tx700151t

Chem. Res. Toxicol. 2007, 20, 1291–1299

1291

Application of Metabonomics in a Comparative Profiling Study Reveals N-Acetylfelinine Excretion as a Biomarker for Inhibition of the Farnesyl Pathway by Bisphosphonates Frank Dieterle,† Götz Schlotterbeck,† Martin Binder, Alfred Ross, Laura Suter, and Hans Senn* F. Hoffmann-La Roche Ltd., Pharmaceuticals DiVision PRBD-E Building 065/512, 4070 Basel, Switzerland ReceiVed May 3, 2007

In this work, the results of metabolic profiling of urine from a preclinical comparative profiling study with the two biphosphonates ibandronate and zoledronate are reported. Toxicological assessment showed very different effects for the two compounds. Ibandronate did not cause major signs of toxicity, whereas zoledronate elicited hepatotoxicity and nephrotoxicity. Increased levels of urinary glucose and decreased levels of urinary creatinine detected by NMR also indicated drug-induced nephrotoxicity. Similarly, increased urinary levels of creatine and taurine indicated hepatotoxicty. Both organ toxicities were later confirmed by histopathology. In addition, the benefit of metabonomics as an open approach as compared to targeted methods was demonstrated by the identification of an unknown molecule in the urine of rats dosed with zoledronate. The structure elucidation revealed this molecule as N-acetylfelinine. Analysis of the pathways proposed for the biochemical synthesis of this molecule showed that the synthesis and excretion of N-acetylfelinine could easily be explained by drug-induced inhibition of farnesyl diphosphate synthase. This is the reported mode of action of bisphosphonates. Until now, N-acetylfelinine was exclusively observed in the urine of felidae species, where it is believed to be a precursor to a pheromone. Introduction Metabonomics, which is also known as metabolomics (1) or metabolic profiling (2), involves the determination of changes of concentration levels of small endogenous metabolites in biological samples due to physiological stimuli or genetic modification (3). In the field of pharmaceutical research, metabonomics has recently gained increasing interest as it has been proven to be a fast and reproducible method directly reflecting biological events (4–12). Therefore, monitoring druginduced disturbances of the homeostasis of the basal metabolome by metabonomics is reported to be more easily accessible, less expensive, more sensitive, and less biased than classical methods widely used in drug development for characterizing safety and efficacy of drugs (13). In this work, we present the results of metabonomics in a profiling study with rats dosed with two bisphosphonates. Bisphosphonates are effective in the treatment of diseases, which show increased osteoplast-mediated bone resorption such as osteoporosis, hypercalcemia of malignancy, and metastatic bone disease (14). Yet, it has been reported that the administration of bisphosphonates can cause renal impairment in clinical and preclinical settings (14–16). Here, the effects of the two bisphosphonates ibandronate and zoledronate were profiled using metabonomics (molecular structures of the two drugs are shown in Figure 1). In addition, conventional toxicological end points were assessed. The focus of this publication is the application of metabonomics to monitor toxicity and to gain new knowledge about molecular mechanisms. Moreover, the potential of metabonomics as an unbiased method for safety assessment is supported * To whom correspondence should be addressed. Tel: +41(0)61 6882028. Fax: +41(0)61 6887408. E-mail: [email protected]. † Contributed equally to this work.

Figure 1. Structures of the two drugs ibandronate and zoledronate.

by our results. In particular, metabolic profiling allowed us to identify a novel drug-induced endogenous metabolite. For the formation of this unexpected metabolite, we postulate a biochemical pathway directly linked with the mode of action of bisphosphonates.

Experimental Procedures Metabonomic Study Data Set. The animal study was performed according to a typical protocol for metabonomics rat studies (17). All animals received humane care as specified by Swiss law and in accordance with the Guide for the Care and Use of Laboratory Animals published by the NIH. After a 2 week acclimatization period, 8 week old male Sprague Dawley rats (Charles River, Sulzfeld, Germany) were assigned to five groups with 10 animals each. An overview about termination time points (48 and 168 h) and dose groups is presented in Table 1. The animals were housed individually in metabolism cages and had free access to water and food (Purina Chow 5002, PMI Nutrition International, Brentwood, MO). Urine was continuously collected from 1 day before dosing until termination and fractionated at –16, 0, 8, 24, 48, 72, 96, 120, 144, and 168 h. For the first termination group, urine was collected only until 48 h. As several animals died unexpectedly, urine samples between 120 and 168 h were not available for all animals. The samples were collected over ice into 1 mL of 1% sodium azide solution. Samples were centrifuged for 15 min, and the supernatant

10.1021/tx700151t CCC: $37.00  2007 American Chemical Society Published on Web 08/04/2007

1292 Chem. Res. Toxicol., Vol. 20, No. 9, 2007

Dieterle et al.

Table 1. Study Design with Doses and Number of Animals per Dose Group and Termination Time Point (48 and 168 h after Dosing) animals compound

dose (mg/kg)

48 h

168 h

vehicle ibandronate ibandronate zoledronate zoledronate

0 1 3 3 6

5 5 5 5 5

5 5 5 5 5

was stored at -80 °C until measurement. The test compounds ibandronate (1 and 3 mg/kg) and zoledronate (3 and 6 mg/kg) were dissolved in isotonic saline and administered in a 2 mL/kg dosing volume by intravenous (i.v., bolus) injection once at time point 0 h. Control animals were dosed with the same volume of the vehicle (see Table 1). Besides metabonomics, toxicological end points were also assessed in this study. A complete set of serum chemistry parameters, urine analyses, and histopathological assessments of liver and kidney were performed. Serum chemistry measurements included glucose, urea (BUN), creatinine, total bilirubin, total cholesterol, triglycerides (trigly), phospholipids (phospholip), aspartate aminotransferase (AST), alanine aminotransferase (ALT), lactate dehydrogenase (LDH), alkaline phosphatase, γ-glutamyltransferase (γ-GT), glutamate dehydrogenase (GLDH), total bile acids, fatty acids, sodium, potassium, chloride, calcium, phosphorus, total protein, and protein electrophoresis. Urine analyses included volume, pH, color, osmolality, glucose, protein, creatinine, alkaline phosphatase, γ-GT, LDH, AST, ALT, NAG, sodium, potassium, chloride, magnesium, ketone bodies, nitrite, bilirubin, urobilinogen, leucocytes, and erythrozyten/hemoglobin. The results of these end points are not presented in detail but only briefly discussed in relation to the outcome of the metabonomic assessment. Sample Preparation and NMR Spectroscopy. Before measurement, 200 µL of 0.2 M sodium phosphate buffer (pH 7.4) containing 1 mM TSP, 20% D2O, and 3 mM sodium azide was added to 400 µL urine samples. The samples were then centrifuged for 15 min at 2250g relative centrifugation force (rcf). The NMR spectra were recorded with a 500 MHz BEST NMR system (Bruker Biospin, Karlsruhe, Germany) equipped with a 4 mm TXI flow probe. The spectral acquisition followed a typical standard protocol for metabonomics data acquisition (17). It was based on a NOESY pulse sequence with an acquisition time of 1.36 s. For solvent suppression, the water signal was irradiated during a 1 s relaxation delay and during a 100 ms mixing time. In total, 32768 data points were collected with a spectral width of 20.036 ppm and a linebroadening factor of 1 Hz prior to Fourier transformation. The acquisition was stopped if the signal to noise of the citrate resonances exceeded 2000:1 or if maximally 256 scans were summed. The spectra were phased, baseline-corrected, and referenced to TSP using a routine programmed in MATLAB (NMRProc 0.3, Dr. Tim Ebbels and Dr. Hector Keun, Imperial College, London, United Kingdom). Sample Enrichment and Structure Elucidation. Sample enrichment of the unknown drug-induced endogenous metabolite was achieved by a generic solid-phase extraction (SPE)1 procedure. General purpose Oasis HLB SPE cartridges (3 mL, 30 mg, Waters AG, Buchs, Switzerland) were preconditioned with 1 mL of methanol and 1 mL of water, respectively. An Aliquot of 500 µL ofurine was diluted with 500 µL of water and loaded onto the SPE cartridge, washed with 1 mL of water, and eluted with 1 mL of methanol. The eluate, the water wash, and the methanol fraction were evaporated to dryness using a Speedvac evaporator. The residues were dissolved in 70 µL of 0.2 M sodium phosphate buffer (pH 7.4) containing 1 mM 20% TSP D2O, 3 mM sodium azide, 1 Abbreviations: PCA, principal component analysis; SPE, solid-phase extraction; HSQC, heteronuclear correlation spectroscopy; HMBC, heteronuclear multiple bond correlation.

and 140 µL of water. After centrifugation for 15 min at 2250g rcf, the supernatant was transferred into a 3 mm NMR tube. Structure elucidation of the unknown marker was performed on a Bruker AV 600 spectrometer equipped with an 5 mm TCI cryoprobe. First, we employed a standard sensitivity-enhanced gradient inverse-detection pulse sequence 1H–13C heteronuclear correlation spectroscopy (HSQC) (18) from the library supplied by the vendor. During acquisition, a broadband GARP (19) decoupling was applied. The delay for the one-bond coupling was optimized for a proton carbon coupling constant of 145 Hz. Four hundred t1 increments with 16 transients and 1600k complex data points were acquired with a spectral width of 6009 Hz in f2 and 24901 Hz in f1, respectively. The total acquisition time amounted to 3 h and 1 min. The data were treated with a shifted (π/2) squared sine bell window function in both dimensions and zero-filled in the f1 dimension to 1024 data points. In addition, a 1H–13C heteronuclear multiple bond correlation (HMBC) (20) experiment was performed using a standard pulse sequence from the library supplied by the vendor. Here, 900 t1 increments with 128 transients and 4096 complex data points were recorded with a spectral width of 6613 Hz in f2 and 30183 Hz in f1, resulting in a total acquisition time of about 57 h and 36 min. The delay for the proton carbon long-range coupling was optimized for 10 Hz. For processing, a (π/2) squared sine bell window function in both dimensions was applied. Data comprising 4096 data points were processed in f2 and 2048 in f1, respectively. LC-MS analysis of urine was performed using an Agilent 1100 HPLC system coupled to a Bruker Esquire 3000+ mass spectrometer equipped with an electrospray interface. Urine samples were diluted four-fold with distilled water, and 2 µL injections were made from a well plate maintained at 4 °C into a 150 mm × 3.9 mm Waters Atlantis dC18 3 µm HPLC column maintained in an oven at 30 °C. The column was eluted at a flow rate of 1 mL/min; mobile phase A consisted of 20 mM ammonium acetate, and mobile phase B consisted of acetonitrile. A gradient elution started with 100% A for 5 min was linearly increased to 95% B in 15 min and maintained at 95% B for 3 min, returned to 100% A over 1 min, and then re-equilibrated over a final 5 min prior to injection of the next sample. The mass spectrometer was operated in positive and negative mode with a dry gas flow of 8 L/min, nebulizer pressure of 27 psi, and dry temperature of 330 °C. The instrument was set to acquire over the mass range m/z 50–800. Data Analysis. For multivariate analysis using principal component analysis (PCA), each NMR spectrum (0.2–10 ppm) was reduced by an equidistant binning method with a bin width of 0.04 ppm (AMIX 2.6, Bruker Biospin, Karlsruhe, Germany). The spectral region 4.50–5.98 ppm was deleted to remove variability due to suppression of water resonances and cross-relaxation effects. The regions around the citrate resonances (2.50–2.58 and 2.66–2.74 ppm) were summed up to compensate for highly shifting citrate signals. To account for different dilutions of urine, the spectra were first normalized by an integral normalization and afterwards by a probabilistic quotient normalization described elsewhere with the median spectrum of all control samples and predosed samples as a reference spectrum (21). This normalization is similar to the normalization to urinary creatinine often performed by clinical chemistry but more exact and more robust, as it takes the complete metabolome into account instead of one single biological parameter. Changes of metabolites, which were quantified by peak integration of the spectra, are consequently expressed as relative changes of metabolites independent from the dilution of urine (similar to total excretion). For the analysis with PCA, all spectra were centered but not scaled. This means that the average spectrum of all spectra involved was subtracted. The relative changes from spectrum to spectrum remain the same, but the interpretations of the PCA are easier, as the number of principal components needed for a reasonable interpretation is reduced by one. The PCAs were performed in an iterative way: After identification of significantly changed signals in a first PCA and after assignment to metabolites, the variables representing the corresponding metabolites were removed and a new PCA was performed revealing other signifi-

N-Acetylfelinine Excretion as a Biomarker

Chem. Res. Toxicol., Vol. 20, No. 9, 2007 1293

Table 2. Serum Chemistry Analysis: Group Means ( SD U/L creatinine (µmol/L)

time

compounda

48 h (N ) 5)

vehicle Iban, 1 mg/kg Iban, 3 mg/kg Zole, 3 mg/kg Zole, 6 mg/kg vehicle Iban, 1 mg/kg Iban, 3 mg/kg Zole, 3 mg/kgb Zole, 6 mg/kg

168 h (N ) 5)

a

26.92 25.56 28.70 30.00 27.66 29.62 28.90 29.78 57.60 NA

( ( ( ( ( ( ( ( (

1.18 2.11 1.54 2.63 2.60 2.87 1.00 0.93 NA

mmol/L

ALT

AST

GLDH

Trigly

47.92 ( 9.06 43.88 ( 6.50 45.14 ( 6.92 70.38 ( 8.40 116.72 ( 42.06* 42.18 ( 8.13 48.52 ( 8.54 53.80 ( 12.33 48.90 ( NA NA

98.80 ( 9.72 86.34 ( 10.77 95.42 ( 7.76 130.26 ( 11.54 204.72 ( 56.34* 94.32 ( 19.75 104.54 ( 8.66 133.52 ( 20.68* 227.00 ( NA NA

5.46 ( 0.43 8.62 ( 9.02 5.08 ( 0.56 8.54 ( 1.14 23.70 ( 12.73* 5.06 ( 0.43 5.48 ( 1.31 6.56 ( 1.32 11.20 ( NA NA

1.47 1.32 0.92 1.19 0.59 1.46 1.20 0.90 1.06 NA

( ( ( ( ( ( ( ( (

0.35 0.29 0.42 0.30 0.62* 0.29 0.19 0.32* NA

Phospholip

BUN

( ( ( ( ( ( ( ( (

6.83 ( 0.71 6.60 ( 1.06 7.19 ( 0.63 5.99 ( 0.76 4.77 ( 0.84* 6.49 ( 0.98 6.80 ( 0.98 6.79 ( 0.29 17.76 ( NA NA

1.73 1.58 1.47 1.75 1.22 1.54 1.41 1.34 1.41 NA

0.09 0.16 0.29 0.27 0.34* 0.13 0.07 0.07* NA

Iban, ibandronate; Zole, zoledronate. b Group Zole 3 mg/kg at 168 h N ) 1; *p e 0.05; **p e 0.01.

Table 3. Urine Analysis: Group Means ( SD U/L time

compounda

48 h (N ) 10)

vehicle Iban, 1 mg/kg Iban, 3 mg/kg Zole, 3 mg/kg Zole, 6 mg/kg vehicle Iban, 1 mg/kg Iban, 3 mg/kg Zole, 3 mg/kgb Zole, 6 mg/kg

168 h (N ) 5)

a

volume (mL) 13.85 12.99 14.23 11.18 20.00 16.64 16.96 18.40 24.25 NA

( ( ( ( ( ( ( ( (

2.07 2.75 4.36 1.99 6.77 2.56 3.26 4.51 NA

osmolality (mosm/kg) 1549 ( 244 1551 ( 268 1453 ( 224 1576 ( 254 842 ( 340* 1403 ( 259 1425 ( 268 1373 ( 171 470 ( NA NA

creatinine (µmol/L)

pH 7.99 7.90 8.01 7.70 7.53 7.73 7.34 7.29 6.85 NA

( ( ( ( ( ( ( ( (

0.18 0.22 0.11 0.37 0.47 0.22 0.38 0.21 NA

5945 6093 5912 6733 4307 6071 5877 5868 1707 NA

( ( ( ( ( ( ( ( (

882 1051 1170 957 1406* 1317 1193 898 NA

γ-GT

NAG

LDH

928 ( 344 680 ( 201 666 ( 321 648 ( 220 336 ( 81** 926 ( 373 893 ( 419 1071 ( 379 125 ( NA NA

14.28 ( 3.07 12.59 ( 3.18 13.08 ( 3.82 11.52 ( 3.00 9. 39 ( 2.98 ** 12.50 ( 2.45 13.96 ( 3.34 15.79 ( 3.29 25.08 ( NA NA

20.74 ( 6.35 25.43 ( 8.06 24.86 ( 5.42 36.47 ( 13.28** 33.01 ( 10.66 18.06 ( 4.44 18.38 ( 6.54 21.10 ( 8.02 577.10 ( NA NA

Iban, ibandronate; Zole, zoledronate. b Group Zole 3 mg/kg at 168 h N ) 2; *p e 0.05; **p e 0.01.

cantly changed metabolites. This procedure was repeated until no significantly changed metabolite could be identified any more. All changes were reconfirmed by visual inspections of the spectra. The multivariate data analysis was performed using SIMCA 10.5 (Umetrics, Umea, Sweden).

Results Classical End Points. The administration of zoledronate caused severe clinical signs from days 3 (6 mg/kg) and 4 (3 mg/kg) onward, ending with premature death of all animals between day 5 and day 7. A severe body weight loss was observed from day 1 (6 mg/kg) to day 3 (3 mg/kg). Results from relevant serum chemistry parameters and urine analysis are listed in Tables 2 and 3, respectively. At 48 h, zoledronate caused a significant increase in serum levels of ALT, AST, and GLDH and decreased levels of triglycerides, phospholipids, and blood urea, especially at 6 mg/kg. Serum creatinine seemed elevated 168 h after administration of zoledronate: At 3 mg/ kg, the only remaining animal showed a nearly two-fold increase in creatinine with respect to the time-matched control. Because of mortality, no assessment could be done at 6 mg/kg. The urine volume was slightly increased (not statistically significant) after administration of zoledronate as measured at 48 (6 mg/kg) and 168 h (3 mg/kg). Urine analysis revealed significantly decreased osmolality, pH, creatinine, γ-GT, and NAG, whereas leukocytes and LDH were significantly increased. The treatment also caused macroscopic hepatic enlargement and a variety of microscopic changes in the kidneys and the liver, among which most prominent were necrosis of the liver at both dose levels, renal tubular vacuolation at 3 mg/kg, and renal tubular necrosis at 6 mg/kg. Under the experimental conditions, ibandronate did not cause morbidity, lethality, or morphological changes in liver or kidney. Serum chemistry showed a treatment-related decrease in trig-

lycerides, phospholipids, and proteins. Also, an increased activity of AST 168 h after 3 mg/kg and decreased chloride and increased phosphates at both dose levels, especially after 168 h, were noted. In summary, the classical toxicology end points showed signs of hepatotoxicity and moderate to marked nephrotoxicty for both dose groups of zoledronate. Besides the increased AST levels, no relevant findings were observed after the treatment with ibandronate. Metabonomics. To obtain an overview of the metabolic changes, a PCA was performed on the spectra of the urine from the rats dosed with ibandronate or vehicle (control rats). The plots depicted in Figure 2 show that mainly predosed samples (time points -16 and 0 h) are separated from the other samples. The corresponding chemical shifts can be attributed to slight changes of the metabolites citrate, 2-oxoglutarate, hippurate, taurine, and creatinine. This indicates that time effects common to all dose groups and controls were more prominent than effects due to the administration of ibandronate. The differences between the -16 and the 0 h samples could be attributed either to the adaptation phase of the animals or to the fact that these two urine collection times were shorter (8 and 16 h, respectively) than for the other samples (24 h). Removing these samples and repeating the PCA did not reveal significant changes of metabolites due to the administration of ibandronate. In Figure 3, the PCA plots for the animals dosed with zoledronate and vehicle are shown. High-dose (6 mg/kg) animals separate from controls at time points later than 24 h. Low-dose (3 mg/kg) animals started to separate from 96 h on. The time trajectory of the high-dose samples was very distinctive and biphasic. In the first phase, the effect of the treatment with the high dose was dominated by elevated levels of betaine, partly at 24 h and clearly at 48 and 72 h. Increased levels of taurine and creatine and decreased levels of hippurate and 3-(3-


Dieterle et al.

Figure 2. Scores and loadings plot with the first two components of a PCA of spectra of control animals and animals dosed with ibandronate. The samples in the scores plot (left side) are labeled by time point. Green squares represent control samples and predosed samples, red circles represent low-dosed animals, and black diamonds represent high-dosed samples. In the loadings plot, the variables are labeled by chemical shift.

Figure 3. Scores and loadings plot with the first two components of a PCA of spectra of control animals and animals dosed with zoledronate. The samples in the scores plot (left side) are labeled by time point. Green squares represent control samples and predosed samples, red circles represent low-dosed animals (3 mg/kg), and black diamonds represent high-dosed samples (6 mg/kg). In the loadings plot, the variables are labeled by the chemical shift.

hydroxyphenyl)propionate (3-HPPA) dominated the metabolic changes in urines from the second phase between 96 and 120 h. In that second phase, decreased concentration levels of all intermediates of the citrate cycle accessible by NMR (citrate, 2-oxoglutarate, fumarate, malate, succinate, and isocitrate) were observed, whereas concentration levels of betaine were further increased (see Figure 4 for spectra at 96 h). The trajectories are best visible when looking at the samples labeled with time points in the score plot of Figure 3 and then comparing with the variables significantly changed in the same direction (or opposite direction) of the corresponding loading plot. An ultimate verification of significantly changed metabolites at certain time points is best performed by visually inspecting normalized spectra of the different dose groups ordered by time points. The trajectory of low-dose animals did not show the first phase (increase of betaine only), but similarly to the high-dose samples, it also showed the second phase with simultaneously increased levels of betaine, taurine, and creatine and decreased levels of hippurate, 3-HPPA, and all intermediates of the citrate cycle accessible by NMR. For both dose groups, no recovery of the time trajectories is visible. The trajectory of the low-dose animals reached the same end point as the time trajectory of the high-dose animals but was significantly delayed (e.g., the decrease of concentration levels of citrate cycle intermediates starts at 48 h for the high-

dose animals whereas the decrease for the low-dose animals starts at 72 h). Furthermore, significantly lower concentrations of the metabolite trigonelline (n-methylnicotinate, caffearin, and gynesine), involved in the nicontinate and nicotineamide metabolism, were observed for the high-dose animals at 96 h and for the low-dose animals at 144 h. Additionally, creatinine levels were decreased for the high-dose animals starting at 72 h and for the low-dose animals at 144 h. Finally, the amount of glucose in urine was significantly increased in some of the zoledronatetreated animals: four high-dose animals at 72 h, two high-dose animals at 96 h, and one low-dose animal at 120 and 144 h. In summary, the endogenous metabolite pattern remained unchanged after treatment with either 1 or 3 mg/kg ibandronate. On the other hand, zoledronate at both doses (3 and 6 mg/kg) caused a severe perturbation of the endogenous metabolite pattern. The changes of the metabolites for the zoledronatedosed animals are listed in Table 4. In addition, this table also shows the level of significance (t-test) of the metabolites based on comparison of peak integrals between the dosed groups and the control group. It is also obvious that both the low-dose and the high-dose group show very consistent changes, whereby most changes were even more pronounced in the low-dosed group. This means that the observed effects were not caused



Figure 4. 1H NMR spectrum of rat urines (a) control, (b) dosed with ibandronate, and (c) dosed with zoledronate at 96 h.

Table 4. Metabolites with Significantly Changed Concentration Levels for the Animals Dosed with Zoledronatea high-dosed metabolites hippurate succinate 2-oxoglutarate citrate trigonelline fumarate creatinine 3-HPPA isocitrate malate taurine creatine betaine N-acetylfelinineb glucose

reference chemical shifts 3.97, 2.41 2.44, 2.54, 4.45, 6.52 3.05, 2.48, 2.44, 2.37, 3.27, 3.04, 3.27, 1.32, 3.52,

7.56, 7.64, 7.84 3.01 2.66 8.09, 8.85, 9.13 4.06 2.84, 6.76, 6.8, 6.87, 7.25 2.5, 2.98, 3.99 2.68, 4.31 3.43 3.94 3.9 1.83, 2.08, 2.91, 3.04, 3.74, 4.36, 8.08 3.57, 3.58, 4

low-dosed

time (h)

concentration

p

time (h)

concentration

p

96 96 96 96 96 96 96 120 120 96 96 72 96 72 72

0.10 0.14 0.18 0.18 0.26 0.26 0.44 0.45 0.61 0.73 1.6 1.8 3.0 >4c 0.8, 1.5, 2.0, 2.6, 12.9d

0.00 0.00 0.01 0.00 0.00 0.00 0.02 0.03 0.04 0.03 0.57 0.34 0.05

144 144 144 144 144 144 144 144 144 144 144 120 144 144 144

0.20 0.06 0.11 0.13 0.13 0.24 0.48 0.42 0.66 0.67 2.8 2.1 2.7 >8c 1.1, 1.4, 1.8, 5.7d

0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.03 0.10 0.00 0.01 0.00

c d

c d

a The names of metabolites, the time points with most significantly changed concentration levels, and the relative concentration levels (median of fold changes) as compared to the time-matched control animals are listed. The concentrations were determined by integrating the corresponding signals in the raw spectra after application of the corresponding spectrum normalization factors. The metabolites are listed in increasing order. The p values were derived from a two-sided t test using the peak integral values of dosed animals vs those of time-matched control animals. b Chemical shifts at pH 7.4 c N-acetyl-felinine peaks could not be identified in control samples. Therefore, the signal intensities were related to the background signal at the corresponding locations, which corresponds to the highest nondetectable concentration of n-acetyl-felinine in control animals. d The variance of glucose concentration levels within dosed animals was very high. Therefore, relative concentrations of single dosed animals versus median concentrations of control animals are listed.

by moribund animals but could be attributed to more specific physiological changes. Structure Elucidation of N-Acetyl-Felinine. Besides the changes of the well-known metabolites described before, a signal at δ ) 1.32 ppm of an unknown metabolite was identified with the help of a PCA after removal of all variables corresponding to all significantly changed metabolites mentioned above. A visual inspection of the 1H NMR spectra showed that this peak was present in the urine of zoledronate-treated animals but not in control animals (see Figure 4). As the signal was most intensive at the late time points, we assumed that this metabolite is unlikely to be a drug metabolite but most probably an

endogenous metabolite. We identified and confirmed the structure of this metabolite by the following steps. (i) Enrichment of the unknown metabolite by a SPE method for a subsequent structure elucidation process by NMR spectroscopy: The eluate, the water wash, and the methanol fraction of the generic SPE procedure were carefully checked for the presence of the unknown metabolite. For this, each SPE fraction was investigated by 1H NMR spectroscopy for the appearance of the most intense signal at δ ) 1.32 ppm. As expected, the metabolite of interest was found in the methanol fraction. (ii) Elucidation of the structure of the unknown compound by application of two-dimensional (2D) 1H–13C HSQC and


Dieterle et al.

Figure 5. Pathways proposed for the synthesis of N-acetylfelinine in cat species. Pathway A involves a synthesis of the tripeptide 3-methylbutanolglutathione (3-MGB) in the liver, which is transported via blood to the kidney and subsequently metabolized in the proximal tubular cells to felinine, N-acetylfelinine, and other derivatives. Pathway B on the right side proposes a direct synthesis of felinine and N-acetylfelinine in the kidney. The boxes represent the matrices involved. 1

H–13C HMBC spectra (see Supporting Information S1 and S2): These 2D NMR experiments revealed the connectivity of directly (HSQC) and remote (HMBC) attached protons and carbon atoms. First, the isopentyl moiety with the most intense resonance of the two methyl groups (1H δ ) 1.32 ppm, 13C δ ) 28 ppm) was observed in the 1H NMR spectrum. The 13C NMR shift of these methyl groups was revealed by 1H–13C HSQC data. With the help of the 1H–13C HMBC spectrum, the carbon backbone of the metabolite was elucidated. Starting with the resonances of the methyl groups, the connectivity of the isopentyl moiety with the cysteine part of the metabolite was determined and finally the complete structure was solved. This molecule 2-(acetylamino)-3-[(3-hydroxy-1,1-dimethylpropyl)thio]propanoic acid is known as N-acetylfelinine in the literature, and a metabolite of felinine so far has been found exclusively in the urine of Felidae species such as domestic cats (22, 23). (iii) Confirmation of the structural identity of the metabolite found in the urine of rats dosed with zoledronate by chemical synthesis of N-acetylfelinine (24): One-dimensional (1D) and 2D NMR spectra of the endogenous metabolite and the synthesized material recorded under identical conditions are in full agreement. N-Acetylfelinine could not be detected by NMR in the urine of control animals or in the urine of animals dosed with ibandronate. Therefore, it was unclear if the metabolite was not present in these samples or if the concentrations were too low to be detected by NMR. We thus applied an LC-MS method to investigate the presence of N-acetylfelinine with higher sensitivity. Under these conditions, N-acetylfelinine was exclusively found in urine samples of rats dosed with zoledronate. The retention time was 9.6 min with the expected m/z 248 in negative mode and m/z 250 in positive mode, respectively. The MS/MS experiments revealed the expected fragment m/z 119. Therefore,

the results showed that this metabolite was either absent in control samples and in the urine of rats dosed with ibandronate or present at concentrations below the detection limit of our LC-MS system.

Discussion In this comparative profiling study, the bisphosphonates zoledronate and ibandronate were administered to rats. The goal was to profile both drugs using a metabonomics approach. It might be of interest to readers that the bioanalytical analysis and interpretation were carried out under fully blinded conditions; that is, the chemical nature of the two drugs as well as their biological and pharmacological properties remained unknown to the analytical department during the entire study. Unblinding of the drug structures occurred during the compilation of the report. The toxicological assessment based on clinical chemistry parameters and histopathology showed very different effects for the two compounds. The animals dosed with ibandronate did not show major signs of toxicity, whereas the animals dosed with zoledronate showed hepatotoxicity and nephrotoxicity at both dose levels (3 and 6 mg/kg). In general, serum chemistry parameters, urine enzymes, and histopathology supported this assessment, albeit atypical decreases in urine NAG and in serum urea (BUN) were observed. These toxicity findings were rather surprising as compared to previous studies (14), since biphosphonates were expected to cause mild to moderate nephrotoxicity and no hepatotoxity at the doses used in this study. As no serum compound levels were measured in this study, it is unclear if these unexpected findings can be attributed to significantly different exposures to both compounds as compared with previous studies. Thus, the goal to compare the toxic effects of



Figure 6. Molecular mode of action of bisphosphonates is the inhibition of the farenesyldiphosphate synthase (FPP synthase).

both compounds side by side could not be fulfilled with this study. However, the metabolic profiles and the interpretation thereof reveal new biochemical insights in the changes of pathways after dosing of bisphosphonates. First, the metabolic profiles throughout the study were compared with the histopathology outcome. For the animals dosed with ibandronate, the absence of metabolic changes corresponds very well with the absence of microscopic changes in kidney and liver. For animals dosed with zoledronate, the biochemical interpretation for the observed metabolic changes, as shown in Table 4, was based on patterns and pathways reported previously in literature. The decrease of concentration levels of the citrate cycle intermediates citrate, 2-oxoglutarate, fumarate, malate, succinate, and isocitrate corresponds to a reduction in energy metabolism. This has been often described in literature (25–30) and is a common finding in rats undergoing many types of toxicity. The metabolites hippurate and 3-HPPA have been attributed to the gut microflora in literature (31–33). The decreased concentrations of both metabolites correspond to a loss of the gut microflora, as also observed after treatment with antibiotics (unpublished data). Both the decreased levels of hippurate and 3-HPPA and the changes of trigonelline have been previously associated with unspecific toxicity (34). The simultaneous increase of taurine and creatine in urine has been attributed to hepatocyte necrosis and is a known metabonomics signature for hepatotoxicity (25–30). Decreased levels of creatinine and increased levels of glucose are clear signs of nephrotoxicity (35–37). Creatinine, which is constantly produced in the body, is normally freely filtered by the glomeruli and excreted into urine. In addition, about 20% of the urinary creatinine is secreted in the tubules (38, 39). Reduced concentrations of creatinine, especially in controlled rodent studies, can be attributed primarily to an impairment of the renal function. Glucose is largely reabsorbed in the proximal convoluted tubules. Excessive excretion of glucose is a clear sign of tubular impairment. Thus, it can be concluded that in this study, published metabolic patterns with respect to nephrotoxicity and

hepatotoxicity could be reproduced also in accordance with a histopathology assessment. The identification and subsequent structure elucidation of N-acetylfelinine in urine samples dosed with zoledronate showed the advantage of metabonomics as a nontargeted, open analytical method. N-Acetylfelinine belongs to a family of felinine derivatives, to which increasing interest has been paid to recently. Felinine and its derivatives are found exclusively in the urine of cat species such as Felis catus, Felis rufus, Felis pardalis, Panthera pardus, and Felis bengalensis, but not in other species (23). Its function is not yet clear, but it is assumed to be a precursor to a pheromone as its amount in the domestic cat is significantly higher in intact males as compared with castrated males and entire females and castrated females (40–42). Currently, it is believed that felinine production is a cat-specific metabolic pathway (43). As is shown in Figure 5 (pathway B), a metabolic pathway directly involving isopentenylpyrophosphate and cysteine for the formation of felinine has been proposed (44–46). Because free felinine could not be detected in blood, it was assumed that felinine is directly synthesized in the kidney. More recently, another pathway was proposed for the biosynthesis of felinine (22, 47) shown as pathway A in Figure 5. Here, it was suggested that the tripeptide γ-glutamylfelinylglycine (3-methylbutanolglutathione) is a direct condensation reaction of isopentenylpyrophosphate and glutathione in the liver mediated by a γ-glutathionetransferase enzyme. The tripeptide, which has been identified in the plasma of cat species, is transported via blood to the kidney. It is filtered by the glomeruli and converted by γ-glutamyltransferase to felinylglycine (3-methlybutanolcysteinylglycine) at the brush border of proximal tubular cells. Felinylglycine can subsequently be hydrolyzed to felinine and glycine by renal dipeptidases, whereby glycine is absorbed by glycine transporters. In both pathways, felinine is acetylated by the cysteine-S-conjugate N-acetyltransferase to N-acetylfelinine, which is excreted together with felinine. Most interestingly, in the context of our results, both pathways for the synthesis of


felinine propose that felinine and N-acetylfelinine are synthesized from the same isoprenoid pool as cholesterol and steroids. The isoprenoid pool is the direct link to the mode of action of nitrogen containing bisphosphonates, as depicted in Figure 6. The molecular target of the nitrogen-containing bisphosphonates is the inhibition of the farnesyl diphosphate synthase (FPPsynthase) in the cholesterol biosynthesis pathway (48–52). The inhibition of FPP-synthase prevents the linkage of farnesyl diphophate or geranylgeranyl diphosphate to several regulatory proteins in a branch pathway to the cholesterol synthesis. The regulatory proteins play a rate-limiting role in the activity of the bone-resorbing osteoclasts, which is the basis of the therapeutic response of suppressing bone turnover. The blocking of the farnesyl diphosphate synthase might cause an increase in the isoprenoid pool. Therefore, it can be speculated that the N-acetylfelinine synthesis observed in the animals dosed with zoledronate is an alternative pathway activated by high amounts of isoprenoids. If so, either cysteine or glutathione could serve as scavenger molecules to reduce the “overflowing” isoprenoid pool. Unfortunately, in this study, we did not have any remaining serum samples; therefore, we could not determine if the proposed scavenger reaction would correspond to pathway A or pathway B (Figure 5). However, our results provide strong evidence that the synthesis of N-acetylfelinine is a consequence of the inhibition of the farnesyl diphosphate synthase. Thus, we propose that N-acetylfelinine could be a urinary biomarker for monitoring efficacy of the inhibition of the farnesyl pathway. Further research for the systematic analysis of the N-acetylfelinine with more sensitive methods is needed to monitor the excretion of N-acetylfelinine. Lower doses of zoledronate or other nitrogen-containing bisphosphonates such as ibandronate might elicit the production of N-acetylfelinine at concentrations below the detection limit of the analytical equipment used in this study. In this study, it was not possible to identify the nonacetylated felinine in urine, which could also be attributed to the low stability due to the presence of urea in urine (53, 54). Finally, we believe that it would be interesting to evaluate this biomarker for clinical applications.

Conclusions In this work, the results of metabolic profiling of urine from a preclinical comparative profiling study with the two biphosphonates ibandronate and zoledronate are reported. Urinary signatures of known metabolites can identify nephrotoxicty and hepatotoxicty of animals early and reliably. These results are in agreement with histopathology. In addition, the benefit of metabonomics as compared to targeted methods was demonstrated by the identification of N-acetylfelinine. Until now, this molecule had only been reported in the urine of felidae where it is assumed to be precursor to a cat-specific pheromone. An analysis of the pathways proposed for the biochemical synthesis of this molecule shows that the synthesis and excretion of N-acetylfelinine can be directly linked to the mode of action of bisphosphonates, which is the inhibition of the farnesyl diphosphate synthase. Thus, N-acetylfelinine is proposed as a new biomarker to monitor the extent of in vivo inhibition of the drug target farnesyl diphosphate synthase, which potentially may correlate with beneficial drug efficacy or detrimental side effects. Acknowledgment. We are indebted to Dr. E. Kitas for the synthesis of N-acetylfelinine and to Dr. T. Pfister for his support with the study design. We acknowledge the group of Prof. J.

Dieterle et al.

Nicholson at Imperial College for continuous discussions and for providing the program NMRPROC. Supporting Information Available: Images of 2D NMR spectra. This material is available free of charge via the internet at http://pubs.acs.org.

References (1) Fiehn, O. (2002) Metabolomics-the link between genotypes and phenotypes. Plant. Mol. Biol. 48, 155–171. (2) Trethewey, R. N., Krotzky, A. J., and Willmitzer, L. (1999) Metabolic profiling: A rosetta stone for genomics? Curr. Opin. Plant Biol. 2, 83–85. (3) Nicholson, J. K., Lindon, J. C., and Holmes, E. (1999) “Metabonomics”: Understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29, 1181–1189. (4) Lindon, J. C., Nicholson, J. K., Holmes, E., and Everett, J. R. (2000) Metabonomics: metabolic processes studied by NMR spectroscopy of biofluids. Concepts Magn. Res. 12, 289–320. (5) Nicholson, J. K., Connelly, J., Lindon, J. C., and Holmes, E. (2002) Metabonomics: A platform for studying drug toxicity and gene function. Nat. ReV. Drug DiscoVery 1, 153–161. (6) Shockcor, J. P., and Holmes, E. (2002) Metabonomic applications in toxicity screening and disease diagnosis. Curr. Top. Med. Chem. 2, 35–51. (7) Nicholson, J. K., and Wilson, I. D. (2003) Understanding “global” systems biology: Metabonomics and the continuum of metabolism. Nat. ReV. Drug DiscoVery 2, 668–676. (8) Fernie, A. R., Tretewey, R. N., Krotzky, A. J., and Willmitzer, L. (2004) Metabolite profiling: From diagnostics to systems biology. Nat. ReV. Mol. Cell Biol. 5, 1–7. (9) Lindon, J. C., Homes, E., Bollard, M. E., Stanley, E. G., and Nicholson, J. K. (2004) Metabonomics technologies and their applications in physiological monitoring, drug safety assessment and disease diagnosis. Biomarkers 9, 1–31. (10) Bollard, M. E., Stanley, E. G., Lindon, J. C., Nicholson, J. K., and Holmes, E. (2005) NMR-based metabonomic approaches for evaluating physiological influences on biofluid composition. NMR Biomed. 18, 143–162. (11) Dieterle, F., Schlotterbeck, G., Ross, A., and Senn, H. (2006) Application of metabonomics in a compound ranking study in early drug development revealing drug-induced excretion of choline into urine. Chem. Res. Toxicol. 19, 1175–1181. (12) Schlotterbeck, G., Dieterle, F., Ross, A., and Senn, H. (2006) Metabolic profiling technologies for biomarker discovery in Biomedicine and drug development. Pharmacogenomics 7, 1055–1075. (13) Bugrim, A., Nikolskaya, T., and Nikolsky, Y. (2004) Early prediction of drug metabolism and toxicity: Systems biology approach and modeling. Drug DiscoVery Today 9, 127–135. (14) Pfister, T., Atzpodien, E., and Bauss, F. (2003) The renal effects of minimally nephrotoxic doses of ibandronate and zoledronate following single and intermittent intravenous administration in rats. Toxicology 191, 159–167. (15) Rosen, L.S., Gordon, D., Kaminski, M., Howell, A., Belch, A., and et al. (2001) Zoledronic acid versus pamidronate in the treatment of skeletal metastases in patients with breast cancer or osteolytic lesions of multiple myeloma: A phase II, double-blind, comparative trial. Cancer J. 7, 377–387. (16) Markowitz, G. S., Fine, P. L., Stack, J. I., Kunis, C. L., and Radhakrishnan, J. (2003) Toxic acute tubular necrosis following treatment with zoledronate (Zometa). Kidney Int. 64, 281–289. (17) Keun, H. C., Ebbels, T. M. D., Antti, H., Bollard, M. E., Beckonert, O., Schlotterbeck, G., Senn, H., Niederhauser, U., Holmes, E., Lindon, J. C., and Nicholson, J. K. (2002) Analytical reproducibility in 1H NMR-based metabonomic urinalysis. Chem. Res. Toxicol. 15, 1380– 1386. (18) Palmer, A.G., III, Cavanagh, J., Wright, P. E., and Rance, M. (1991) Sensitivity improvement in proton-detected two-dimensional heteronuclear correlation spectroscopy. J. Magn. Reson. 93, 151–170. (19) Shaka, A. J., Barker, P. B., and Freemann, R. (1985) Computer optimized decoupling scheme for wideband applications and low level operation. J. Magn. Reson. 64, 547–552. (20) Cicero, D. O., Barbato, G., and Bazzo, R. (2001) Sensitivity Enhancement of a Two-dimensional experiment for the measurement of heteronuclear long-range coupling constants, by a new scheme of coherence selection by gradients. J. Magn. Reson. 148, 209–213. (21) Dieterle, F., Ross, A., Schlotterbeck, G., and Senn, H. (2006) Probabilistic quotient normalization as robust method to account for dilution of complex biological mixtures-application in 1H-NMR metabonomics. Anal. Chem. 78, 4281–4290.

N-Acetylfelinine Excretion as a Biomarker (22) Hendriks, W. H., Harding, D. R. K., and Rutherfurd-Markwick, K. J. (2004) Isolation and characterization of renal metabolites of γ-glutamylfelinylglycine in the urine of the domestic cat. Comp. Biochem. Physiol. B 139, 245–251. (23) Hendriks, W. H., Moughan, P. J., Tarttelin, M. F., and Woolhouse, A. D. (1995) Felinine: A urinary amino acid of Felidae. Comp. Biochem. Physiol. B 112, 581–588. (24) Riordan, K. J., and Vallee, B. L. (1967) Acetylation. Methods Enzymol. 11, 565–570. (25) Dieterle, F., Ross, A., Schlotterbeck, G., and Senn, H. (2006) Metabolite projection analysis for fast identification of metabolites in metabonomics. Application in an amiodarone study. Anal. Chem. 78, 3551–3651. (26) Beckwith-Hall, B. M., Nicholson, J. K., Nicholls, A. W., Foxall, P. J. D., and Lindon, J. C. (1998) Nuclear magnetic resonance spectroscopic and principal components analysis investigations into biochemical effects of three model hepatotoxins. Chem. Res. Toxicol. 11, 260–272. (27) Waters, N. J., Holmes, E., Williams, A, Waterfield, C. J., Farrant, R. D., and Nicholson, J. K. (2001) NMR and pattern recognition studies on the time-related metabolic effects of R-Nahpthylisothiocyanate on liver, urine, and plasma in the rat: An integrative metabonomic approach. Chem. Res. Toxicol. 14, 1401–1412. (28) Waters, N. J., Waterfield, C. J., Duncan Farrant, R., Holmes, E., and Nicholson, J. K. (2005) Metabonomic deconvolution of embedded toxicity: Application to thioacetamide hepato- and nephrotoxicity. Chem. Res. Toxicol. 18, 639–654. (29) Nicholls, A. W., Holmes, E., Lindon, J. C., Shockcor, J. P., Duncan Farrant, R., and et al. (2001) Metabonomic investigations into hydrazine toxicity in the rat. Chem. Res. Toxicol. 14, 975–987. (30) Holmes, E., Nicholls, A. W., Lindon, J. C., Connor, S. C., Connelly, J. C., and et al. (2000) Chemometric models for roxicity classification based on NMR spectra of biofluids. Chem. Res. Toxicol. 13, 471– 478. (31) Williams, R. E., Eyton-Jones, H. W., Farnworth, M. J., Gallagher, R., and Provan, W. M. (2002) Effect of intestinal microflora on the urinary metabolic profile of rates: a 1H-nuclear magnetic resonance spectroscopy study. Xenobiotica 32, 783–794. (32) Gavaghan, C. L., Nicholson, J. K., Connor, S. C., Wilson, I. D., Wright, B., and Holmes, E. (2001) Directly coupled high-performance liquid chromatography and nuclear magnetic resonance spectroscopic with chemometric studies on metabolic variation in sprague-dawley rats. Anal. Biochem. 291, 245–252. (33) Nicholls, A. W., Mortishire-Smith, R. J., and Nicholson, J. K. (2003) NMR spectroscopic-based metabonomic studies of urinary metabolite variation in acclimatizing germ-free rats. Chem. Res. Toxicol. 16, 1395–1404. (34) Connor, S. C., Wu, W., Sweatman, B. C., Manini, J, Haselden, J. N., Crowther, D. J., and Waterfield, C. J. (2004) Effects of feeding and body weight loss on the 1H-NMR-based urine metabolic profiles of male Wistar Han rats: Implications for biomarker discovery. Biomarkers 9, 156–179. (35) Lenz, E. M., Bright, J., Knitght, R., Wilson, I. D., and Major, H. (2004) Cyclosporin A-induced changes in endogenous metabolites in rat urine: a metabonomic investigation using high field 1H NMR spectroscopy, HPLC-TOF/MS and chemometrics. J. Pharm. Biomed. Anal. 35, 599– 608. (36) Holmes, E., Nicholson, J. K., Nicholls, A. W., Lindon, J. C., Connor, S. C., Polley, S., and Connelly, J. (1998) The identification of novel biomarkers of renal toxicity using automatic data reduction techniques and PCA of proton NMR spectra of urine. Chemom. Intell. Lab. Syst. 44, 245–255. (37) Anthony, M. L., Sweatman, B. C., Beddell, C. R., Lindon, J. C., and Nicholson, J. K. (1994) Pattern recognition classification of the site


(38)

(39) (40) (41) (42) (43)

(44) (45)

(46)

(47)

(48)

(49)

(50)

(51)

(52) (53)

(54)

of nephrotoxictiy based on metabolic data derived from proton nuclear magnetic resonance spectra of urine. Mol. Pharmacol. 46, 199–211. Tomlanovich, S., Golbetz, H., Perlroth, M., Stinson, E., and Myers, B. D. (1986) Limitations of creatinine in quantifying the severity of cyclosporine-induced chronic nephropathy. Am. J. Kidney Dis. 8, 332– 337. Rahn, K. H., Heidenreich, S., and Brückner, D. (1999) How to assess glomerular function and damage in humans. J. Hypertens. 17, 309– 317. Hendriks, W. H., Tarttelin, M. F., and Moughan, P. J. (1995) Twentyfour hour felinine excretion patterns in entires and castrated cats. Physiol. BehaV. 58, 467–469. MacDonald, M. L., Rogers, Q. R., and Morris, J. G. (1984) Nutrition of the domestic cat, a mammalian carnivore. Annu. ReV. Nutr. 4, 521– 562. Tarttelin, M. F., Hendriks, W. H., and Moughan, P. J. (1998) Relationship between plasma testosterone and urinary felinine in the growing kitten. Physiol. BehaV. 65, 83–87. Micazaki, M., Yamashita, T., Suzuki, Y., Saito, Y., Soeta, S., Taira, H., and Suzuki, A. (2006) A major urinary protein of the domestic cat regulates the production of felinine, a putative pheromone precursor. Chem. Biol. 13, 1071–1079. Eggerer, H. (1962) Synthese von natürlichem Felinin. Liebigs Ann. Chem. 657, 212–218. Borchers, J., Clauss, E., Decker, P., and Schöberl, A. (1967) Zur synthese und biologischen bedeutung des felinins, eines aus katzenharn isolierten schwefelhaltigen isoprenderivates. Dtsch. Tieraerztl. Wochenschr. 74, 532–535. Hendriks, W. H., Rutherfurd, S. M., and Rutherfurd, K. J. (2001) Importance of sulfate, cysteine and methionine as precursors to felinine syntesis by domestic cats (Felis catus). Comp. Biochem. Physiol. 129C, 211–216. Rutherfurd, K. J., Rutherfurd, S. M., Moughan, P. J., and Hendriks, W. H. (2002) Isolation and characterization of a felinine-containing peptide from the blood of the domestic cat (Felis catus). J. Biol. Chem. 227, 114–119. Berstrom, J. D., Bostedor, R. G., Masarachia, P. J., Reszka, A. A., and Rodan, G. (2000) Alendronate is a specific, nanomolar inhibitor of farnesyl diphosphate synthase. Arch. Biochem. Biophys. 373, 231– 241. Van Beek, E., Pieterman, E., Cohen, L., Lowik, C., and Papapoulos, S. (1999) Nitrogen-containing bisphosphonates inhibit isopentenyl pyrophosphate isomerase/farnesyl pyrophosphate synthase activity with relative potencies corresponding to their antiresorptive potencies in vitro and in vivo. Biophys. Res. Commun. 255, 491–494. Van Beek, E., Pieterman, E., Cohen, L., Lowik, C., and Papapoulos, S. (1999) Farnesyl pyrophosphate synthase is the molecular target of nitrogen-containing bisphosphonates. Biophys. Res. Commun. 264, 108–111. Dunford, J. E., Thompson, K., Coxon, F. P., Luckman, S. P., Hahn, F. M., and et al. (2001) Structure-activity relationships for inhibition of farnesyl diphosphate synthase in vitro and inhibition of bone resorption in vivo by nitrogen-containing bisphosphonates. J. Pharmacol. Exp. Ther. 296, 235–242. Reszka, A. A., and Rodan, G. A. (2004) Nitrogen-containing bisphosphonate mechanism of action. Mini-ReV. Med. Chem. 4, 711–719. Rutherfurd, S. M., Zhang, F, Harding, D. R. K., Woolhouse, A. D., and Hendriks, W. H. (2004) Use of capillary zone electrophoresis for determining felinine and its application to investigate the stability of felinine. Amino Acids 27, 49–55. Rutherfurd, S. M., Kitson, T. M., Woolhouse, A. D., McGrath, M. C., and Hendriks, W. H. (2007) Felinine stability in the presence of selected urine compounds. Amino Acids 32, 235–242.

TX700151T

tx700151t

Recommend Documents