TCMs and the HMs with synergic features [16]. imposed by the retention time shifts. For instance, the
retention time shifts happened in HPLC are caused by
the variation sources which might be due to (i) the
2.1 Information features of CFs of TCM degradation of the stationary phase, especially, the low
stability of silica and silica-based supports at high pH
If one wants to obtain an informative fingerprint of TCMs, a values and the collapse of C18 bonded phase because
good extracting method and a chromatogram with good of a high content of water in polar mobile phase eluted;
resolution are needed. Thus, optimization of the extraction (ii) minor changes in mobile phase composition caused
method and operation procedure is an important task. by temperature and pressure fluctuations, variations
Suppose that we have obtained some fingerprints, the next in flow-rate, and gradient dispersion; (iii) some problems
step will be to evaluate the information contents of the CFs involved in the detectors, for example, a wavelength
of HMs reasonably and efficiently. From the point of view of shift in the UV spectrometer, a spectroscopic intensity
multivariate, the information content of a chromatogram variation and the misalignment of the monochromator;
with lots of peaks might be calculated by means of various (iv) the column overloading on account of the great
approaches [17–21]. In fact, a CF of a TCM could be injected amount or some components with high concentra-
regarded as a continuous signal determined by its chroma- tion; (v) the possible interaction between analytes; (vi) other
tographic shape. Based on information theory, the informa- unknown shifts in the instrument. These variations
tion content (F) for CFs of TCMs could be defined [22], can cause imperfect alignment of the data when comparing
that is runs. Being able to determine which peaks appear reprodu-
X ! xi " ! xi " cibly across chromatograms is difficult if the profiles are
U¼" P log P ð1Þ misaligned. Furthermore, misalignment in chromatographic
xi xi
data is rarely a simple shift. Most often, there is extension
where xi is the real chromatographic response of the and compression throughout the chromatogram at varying
chemical components involved in the CF under study. points. A simple example of peak alignment is shown in
Here, the normalization of xi divided by their sum is to Fig. 2. Thus, it is important to choose an alignment protocol
make the chromatogram investigated be of probability that will compare points throughout the chromatogram.
property. In this way, Eq. (1) is exactly the expression of Pattern recognition depends on the ability to directly compare
Shannon entropy, that is, the information content uniform data files. If the files are not aligned, a pattern
of the chromatogram investigated. Noting that in recognition algorithm may fail to recognize consistent signals
information theory, if and only if xi with unchangeable simply because they are not found at the same location each
variance is characterized by normal distribution can its time.
information content F reach maximum [23]. Under an ideal During the past decades, several kinds of useful
situation, all the chromatographic peaks in a chromatogram chemometric approaches have been developed for peak
can be separated completely and each peak confined to a synchronization in chromatographic profiles [25–38]. Some
narrow zone might correspond to a normal distribution of them corrected the retention time shifts by making
profile [24]. A CF with all of peaks just completely separated internal standards added or marker peaks coinciding in all
should be featured by maximal information content. chromatograms under study [25, 27–29]. In Refs. [26,
However, in reality, some peaks in a complex fingerprint 30–32], some objective functions on the correlation between
are almost inevitably overlapped with its adjacent one; such the target and sample chromatograms were optimized
overlapped peaks will surely show non-Gaussian normal and then the sample chromatographic profiles were
distribution and therefore undoubtedly cause a loss of the aligned automatically with the target. In general, the
information content. The method uses the whole chromato- methods must be very efficient and elegant if the samples
gram with a simple normalization, thus it is not necessary investigated are quite similar in the concentration profiles of
to identify the retention time, peak intensity, peak width, the chemical components. However, if the concentration
peak area, and/or peak height for all the peaks identified. profiles change greatly for the complex samples such as
The calculation burden is reduced significantly. Moreover, HMs from the different habitats and/or from the various
the theoretic background of the method is simple and harvest seasons, wrong results might be obtained by simply
reasonable. Figure 1 shows such a situation discussed seeking the optimal correlation coefficient between the
above. chromatograms.
More recently, some new techniques were developed in
chemometrics in peak alignment [33–38]. Among them,
2.2 Peak alignment of CFs by chemometrics from the point of view of information usage, the methods
can be roughly classified into two kinds. Some were trying
The analysis of complex CFs can be quite challenging. When to use the information from spectrum to correct the chro-
one deals with several CFs jointly with all data points matographic shifts, since the spectral information will be
& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com
412 Y. Liang et al. J. Sep. Sci. 2010, 33, 410–421
very useful for featuring the chromatographic peaks [37–38]. 2.3 Quality control of TCM based on pattern analysis
The other kind of methods were trying to fully use the of CFs
feature embedded in chromatograms with the help of
statistic techniques, such as analysis of variance feature By definition, a CF of a TCM, in practice, is a chromato-
selection, Kalman tracking, and principal component graphic pattern of the extract of some common chemical
analysis (PCA) [33–35]. components of pharmacological activity or chemical char-
After such a correction of the chromatographic shifts of acteristics [39–41]. Several works using the CFs obtained by
the CFs resulted from HPLC, GC, CE, etc., the identity, HPLC or GC for quality control of HMs have been reported
stability, and consistency of TCMs as well as the differ- with the help of similarity analysis and chemical pattern
entiation of adulterants could then be done by similarity recognition [42–50].
analysis and chemical pattern recognition developed in To identify Chinese Angelica (CA) from related herbs,
chemometrics. such as Japanese Angelicae Root (Angelica radix, JA), Szech-
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J. Sep. Sci. 2010, 33, 410–421 Other Techniques 413
& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com
414 Y. Liang et al. J. Sep. Sci. 2010, 33, 410–421
Figure 3. HPLC chromatograms measured at UV 280 nm of (A) 40 Chinese Angelica samples; (B) four Japanese Angelicae Root samples;
(C) six Szechwan Lovage Rhizome samples; and (D) three Cnidium Rhizome sample. The peaks marked by numbers represent ferulic acid
(1), coniferyl ferulate (4), senkyunolide A (5), and Z-ligustilide (9), respectively.
Table 1. Total classification errors and incorrect rates of the test sets for ten times of calculations of the final injection products (letters A,
B, C, D, E and F denote different manufactures, respectively)
Mahalanobis distance Incorrect rates Similarity method Incorrect rates OP technique Incorrect rates
A B C D E F A B C D E F A B C D E F
and its final injection products from six different manu- determination and identification of unknown samples
facturers were studied. The results are summarized shows it could be a powerful tool for quality control in HM
in Table 1. The good performance of OP technique in production [55].
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J. Sep. Sci. 2010, 33, 410–421 Other Techniques 415
3 Further qualitative and quantitative powerful tools to accomplish this job [60–69]. With the help
analysis of TCM fingerprints with the of chemometric resolution methods, the qualitative and
help of hyphenated chromatographic relatively quantitative analysis for some CFs of volatile
techniques and chemometrics components in TCMs obtained from GC-MS were also
reported [6, 7, 70–72]. When the boiling points of
To understand bioactivities and possible side effects of active compounds are close to each other, co-elution of two or
compounds and to enhance quality control of TCMs, it more different compounds is very possible although the
seems necessary for one to determine most of the chromatographic conditions are optimized. In such a case,
phytochemical constituents of herbal products. With the by direct similarity searches in MS database alone is hard to
development of analytical instruments, especially with the identify the compounds, which will even result in wrong
development of the hyphenated chromatographic instru- conclusions. Therefore, it is extremely necessary to resolve
ments, such as GC-MS, HPLC-DAD, HPLC-DAD-MSn, the overlapping peaks by means of chemometric techni-
HPLC-NMR, CE-DAD, and CE-MS, the qualitative and ques. With the help of chemometric resolution methods,
quantitative ability has been enhanced significantly, since such as heuristic evolving latent projections and subwindow
such instruments provide not only their separation ability factor analysis, determination of volatile components in
but also their qualitative ability with spectroscopic profiles. Cortex Cinnamomi [6], Notoptergium incium [71], Artemisia
It builds the chemical foundation for explanation of the capillaris [72], and peptic powder [7] were conducted by GC-
mechanism of pharmacological activity. Just like the MS. Tentative identifications were performed by comparing
situation in metabolomics, as pointed out by Van de Greef, the retention time and mass spectra of samples with stan-
‘‘the comprehensive identification of metabolites remains a dards or/and earlier publications.
key challenge’’ [56]. Based on the CFs obtained, compre-
hensive identification of secondary metabolites of the TCMs
should be very momentous, and the assistance of chemo- 3.2 Comparing analysis between CFs with the help
metric measurement is also indispensable. of chemometrics
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416 Y. Liang et al. J. Sep. Sci. 2010, 33, 410–421
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J. Sep. Sci. 2010, 33, 410–421 Other Techniques 417
as against atherosclerosis and coronary heart diseases [98]. makes it an attractive candidate for mode of action studies
These positive actions of green tea are related to its anti- [107]. Metabolic profile is being used to evaluate the pharma-
oxidant capacity and therefore it was tried to predict the total cological mechanism of the drugs or drug candidates. The
antioxidant capacity of green tea from CFs by linear multi- method is particularly useful when a moderate number of
variate calibration techniques [99]. The predicted antioxidant different outcomes (e.g. modes-of-action, disease states) can be
capacities can then be a measure for the protective effects pre-defined [108].
and for the quality of the tea. However, for chromatographic Using metabolomic profile and nine antibacterial
data, e.g. fingerprints, only few multivariate calibration substances with known modes of action, the antibacterial
applications are described. Recently, Dumarey et al. explored mode of berberine on Staphylococcus aureus was recently
linear multivariate calibration techniques to predict the total investigated [109]. The working procedure is elucidated
antioxidant capacity of green tea from CFs. Also, van briefly in Fig. 5. With the help of HPLC/ESI-MS, metabolic
Nederkassel et al. [95] predicted the total antioxidant capacity profiles of S. aureus treated by berberine and nine anti-
of green tea from their CFs by the use of PLS [99, 100] and bacterial substances with known modes of action (see
uninformative variable elimination PLS [101]. More recent- Table 2) were firstly acquired. After data pretreatment, those
ly, using whole chromatographic profiles and measure- profiles acquired were reduced into several MS vectors
ments of total bioactivity as input, a quantitative containing 900 m/z values. Then, PCA was carried out upon
pattern–activity relationship approach [102] was proposed as those metabolic profiles in order to classify those drugs
a general method for providing two pieces of crucial infor- according to their mechanisms. From the result obtained by
mation about complex bioactive mixtures available: (i) a PCA, the possible antibacterial mode of berberine was
model for predicting total bioactivity from the CF and (ii) the explored. Also the antimicrobial roles of dihy-
features in the chromatographic profile responsible for the drocucurbitacin F-25-O-acetate, one of the major compo-
bioactivity. The targeted approach makes information about nents in Hemsleya pengxianensis, on S. aureus were also
bioactivity available at the molecular level and provides explored with the similar approach [110]. The result
possibilities for assessment of HM possible beyond just obtained showed the mechanism may be to inhibit cell wall
authentication and total bioactivity. As an example, the synthesis.
antioxidant property of the HM Radix Puerariae lobatae was Another example of score plot from PCA (the variance
measured through its reducing power toward a ferric ion of the first two PC being 89.5% of total variance of the data)
complex. A PLS model was created to predict the antioxidant for exploring the antibacterial mode of TCM Aquilegia
activity from the CF. Using the antioxidant activity as a oxysepala is shown in Fig. 6. From Fig. 6, one could see
target, the most discriminatory projection in the multi- clearly that 90 samples treated with different drugs and
variate space spanned by the chromatographic profiles was controls are well-separated. Cefataxime, whose target is on
revealed. transpeptidases and carboxpeptidases, formed a distinct
On the other hand, the mechanism of TCMs is usually cluster separated from the other antibiotics based on its
unknown, which also poses challenges to the pharmaceutical different mode of action. Acheomycin, lincolmensin,
and agrochemical industries [103–105]. Metabolic profile is a erythromycin, chloromycetin, and streptomycin cluster
very sensitive indicator of environmental influences and might together. As known from Table 2, lincolmensin, erythro-
be used to detect and analyze changes of the total metabolic mycin, and chloromycetin have effects on 50S ribosomal
state of microbe due to pathophysiological stimuli [106] [http:// subunit; streptomycin and acheomycin act on 30S riboso-
www.touchbriefings.com/download.cfm?FileId 5 2386], which mal subunit. In a word, the mode of action of those five
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418 Y. Liang et al. J. Sep. Sci. 2010, 33, 410–421
5 Concluding remarks
Drug/class Function inhibited Molecular target This work is financially supported by the National Nature
Foundation Committee of P. R. China (Grant No. 20875104)
Chloromycetin Protein synthesis 50S ribosomal subunit and the international cooperation project on traditional Chinese
Streptomycin Protein synthesis 30S ribosomal subunit medicines of Ministry of Science and Technology of China
Acheomycin Protein synthesis 30S ribosomal subunit (2007DFA40680).
Erythromycin Protein synthesis 50S ribosomal subunit
Lincolmensin Protein synthesis 50S ribosomal subunit
Norfloxacin DNA replication/ Gyrase and topoisomerase IV The authors have declared no conflict of interest.
transcription
Rifampicin Transcription RNA polymerase
Cefataxime Peptidoglycan Transpeptidases and
synthesis carboxypeptidases
Vancomycin Peptidoglycan Cell wall peptidoglycan
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