Abstract
Surface plasmon resonance biosensor technology was used to directly measure the binding interactions of small molecules to the ligand-binding domain of human estrogen receptor. In a screening mode, specific ligands of the receptor were easily discerned from nonligands. In a high-resolution mode, the association and dissociation phase binding responses were shown to be reproducible and could be fit globally to a simple interaction model to extract reaction rate constants. On average, antagonist ligands (such as tamoxifen and nafoxidine) were observed to bind to the receptor with association rates that were 500-fold slower than agonists (such as estriol and β-estradiol). This finding is consistent with these antagonists binding to an altered conformation of the receptor. The biosensor assay also could identify subtle differences in how the same ligand interacted with two different isoforms of the receptor (α and β). The biosensor's ability to determine kinetic rate constants for small molecule/protein interactions provides unique opportunities to understand the mechanisms associated with complex formation as well as new information to drive the optimization of drug candidates.
Surface plasmon resonance (SPR) biosensor technology has advanced to the point where it is possible to measure directly small molecules interacting with immobilized macromolecular targets (1, 2). This development suggests that biosensor analysis will become an important secondary screening tool in drug discovery, confirming hits from primary screens and providing detailed kinetics for lead optimization (3, 4). To illustrate the utility of current SPR technology, the binding properties of small compounds (200–500 Da) interacting with human estrogen receptor (ER) were analyzed.
Ligand binding to ER is responsible for controlling the basic biology of estrogen-sensitive tissues. Using selective agonists or antagonists to modulate this biology is the focus of significant activity in the pharmaceutical industry (5–9). To date, a ligand's binding properties for ER have mainly been determined by equilibrium binding assays that often employ radiolabeled compounds and require overnight incubations. Here, we demonstrate how optical biosensors may be used to determine both kinetic and equilibrium binding constants for compounds interacting with ER in real time without labeling either binding partner.
SPR biosensor experiments require immobilizing one reactant on a surface and monitoring its binding to a second reactant in solution. An antibody-capturing method was used to study the dynamics of ER/ligand interactions. This assay format created a chemically homogenous receptor surface and allowed us to determine rapidly the binding properties of a variety of compounds. We examined the binding of 12 compounds (shown in Fig. 1) having differing receptor activities: both estrogen and non-estrogen agonists, SERMs (selective ER modulators, which for this discussion are referred to as antagonists), and nonbinding control compounds that possess core structures similar to those of the estrogen agonists.
Figure 1.
Panel of compounds studied. (A) Estrogen agonists. (B) Non-estrogen agonists. (C) Antagonists. (D) Nonbinding compounds included as controls.
These results illustrate that current biosensor technology can be used both qualitatively and quantitatively to monitor nuclear receptor/ligand interactions. In a qualitative screening mode, receptor binders and nonbinders were identified. In a quantitative high-resolution mode, precise kinetic and affinity parameters were obtained for compounds across a wide dynamic range. These mechanistic data complement static structural information about ER (10–14), revealing how radically different rate constants govern the binding of agonist and selected antagonist ligands.
Methods
Reagents.
Ligand-binding domains of human ER-α and -β were expressed in Escherichia coli as His-tagged proteins and purified by metal-affinity chromatography. The ER-α fragment was expressed as a 21 amino acid tag sequence (MGSSHHHHHHSSGLVPRGSHM) followed by residues 305–548 of human ER-α with the mutations Cys381→Ser, Cys417→Ser, and Cys530→Ser. Conversion of these free Cys residues to Ser helps stabilize the protein, but does not change the ligand-binding activity (unpublished results). Electrospray mass spectrometry demonstrated that the initiator Met was absent in the purified product (theoretical mass of 29,990 Da; observed mass of 29,993 Da), and that ≈50% of the product was modified by N-terminal gluconoylation, adding 178 Da to the mass (15). The ER-β fragment had the same tag followed by residues 258–498 of the receptor, with the mutations Cys334→Ser, Cys369→Ser, and Cys481→Ser [theoretical mass (without the Met initiator) of 29,319 Da; observed mass of 29,317 Da].
His4 mAb was purchased from Qiagen (Chatsworth, CA), coupling reagents (EDC, NHS, and ethanolamine HCl) were purchased from Biacore (Uppsala, Sweden), and gentle Ag/Ab elution buffer was purchased from Pierce. Corticosterone, dexamethasone, diethylstilbestrol, 17β-estradiol, estriol, estrone, 4-hydroxytamoxifen, nafoxidine, prasterone (also known as dehydroisoandrosterone), testosterone, and tamoxifen were purchased from Sigma. Bisphenol A was purchased from Fluka. The compounds were prepared as 1 mM stock solutions in DMSO to ensure complete dissolution. Immediately before analysis, each compound was diluted in 20 mM sodium phosphate, 150 mM sodium chloride, 1 mM DTT, pH 7.4 to yield a final DMSO concentration of 3% and a compound concentration of 30 μM. Concentration series were prepared by serial dilution of the 30 μM solutions with 20 mM sodium phosphate, 150 mM sodium chloride, 1 mM DTT, 3% (vol/vol) DMSO, pH 7.4.
Instrumentation.
Surface plasmon resonance analyses were performed by using Biacore 2000 and Biacore 3000 optical biosensors equipped with research-grade CM5 sensor chips (Biacore).
Immobilization of His4 mAb.
His4 mAb surfaces were prepared by using standard amine-coupling procedures (16) and HBS (Hepes-buffered saline: 20 mM Hepes, 150 mM sodium chloride, 0.005% P20, pH 7.4) as the running buffer. Flow cells were activated for 7 min by injecting 140 μl of 50 mM N-hydroxysuccinimide (NHS):200 mM ethyl-3(3-dimethylamino) propyl carbodiimide (EDC). Fifty microliters of a 10 μg/ml His4 mAb solution (in 10 mM sodium acetate, pH 5.0) was injected for 5 min at 10 μl/min, followed by a 70-μl injection of ethanolamine to block any remaining activated groups on the surface. Typically, this method resulted in ≈10,000 RU antibody immobilized. The stability of the antibody surface was demonstrated by the flat baseline achieved at the beginning (0–100 s) of each sensorgram.
Capture of ER by His4 mAb.
Receptor surfaces were prepared by using 20 mM sodium phosphate, 150 mM sodium chloride, 1 mM DTT, 3% (vol/vol) DMSO, pH 7.4 as the running buffer. ER (2 μM) in this buffer was injected at 10 μl/min for 5 min across immobilized His antibody, resulting in the capture of ≈1,800 RU receptor. The receptor/antibody complex was stable over the time course of each ligand-binding cycle. It is likely that ER is dimerized at the surface, providing enhanced stability due to an avidity effect.
Screening of Ligand Binding to ER.
In a screening format, 1 μM of each compound was injected at a flow rate of 50 μl/min over antibody-captured ER. An His4 mAb surface served as a reference. Ligands were allowed to associate with the receptor for 30 s and dissociation was monitored for 2 min. Ligand/receptor complexes were stripped from the antibody surface by two 18-s injections of 2:1 gentle Ab/Ag elution buffer:10 mM H3PO4.
Kinetic Analysis of Ligand/ER Interactions.
To collect detailed kinetic data, a concentration series of each compound was injected at a flow rate of 50 μl/min over antibody-captured ER and the His4 mAb reference surface at 20°C. Triplicate injections of each ligand concentration were analyzed in random order, with buffer blanks injected periodically for double referencing. For analysis of bisphenol A and prasterone, both the association and dissociation phases were 30 s; for diethylstilbestrol, 17β-estradiol, estriol, and estrone, the association and dissociation phases were 30 and 180 s, respectively; and for 4-hydroxytamoxifen, nafoxidine, and tamoxifen, the association and dissociation phases were 3 and 10 min, respectively. When necessary, buffer samples containing 2.9–3.1% (vol/vol) DMSO were injected to construct a DMSO calibration plot to correct for bulk refractive index shifts (17). The antibody surface was regenerated between binding cycles with two 18-s injections of 2:1 gentle Ab/Ag elution buffer:10 mM H3PO4. The complete kinetic analysis of each ligand/receptor interaction was performed three or more times over different His4 mAb surfaces. Data were collected at a rate of 2.5 Hz.
Data Processing and Analysis.
All sensorgrams were processed by using double referencing (18). First, the responses from the reference surface were subtracted from the binding responses collected over the reaction surfaces to correct for bulk refractive index changes. Second, the response from an average of the blank injections was subtracted to remove any systematic artifact observed between the reaction and reference flow cells. To obtain kinetic rate constants, corrected response data were then fit in CLAMP, a data analysis program that combines numerical integration and nonlinear global curve fitting routines (19). A kinetic analysis of each ligand/receptor interaction was obtained by fitting the response data to a reversible 1:1 bimolecular interaction model that includes a term for mass transport (Ao = A + B = AB) (20). The equilibrium dissociation constant (KD) was determined by the quotient kd/ka. Constants reported in Table 1 represent the average of three or more independent analyses of each receptor/ligand interaction.
Table 1.
Affinity and rate constants for estrogen receptor/ligand interactions
Interaction | ka (M−1 s−1)a | kd (s−1)a | KD (nM) from biosensor (ligand-binding domain)a | KD (nM) from literatureb (wild type, full-length) | KD (nM) from literaturec (ligand-binding domain) |
---|---|---|---|---|---|
Agonist ligand | |||||
prasterone | —d | —d | 4400 (2000) | 235–5400ef | 0.92,ik 0.3l |
bisphenol A | 1.3 (1) × 106 | 2.7 (1) × 10−1 | 210 (10) | 195–32000g | |
17β-estradiol | 1.3 (6) × 106 | 1.2 (2) × 10−3 | 0.9 (4) | 0.05–15.0h | |
estriol | 1.0 (2) × 106 | 1.3 (3) × 10−2 | 13 (5) | 1.4–9.3em | |
estrone | 1.1 (2) × 106 | 9 (2) × 10−3 | 8 (3) | 0.3–626en | |
diethylstilbestrol | 6.0 (7) × 106 | 5 (2) × 10−5 | 0.009 (3) | 0.04–11o | |
Antagonist ligand | |||||
tamoxifen | 4.5 (1) × 103 | 1.0 (1) × 10−3 | 220 (20) | 3.4–423p | 0.22l |
4-hydroxytamoxifen | 2.3 (1) × 103 | 4.1 (1) × 10−5 | 18 (1) | 0.1–96q | |
nafoxidine | 6.3 (2) × 103 | 1.6 (1) × 10−4 | 25 (2) | 0.3–125er |
a Experimental error is reported in parentheses and was obtained from three or more independent analyses using different biosensors, sample preparations, and receptor densities on the flow cell surfaces.
Range of literature values reported (KD, KI, IC50, EC50, and RBA) for full-length wild-type human estrogen receptor-α.
Range of literature values reported (KD, KI, IC50, EC50, and RBA) for wild-type human estrogen receptor-α ligand-binding domain.
Not determined.
From both human and nonhuman estrogen receptor-α.
Determined using a three Cys→Ser mutant ER construct.
Ref. 10.
Ref. 33.
Results
Ligand-Binding Assay.
A capturing system was used to monitor ligand binding to ER on the SPR biosensor (Fig. 2). First, ER was captured by His4 mAb immobilized on the sensor chip surface. Second, ligand was made to flow across the captured receptor, and binding events were monitored for several minutes. Third, the ligand/receptor complex was stripped from the antibody surface by a short injection of mild acid. An example of the primary data collected for the capture and ligand-binding assay is shown in Fig. 3. Injection of 2 μM ER across the His4 mAb surface for 5 min resulted in ≈1,800 RU of captured receptor. The receptor was bound tightly, as indicated by the minor loss in signal during the wash phase (≈450–600 s). At 600 s, ligands were injected across the captured receptor to collect binding data. Because the SPR responses are proportional to mass, ligand-binding signals are small in comparison to the large signal corresponding to the mAb capturing of ER. In this instance, an ≈100-fold mass difference between the receptor and the ligand exists, so an ≈100-fold difference in responses between the receptor-capturing step and the ligand-binding step is expected (16).
Figure 2.
Design of the receptor/ligand assay. His4 mAb was covalently immobilized on the biosensor surface, followed by capture of the estrogen-receptor construct (≈28 kDa) via its His tag. Compounds were injected across the surface, and the ER/ligand interaction was monitored. The ER/ligand complex was readily stripped from the antibody, and fresh receptor was captured before the next ligand-binding test.
Figure 3.
Sensorgrams of the complete antibody/receptor/ligand binding cycle. As noted in the figure, ER was made to flow over the anti-His4 mAb surface (yielding a response of ≈1800 RU), the surface was washed with buffer, ligand was injected over the captured receptor (yielding a response of ≈30 RU), and mild acid was injected over the surface to disrupt the receptor/antibody interaction. Reproducibility of the capturing assay is demonstrated by the overlay of 40 replicate binding cycles shown here in different colors.
After ligand binding to the captured receptor was monitored, the surface was washed with mild acid, stripping the captured ER/ligand complex from the antibody surface and returning the signal to baseline (t > 960 s). The data shown in Fig. 3 were obtained from 40 repeated cycles. The excellent overlay of these sensorgrams demonstrates the ability to capture reproducibly the same density of receptor, which is critical when comparing the responses generated by different ligands (or a concentration series of one ligand) binding to the receptor. Having demonstrated the reliability of receptor capture as an assay method, we could examine ligand binding with confidence that the receptor surfaces were identical.
Prasterone Equilibrium Analysis.
As an initial test for ligand binding, we monitored prasterone (288 Da) interacting with the receptor surface. Prasterone is a small ER agonist with a reported weak affinity of 0.2–5.4 μM (21, 22). Injecting a concentration series of prasterone (0.12–30 μM) across the captured ER yielded the sensorgrams shown in Fig. 4A. The concentration-dependent responses rapidly reach equilibrium and return to baseline within seconds, indicating a weak interaction between prasterone and the receptor. To extract a binding constant for this interaction, the responses at equilibrium were plotted against prasterone concentration and fit to a simple binding isotherm (Fig. 4B). To test the reproducibility of the assay, the entire analysis was performed by using nine different densities of captured receptor to yield an average KD of 4.4 ± 2.0 μM (Table 1).
Figure 4.
Interaction of weak-affinity binders with ER. (A) Representative sensorgrams obtained from injections of prasterone at concentrations of 0, 0.12, 0.37, 1.1, 3.3, 10, and 30 μM over ER captured on the His4 antibody surface. (B) Sensorgram responses at equilibrium (t ≈ 25 s) were plotted against prasterone concentration and fit to a simple binding isotherm to yield an equilibrium dissociation constant. (C) Representative sensorgrams (black lines) obtained from triplicate injections of bisphenol A at concentrations of 0, 0.037, 0.11, 0.33, 1.0, and 3.0 μM over ER captured on the anti-His4 antibody surface. Red lines depict the global fit of the data to a simple 1:1 bimolecular interaction model, yielding ka = 1.3 (1) × 106 M−1 s−1 and kd = 0.27 (1) s−1.
Bisphenol A Kinetics.
Bisphenol A is one of the smallest of the ER's agonist ligands and binds ER with a reported affinity of 0.2–32 μM (21, 23–26). Fig. 4C depicts triplicate injections of 0.037–3.0 μM bisphenol A (228 Da) to the receptor surface. The binding responses were reproducible and concentration-dependent. From the visual comparison of Fig. 4 A and C, however, it is evident that bisphenol A dissociates slower than prasterone from the receptor surface. In fact, the bisphenol A/receptor reaction is slow enough to provide sufficient information for the determination of kinetic rate constants. The binding responses were globally fit to a simple 1:1 interaction model (shown as red lines in Fig. 4C). To establish the reliability of the kinetic assays, the entire bisphenol A analysis was performed by using nine different densities of captured receptor (1.7–2.3 kRU) to yield ka = 1.3 (1) × 106 M−1 s−1 and kd = 0.27 (1) s−1. An equilibrium dissociation constant (KD) of 210 ± 10 nM was calculated from the ratio of the association and dissociation rates.
Ligand Screening.
To compare the binding of diverse compounds to ER, the biosensor assay was performed in a qualitative screening mode. In this assay, the panel of compounds shown in Fig. 1 was tested for receptor binding. All of the compounds were assayed at the same concentration (1 μM) to rank binding to ER by response intensity as well as by association and dissociation rates. Three compounds (testosterone, dexamethasone, and corticosterone) were included as controls in the analysis because they are not recognized by ER, even though their core structures resemble those of the estrogen metabolites (21, 26, 27). As shown in Fig. 5, these control compounds did not show any binding to ER. Receptor binding of the other nine compounds was evident, even for the weak binders, bisphenol A and prasterone.
Figure 5.
Screen of drug panel for binding to ER-α. Responses were generated from the injection of 1 μM each of non-estrogen agonists (green), estrogen agonists (red), antagonists, (blue), and control compounds (black).
The differences in binding kinetics of the non-estrogen agonists (prasterone, bisphenol A, and diethylstilbestrol) were dramatic. Although each of these ligands displayed rapid association to the ER surface, the dissociation rates varied tremendously. Prasterone and bisphenol A dissociated from the receptor within seconds (as expected from the results described in Fig. 4 A and C). Diethylstilbestrol, however, formed a stable complex, as indicated by its very slow dissociation from the surface during the washout phase. The greater response intensity and stable complex formation observed for diethylstilbestrol is consistent with it having a high affinity (0.04–11 nM, based on literature values) for human ER (21, 23–26, 28, 29).
The three estrogen metabolites, 17β-estradiol, estriol, and estrone, all displayed rapid association to ER, but differences in their respective dissociation rates. Visually comparing the kinetics for the estrogen metabolites illustrates the biosensor's ability to detect subtle differences in dissociation rates of ligands having similar core structures. In contrast, the antagonist ligands screened here (tamoxifen, 4-hydroxytamoxifen, and nafoxidine) all demonstrated relatively slow association to the receptor, but once bound, formed stable complexes.
High-Resolution Kinetic Analysis.
A detailed kinetic analysis for the agonists and antagonists was performed to determine the rate constants associated with each compound. Fig. 6 depicts the binding responses obtained for concentration series of 17β-estradiol, estriol, estrone, diethylstilbestrol, tamoxifen, and nafoxidine injected across the ER-α surface. From inspection, the differences in the six ligands' dissociation rates are apparent. Each of the binding responses shown in Fig. 6 were well described by a 1:1 interaction model. As shown in Table 1, the kinetic rate constants observed for the antagonists (2–6 × 103 M−1 s−1 for tamoxifen, 4-hydroxytomaxifen, and nafoxidine) were on average ≈500-fold slower than the agonist (1–6 × 106 M−1 s−1 for 17β-estradiol, estriol, estrone, and diethylstilbestrol) rate constants.
Figure 6.
Representative data sets (black lines) for kinetic analysis of ligand–ER interactions. The estrogen agonists 17β-estradiol (A) and estriol (B) were injected at concentrations of 0, 0.0041, 0.012, 0.037, 0.11, 0.33, and 1.0 μM for 60 s, and dissociation was monitored for 3 min. Another estrogen agonist, estrone (C), was injected at concentrations of 0, 0.69, 2.0, 6.2, 19, 56, and 170 nM for 60 s, and dissociation was monitored for 3 min. The non-estrogen agonist, diethylstilbestrol (D), was injected at concentrations of 0, 0.012, 0.037, 0.11, 0.33, and 1.0 μM for 30 s, and dissociation was monitored for 3 min. The antagonists, nafoxidine (E) and tamoxifen (F), were injected at concentrations of 0, 0.032, 0.063, 0.13, 0.25, and 0.50 μM for 3 min, and dissociation was monitored for 10 min. Red lines represent the global fits of the data to a 1:1 bimolecular interaction model. The kinetic parameters obtained from each interaction are reported in Table 1.
Selectivity Assays.
The results described to this point were obtained from the analysis of the α isoform of ER only. Current Biacore 2000 and 3000 instruments are capable of monitoring the interactions within four flow cells simultaneously. Therefore, to collect information on receptor selectivity, both α and β isoforms of ER were immobilized onto the same sensor chip, but within different flow cells. The data presented in Fig. 7 illustrate the differences observed when estriol was injected over both receptor surfaces simultaneously. It is clear from a visual inspection of the data that estriol dissociates from the α isoform faster than from the β isoform. Both data sets could be described by using a simple 1:1 interaction model yielding the following rate constants for each interaction: ka = 1.0 × 106 M−1 s−1, kd = 1.8 × 10−2 s−1 for α, and ka = 5.7 × 105 M−1 s−1, kd = 3.2 × 10−3 s−1 for β. The kinetics provide a detailed picture of the threefold difference in affinity observed for estriol binding to β (KD = 5.6 nM) and α (KD = 18 nM) isoforms of the receptor.
Figure 7.
Kinetic analysis of estriol binding to different estrogen-receptor isoforms. Estriol was injected at concentrations of 0, 0.019, 0.056, 0.17, 0.50, and 1.5 μM over captured α (A) and β (B) ER for 30 s, and dissociation was monitored for 6 min. Colored lines represent the global fits of the sensorgrams (black lines) to a 1:1 bimolecular interaction model. From the data shown here, the kinetic parameters obtained for each interaction are ka = 1.0 × 106 M−1 s−1, kd = 1.8 × 10−2 s−1, kd =18 nM for α and ka = 5.7 × 105 M−1 s−1, kd = 3.2 × 10−3 s−1, KD = 5.6 nM for β.
Discussion
The results presented here illustrate that it is possible to observe small ligands (<300 Da) binding to a captured receptor surface by using SPR biosensors. The use of a capturing system has several advantages over covalent immobilization of the receptor. Because the His tag is engineered into the receptor at a site spatially distant from the ligand-binding site, receptor immobilization does not interfere with ligand binding. Receptor molecules are homogeneously bound to the surface, thus minimizing surface heterogeneity. Capturing levels are reproducible and easily controlled. Disrupting the antibody/receptor interaction is simpler than determining regeneration conditions that effectively remove a tightly bound ligand from the receptor, yet leave the receptor undamaged. The immobilized antibody is robust under these conditions, for hundreds of receptor-capturing/ligand-binding cycles can be performed on a single antibody surface.
The validity and sensitivity of the biosensor assay was demonstrated by its ability to discriminate between estrogen-receptor ligands and nonligands (including the detection of prasterone as a ligand, even though it was screened at a concentration below its KD), as well as to yield equilibrium dissociation constants that fall within the range previously reported for each ligand/receptor pair (Table 1).
Prior functional and structural analyses of ligand-bound receptor provided the groundwork for understanding ER regulation by agonist and antagonist ligands: (i) the two ligand types bind to ER at the same site, and with similar affinities, but (ii) the receptor exists in different conformations when it is complexed with agonists or antagonists (10–14). Structural studies demonstrated that when an agonist is bound, the C-terminal helix of the estrogen-receptor ligand-binding domain folds back atop the ligand-binding pocket in a manner that facilitates coactivator binding and the subsequent activation of transcription. When an antagonist is bound, its bulky side chain prevents the C-terminal helix from occupying its normal packing site, and coactivator binding is not possible (11–12). Although the structural data provide a detailed snapshot of conformation states of the receptor, they do not provide any dynamic information on complex formation.
The biosensor analysis revealed clear mechanistic differences in how agonist and antagonist ligands bind to ER. As a group, agonists all displayed relatively fast association rate constants, which averaged around 2 × 106 M−1 s−1. In contrast, the antagonists possessed association rates that were nearly 500-fold slower, averaging 4.4 × 103 M−1 s−1. The slower association rates are consistent with conformational adaptation accompanying antagonist complex formation. It is likely that the antagonists recognize a conformation of the receptor that is normally low in population, leading to the observed slow association rate. Whether or not the divergence in rate constants observed for ER trends with other known agonist and antagonist ligands and other nuclear receptor systems is currently under investigation. We are also investigating how ligands bind ER in the presence of coactivator proteins (27, 30, 31).
By taking advantage of the multiple reaction surfaces available in the optical biosensor, we simultaneously examined ligand binding by the α and β isoforms of the receptor. Although estriol bound more rapidly to the α isoform, it also dissociated more rapidly, giving it an overall weaker affinity than for the β isoform. These results illustrate the important insights that can be obtained from binding kinetics rather than performing purely equilibrium-based measurements. The high resolution available with the biosensor may provide the basis for the design of ligands that specifically target only one receptor isoform, thereby increasing tissue selectivity and decreasing undesirable effects of new therapeutic agents.
Our results demonstrate that it is possible to detect small ligands binding to large proteins captured on the biosensor, as well as to obtain reaction rate and affinity information, even for weak binders. The biosensor assay is robust, requires no labels, and current instruments have a throughput of ≈100–200 assays per day. The kinetic information accessible with the biosensor offers new insight into receptor–ligand interactions, as well as new criteria for lead optimization.
Acknowledgments
This research was supported by National Science Foundation Grant NSF MCB 00-78143 (to D.G.M.) and National Institutes of Health Fellowship F32 DK10150 (to R.L.R.).
Abbreviations
- SPR
surface plasmon resonance
- ER
estrogen receptor
References
- 1.Rich R L, Day Y S, Morton T A, Myszka D G. Anal Biochem. 2001;296:197–207. doi: 10.1006/abio.2001.5314. [DOI] [PubMed] [Google Scholar]
- 2.Day Y S, Baird C L, Rich R L, Myszka D G. Prot Sci. 2002;11:1017–1025. doi: 10.1110/ps.4330102. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Myszka D G, Rich R L. Pharm Sci Technol Today. 2000;3:310–317. doi: 10.1016/s1461-5347(00)00288-1. [DOI] [PubMed] [Google Scholar]
- 4.Rich R L, Myszka D G. Curr Opin Biotechnol. 2000;11:54–61. doi: 10.1016/s0958-1669(99)00054-3. [DOI] [PubMed] [Google Scholar]
- 5.Gao H, Williams C, Labute P, Bajorath J. J Chem Inf Comput Sci. 1999;39:164–168. doi: 10.1021/ci980140g. [DOI] [PubMed] [Google Scholar]
- 6.Schapira M, Raaka B M, Samuels H H, Abagyan R. Proc Natl Acad Sci USA. 2000;97:1008–1013. doi: 10.1073/pnas.97.3.1008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Norris J D, Chang C, McDonnell D P. Ernst Schering Res Found Workshop. 2001;34:181–201. doi: 10.1007/978-3-662-04645-6_10. [DOI] [PubMed] [Google Scholar]
- 8.Grese T A, Cho S, Finley D R, Godfrey A G, Jones C D, Lugar C W, 3rd, Martin M J, Matsumoto K, Pennington L D, Winter M A, et al. J Med Chem. 1997;40:146–167. doi: 10.1021/jm9606352. [DOI] [PubMed] [Google Scholar]
- 9.Rosati R L, Da Silva Jardine P, Cameron K O, Thompson D D, Ke H Z, Toler S M, Brown T A, Pan L C, Ebbinghaus C F, Reinhold A R, et al. J Med Chem. 1998;41:2928–2931. doi: 10.1021/jm980048b. [DOI] [PubMed] [Google Scholar]
- 10.Gangloff M, Ruff M, Eiler S, Duclaud S, Wurtz J M, Moras D. J Biol Chem. 2001;276:15059–15065. doi: 10.1074/jbc.M009870200. [DOI] [PubMed] [Google Scholar]
- 11.Brzozowski A M, Pike A C, Dauter Z, Hubbard R E, Bonn T, Engstrom O, Ohman L, Greene G L, Gustafsson J A, Carlquist M. Nature (London) 1997;389:753–758. doi: 10.1038/39645. [DOI] [PubMed] [Google Scholar]
- 12.Shiau A K, Barstad D, Loria P M, Cheng L, Kushner P J, Agard D A, Greene G L. Cell. 1998;95:927–937. doi: 10.1016/s0092-8674(00)81717-1. [DOI] [PubMed] [Google Scholar]
- 13.Tanenbaum D M, Wang Y, Williams S P, Sigler P B. Proc Natl Acad Sci USA. 1998;95:5998–6003. doi: 10.1073/pnas.95.11.5998. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Eiler S, Gangloff M, Duclaud S, Moras D, Ruff M. Protein Expression Purif. 2001;22:165–173. doi: 10.1006/prep.2001.1409. [DOI] [PubMed] [Google Scholar]
- 15.Geoghegan K F, Dixon H B F, Rosner P J, Hoth L R, Lanzetti A J, Borzilleri K A, Marr E S, Pezzullo L H, Martin L B, LeMotte P K, et al. Anal Biochem. 1999;267:169–184. doi: 10.1006/abio.1998.2990. [DOI] [PubMed] [Google Scholar]
- 16.Jonsson U, Malmqvist M. Adv Biosensors. 1992;2:291–336. [Google Scholar]
- 17.Frostell-Karlsson A, Remaeus A, Roos H, Andersson K, Borg P, Hamalainen M, Karlsson R. J Med Chem. 2000;43:1986–1992. doi: 10.1021/jm991174y. [DOI] [PubMed] [Google Scholar]
- 18.Myszka D G. J Mol Recognit. 1999;12:279–284. doi: 10.1002/(SICI)1099-1352(199909/10)12:5<279::AID-JMR473>3.0.CO;2-3. [DOI] [PubMed] [Google Scholar]
- 19.Myszka D G, Morton T A. Trends Biochem Sci. 1998;23:149–150. doi: 10.1016/s0968-0004(98)01183-9. [DOI] [PubMed] [Google Scholar]
- 20.Myszka D G, He X, Dembo M, Morton T A, Goldstein B. Biophys J. 1998;75:583–594. doi: 10.1016/S0006-3495(98)77549-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Kuiper G G, Carlsson B, Grandien K, Enmark E, Haggblad J, Nilsson S, Gustafsson J A. Endocrinology. 1997;138:863–870. doi: 10.1210/endo.138.3.4979. [DOI] [PubMed] [Google Scholar]
- 22.Kloas W, Schrag B, Ehnes C, Segner H. Gen Comp Endocrinol. 2000;119:287–299. doi: 10.1006/gcen.2000.7521. [DOI] [PubMed] [Google Scholar]
- 23.Bolger R, Wiese T E, Ervin K, Nestich S, Checovich W. Environ Health Perspect. 1998;106:551–557. doi: 10.1289/ehp.98106551. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Barkhem T, Carlsson B, Nilsson Y, Enmark E, Gustafsson J, Nilsson S. Mol Pharmacol. 1998;54:105–112. doi: 10.1124/mol.54.1.105. [DOI] [PubMed] [Google Scholar]
- 25.Routledge E J, White R, Parker M G, Sumpter J P. J Biol Chem. 2000;275:35986–35993. doi: 10.1074/jbc.M006777200. [DOI] [PubMed] [Google Scholar]
- 26.Kuiper G G, Lemmen J G, Carlsson B, Corton J C, Safe S H, van der Saag P T, van der Burg B, Gustafsson J A. Endocrinology. 1998;139:4252–4263. doi: 10.1210/endo.139.10.6216. [DOI] [PubMed] [Google Scholar]
- 27.Jisa E, Dornstauder E, Ogawa S, Inoue S, Muramatsu M, Jungbauer A. Biochem Pharmacol. 2001;62:953–961. doi: 10.1016/s0006-2952(01)00731-6. [DOI] [PubMed] [Google Scholar]
- 28.Nikov G N, Eshete M, Rajnarayanan R V, Alworth W L. J Endocrinol. 2001;170:137–145. doi: 10.1677/joe.0.1700137. [DOI] [PubMed] [Google Scholar]
- 29.Labrie F, Labrie C, Belanger A, Simard J, Gauthier S, Luu-The V, Merand Y, Giguere V, Candas B, Luo S, et al. J Steroid Biochem Mol Biol. 1999;69:51–84. doi: 10.1016/s0960-0760(99)00065-5. [DOI] [PubMed] [Google Scholar]
- 30.Warnmark A, Almlof T, Leers J, Gustafsson J A, Treuter E. J Biol Chem. 2001;276:23397–23404. doi: 10.1074/jbc.M011651200. [DOI] [PubMed] [Google Scholar]
- 31.Wong C W, Komm B, Cheskis B J. Biochemistry. 2001;40:6756–6765. doi: 10.1021/bi010379h. [DOI] [PubMed] [Google Scholar]
- 32.Parker G J, Law T L, Lenoch F J, Bolger R E. J Biomol Screen. 2000;5:77–88. doi: 10.1177/108705710000500204. [DOI] [PubMed] [Google Scholar]
- 33.Sun J, Meyers M J, Fink B E, Rajendran R, Katzenellenbogen J A, Katzenellenbogen B S. Endocrinology. 1999;140:800–804. doi: 10.1210/endo.140.2.6480. [DOI] [PubMed] [Google Scholar]
- 34.Carlson K E, Choi I, Gee A, Katzenellenbogen B S, Katzenellenbogen J A. Biochemistry. 1997;36:14897–14905. doi: 10.1021/bi971746l. [DOI] [PubMed] [Google Scholar]
- 35.Schobel U, Frenay M, van Elswijk D A, McAndrews J M, Long K R, Olson L M, Bobzin S C, Irth H. J Biomol Screen. 2001;6:291–303. doi: 10.1177/108705710100600503. [DOI] [PubMed] [Google Scholar]
- 36.Ke H Z, Paralkar V M, Grasser W A, Crawford D T, Qi H, Simmons H A, Pirie C M, Chidsey-Frink K L, Owen T A, Smock S L, et al. Endocrinology. 1998;139:2068–2076. doi: 10.1210/endo.139.4.5902. [DOI] [PubMed] [Google Scholar]
- 37.Blair R M, Fang H, Branham W S, Hass B S, Dial S L, Moland C L, Tong W, Shi L, Perkins R, Sheehan D M. Toxicol Sci. 2000;54:138–153. doi: 10.1093/toxsci/54.1.138. [DOI] [PubMed] [Google Scholar]
- 38.Nijs M, Brassinne C, Coune A. Cancer Biochem Biophys. 1992;12:263–274. [PubMed] [Google Scholar]
- 39.Kraft K S, Ruenitz P C, Bartlett M G. J Med Chem. 1999;42:3126–3133. doi: 10.1021/jm990078u. [DOI] [PubMed] [Google Scholar]
- 40.Weatherman R V, Clegg N J, Scanlan T S. Chem Biol. 2001;8:427–436. doi: 10.1016/s1074-5521(01)00025-4. [DOI] [PubMed] [Google Scholar]
- 41.Carlson K E, Coppey M, Magdelenat H, Katzenellenbogen J A. J Steroid Biochem. 1989;32:345–355. doi: 10.1016/0022-4731(89)90206-9. [DOI] [PubMed] [Google Scholar]
- 42.Bindal R D, Katzenellenbogen J A. J Steroid Biochem. 1985;23:929–937. doi: 10.1016/0022-4731(85)90049-4. [DOI] [PubMed] [Google Scholar]