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Predicting Phospholipidosis: A Fluorescence Noncell Based in Vitro Assay for the Determination of DrugPhospholipid Complex Formation in Early Drug Discovery Liping Zhou,*,† Gina Geraci,‡ Sloan Hess,‡,§ Linhong Yang,‡ Jianling Wang,‡ and Upendra Argikar‡ †
Chemical and Pharmaceutical Profiling, Novartis Institutes for BioMedical Research, 250 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States ‡ Metabolism and Pharmacokinetics, Novartis Institutes for BioMedical Research, 250 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States ABSTRACT: This paper describes for the first time, a high-throughput fluorescence noncell based assay to screen for the drugphospholipid interaction, which correlates to phospholipidosis. Anionic amphiphilic phospholipids can form complexes in aqueous solution, and its critical micelle concentration (CMC) can be determined using the fluorescence probe N,N-dimethyl-6propionyl-2-naphthylamine (Prodan). Upon interaction with drug candidates, this CMC may shift to a lower value due to the association between lipids and drug candidates, the stronger the interaction, the greater the shift. Metabolism of a drug can change the degree of phospholipidosis depending on the rate of metabolism and the nature of the metabolite(s). Our data from 45 drugs and metabolites of 10 drugs using this fluorescence approach demonstrate a good correlation with phospholipidosis as reported with human studies, in vivo testing, and cellular assays. This assay therefore offers a fast, reliable, and cost-effective screening tool for early prediction of the phospholipidosis-inducing potential of drug candidates.
D
rug-induced phospholipidosis (PLD), though not called so, was first reported in 1948 by Nelson and Fitzhugh with the observation of foamy macrophages in rats under long-term treatment of chloroquine.1 Later studies have indicated that cationic amphiphilic drugs (CADs) are responsible for inducing this lipid accumulation in cells and causing the presence of lamellar inclusion bodies that are primarily lysosomal in composition.25 The mechanisms behind PLD are not fully understood. The two leading hypotheses include (i) the binding between CAD and phospholipids through both hydrophobic and electrostatic interactions resulting in druglipid complexes indigestible by lysosomal phospholipases and (ii) a direct inhibition of lipid digestion enzyme by the CAD.3,69 There is no clear evidence linking drug-induced PLD to cell toxicity. This lipid storage disorder is considered to be a cell’s adaptive response to CAD exposure10 rather than a toxicological manifestation and is reversible upon the termination of the administration.11,12 The altered lipid metabolism resulting from PLD is of concern as it can occur in a range of tissue types including lung, liver, brain, nervous system, and lymphatic system.13 In certain cases, it can lead to an accumulation of drugs and/or their metabolites as high as millimolar concentration in lamellar bodies and cause cell injury.2,14 Therefore, the extent and duration of the reversibility of PLD by a compound is investigated to assess its safety margin. In drug discovery and development, the accumulation of drugs in critical tissues such as brain, eye, liver, and heart are of major concerns and it is clearly a disadvantage when compared to a competitor without PLD indication. r 2011 American Chemical Society
A diagnosis of PLD requires confirmation by transmission electron microscopy (TEM), which is widely accepted as the standard approach to characterize drug-induced lipidosis.9,1518 Under TEM, the onionlike lysosomes in macrophages are characteristic of PLD. However, TEM is neither commonly available nor readily amendable for the requirement in early drug discovery and development because of its high cost, the need to sacrifice laboratory animals, and the variation from study to study in terms of experimental design, dose, etc. Many tools, such as in silico evaluation, in vitro biological screening, and in vivo biomarkers have been developed to address the needs at different phases of drug discovery and development to predict or identify phospholipidosis. Because of the characteristic properties of CADs, in silico prediction models for PLD focus on screening for a candidate’s lipophilicity and its charge at neutral13,19 or a lower pH, representative of the condition in the lysosome.20 Later models also incorporate detailed compound structural information13 or pharmacokinetic properties to improve predictability.10 Though applicable as first tier flagging tools, in silico models shall be used with caution as they may project a PLD snapshot especially for virtual molecules rather than a full mechanistic assessment including dose dependency and time dependency. In addition, these tools cannot predict inducers that are non-CADs, such as gentamicin which is Received: March 17, 2011 Accepted: July 26, 2011 Published: July 26, 2011 6980
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Figure 1. Reproducibility of the assay illustrated with the average CMC of different test articles obtained on different assay dates. Error bars represented the standard deviations.
highly hydrophilic.21 In most pharmaceutical companies’ PLD screening strategies, the next level screening assays are cell-based biological assays with either fluorescent lipids or lipophilic dyes inside cells.2225 A 96-well based gene-expression assay26 has been recently reported; however, this assay has been demonstrated to be less sensitive.22 There has been no noncell based in vitro screening assay available until recently. A high-throughput langmuir-balance approach linking the change in the critical micelle concentration (CMC) after the treatment with test compound to PLD observed in human, in animal, and in cell has been reported.27 This approach greatly enhances the quality of prediction compared to computational models and increases throughput compared to cellular assays and animal models; however, this method requires the application of a specialized device, an eight channel surface-tensiometer (Delta 8, Kibron Inc., Helsinki, Finland), which is not readily available in most laboratories. In this report, we describe an alternative approach for the determination of CMC and therefore a drug’s phospholipogenic potential in alignment with the langmuir-balance approach. We measure druglipid complex formation via changes in CMC of a short chain lipid with a fluorescent dye probe. Some fluorescent dye probes have long been used for the determination of CMCs,28,29 including lipids30,31 based on the microenvironmental changes upon the formation of micelles affecting the fluorescent emission of the dye probe. The instrument required is a fluorescent plate reader which is available in most biology and biochemistry laboratories. Drug metabolism can affect PLD in at least two ways. When a polar metabolite of a CAD is formed, it can be rapidly excreted making the parent less likely to accumulate. On the other hand, the formation of a cationic amphiphilic metabolite from a nonCAD parent can also induce PLD.32 Such mechanistic insights may be valuable in explaining the disconnection between in vitro screening results and in vivo animal data. For this reason, we have also investigated the phospholipogenic potential of major metabolites of some of the test compounds.
’ METHODS Equipments and Materials. Equipment. A 96-well fluorescence plate reader (Sepctra Max-Gemini EM, Molecular Devices,
Sunnyvale, CA) coupled with a 96-shallow well fluorescent plate (Greiner Bio-one, Kremsmuenster, Austria) was employed. Materials. All standard compounds used to validate this method were purchased from Fisher Scientific/A.G. Scientific/ Aldrich/Acros/Tocris/MP Biomedicals or obtained from Novartis repository and used without further purification. Buffers. A pH 7.2 N-2-hydroxyethylpiperazine-N0 -2-ethanesulfonic acid (HEPES) buffer, a 20 mM with 0.1 mM ethylenediamine tetraacetic acid (EDTA) (MP biomedicals, Solon, OH), and a pH 4.8 acetate buffer, 40 mM were used. Fluorescent Dye. N-N-Dimethyl-6-propionyl-2-naphthylamine (Prodan) was purchased from Fisher Scientific (Fair Lawn, NJ). Anionic Lipid. 1,2-Dioctanoyl-sn-glycero-3-phospho-L-serine (sodium salt) (diC8PS) was purchased from Avanti Polar Lipids Inc. (Alabaster, AL). Sample Preparation. Stock Solutions of Test Compounds. Test compounds were dissolved in Dimethyl sulfoxide (DMSO) at concentrations of 10, 1, or 0.1 mM. For compounds such as gentamicin that were not fully soluble in DMSO at the above concentrations, distilled water was used instead. Lipid Solution. The 50 mg/mL stock solution of diC8PS in chloroform purchased from Avanti was further diluted in chloroform/methanol (5:1 v/v) to yield a concentration of 16 mg/mL and stored at 80 °C when not used. A volume of 4 mL of this solution was transferred to a clean 20 mL glass vial, and the solvent was evaporated under a gentle nitrogen stream. The dry lipid film was dispersed in 10 mL of 20 mM HEPES buffer, 0.1 mM EDTA, pH 7.2, to obtain a final concentration of 6 mg/mL. The solution was vortexed vigorously and placed in a 60 °C water bath and incubated for 45 min before use. This solution was stored at 4 °C when not in use and then diluted with the same HEPES buffer described above to obtain 4 and 1 mg/mL solutions prior to use. Dye Solution. Prodan was dissolved in methanol to make a 0.3 mg/mL stock solution. The container of the solution was wrapped in foil and stored in the dark at room temperature. The solution was diluted to 0.05 mg/mL using methanol before adding to the sample solutions. Sample Plate Preparation and Measurement. The sample plate was prepared by mixing 10 μL of compound stock solution 6981
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Figure 2. Fluorescence emission recorded at different concentrations of lipid diC8PS ranging from 64 μg/mL to 3.47 mg/mL. In the control, with neat DMSO added in place of test compound (O), the sharp rise at ∼1.1 mg/mL marked the CMC of diC8PS. With 10 μL of 10 mM thioridazine (9) introduced to the matrix (diC8PS in 20 mM HEPES buffer), the CMC shifted to lower concentration (0.042 mg/mL). RFU: relative fluorescence unit.
(pure DMSO for control), 10 μL of Prodan solution, and the correct amount of lipid solution to make the final lipid concentrations of 3.3, 2, 1, 0.8, 0.5, 0.25, 0.1, 0.08, 0.06, 0.006, and 0.0006 mg/mL, with a total volume of 110 μL in each well adjusted by addition of the buffer solution. The final drug concentrations were 910, 91, and 9.1 μM from 10, 1, and 0.1 mM DMSO stock solutions, respectively. The plate was read using the Spectra Max-Gemini EM plate reader with an excitation wavelength of 360 nm and an emission wavelength of 430 nm. Determination of Critical Micelle Concentration. The fluorescence readings were plotted against the concentration of the lipid. The CMC was defined as the concentration point above which the enhancement of fluorescent signal was a function of concentration as illustrated by Figure 1. This intercept of the biphasic linear plots was determined automatically by an in-house Microsoft Excel worksheet developed by Novartis IT. The Microsoft Excel worksheet located the best fit for the vertical linear curve by looking for the best R2 value from a moving window of points in the data. The remaining data was used for the horizontal linear curve. The intercept point, which was the CMC value, was calculated by subtracting the horizontal curve from the vertical curve. The intersection in the control experiment represented the CMC of the lipid in the matrix of the media. Assay Reproducibility. To test the reproducibility of the assay, some compounds were tested multiple times on different assay dates. Together with the data of controls which were ran on every assay date, the coefficient of variations (CVs) ranged from 4 to 8%, indicating good reproducibility of the current approach (Figure 1).
’ RESULTS Shift of Lipid CMC upon Incubation with Test Compounds. The negatively charged lipid diC8PS, being amphiphilic in nature, aggregated and formed micelles in aqueous solution, generating a more lipophilic microenvironment. When Prodan interacted with the micelles, its fluorescence emission was shifted. A discontinuity was observed from the fluorescence concentration profile of diC8PS (Figure 2) with the transitioning lipid concentration being its CMC (CMCL = 1.1 mg/mL; L-lipid). This CMC value was
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similar to the one determined by Vitovic using the surface tension approach under similar test conditions.27 When test compound thiorizadine was added to the matrix, the CMC of the complex (CMCDL; DL, druglipid complex) shifted to 0.042 mg/mL (Figure 2). At lipid concentrations above 0.5 mg/mL in the sample, the fluorescent signal was quenched, giving lower values; however, this did not affect the determination of CMC. The ratio between CMCDL and CMCL was utilized to quantify the shift. The CMC values of the druglipid complex were determined for 45 commercial compounds and compared with PLD observed in humans, in animals, or in cultured cells (Table 1). These compounds were grouped into four classes, respectively, as suggested in the literature.19,27 The degree of the CMC shift was represented by the CMC ratio (CMCDL/CMCL) (Figure 3). With the comparison of the PLD data derived either in humans, in animals, or in cultured cells with the CMC shift detected using this fluorescent approach (Figure 3) and using the CMC ratio at 0.75 as the cutoff value, most compounds demonstrated a consistent ranking between the in vivo and in vitro data except for two: warfarin and amlodipine. Both warfarin20 and amlodipine10 were reported as having low or no PLD in vivo, but CMC shifts were observed in this fluorescent assay. Concentration Dependency. The degree of PLD in in vivo studies was dose dependent.24,33 In in vitro assays, concentration control could be used to estimate dose dependency. A group of seven reported PLD inducers were tested at three different concentrations: 910, 91, and 9.1 μM, respectively (Figure 4). For chloroquine and ketoconazole, either they were not fully soluble at 10 mM in DMSO or they salted out upon mixing with buffer when using 10 mM DMSO stocks, their highest concentration points were taken out. All compounds demonstrated concentration dependency toward CMC shift the PLD inducing potential with a varying extent. Fenfluramine appeared to be a weak inducer even at 910 μM, whereas thioridazine showed significant changes from concentration to concentration. At the lowest concentration of 9.1 μM, none of the seven compounds appeared to be able to induce PLD according to this in vitro data. Compound Self-Aggregation. Similar to phospholipids, most of the PLD inducers were amphiphilic. Though bearing different signs of charges, they could also aggregate and form micelles. Labetalol20,34 and quinidine35 were reported as PLD inducers; however, we were not able to determine the CMC of the druglipid complex of either under the test conditions applied. The RFU values obtained were equal or lower compared to those in the blank (compound with fluorescent probe but no lipid). Further studies with varying drug concentrations but no lipid (0 mg/mL lipid) were carried out, and CMC values of 26 and 20 μM were revealed for labetalol and quindine, respectively, in the lipid-free assay buffer. These CMC values were well below the test concentrations of these compounds in the PLD screening, and it was suspected that the compound’s self-aggregation could interfere with the detection of the druglipid complex formation thus making the CMCDL not determinable. PLD Induced by Metabolites. To investigate the effect of metabolism on PLD, 10 compounds with major metabolism events were selected and their major metabolites were screened using the reported assay, exhibiting distinct behaviors (Figure 5 and Table 2). Desethylamiodarone, the major metabolite of amiodarone showed a close to 10 times higher lipid binding potential than its parent. For chloroquine, clozapine, and mianserin, their metabolites fell into the PLD noninducer group, contradictory to the parent compounds which were inducers. Because of solubility limitations, test 6982
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Table 1. List of Compounds Used in the Validation of the Fluorescent Probe Approach with Their PLD Inducing Potential Detected/Estimated by in Vivo, in Vitro, and in Silico Models in vivo/in vitro cellular screening
in silico prediction
in vitro noncell based fluorescent screening, CMCDL/CMCL
Ploemen
Tomizawa
PLD induction classb
refs
model19
model20
pH 7.2
pH 4.8
acetaminophen
IV
10,20,27,56
negative
low
1.043
0.91
amikacin amiodarone
II I, II
10,56,57 40,5861
negative positive
none high
0.193 0.645
0.95
amitryptyline
II
62
positive
high
0.1
compounda
amlodipine
IV
10
positive
high
0.191
0.06
atenolol
IV
10,27
negative
low
0.98
0.86
atropine
IV
10,20,27
positive
low
0.944
1.05
bupropion
IV
10
negative
high
0.762
0.63
buspirone
IV
27
negative
med
0.902
0.97
carbamazepine chloroquine (0.091 mM)
IV I, II
10 2,62
negative positive
low high
0.843 0.333
0.99 0.47
chlorpromazine
II
62,63
positive
high
0.047
0.08
cimetidine
IV
20
negative
low
1.033
citalopram
II
64
positive
high
0.272
clomipramine
II
10,23
positive
high
0.082
0.84
clozapine
II
62
positive
high
0.665
0.83
desipramine
II
65
positive
high
0.155
0.28
disopyramide erythromycin
IV II
27 66
positive negative
high med
1.001 0.739
0.79 0.89
famotidine
IV
20,27
negative
low
0.92
0.87
fenfluramine
II
67,68
positive
high
0.702
fluoxetine
I, II
69
positive
high
0.047
furosemide
IV
20,27
negative
none
0.929
gemfibrozil
IV
10
negative
none
1.039
gentamicin
I,II
36,70
negative
none
0.072
haloperidol imipramine
II II
10,62 62
negative positive
high high
0.125 0.201
0.81
ketoconazole (0.091 mM)
II
71
negative
high
0.558
ketoprofen
IV
10,27
negative
none
1.026
lidocaine
IV
10,20,27
negative
medium
1.013
maprotiline
II
72
positive
high
0.072
0.15
mianserin
III
62
negative
high
0.217
0.94
nortriptyline
III
62
positive
high
0.149
pentamidine perhexiline
I I, II
73 74
positive positive
high high
0.163 0.043
0.31 0.05
procaine
IV
10
positive
med
0.851
0.97
promazine
II
63
positive
high
0.056
propranolol
III
35
positive
high
0.076
ranitidine
IV
10
negative
low
0.884
sotalol
IV
10,75
negative
low
0.933
suldinac
IV
10
negative
low
0.979
tamoxifen thioridazine
II II
62 62
positive positive
high high
0.308 0.042
0.09
0.29
valproic acid
IV
10,20,27
negative
low
0.997
1.04
warfarin
IV
10,20
negative
low
0.401
0.75
a
Final compound concentration was 0.91 mM unless otherwise indicated. b Compounds were grouped based on in vivo and cellular assay data. Class I: PLD in humans; Class II: PLD in animals; Class III: PLD in cells but not in animals; Class IV: no PLD observed or reported.
concentrations of 8-hydroxymianserin and des-methyl clozapine were 0.091 mM, lower than those of their parent compounds (1 mM).
The other metabolites showed comparable PLD inducing potential comparing to their parent compounds while others did not. 6983
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Figure 3. Comparison between the CMC shift (represented by the ratio between CMC of the druglipid complex (DL) and CMC of lipid alone (L): CMCDL/CMCL) observed in this fluorimetric assay at pH 7.2 with in vivo human, in vivo animal, or in vitro cellular PLD assays. A cutoff value of 0.75 in CMCDL/CMCL separated PLD inducers (b, in vivo assay; [, cellular assay) from PLD noninducers (9) with only two outliers: amlodipine and warfarin.
Figure 4. The CMC shift (represented by the ratio between CMC of the druglipid complex (DL) and CMC of lipid alone (L): CMCDL/ CMCL) of test compounds with a different final concentration in the sample wells at pH 7.2.
Assay pH Effect. The lipid disorder in PLD was mainly observed in the lysosomal compartment which constituted an acidic environment. To mimic the lysosomal condition, pH 4.8 acetate buffer was employed in the PLD screening studies with 25 commercial compounds (Table 1) using the same procedure described above. Most of the compounds gave similar results in both buffers; however, amiodarone, clomipramine, mianserin, and warfarin gave very different data, shifting the front three compounds from PLD inducers to noninducers and warfarin from noninducer to inducer from pH 7.2 to pH 4.8.
’ DISCUSSION Here we present a novel, high-throughput, noncell based in vitro screening approach predictive of PLD using a fluorimetric probe by monitoring the CMC of phospholipid with and without interaction with the test article. While the Langmuir balance approach27 provides a reliable avenue to assess PLD via the CMC shift, current fluorimetric methodology offers an unique alternative to predict PLD risk. Such a microplate-compatible platform is more cost-effective, easier to operate, and has higher throughput, amendable for PLD risk assessment in early drug discovery. The fluorescent probe selected, Prodan, is suitable for the determination of CMCs of both the lipid as well as test compounds that form micelles. We clearly demonstrate in vivo versus in vitro or noncell based versus cellular assay correlation using the current method with an overall concordance of 91% when applying a suitable cutoff value (CMCDL/CMCL = 0.75 in this assay). This is better compared to the two in silico models that we also applied to our validation set whose concordance values were 76 and 80% for Ploemen19 and Tomizawa20 models, respectively. The sensitivity (PLD inducers identified as positive) and selectivity (non-PLD inducers identified as negative) of our model were 92% and 90%, which were also better than those for the two in silico models (Table 3). Both in silico and in vitro assays utilized the inherent physicochemical properties of the test compounds that made them more affinitive toward phospholipids; however, the in vitro models could also identify the effect of drug concentrations on druglipid interactions which was not predictable by in silico models. Furthermore, the steric chemistry of the molecule and the spatial distribution of charge as well as its polar and nonpolar moieties could play a role in the reactivity of the test compound and these factors were not captured by in silico models. In addition, this in vitro model correctly assigned the PLD inducing potential of non-CAD drugs like gentamicin 6984
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and erythromycin because in vitro models evaluated the overall interactions between the test compound and lipid thus were more advanced than in silico models. Conversely, for compounds with solubility issues at desired test concentrations, an alternative solvent should be identified or the data could be misleading. In silico models did not have this barrier and could be applied to any compounds with defined structures. Pharmacokinetics was reported to have an impact on PLD as the dose,24,33,36 the metabolism,32,3739 and the disposition10 of the drug all affected the severity of PLD in vivo. Creation of a successful candidate required clear understanding of the cause of
PLD and thus redesigning the chemical structure or assessing an appropriate therapeutic window. The minimum dose required for PLD differed from compound to compound and sometimes was gender dependent.24 Directly linking the in vivo dose with the in vitro test concentration could be challenging as the plasma concentration of the drug could be well affected by its permeability, solubility, metabolism, excipient utilized, route of administration, frequency of drug intake, and so on. However, by monitoring the concentration dependency of the test molecule toward PLD capability, which was unlikely to be linear as shown in Figure 4 and would be hard to estimate, we could identify the potential relationship between dose and lipid binding, thus assess the safety window with a limited number of in vivo tests. There have been a number of publications describing PLD caused by drug metabolites. Among them, the primary metabolite of amiodarone, desethylamiodarone, had been discussed extensively.14,3840 Preferential accumulation of the metabolite over amiodarone had been observed especially for short-term treatments.39 This offered a possible explanation for our assay data where desethylamiodarone, a major metabolite of amiodarone,41,42 demonstrated much higher PLD inducing potential. Similarly, the CMC shift difference between 8-hydroxymianserin, the major oxidative metabolite of mianserin,43,44 and mianserin was more significant than the difference between the other two pairs of parents and metabolites. Because of solubility limitations, dose concentrations were different for the parents and metabolites for clozapine and mianserin. It was possible that this might lead to remarkable differences in the CMC shift observed between parent and metabolite. When tested at a lower concentration, clozapine switched from a low potential inducer to a noninducer, whereas mianserin remained as an inducer but with higher CMCDL/CMCL value. It was worth noting most CADs in
Figure 5. The CMC shift (represented by ratio between CMC of the druglipid complex (DL) and CMC of lipid alone (L): CMCDL/ CMCL) of test compounds (black) and their major metabolites (gray, primary metabolite; white, secondary metabolite) analyzed in pH 7.2 HEPES buffer. The drug concentrations used were 1 mM unless otherwise indicated in Table2. Error bars were assigned to those compounds with n g 3 tests. For clozapine and mianserin, both 0.91 and 0.091 mM were used in the tests but only data from the 1 mM tests were plotted.
Table 3. Predictability of Various Models Ploemen19
Tomizawa20
Novartis
sensitivity (%)
72
88
92
selectivity (%)
80
70
90
concordance (%)
76
80
91
model
Table 2. List of Compounds Used in the Validation of Metabolite Effects on PLD parent compound
PLD class
CMC shift of parent compound
CMC shift of metabolite 1
metabolite 1
amiodarone
I, II
0.604
desethylamiodarone
0.075
amitryptyline
II
0.175
nortryptyline
0.065
metabolite 2
CMC shift of metabolite 2
refs
amitriptalline N-glucuronide
N/D
4850
41,42
amlodipine
IV
0.045
dehydro amlodipine oxalate
0.180
chloroquine
I, II
0.657
desethyl chloroquine
0.980
bidesethyl chloroquine
N/D
51,52
76,77
chlorpromazine clomipramine
II II
0.047 0.083
N-desmethyl chlorpromazine N-des methyl clomipramine
0.056 0.060
chlorpromazine-5-sulfoxide clomipramine-5S-oxide
N/D 0.877
4547 53,54
clozapine
II
0.712
des-methyl clozapine (0.1 mM)
0.917
clozapine-N-oxide (0.1 mM)
1.015
78,79
(0.091 mM)
clomipraimne n-oxide clozapine
0.924
(0.091 mM) desipramine
II
0.161
N-desmethyl desipramine
0.080
desipramine N-hydroxy
1.040
43,50
imipramine
II
0.235
desipramine
0.155
imipramine-N-glucuronide
N/D
43,50
0.225 0.675
8-hydroxymianserin (0.1 mM)
0.877
mianserin III mianserin (0.091 mM)
6985
43,44
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Analytical Chemistry the current test set were reported to be metabolized oxidatively to their corresponding des-alkyl primary metabolites. In order to understand the PLD potential of the corresponding primary metabolites, we tested the additional metabolites. Among the metabolites tested were primary des-methyl metabolites chlorpromazine,4547 amitryptyline,4850 imipramine,43,50 and primary and secondary des-ethyl metabolites of chloroquine.51,52 In addition, oxidative metabolites formed by heteroatom oxidation and des-alkyl metabolites of desipramine43,50 and clominpramine53,54 were evaluated. Metabolites, like other CADs, could induce PLD if they had suitable physicochemical properties.32 Conversely, a metabolite would lose the capability of binding with lipid if CAD charactersistics are lost, such as observed with clomipramine N-oxide and desipramine N-hydroxy (Figure 4 and Table 2). It has been known that the levels and time in circulation may vary for different metabolites and from one drug to another; however, the amounts (in moles) or dose equivalents of circulating metabolites may never be greater than those of the administered drug. In the present study, the metabolites were tested at the same or lower concentrations compared to their parents based on the allowance of their solubility. It should be noted that this assay was developed as a prospective screening tool; therefore, the underlying premise is the testing metabolites at the same concentration as that of the parent. In cases where the PLD potential of the metabolites is of interest, a concentration dependent study may be conducted with the concerned metabolite. However, such a study was beyond the scope of the present investigation. The identification of lamellar bodies via transmission electron microscopy (TEM) was the first indication of lysosome involvement in PLD9 and indicated that lysosomal pH may be a critical factor;20 however, initially there was no direct evidence of the origin and function of lysosomal involvement.3 A study carried out by Maxfield and MacGraw showed evidence of rapid sequestration of endosomes formed in the presence of phospholipogenic drugs that became lysosomes;55 however, it was possible that the acidic pH of lysosomes could change the severity of interaction between the lipid and drug of interest with the formation of lysosomal inclusion bodies. For these reasons, we believed it valuable to study both pH conditions and therefore obtain a more comprehensive risk assessment. In our validation set, most compounds gave similar CMC shifts under both pH 7.4 and 4.8 except for mianserin, amiodarone, and warfarin, and all three compounds were proven to be PLD inducers by varied in vivo and cellular assays. This assay showed high reproducibility and predictability. Similar to other in vitro assays which could not replace in vivo measurements for a confirmative result, this less expensive, less time-consuming fluorimetric approach could provide useful information on druglipid interaction early on. Furthermore, such an approach could be used for rank ordering candidates, aiding drug design, and estimating potential risk.
’ AUTHOR INFORMATION Corresponding Author
*Phone: 617-871-7143. E-mail:
[email protected]. Present Addresses §
Department of Chemistry, University of Colorado-Denver, Denver, CO 80205.
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