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Research ArticleArticle

Quantitative Structure Activity Relationships for the Glucuronidation of Simple Phenols by Expressed Human UGT1A6 and UGT1A9

Brian T. Ethell, Sean Ekins, Jibo Wang and Brian Burchell
Drug Metabolism and Disposition June 2002, 30 (6) 734-738; DOI: https://doi.org/10.1124/dmd.30.6.734

Abstract

UGT1A6 and UGT1A9 have both been demonstrated to rapidly glucuronidate simple phenolic compounds. A series of simple phenols were selected and screened with both isoforms and then used as model substrates for the generation of Vmax andKm values. UGT1A6 showed a more restricted acceptance of phenolic substrates compared with UGT1A9. However, the affinity of UGT1A6 for these compounds exhibited higherKm values than UGT1A9, although rates of turnover were similar. Molecular surface-weighted holistic invariant molecular descriptors were generated for each substrate and used to produce the first quantitative structure activity relationship models generated for expressed human UGTs. Models relating log of theKm value to the generated descriptors correlated well with the experimental datar2 value of 0.996 for UGT1A6 andr2 value of 0.83 for UGT1A9. Cross validation by a leave-one-out method also showed good predictive capability within the subset with a q2 value of 0.98 for UGT1A6 and q2 value of 0.73 for UGT1A9. Empirically, UGT1A6 Vmax decreased as the 4-substituent increased in size, and a trend was observed when UGT1A6 Vmax was plotted against molecular volume. The larger UGT1A6 substrates were typified by low activity and lower Km values than their smaller counterparts. Extrapolating from this, it was demonstrated that phenols with large 4-substituents, which were not UGT1A6 substrates, could inhibit 4-ethylphenol glucuronidation. TheKm values for UGT1A9 showed a similar relationship to UGT1A6 but with much lowerKm values and greater variability in range of this value.

Glucuronidation is an important metabolic process for the clearance of drugs, endobiotics, and xenobiotics in all mammalian species. There are numerous instances where drugs are cleared extensively by direct glucuronidation (3′-azido-2′,3′-dideoxythymidine, valproic acid, propofol, and morphine; Bertz and Granneman, 1997), although in many other cases, the involvement of glucuronidation is restricted to the conjugation of glucuronic acid to metabolites of phase I oxidative metabolism. Where drugs are significantly glucuronidated independently of phase I metabolism, the functional group to which the glucuronic acid is transferred can be a hydroxy (phenolic or aliphatic), a carboxylic acid or, in some cases, an amino group (primary, secondary, or tertiary) moiety.

The UDP-glucuronosyltransferases (UGT1) family can be separated into two distinct subfamilies by sequence similarity. The UGT1 family are all derived from a single gene by alternative splicing of four constant exons (exons 2–5) to a variable exon 1. The RNA transcript leads to a transferase protein exhibiting a certain substrate specificity. The UGT2 family of isoforms are known to be encoded by individual genes (Mackenzie et al., 1997).

Characterization of cloned and expressed human UGT has demonstrated that many UGT family 1 isoforms are capable of glucuronidating phenols to varying degrees including UGT1A1 (Senafi et al., 1994), UGT1A3 (Green et al., 1998), UGT1A4 (Green and Tephly, 1996), UGT1A8, and UGT1A10 (Cheng et al., 1999). UGT family 2 isoforms also display activity toward phenols, although substrate acceptance and rate of glucuronidation seems to be more restricted (UGT2B15, Green et al., 1994; UGT2B7, Coffman et al., 1998). Two of the earliest UGT isoforms to be characterized were done so on the basis of their ability to glucuronidate phenols. UGT1A6 and UGT1A9 were both classified as phenol UGT isoforms due to the high turnover rates of these substrates (Ebner and Burchell, 1993). UGT1A9 demonstrated greater proficiency in glucuronidating bulky and complex phenols than UGT1A6, which was considered to be only capable of glucuronidating simple or planer phenols (Ebner and Burchell, 1993). The high glucuronidation activity toward simple phenolic substrates has been clearly illustrated to be present in human liver microsomes (Temellini et al., 1991), and UGT1A6 comprises a significant proportion of liver UGT 1-naphthol glucuronidation capacity (Ouzzine et al., 1994).

Phenols have also been used as probe substrates for simple quantitative structure activity relationship modeling, although very few reports on glucuronidation quantitative structure activity relationships (QSAR) have been reported. Enzyme activity data sets for phenols and benzoic acids incubated with rabbit and rat liver microsomes, published before UGT heterogeneity were recognized (Bray et al., 1952; Mulder and Van Doorn, 1975; Illing and Benford, 1976; Mulder and Meerman, 1978) and have subsequently been used for QSAR modeling (Hansch et al., 1968;Schaefer et al., 1981; Kim, 1991). These original reports and much of the data contained within has more recently been reanalyzed (Hansch and Leo, 1995). Kinetic constants for simple phenolic substrate glucuronidation were modeled by QSAR to characterize a partially purified rat UGT (Yin et al., 1994).

No single study to date has yet yielded enough kinetic data on an individual-expressed human UGT isoform to be able to perform any quantitative analysis. The objective of this report was to generate the kinetic parameters that describe the glucuronidation of simple 4-substituted phenols by the human UGT1A6 and UGT1A9 isoenzymes. Models were then generated for UGT1A6 and UGT1A9 from a range of molecular surface (MS-WHIM) and atomic (AT-WHIM) descriptors to determine whether the Km for phenol glucuronidation could be predicted. The models were used to look for similarities and differences in the way that these two isoforms glucuronidate phenols and were also used to determine the viability of this process for developing QSAR models for more complex and diverse substrates in the future.

Materials and Methods

Chemicals.

Phenols, control substrates, UDPGA, and other reagents used in the assays were purchased from Sigma-Aldrich Ltd. (Gillingham, Dorset, UK) and British Drug Houses (Merck, Poole, Dorset, UK) and were of the highest grade available. [14C] UDPGA (293.6 mCi/mmol, 99.7%) was purchased from PerkinElmer Life Sciences (Stevenage, Hertfordshire, UK).

Tissue Culture.

V79 and recombinant cell lines were grown using Dulbecco's modified Eagle's medium containing 10% fetal bovine serum, 100 units/ml penicillin, and 0.1 mg/ml streptomycin (Invitrogen, Paisley, Scotland). The cloning and stable expression of the UGT isoforms has been reported elsewhere (Harding et al., 1988; Fournel-Gigleux et al., 1990; Wooster et al., 1991). V79 cell lines heterologously expressing human UGTs were maintained under optimized constant selection concentrations of geneticin (G418; Invitrogen), V79/UGT1A6 (100 μg/ml), and V79/UGT1A9 (200 μg/ml).

Cellular Sonication.

Cells were disrupted by a standardized sonication method. Pellets containing cells harvested from two 75-cm2 tissue culture flasks were thawed prior to assaying and resuspended in 200 μl of water to lyse the cells. Each 200-μl suspension of cells was sonicated for four 5 s bursts (Microson Ultrasonic Cell Disruptor; Heat Technologies, Farmingdale, New York) allowing at least 1 min on ice between bursts. Aliquots of cells prepared by this method were pooled before addition to the assays. Each set of kinetic determinations was performed using cells harvested from the same passage. Two hundred 75-cm2 flasks of each cell line were grown expressly for this purpose.

UGT Assays.

UGT assays for phenolic glucuronidation were performed as described previously (Ethell et al., 1998). Briefly, the incubations contained 100 mM Tris/maleate buffer, pH 7.4, containing 5 mM MgCl2, typically 500 μM substrate, 250 to 350 μg of cellular sonicate, 2 mM UDPGA (0.1μCi [14C] UDPGA/assay) in a total volume of 100 μl. Incubations were run for 40 min and terminated by the addition of 100 μl of methanol that had been prechilled at −20°C. The resulting supernatant was then transferred to an HPLC vial and 150 μl of this volume directly injected onto gradient HPLC using solid scintillant radioactive detection as described previously (Ethell et al., 1998). Product formation was linear for 1-naphthol glucuronidation, with a Vmax value in the same range as substrates for UGT1A6 and UGT1A9, which were most rapidly glucuronidated (Ethell et al, 1998). Control V79 cell lines showed no detectable activity toward these substrates. It was not possible to verify that product formation was linear due to the limited availability of expressed enzyme. Every effort was made to keep protein concentration the same between batches of assays (under which conditions product formation was linear with time).

Substrate solutions were prepared and diluted on the day of assay. Typically, the range of substrate concentrations used was 10, 50, 100, 250, 500, and 1000 μM. Kinetic parameters were calculated by fitting the experimental data to the Michaelis-Menten equation by a nonlinear least-squares regression method (Prism version 2; Graphpad Software, San Diego, CA).

Each kinetic determination was accompanied by an assay with a probe substrate as a control: UGT1A6 with 1-naphthol and UGT1A9 with propofol at a fixed substrate concentration (500 μM) under identical conditions to the assays to determine the kinetic parameters for the test phenols. This value was used to normalize theVmax values produced for the phenol substrate to control for any variability in the activity of the cell preparation and total amount of cell protein added.

Protein Determinations.

Estimation of protein concentration was carried out using the method ofLowry et al. (1951), on dilutions of 1:100 of the cellular sonicates with bovine serum albumin as standard.

MS-WHIM Descriptor Computation.

MS-WHIM and AT-WHIM descriptors were computed using an improved in-house program based on the method of Bravi and Wikel (2000). In this program, the WHIM mathematical strategy (Todeschini et al., 1994) is applied to the coordinates of the critical points of the molecular surface (Lin et al., 1994). For each molecule, atomic three-dimensional coordinates were generated by CORINA (Gasteiger et al., 1990), and critical points were calculated using an in-house procedure according to the method of Lin et al. (1994). Six molecular surface property-weighting schemes (unitary, positive and negative electrostatic potential, hydrogen-bonding acceptor, and donor capacity and hydrophobicity) are used (Bravi and Wikel, 2000). A total of 102 [11 directional and 6 nondirectional (Todeschini and Gramatica, 1997) for each weighting scheme] descriptors were generated per phenol substrate. These descriptors were used along with Cerius2 (Molecular Simulations Inc., San Diego) genetic function approximation software to build a model to relate them to the log Km values. Leave-one-out cross validation was also used to generate a cross-validatedr2(q2).

Results

4-Substituted phenols were screened as potential substrates for UGT1A9 and UGT1A6 regardless of whether or not they had previously been identified as substrates. The phenols used and the structures of the 4-substitutents are shown in Fig. 1. Twenty-four of these phenols were substrates of UGT1A9 and 12 were substrates of UGT1A6. Two of the 12 phenols glucuronidated by UGT1A6 (4-fluorophenol and 4-methoxyphenol) were turned over to such a low extent that it was not possible to accurately measure kinetic parameters using the radiochemical HPLC method. Kinetic parameters for UGT1A6 and UGT1A9 are listed in Table 1and Table 2, respectively.

Figure 1
Figure 1

4-substituents of phenolic compounds used as potential substrates of expressed human UGT1A6 and UGT1A9 to determine which were suitable for use in kinetic determination.

View this table:
Table 1

Kinetic constants for glucuronidation of 4-substituted phenols catalysed by UGT1A6

View this table:
Table 2

Kinetic constants for glucuronidation of 4-substituted phenols catalysed by UGT1A9

The ranges of kinetic values for the various substrates differ significantly between UGT1A6 and UGT1A9; there is a 50-fold difference between the highest and lowest UGT1A6Vmax values but only a 4.5-fold difference for UGT1A9. Conversely, UGT1A9 shows a greater (14.5-fold) variation in Km compared with UGT1A6 (7-fold). Direct comparison of Vmax is particularly difficult for UGT as the quantity of active enzyme cannot be accurately measured, although immunoblotting of the two cell lines suggests similar levels of expression. Comparison ofKm values reveals a distinct difference between UGT1A6 and UGT1A9. UGT1A6 is typified by much higherKm for the same substrates compared with UGT1A9 (Fig. 2). Empirically, it was noted that as the size of substituent decreased, UGT1A6Vmax increased, and correspondingly the Km increased. This trend is better illustrated when the molecular volume of the substituent is plotted against Vmax, as the negative correlation becomes apparent (Fig. 3). It was predicted that substrates not displaying glucuronidation activity when measured using this assay might be bound by UGT1A6 but not glucuronidated, or glucuronidated to such a low extent that no activity was measurable. Three phenols with bulky substituents, 4-npropylphenol, propyl 4-hydroxybenzoate, and 4-hydroxy biphenyl, were all shown to inhibit ethylphenol activity (Km, 551 μM) significantly at a concentration of 500 μM (Fig. 4).

Figure 2
Figure 2

Comparison of Km values of expressed UGT1A6 and UGT1A9 for phenols that are substrates for both isoforms.

The substrates are not listed in the order that they appear in Tables 1and 2.

Figure 3
Figure 3

UGT1A6 Vmax correlated to the molecular volume of the substituent.

Figure 4
Figure 4

The inhibition of UGT1A6 4-ethylphenol glucuronidation by phenols with bulky substituents.

The phenols used were 4-n propylphenol, propyl 4-hydroxybenzoate and 4-hydroxy biphenyl from left to right. The 4-ethylphenol concentration used was 500 μM and the interfering phenol concentration range used was 50, 100, 250, and 500 μM.

Application of the Cerius2 genetic function approximation software to the experimental data produced models for UGT1A6 and UGT1A9. These models relate logKm to the AT- and MS-weighted holistic invariant molecular descriptors shown in eqs. 1 and 2.log UGT1A6 Km=−233.08+JWMWGW5−8.75×JWMWH2W2−0.15×JWAWAW3−0.40×JWAWS3W6 (r2=0.994,q2=0.98,n=10) Where JWMWGW5 is an MS-WHIM descriptor using hydrogen-bond donor capacity as weight, the total symmetry descriptor. JWMWH2W2 is an MS-WHIM descriptor using positive molecular electrostatic potential as the weight, the emptiness descriptor. JWAWAW3 is the AT-WHIM descriptor using atomic mass as weight, the quadratic contribution descriptor. JWAWS3W6 is an AT-WHIM descriptor using absolute atomic partial charge as weight, the second symmetry descriptor. log UGT1A9 Km=1.55+2.06×JWAWE3W6+0.82×JWMWH2W3−2.68×JWMWP2W4+1.20×JWAWP2W5 (r2=0.83,q2=0.73,n=24) Where JWAWE3W6 is an AT-WHIM descriptor using absolute atomic partial charge as weight, the third eigen value. JWMWH2W3 is an MS-WHIM descriptor using negative molecular electrostatic potential as weight, the second emptiness descriptor. JWMWP2W4 is an MS-WHIM descriptor using hydrogen-bonding acceptor capacity as weight, the second proportion descriptor. JWAWP2W5 is an AT-WHIM descriptor using atomic polarizability as weight, the second proportion descriptor.

Discussion

Glucuronidation QSAR to date has typically relied on data garnered from literature sources for quantitative analysis. The relatively small number of reports on glucuronidation QSAR reflects the lack of appropriate data that is available for this purpose and explains why little progress has been made in this area in recent years. This is also apparent by the number of times that the same data has been analyzed either completely or in part by different groups attempting to apply this type of analysis. With the exception of one report of a partially purified rat UGT (Yin et al., 1994), glucuronidation QSAR has been carried out with data from assays using microsomal sources of the UDP-glucuronosyltransferase enzyme (Hansch et al., 1968; Schaefer et al., 1981; Kim, 1991; Hansch and Leo, 1995). Using rat microsomal systems for this type of work adds the complication of modeling a heterogenous population of enzymes that can display a considerable overlap in substrate specificity for the type of simple compounds that are used. Taking into account these considerations, it seems unlikely that these models derived from rat microsomes can provide much in the way of useful information. The benefit of studying isolated enzymes is that the complications introduced by trying to predict the glucuronidation activities of a heterogenous population of isoforms is avoided, and the substrate physicochemical parameters can be directly related to their influence on activity and affinity of a single active site.

The rationale behind the selection of the phenolic compounds as probe substrates is their availability, as well as permitting considerable diversity in the type and size of substituent. Furthermore, phenolic molecules were likely to be adequate substrates for the isoforms in question, providing kinetic data for the analysis, something which to date has not been attempted with expressed human UGT isoforms. The data set was intended to form the basis of a set of compounds that could be expanded to include more diverse compounds in the future and be used to evaluate the quality and value of QSAR analysis of glucuronidation.

The data presented here has been generated with single UGT isoforms with the express purpose of QSAR analysis to compare and contrast two human UGT isoforms that display a considerable overlap in substrate specificity. It is immediately clear that the same restrictions on substrate acceptance by UGT1A6 in comparison with UGT1A9 that have been reported previously (Ebner and Burchell, 1993) are also apparent by the results of this study. Although the potential substrates that were screened by both of the expressed isoforms only vary by way of the substituent at the 4-position, this position seems to be an important factor in whether a compound is or is not a substrate of UGT1A6. Again, UGT1A9 demonstrates proficiency toward the glucuronidation of a wide range of substituted phenols as previously reported (Ebner and Burchell, 1993). UGT1A6 is typified by lowerKm values ranging from micromolar to low millimolar values. This is the first indication of significant differences between the two isoforms as UGT1A9, in general, has lowerKm values than UGT1A6. Comparing theKm values for the set of phenol substrates that are glucuronidated by both isoforms clearly indicates substantially lower Km values for UGT1A9 than UGT1A6 (Fig. 4); however, the ranges ofVmax are similar between the two.

The models generated from the kinetic data relate theKm values to four separate determinants of surface properties of the substrates. The two isoforms are related by totally different descriptors from the identical set of 112 that were originally applied to the experimental data. The correlation coefficients for the fit of the data are good and the cross-validation (q2) values indicate that the predictive capability of these models is good. The application of a test set of compounds for external validation would be the ideal way to evaluate the models, but all the compounds were included in the analysis. It seems unlikely that a model generated from such simple compounds would be able to predict theKm values of more complicated structures. But this work does suggest that for a closely related set of compounds, in this case simple phenols, QSAR models can be generated quite simply, which can predict Kmaccording to the internal validationq2 value. The greatest problem of the data set that was used for this modeling is that it does not contain a wide range of Km values. This indicates that the structural features of the probe molecules are not diverse enough to map the sample space of the active site. Both of these isoforms are able to glucuronidate larger phenols and other bulkier molecules; hence, it seems likely that to gain more meaningful insight into substrate, UGT interactions the size and diversity of the probe substrates used need to be increased.

Another point of interest is the trend observed between UGT1A6Vmax and the molecular volume. Even without the application of QSAR analysis, it was clear that UGT1A6Vmax values were decreasing as the bulk of the substituent increased. Plotting theVmax against molecular volume of the substrate showed an obvious trend (Figure 3), although plottingKm against molecular volume does not show any appreciable correlation at all. The hypothesis proposed was that if Vmax decreased as substrate volume increased then more bulky substrates may be accepted into the active site but may not be glucuronidated, or are glucuronidated below the limits of detection. The inhibitory effect of bulky phenols on the glucuronidation of 4-ethylphenol suggests that this might indeed be the case.

This report demonstrates the potential utility of applying QSAR analysis to glucuronidation data. The limitations of the data set are acknowledged and are presented as the starting point for building more complex models in the future, which can help predict the features of a molecule that make it acceptable as a substrate of UGT1A6 and UGT1A9. Industrial drug design is now more adept at avoiding compounds that are highly metabolized by cytochrome P450 isozymes by screening for high metabolic turnover early in development. If successful circumvention of phase I metabolism leads to the development of more potential drugs that are glucuronidated, then the next evolution in QSAR modelling for the pharmaceutical industry will require models like those suggested in this study (Ekins et al, 2000).

Footnotes

  • Abbreviations used are::
    UGT
    UDP-glucuronosyltransferases
    QSAR
    quantitative structure activity relationship
    WHIM
    weighted holistic invariant molecular
    MS-WHIM
    molecular surface-WHIM
    AT-WHIM
    atomic-WHIM
    UDPGA
    UDP-glucuronic acid
    HPLC
    high-performance liquid chromatography
    • Received November 12, 2001.
    • Accepted March 11, 2002.

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Quantitative Structure Activity Relationships for the Glucuronidation of Simple Phenols by Expressed Human UGT1A6 and UGT1A9

Brian T. Ethell, Sean Ekins, Jibo Wang and Brian Burchell
Drug Metabolism and Disposition June 1, 2002, 30 (6) 734-738; DOI: https://doi.org/10.1124/dmd.30.6.734
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