Study of the interaction between 10-hydroxycamptothecine and DNA with the use of ethidium bromide dye as a fluorescence probe

Sensors and Actuators B 156 (2011) 290–297

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Sensors and Actuators B: Chemical journal homepage: www.elsevier.com/locate/snb

Study of the interaction between 10-hydroxycamptothecine and DNA with the use of ethidium bromide dye as a fluorescence probe Yongnian Ni a,b,∗ , Yingxia Wang b , Serge Kokot c a b c

Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, China Department of Chemistry, Nanchang University, Nanchang 330031, China Chemistry, Faculty of Science and Technology, Queensland University of Technology, Brisbane 4001, Australia

a r t i c l e

i n f o

Article history: Received 18 May 2010 Received in revised form 9 April 2011 Accepted 13 April 2011 Available online 21 April 2011 Keywords: Spectroscopy 10-Hydroxycamptothecine PARAFAC MCR-ALS DNA Ethidium bromide

a b s t r a c t The interaction of 10-hydroxycamptothecine (HCPT) with DNA under pseudo-physiological conditions (Tris–HCl buffer of pH 7.4), using ethidium bromide (EB) dye as a probe, was investigated with the use of spectrofluorimetry, UV–vis spectrometry and viscosity measurement. The binding constant and binding number for HCPT with DNA were evaluated as (7.1 ± 0.5) × 104 M−1 and 1.1, respectively, by multivariate curve resolution-alternating least squares (MCR-ALS). Moreover, parallel factor analysis (PARAFAC) was applied to resolve the three-way fluorescence data obtained from the interaction system, and the concentration information for the three components of the system at equilibrium was simultaneously obtained. It was found that there was a cooperative interaction between the HCPT–DNA complex and EB, which produced a ternary complex of HCPT–DNA–EB. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Camptothecin, a cytotoxic alkaloid obtained from Camptotheca acuminata Decne, has strong antitumor activity against a wide range of experimental tumors. Camptothecin is insoluble in both organic and aqueous solvents. This insolubility has impeded the clinical development of camptothecin and its analogs [1]. 10Hydroxycamptothecine (HCPT, CAS No. 19685-09-7, molecular formula C20 H16 N2 O5 , molecular weight 364.4) is one of its analogs. HCPT is a minor alkaloid isolated from Camptotheca acuminata, or manufactured by semisynthesis from camptothecine [2]. HCPT and its analogs stabilize type 1 topoisomerase–DNA (deoxyribonucleic acid) complex and inhibit the synthesis of RNA (ribonucleic acid) [3]. HCPT is mainly used clinically for the treatment of gastrointestinal, jecoral, rectal tumors and leucocythemia. Nucleic acids are the basic biomolecules of life [4]. Many anticancer drugs are known to interact with DNA to exert their biological activities. Generally, DNA-acting anticancer drugs can be classified into three categories: covalent linkages with DNA; noncovalent complexes with DNA by either intercalation or groovebinding; and drug initiated DNA backbone cleavages [5]. Studies of the binding interaction between the drug and DNA are beneficial

∗ Corresponding author at: Department of Chemistry, Nanchang University, Nanchang 330047, China. Tel.: +86 791 3969500; fax: +86 791 3969500. E-mail address: [email protected] (Y. Ni). 0925-4005/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.snb.2011.04.035

not only for understanding the mechanism of interaction, but also for planning the design of new drugs [6]. It is well known that the interaction of ethidium bromide (EB) with DNA follows the intercalation model and hence, EB is considered as an intercalator [7,8]. These are competitive or cooperative interactions between drugs and fluorescence probe, and it is important to address this issue in order to obtain a fuller description of the interaction [9]. There are many methods to study the DNA binding properties: X-ray diffraction, viscosity measurement; H NMR measurement; agarose gel electrophoresis; spectrometric measurements, including UV–vis spectra, fluorescence spectra, circular dichroism and electron paramagnetic resonance spectra; electrochemical measurements, including cyclic and differential pulse voltammetry, and so on [10–14]. Among these methods, spectrophotometric ones are common and convincing [15]. With the development of high order analytical instruments and chemometrics algorithms, it has become easier to obtain and resolve multi-dimensional data from complex reaction systems. A chemometrics method, parallel factor analysis (PARAFAC), has been widely applied to resolve complex data, such as the excitation–emission fluorescence matrices (EEM) spectra [16–18]. However, PARAFAC requires second-order data following low-rank trilinear structures, and such data unavailability is then overcome by multiple curve resolution-alternating least squares (MCR-ALS), another powerful chemometrics tool, which can handle deviations from trilinearity efficiently [19]. MCR-ALS is a soft-modeling

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method [20], and does not need a previously postulated chemical model. MCR-ALS method will give rise to unresolved underlying factor analysis ambiguities [21,22]. However, MCR-ALS allows the analysis of more than one data matrix simultaneously. This greatly reduces the number of possible solutions and ambiguity inherent in factor analysis. The combination of excitation–emission spectroscopy and trilinear chemometrics algorithms could provide a powerful tool for studies of parallel competitive or cooperative binding reactions of many chemical components with DNA in the presence of interferents. Such studies would be very helpful for understanding binding interactions of many drugs used in combination in the clinical treatment of some diseases. Full utilization of the so-called second-order advantage [23] makes it possible to determine the reaction pattern of different interacting pairs in a mixture medium. Recently, the interaction of tetracycline antibiotic and aluminium ions with DNA was studied with spectrofluorimetry and chemometrics-particularly with the application of PARAFAC [24]. In this study, the application of the MCR-ALS method for the simultaneous resolution of the UV–vis and fluorescence spectra collected from the HCPT–DNA mixtures was investigated. The pure spectra and the concentration profiles of the three constituents, HCPT, DNA and HCPT–DNA complex, were evaluated from the measured overlapping spectral data. All of these objectives are generally difficult to achieve by conventional means of data interpretation. In addition, a three-way data array of the complex system consisting of the anti-cancer drug HCPT, fluorescence probe EB and DNA has been obtained by excitation–emission fluorescence spectroscopy and resolved by PARAFAC. 2. Experimental

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in the concentration range of 0.0–2.2 × 10−5 mol L−1 at intervals of 1.0 × 10−6 mol L−1 (total 23 solutions). 2.3.2. Experiment 2 The concentration of HCPT was kept constant (2.0 × 10−5 mol L−1 ), then different amounts of DNA were added in the range of 0.0–4.4 × 10−5 mol L−1 at intervals of 2.0 × 10−6 mol L−1 . A total of 23 solutions were prepared. Each solution sample of experiments 1 and 2 was allowed to stand for 10 min and then its UV–vis (200–450 nm) and fluorescence (330–580 nm, ex = 320 nm) spectra were collected every 1 and 0.5 nm, respectively. Thus, four data matrices DDNA UV (23 × HCPT HCPT (23 × 501), D (23 × 251) and D (23 × 501) were 251), DDNA F UV F obtained from these measurements (Fig. 1A–D), and a column- and row-wise expanded data matrix with two different measurements for the two different experiments was constructed. It was resolved by a chemometrics approach, MCR-ALS (see Section 2.4.2). 2.3.3. Experiment 3 Viscosity measurements were performed using a viscometer, which was immersed in a thermostat water-bath at 25 ± 0.1 ◦ C. Double-stranded calf thymus DNA (10.1 × 10−5 mol L−1 ) was placed in the viscometer and titrations were performed by adding aliquots of solution of HCPT (1.0 × 10−5 mol L−1 ). After each addition, the solution was carefully mixed with a small flow of air through the dilution bulb of the viscometer, and the flow time was measured at least in triplicate with a precision of ±0.2 s, and an average time was calculated. Flow times were larger than 200 s, and the data were presented as (/0 )1/3 versus ([HCPT]:[DNA]), where  and 0 are the viscosities of DNA in the presence and absence of the HCPT, respectively.

2.1. Apparatus The fluorescence spectra were measured on a Perkin-Elmer LS55 luminescence spectrometer equipped with a thermostatic bath (Model ZC-10, Tianheng Instruments Factory, Ningbo, China) and a 10 mm quartz cuvette. The excitation and emission slits were set at 10 nm while the scanning rate was 1500 nm min−1 . The UV–vis absorption spectra were measured on an Agilent UV-8453 spectrophotometer with the use of a 10 mm cuvette. The viscosity measurements were carried out using an Ubbelohde viscometer (Shanghai Dipu Instrumental Co.).

2.3.4. Experiment 4 HCPT and DNA solutions were mixed thoroughly in a 1:1 ratio (each of 2.0 × 10−5 mol L−1 ), and then the EB solution (0.0–2.3 × 10−5 mol L−1 in steps of 1.0 × 10−6 mol L−1 ; total: 24 samples) was added to the mixture. The fluorescence spectra of the mixtures of HCPT–DNA and EB were obtained within the excitation range of 300–590 nm (every 10 nm) and emission range of 370–680 nm (every 0.5 nm). Thus, the three-way EEM stacks, XI × J × K , which the dimensions of 24 (samples) × 30 (ex ) × 621 (em ), as defined by the I × J × K, were obtained and then decomposed by PARAFAC (see Section 2.4.3).

2.2. Reagents The calf thymus DNA (ct-DNA) was obtained from Sigma Co., and was dissolved in doubly distilled deionized water containing 50 mmol L−1 NaCl. The purity of the DNA was checked by monitoring the absorption ratio at 260/280 nm (A260 /A280 ). The ratio was observed to be 1.82, which indicated that DNA was free of protein [25]. The DNA concentration (2.0 × 10−3 mol L−1 , in this work) was determined from the UV absorbance at 260 nm by using the molar extinction coefficient of 6600 M−1 cm−1 [26]. The prepared DNA solution was stored at 4 ◦ C. A stock solution (5.0 × 10−3 mol L−1 ) of HCPT (Huangshi Feiyun Pharmacy Co., China) was made up in ethanol and doubly distilled water (10% ethanol). The stock solution (1.0 × 10−3 mol L−1 ) of ethidium bromide (EB, Sigma) was made up with doubly distilled water. 2.3. Experimental procedure 2.3.1. Experiment 1 The concentration of DNA was kept constant (5.0 × 10−5 mol L−1 ), and different amounts of HCPT were added

2.4. Data treatment 2.4.1. Number of species (N), and initial estimates of the concentration profiles and pure spectra The number of species, N, is directly related to the number of main factors in the expanded data matrix, D. For the MCR-ALS methods number is important and is generally estimated by rank analysis, with the use of singular value decomposition (SVD) [27] or some other related technique based on factor analysis. The rank of the matrix calculated by any of these methods is generally assumed to be the number of chemical species, N, in the system. Sometimes, the estimation is difficult, especially when the measured spectra of matrix D are similar or the concentrations of components are low. Initial estimates of concentration profiles and spectra can be provided either by the evolving factor analysis (EFA) [28] or the pure-variable detection methods e.g. SIMPLISMA [29]. EFA has been applied in spectroscopic studies of multi-equilibria systems [30], and it is based on the evaluation of the magnitude of the singular values of the submatrices (of the matrix D) built up by adding successively, one by one, all the rows of the original data matrix in the

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DNA Fig. 1. Experimental data matrices. Experiment 1: (A) absorption (data matrix DDNA ), cDNA = 5.0 × 10−5 mol L−1 , The concentration range of HCPT UV ) and (B) fluorescence (DF ) and (D) fluorescence (DHCPT ), cHCPT = 2.0 × 10−5 mol L−1 , DNA was was 0.0–2.2 × 10−5 mol L−1 for curves 1–23, respectively; Experiment 2: (C) absorption (data matrix DHCPT UV F added at different concentrations 0.0–4.4 × 10−5 mol L−1 for curves 1–23, respectively.

forward direction. In this work, EFA was used to obtain the initial concentration profiles. 2.4.2. Multivariate curve resolution-alternating least squares (MCR-ALS) MCR-ALS is an algorithm, which can solve the problems of linear dependency by resorting to matrix augmentation [31]. Multivariate data were analyzed with the soft modeling MCR procedure to evaluate concentration profiles and pure spectra of spectroscopically active components present in the system by decomposing the matrix D (NC × NS ) according to: D = C × ST + E

(1)

where C is the concentration matrix of the analytes with dimensions of NC × N (NC is the number of spectra recorded with different concentration ratio of ([DNA]:[HCPT]) and N is the number of the detected species), ST is the pure spectra matrix with dimension of N × NS (NS is he number of the wavelengths), and E (NC × NS ) is the error matrix containing the data variance, which is unexplained by the proposed model. Moreover, since the same samples were measured simultaneously by two spectrometric methods, i.e., UV–vis and fluorescence spectrometry, the data may be arranged as follows: [DUV DF ] = C × [S UV S F ]T + [E UV E F ]

(2)

Further more, two kinds of experiments: one with the [DNA] kept constant and the other with the [HCPT] constant, were performed for system as described in Section 2.3. In both experimental

cases, the same spectroscopic technique was applied, and the spectral data interpretation can be expressed as Eq. (3):



DDNA DHCPT



 =

C DNA



 T

×S +

C HCPT

E DNA

 (3)

E HCPT

where [DDNA ; DHCPT ] is the column-wise augmented matrix obtained by formatting one individual matrix above the other. The data matrices DHCPT and DDNA correspond to the two different experiments 1 and 2, respectively (see Section 2.3). The analytes were analyzed by the same spectroscopic method e.g. absorption spectrophotometry. The new column-wise augmented data matrix, [CDNA ; CHCPT ], is the corresponding augmented column-wise concentration matrix. Each column of this augmented matrix has a concentration profile of one species in each of the two different experiments. For each species, its concentration profile, obtained with the use of the two mole-ratio methods, has a different shape. [EDNA ; EHCPT ] is the column-wise augmented error matrix. In general, it is important to note that in this data arrangement, it is implicitly assumed that some or all of the species formed in the two experiments are common i.e., they will have the same spectral profile, although their concentrations or concentration profiles are different in the different experiments. Finally, the last model applied for data interpretation is:



DDNA UV

DDNA F

DHCPT UV

DHCPT F



 =

C DNA C HCPT



 × [ S TUV

S TF

]+

E DNA UV

E DNA F

E HCPT UV

E HCPT F

 (4)

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where [[DUV , DF ]DNA ; [DUV , DF ]HCPT ] is the row- and columnwise augmented experimental data matrix, which contains all the data from the two different experiments as measured by the two different spectroscopic techniques. An expanded data matrix (combination of four individual data matrices) was analyzed using this model (Eq. (4)). [CDNA ; CHCPT ] is the column-wise augmented concentration matrix as in Eq. (3), [SUV SF ]T is the row-wise augmented spectral matrix as in Eq. (2), and [[EUV EF ]DNA ; [EUV EF ]HCPT ] is the row- and column-wise augmented error matrix derived from the two different experiments and the two spectral techniques. 2.4.3. Parallel factor analysis algorithm (PARAFAC) PARAFAC is based on the so-called trilinear tensor theory [32]. It is a chemometrics method for multi-way data decomposition, which was used to resolve the three-way EEM obtained from experiment 4 in Section 2.3. For a trilinear spectral data array with an appropriate number of selected model factors, PARAFAC will produce unique solutions, which correspond to the true underlying spectra. In addition, concentrations of the analytes can also be extracted [33]. A PARAFAC model of a three-way array is given by three loading matrices A, B and C with elements an , bn and cn . If I equilibrium mixtures containing N fluorescing components were measured at J excitation and K emission wavelengths, the I of J × K matrices of the excitation–emission fluorescence spectra could be obtained. Thus, a three-way data array X (I × J × K) is formulated as follows [8]: XI×J×K =

N 

an ⊗ bn ⊗ c n + EI×J×K

(5)

n=1

where the symbol ‘⊗’ denotes a tensor product; an , bn and cn are concentration, excitation and emission profiles of the nth fluorescing chemical component, respectively; XI × J × K is an element of the trilinear data set X, and EI × J × K is an element of three-way array of residuals E. Given the ALS method, if any two loadings modes are known, the third may be estimated, and then the solution to the PARAFAC model can be obtained [34]. Thus, if estimates of b and c are given, it is possible to determine a by the least squares solution to the model X = A(B ⊗ C) + E

(6)

If the vector (b⊗c) is defined as Z in the case of more than one component, the model defining A is X = AZ

(7)

The least squares estimate of A is A = XZ T (ZZ T )

−1

(8)

Likewise, B and C can be obtained. A typical iterative procedure follows the following scheme: (i) estimate the number of chemical components, N; (ii) initialize matrices B and C and estimate A from X, B, and C by least squares regression; (iii) estimate matrices B and C in the same way as matrix A in step (ii); and (iv) return to step (ii) until convergence. 3. Results and discussion 3.1. The fluorescence and UV–vis study between HCPT and DNA interactions Results from the experiments (Section 2.3 and Table 1) are presented as the UV–vis and fluorescence spectra obtained from: (i) the mole ratio method in which the cDNA was kept constant (Fig. 1A

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Table 1 Experimental conditions for DNA/HCPT systems. Experiment method Constant cDNA Constant cHCPT

cDNA (mol L−1 )

cHCPT (mol L−1 )

Data matrices obtained

5.0 × 10−5

0–2.2 × 10−5

DNA DDNA UV and DF

−5

−5

0–4.4 × 10

2.0 × 10

DHCPT and DHCPT UV F

and B), and (ii) the mole-ratio method in which the cHCPT was kept constant (Fig. 1C and D). The fluorescence spectrum of HCPT with an excited wavelength of 320 nm was enhanced by the addition of DNA at different concentrations (Fig. 1D). It appeared that as the concentration ratio changed, the band at 445 nm blue shifted to 422 nm and resolved into a shoulder peak; another broad maximum at ∼425 nm, blue shifted to ∼393 nm (these two cases are shown in Fig. 1B and D). The peak at 525 nm decreased and had a slight blue-shift when DNA was added, and there was an isoactinic point at 507 nm. The UV–vis absorption spectrum of DNA (Fig. 1A, spectrum 1) had a peak at about 260 nm, while the UV–vis absorption spectrum of HCPT (Fig. 1C, spectrum 1) had several peaks, 221, 265, 333, 363 and 383 nm. Clearly, a spectrum from a mixture of the two substances (DNA and HCPT) would only have a composite profile consisting strongly overlapping spectra from the two individual analytes. Thus, it is difficult to recognize the spectrum of the HCPT–DNA complex and to follow its formation spectrally as the reaction progresses (e.g. spectra 1–23 in Figs. 1A and C). Similar phenomena were also observed from the fluorescence spectra of the system (see Fig. 1B and D). Therefore, the four spectral data matrices were combined and submitted to MCR-ALS analysis (see Eq. (4)) in an attempt to extract the pure spectra of all molecular components and the associated concentration profiles. 3.2. Interpretation by MCR-ALS The expanded data matrix, D, (see Table 1, obtained from Section 2.3) was processed by MCR-ALS according to Eq. (4). The number of significant factors, related to the chemical species, was evaluated with the application of the SVD method to the augmented data matrix. The first four eigen values were 30.27, 5.19, 0.191 and 0.020, and thus, three significant factors were sufficient to account for the data. The UV–vis and fluorescence data from experiment 1 clearly showed the presence of only three main factors. These were related to the HCPT, DNA and HCPT–DNA complex. However, no estimates of the initial concentrations of these three species could be obtained because of the serious spectral overlap. In general, the MCR-ALS analysis has to be initialized with estimates of the pure spectra or concentrations for the three postulated species. In this work, as described in Section 2.4.1, EFA was applied to each of the experiments to estimate the initial concentrations, which corresponded to the three analytes, and then these estimates were optimized by MCR-ALS model. The concentration profiles calculated were constrained to be positive or zero and to give unimodal profiles [21]. In addition, as the concentrations of HCPT and/or DNA were known in the experiments, this information was also included as a closure constraint for the concentrations profiles. The concentration profiles recovered by the MCR-ALS for experiments at constants cHCPT and cDNA (Fig. 2C and D, respectively) correspond to data matrices CHCPT and CDNA (Eq. (4)). It can be seen that the concentration of the complex HCPT–DNA increased and the one for free HCPT decreased gradually with increasing concentration of the added DNA (Fig. 2C); and from Fig. 2D, the concentration of complex HCPT–DNA increased and the one for DNA decreased with the added HCPT. Moreover, the [DNA]:[HCPT] mole ratio in the complex was ∼1.1 and ∼0.9 as the concentrations of HCPT–DNA

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Fig. 2. Results of the simultaneous analysis of the UV–vis and fluorescence data of the two experiments from Eq. (4). Recovered UV–vis (A) and fluorescence (B) spectra, corresponding to SUV and SF , respectively and concentration profiles for experiment 1 (C) and experiment 2 (D), corresponding to CDNA and CHCPT , respectively.

complex remained nearly unchanged, it was deduced that one HCPT molecule was bound to about one base pair. The average value for the binding number was 1.0 ± 0.1 (∼1), and for the average binding constant, it was calculated as (7.1 ± 0.5) × 104 M−1 (obtained from the equation of K = [HCPT–DNA]/{[HCPT][DNA]} using the corresponding concentration values at [DNA]:[HCPT] = 1.1 and [HCPT]:[DNA] = 0.9 in Fig. 2C and D, respectively). Furthermore, the pure UV–vis and fluorescence spectra correspond to SUV and SF (see Eq. (4)), respectively, were also resolved, and these recovered UV–vis and fluorescence spectra (see dashed lines in Fig. 2A and B) compared well with the measured spectra (solid lines). Such good agreement between the predicted and the measured spectral profiles suggested that the concentration profiles and the spectra of HCPT–DNA complex were correctly resolved. It should be noted that the UV–vis and fluorescence spectra for the HCPT–DNA complex, which were difficult to obtain by conventional methods, were obtained with the application of MCR-ALS.

Then, the viscosity measurements were conducted at room temperature. The changes in relative viscosity of DNA with increasing concentrations of HCPT were shown in Fig. 3. It can be seen that the relative viscosity of DNA increased steadily with the increasing amounts of HCPT. Such behavior further suggested that an inter-

3.3. Viscosity measurements The viscosity experiment is an effective tool to determine the binding mode of small molecules and DNA. A classical intercalation binding demands the space of adjacent base pairs to be large enough to accommodate the bound ligand and to elongate the double helix, resulting in an increase of DNA viscosity [35]. A series of solutions, contained a fixed concentration of DNA and various concentrations of HCPT, were prepared and stored in darkness for 48 h.

Fig. 3. Plot of the relative viscosity of DNA versus ratio of [HCPT]:[DNA]. cDNA = 1.01 × 10−4 mol L−1 .

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calation binding should be the interaction mode of the HCPT with DNA. 3.4. Ethidium bromide (EB) probe experiment and interpretation by PARAFAC EB is a probe for the DNA structure, and the experimental results are shown in Fig. 4. From this Figure, it can be seen that HCPT has two peaks, 445 and 525 nm. When EB was added to this solution, the main broad maximum at ∼445 nm, blue shifted to ∼425 nm. Another broad maximum at ∼525 nm slowly disappeared, and there was an isoactinic point at 564 nm and a new EB peak at about 599 nm developed. The disappearance of the peak in the 525 nm, suggested that a ternary complex, HCPT–DNA–EB, was formed [36], but the bands were too broad and overlapped seriously, which made any detailed interpretation difficult. Thus, in this work, further clarification was carried out with the use of the PARAFAC method for spectral resolution of the EEM data. The number of significant factors of such a complex system, which could be related to the chemical species, can be estimated with the application of the SVD method to the EEM data matrix of X (I × J × K) (obtained from experiment 4, Section 2.3) at j = 370 nm. The first four eigen values obtained were 45.3, 6.23, 1.19 and 0.02, indicating that there were arguably three significant factors for the prediction of the three separate chemical components in the system, i.e., the HCPT–DNA complex, EB and HCPT–DNA–EB ternary complex. As previously indicated, the spectra of these three substances in mixtures overlapped seriously, and therefore, the estimation of concentrations of each component during the titration process (see Fig. 4) was not possible by conventional methods. Thus, X (I × J × K) was resolved by PARAFAC analysis to extract more information for further investigation. Unconstrained PARAFAC models were used in work to obtain a suitable number of components; the core consistency diagnostic method was applied [37,38]. For data matrix X, up to five components were extracted, and the explained data variance indicated that three components (N = 3, ca. 99% data variance explained) were sufficient to account for the information in the data matrix (Table 2). The resolved spectra (dashed lines, Fig. 5A) of the free EB and HCPT–DNA agreed well with their measured ones (solid lines in Fig. 5A). Moreover, the spectrum of the ternary complex of HCPT–DNA–EB was also estimated, which is difficult to obtain by conventional methods. It should be noted that the spectrum of

Fig. 4. Fluorescence emission spectra of the HCPT–DNA in the presence of EB, ex = 370 nm. [DNA] = 2.0 × 10−5 mol L−1 , [HCPT] = 2.0 × 10−5 mol L−1 , [EB] = 0.0. 1.0, 2.0, . . ., 23.0 × 10−6 mol L−1 (curves 1–24).

295

Table 2 Explained variance (%) versus number of components for PARAFAC modeling of the fluorescence data. No. of components

Explained variance (%)

Core consistency (%)

1 2 3 4 5

57.7 80.1 99.2 99.4 99.7

100.0 88.9 85.1 12.1 0.67

HCPT–DNA was different from the spectrum in Fig. 2B; this may be because the excitation wavelength was different. The resolved spectra were compared with the measured ones (Fig. 5A). It can be seen that the band at 430–445 nm was composed of the fluorescent intensity of both the HCPT–DNA and the ternary complex of HCPT–DNA–EB. It can also be seen that the band grew in intensity at approximately 599 nm with the addition of EB, while the peak at 525 nm for HCPT–DNA decreased as the HCPT–DNA complex interacted with the added EB. The band at approximately 599 nm was a composite of the residual free EB and the new additional band due to the growing concentration of the ternary complex. Thus, the resolution of the overlapping spectra by the PARAFAC permitted the rationalization of the complex overlapping spectrum. This argument also suggests that a HCPT–DNA–EB ternary complex was formed [36].

Fig. 5. (A) Comparison of the measured excitation spectra for the HCPT–DNA–EB, HCPT–DNA and EB with those extracted from the PARAFAC analysis. Dashed line: resolved spectra and solid line: measured spectra. (B) Equilibrium concentrations of the HCPT–DNA–EB, HCPT–DNA and EB extracted by PARAFAC. (A) and (B). Dashed profiles – resolved by MCR-ALS; continuous profiles – the original spectra.

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From the equilibrium concentration profiles (Fig. 5B), it was found that the added EB did not react completely with the HCPT–DNA complex to form the ternary complex. There was still some free EB present in the solution. It can also be seen that the concentration of HCPT–DNA–EB complex increased as the concentration of HCPT–DNA decreased. It is known that EB is one of the most sensitive fluorescent probes having a planar structure that binds to the DNA through intercalation [39,40]. From these results, it was concluded that the interaction mode between HCPT and DNA was intercalation. 4. Conclusion Interactions between small drug molecules and biopolymers are important and significant information may be recorded in the UV–vis and fluorescence spectra. This work used the HCPT interaction with DNA as an example, and showed that the application of the chemometrics methods, MCR-ALS and PARAFAC, can lead to satisfactory spectral data interpretation: 1. An expanded data matrix, which contained UV–vis and fluorescence spectral information, led to successful extraction of the pure HCPT, DNA and especially the HCPT–DNA complex spectra from the heavily overlapping composite responses. This is of particular significance as the extraction of the HCPT–DNA can pave the way for a better understanding of the drug–DNA interaction. 2. The extraction of the pure at each experimental point by MCRALS enabled the construction of the concentration profiles of HCPT, DNA and HCPT–DNA complex under conditions of reaction equilibrium. The calculated binding constants and number of HCPT with DNA were (7.1 ± 0.5)×104 M−1 and 1.0. 3. PARAFAC was used to resolve the interaction between HCPT–DNA and EB. The spectrum of the ternary complex, HCPT–DNA–EB, which cannot be obtained by traditional methods, was extracted. It was concluded that HCPT can intercalate to the DNA, and there was a cooperative interaction between the HCPT–DNA complex and EB. Acknowledgements The authors gratefully acknowledge the financial support by the National Natural Science Foundation of China (NSFC21065007) and the State Key Laboratory of Food Science and Technology of Nanchang University (SKLF-MB-201002 and SKLF-TS-200919). References [1] V. Ciddi, M.L. Shuler, Camptothecine from callus cultures of Nothapodytes foetida, Biotechnol. Lett. 22 (2000) 129–132. [2] M. Meloun, S. Bordovska, A. Vrana, The thermodynamic dissociation constants of the anticancer drugs camptothecine, 7-ethyl-10-hydroxycamptothecine, 10-hydroxycamptothecine and 7-ethylcamptothecine by the least-squares nonlinear regression of multiwavelength spectrophotometric pH-titration data, Anal. Chim. Acta 584 (2007) 419–432. [3] C. Bendixen, B. Thomsen, J. Alsner, O. Westergaard, Camptothecin-stabilized topoisomerase I-DNA adducts cause premature termination of transcription, Biochemistry 29 (1990) 5613–5619. [4] V.V. Demidov, Golden jubilee of the DNA double helix, Trends Biotechnol. 21 (2003) 139–140. [5] J.H. Doroshow, Role of reactive oxygen metabolism in cardiac toxicity of anthracycline antibiotics, in: W. Priebe (Ed.), Anthracycline Antibiotics. New Analogues, Methods of Delivery, and Mechanisms of Action, American Chemical Society, Washington, DC, 1995, pp. 259–267. [6] M.P. Singh, T. Joseph, S. Kumar, Y. Bathini, J.W. Lown, Synthesis and sequencespecific DNA binding of a topoisomerase inhibitory analog of Hoechst 33258 designed for altered base and sequence recognition, Chem. Res. Toxicol. 5 (1992) 597–607. [7] J.B. Le Pecq, C. Paoletti, A fluorescent complex between ethidium bromide and nucleic acids, J. Mol. Biol. 27 (1967) 87–106. [8] H.P. Xie, X. Chu, J.H. Jiang, H. Cui, G.L. Shen, R.Q. Yu, Competitive interactions of adriamycin and ethidium bromide with DNA as studied by full rank parallel factor analysis of fluorescence three-way array data, Spectrochim. Acta A 59 (2003) 743–749.

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Biographies Yongnian Ni is a Professor of Chemistry in Nanchang University, China. He received his B.Sc. and M.Sc. degrees both from East China University of Science and Tech-

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nology, China in 1970 and 1982, respectively. His research interests include chemometrics, biomedical measurements, food safety, electroanalysis and quality control by fingerprints. Yingxia Wang received her B.Sc. degree from Datong University, China in 2008. She is now studied for a M.Sc. degree in Department of Chemistry, Nanchang University, China. Serge Kokot is an Adjunct Associate Professor of Faculty of Science and Technology, Queensland University of Technology, Australia. He received his PhD from the University of New South Wales, Australia in 1972. His research interests include chemometrics, health, food and environment analysis. He is a Fellow of the Royal Australian Chemical Institute (RACI), and a recipient of the prestigious 2006 Lloyd Smythe Medal, Analytical Chemistry (RACI).