Dynamics of coregulator-induced conformational perturbations in androgen receptor ligand binding domain

Molecular and Cellular Endocrinology 341 (2011) 1–8

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Dynamics of coregulator-induced conformational perturbations in androgen receptor ligand binding domain Mikhail N. Zakharov a,1, Biju K. Pillai a,1, Shalender Bhasin a, Jagadish Ulloor a, Andrei Y. Istomin b, Chao Guo a, Adam Godzik b, Raj Kumar c, Ravi Jasuja a,⇑ a b c

Section of Endocrinology, Boston University School of Medicine, 670 Albany St., Boston, MA 02118, USA Sanford-Burnham Medical Research Institute, 10901 N Torrey Pines Rd, La Jolla, CA 92037, USA Department of Basic Sciences, Commonwealth Medical College, 501 Madison Avenue, Scranton, PA 18510, USA

a r t i c l e

i n f o

Article history: Received 13 January 2011 Received in revised form 24 February 2011 Accepted 2 March 2011 Available online 14 May 2011 Keywords: Androgen receptor Coactivator FRET Conformational dynamics SRC ARA70 D11

a b s t r a c t Androgen receptor (AR) coregulators modulate ligand-induced gene expression in a tissue specific manner. The molecular events that follow coactivator binding to AR and the mechanisms that govern the sequence-specific effects of AR coregulators are poorly understood. Using consensus coactivator sequence D11-FxxLF and biophysical techniques, we show that coactivator association is followed by conformational rearrangement in AR ligand binding domain (AR-LBD) that is enthalpically and entropically favorable with activation energy of 29.8 ± 4.2 kJ/mol. Further characterization of ARA70 and SRC3-1 based consensus sequences reveal that each coactivator induces a distinct conformational state in the dihydrotestosterone:AR-LBD:coactivator complex. Complementary computational modeling revealed that coactivator induced specific alterations in the backbone flexibility of AR-LBD distant from the site of coactivator binding and that the intramolecular rearrangements in AR-LBD backbone induced by the two coactivator peptides were different. These data suggest that coactivators may impart specificity in the transcriptional machinery by changing the steady-state conformation of AR-LBD. These data provide direct evidence that even in the presence of same ligand, AR-LBD can occupy distinct conformational states depending on its interactions with specific coactivators in the tissues. We posit that this coactivator-specific conformational gating may then dictate subsequent binding partners and interaction/affinity for the DNA-response elements. Ó 2011 Elsevier Ireland Ltd. All rights reserved.

1. Introduction Androgen receptor (AR) belongs to the nuclear hormone receptor superfamily which modulates diverse biological functions by ligand-induced alterations in gene expression (Quigley et al., 1995; Jenster et al., 1991, 1992, 1997; Brinkmann et al., 1989, 1992; Tan et al., 1988; Simental et al., 1991; Georget et al., 1999; Matias et al., 2000; Roy et al., 2001; Kuil et al., 1995; Bohl et al., 2005, 2007; Tyagi et al., 2000). Upon ligand binding, the receptor-ligand complex directs the transcription of androgen-regulated genes by the recruitment of coregulators (Roy et al., 2001; Abbreviations: AR, androgen receptor; DHT, 5-a-dihydrotestosterone; AF1, activation function 1; AF2, activation function 2; LBD, ligand binding domain; GST, glutathione S-transferase; FRET, fluorescent resonance energy transfer; TRFRET, time resolved FRET. ⇑ Corresponding author at: Boston University School of Medicine, Section of Endocrinology, Diabetes, and Nutrition, Boston Claude D. Pepper Older Americans Independence Center for Function Promoting Therapies, 670 Albany Street, Boston, MA 02118, USA. Tel.: + 1 617 6388829. E-mail address: [email protected] (R. Jasuja). 1 These authors contributed equally to this study. 0303-7207/$ - see front matter Ó 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.mce.2011.03.003

Gronemeyer et al., 2004) and subsequent association with androgen response elements. AR coregulators that are recruited by the liganded receptor can either enhance or attenuate its transactivation. Furthermore, abnormalities of coactivator binding and related gene expression have been linked to several disorders including androgen insensitivity syndrome and prostate cancer (He et al., 2006; Umar et al., 2005; Duff and McEwan, 2005). However, several fundamental aspects of co-activator interaction with AR remain unknown. In particular, the molecular and biophysical events that follow coactivator binding to AR and which influence AR-mediated transcription are poorly understood and were the subject of this investigation. Additionally, several inconsistencies, described below, exist in our understanding of the mode of interaction of coactivators with AR; the extant model that assumes a monophasic association of AR with its coactivator does not provide a good fit for the experimental data generated in cell culture models. This investigation was intended to resolve some of these inconsistencies in the existing models of coactivator:AR interaction, using state-of-the-art biophysical techniques. The coactivator proteins that interact with AR have been classified broadly into those containing FxxLF and those containing

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LxxLL motifs (Zhou et al., 2002; Bevan et al., 1999; Estebanez-Perpina et al., 2005; Chang and McDonnell, 2002; He and Wilson, 2003; Askew et al., 2007; van de Wijngaart et al., 2006; Dubbink et al., 2006; He et al., 1999, 2001, 2002; Hur et al., 2004). Consensus peptide sequences, typically 15-30 amino acid long encompassing distinct motifs including but not limited to FxxLF and LxxLL, have proven to be useful tools in dissecting out the steps in the AR signaling cascade and in identifying binding partners (Zhou et al., 2002; Chang and McDonnell, 2002; He and Wilson, 2003; van de Wijngaart et al., 2006; Dubbink et al., 2006; He et al., 1999, 2001; Hur et al., 2004; Zhou et al., 2010; Ozers et al., 2007; Dubbink et al., 2004). Previous reports assumed the interaction of co-activator peptides with AR to be a single-step monophasic process. Because the monophasic process did not provide an adequate fit of the experimental data, these reports then had to incorporate additional assumptions, such as cooperativity between the AR-LBD and coactivator interactions, in the model to fit the experimental data. Using a variety of refined biophysical tools that allowed us to deconvolute the process of AR:coactivator interaction, we show here that the interaction of co-activator with ARLBD is a biphasic process involving an initial association followed by conformational rearrangements. This comprehensive biphasic model incorporating the conformational rearrangements that follow the coactivator association step explains the inconsistencies in the earlier studies. We also used molecular modeling to examine the role of sequence-specificity in manifesting alterations in protein flexibility distant from the immediate coactivator binding site. Together, these data provide evidence that slight differences in the coactivator sequences result in significant conformational changes which then regulate the downstream interactions in the transcriptional machinery. Also, the application of these biophysical tools provided novel information about the kinetics and the thermodynamics of AR-LBD:coactivator interaction, which regulate the rates of conformational change and the kinetics of steroid hormone action. Finally using molecular modeling, we describe the intramolecular rearrangements in AR-LBD upon coactivator binding. 2. Materials and methods 2.1. Reagents The purified rat wild-type AR bearing the hinge and ligand binding domains (amino-acids 606-902, AR-LBD) tagged with GST and 6x Histidine (His) at the N-terminus and terbium labeled anti-GST antibody (8 chelates per antibody) were obtained from Invitrogen (Life Sciences Corp. Carlsbad, CA). Corning 384 well assay plates (No. 3676) were acquired from Fischer Scientific (Pittsburgh, PA). DHT was purchased from Sigma–Aldrich (St. Louis, MO). The coregulator peptides based on consensus sequences identified in phage display studies, labeled with fluorescein at the N-terminus, were obtained through Invitrogen (D11-FxxLF, ARA70, NCoRID2, NCoRID1 and SRC3-1 correspond to VESGSSRFMQLFMANDLLT, SRETSEKFKLLFQSYNVND, NLGLEDIIRKALMG, RTHRLITLADHICQIITQDFARN and ESKGHKKLLQLLTCSSDDR, respectively). The effective AR-LBD concentration was calculated from the specific activity provided in the characterization certificate without further purification. This construct has been previously characterized for its ligand binding affinity and coregulator binding, which are similar to those of the full-length receptor from LNCaP lysates (Ozers et al., 2007; Jasuja et al., 2009; Le et al., 2003). Consistent with previous report (Ozers et al., 2007), we confirmed that this AR-LBD protein specifically associated with coactivator upon DHT binding as shown in supplementary Fig. S1. Accordingly, the signal originates specifically from the fraction that is active and associates with the coregulators. 2.2. Reagents handling AR-LBD, fluorescent peptides and antibody conjugates were thawed on ice upon arrival, aliquoted and stored frozen (at 80 °C). For each experiment, once thawed, all AR-LBD dilutions were also performed on ice. All the experimental procedures were performed at room temperature unless otherwise described. 35 mM, 100 lM and 1 lM master stocks of DHT were prepared in DMSO by weight; parent stocks ranging from 1 nM to 100 lM in DMSO were prepared from those stocks by

serial dilutions. Stocks were kept at + 4 °C (frozen) and thawed at room temperature for the measurements. Special care was taken to keep final concentration of DMSO in the assay at 1% by preparing each respective concentration of DHT from the same parent stock. The titrations were performed in 50 mM TRIS in presence of 1 mM DTT and 15% glycerol by volume. 2.3. TR-FRET experiment to detect coactivator binding Steady state TR-FRET experiments were performed using a monochromator based microplate reader: Tecan Infinite M1000 (Tecan Group, Männedorf, Germany). The terbium chelate–donor was excited at 328 nm with 20 nm bandwidth. The donor emission was measured at 490 nm with 7 nm bandwidth. The fluorescent coactivator peptide (acceptor) emission was measured at 523 with 17 nm bandwidth. These settings allow the isolation of the first peak of the terbium emission and limit the amount of fluorescein emission that ‘‘bleeds through’’ into this measurement. The settings were determined by scanning excitation/emission wavelengths and optimizing the Z position for higher signal and bandwidths for less influence of fluorescein emission on terbium signal. Kinetic measurements were performed using Tecan Genios™ Pro, a filter based microplate reader. The donor was excited at 340 nm with 30 nm bandwidth filter. Tb emission was measured using 495 nm (10 nm bandwidth), fluorescein emission by 520 nm filter (20 nm bandwidth). Temperature was controlled and measured using Magellan™ software. Once the temperature equilibrated, data were collected after a delay of 2 min. On both instruments a 100 ls delay and subsequent 200 ls integration time was preset to eliminate the direct excitation of the fluorescein. FRET experiments were conducted in two modes, either by varying coregulator in saturating amounts of DHT (1 lM) or by varying DHT in excess amounts of coregulator (1 lM). The sensitized acceptor emission binding curves were followed by calculating the ratio of the acceptor emission to the donor emission. The binding curves for DHT titration were fit using regular sigmoidal dose–response curves (variable slope) from Origin (OriginLab, Northampton, MA) software package. Alternatively, the integrated intensity from sensitized emission was monitored at 520 nm. All the experiments were performed in triplicates and repeated at least twice unless otherwise noted. 2.4. Kinetic TR FRET studies The kinetics of coactivator D11-FxxLF peptide binding was done by using GENios™ Pro instrument (Tecan Group). In a 384 well plate, 20 ll solution (8 nM antiGSTab-Tb + 8 nM AR-LDB + 1 lM D11-FxxLF) was pre-incubated for 10 min. Subsequently, 20 ll of 2 lM DHT was injected to initiate the coactivator binding. In control wells, instead of DHT, 20 ll buffer was injected. The buffer addition was utilized to identify the mixing dead time of 2 s. The sensitized FRET emission was acquired through the 523 nm filter (17 nm bandwidth) with 340 nm (30 nm bandwidth) excitation. Upon the injection of 20 ll of DHT the TR-FRET was monitored for 600 cycles (30 ms/cycle). Pre-trigger baseline was collected for 300 ms before the DHT injection and cycles 10 to 600 were used for monitoring the kinetics. This experiment was done at different temperatures (290–307 °K) using the Peltier stage on the instrument with varying peptide concentrations. The pseudo-first-order rate constants were calculated for each concentration of peptide at each temperature by using first order exponential rise fit of GraphPad Prism (GraphPad Software, La Jolla, CA). The activation energy (Ea) is calculated from the slope (Ea/R) of the Arrhenius plot (versus inverse of absolute temperature) (Eq. (1)):

lnðKÞ ¼ lnðAÞ 

Ea RT

ð1Þ

2.5. Measurement of thermodynamic parameters associated with coactivator binding We constructed Van’t Hoff plots from the temperature dependence of dissociation constant. These plots allow for the examination of thermodynamic parameters that facilitate the binding of coactivator peptide to the AR-LBD. TR-FRET experiment was set up with coactivator concentration varying from 0 to 5 lM in excess of DHT as described in Section 2.3. Separate TR-FRET experiment was setup in absence of DHT in order to correct for FRET between donor and acceptor in solution. The dissociation constant, Kd was obtained as the result of the non-linear curve fitting to the exact dose–response equation for 2 stage binding model (Eq. (S1) in the Supporting Material). Measurement was repeated at different temperatures (15–42 °C). The thermodynamic parameters including free energy change (DG), enthalpy change (DH), and entropy change (DS) were derived from standard Van’t Hoff plot. The Kd values at different temperatures were used to derive the DG using the Gibb’s free energy relationship (Eq. (2)):

G ¼ H  TS ¼ RT; lnðK a Þ

ð2Þ

where R is the universal gas constant and T is the absolute temperature, Ka = 1/Kd association constant. The values of ln(Ka) were plotted against the inverse of absolute temperature to generate Van’t Hoff’s plot. The enthalpy change (DH) and

M.N. Zakharov et al. / Molecular and Cellular Endocrinology 341 (2011) 1–8 entropy change (DS) were calculated from the slope and y-intercepts, respectively. Overall equilibria are described by Eq. (3) (Hur et al., 2004) and regulated by the rate constants of each step: Rapid

Slow

L : AR þ coac $ L : AR : coac $ L : AR : coac

3

A

ð3Þ

2.6. AR backbone flexibility molecular simulations to capture structural differences Alteration in the flexibility of the protein backbone is computed by analyzing a network of covalent and noncovalent interactions within a protein calculated by FIRST algorithm (Jacobs et al., 2001). Initial protein structure is obtained using the Protein Database (PDB). Subsequently, FIRST approach is employed for each conformer to identify a set of hydrogen bonds and salt bridges using certain cutoff energy. Rigid cluster identification and analysis is employed to compute residuespecific flexibility measure. In order to eliminate the cutoff energy parameter from consideration, the analysis is repeated over a range of its values and thermodynamically weighted averaging of the flexibility is performed. Sensitivity to precise topology of the hydrogen bond network is eliminated by repeating the entire analysis for each conformer and averaging the flexibility results.

3. Results

B

3.1. D11-FxxLF coactivator peptide binding induces conformational rearrangement in the ternary complex with AR-LBD FRET is a well-characterized technique to monitor protein– protein interactions and to characterize changes in global conformation. To enhance the sensitivity when donor and acceptor fluorescence lifetimes are distinct (in the current study, Tb: 400 ls; fluorescein: 4 ns), time-resolved FRET measurements were performed. Accordingly, a delay time (longer than acceptor’s direct emission lifetime) of 100 ls was introduced to eliminate any contribution from the direct excitation of fluorescein (acceptor) to the collected fluorescence. This modality provided a sensitive way to monitor the steady-state binding and time-dependent conformational changes induced by coactivator association. Kinetics of peptide binding to AR-LBD was monitored as described in Section 2.4. The sensitized emission signal at 520 nm upon DHT injection into a mixture of AR-LBD and D11FxxLF is shown in Fig. 1A. In control experiment, buffer was injected instead of DHT to confirm the drop of intensity by dilution (lower curve in Fig. 1A). The observable change in signal (upper curve) was fitted to an exponential rise (0.21 ± 0.02 s1). To examine if the process was monophasic, fit was extrapolated back to the injection time (t = 0). We found that there was a significant component of FRET faster than the detection time. This signal could either originate from a faster phase of conformational rearrangement or from the initial conformation of coactivator bound form which relaxes into a secondary conformational state. The DHT on rate ( > 30 s1) (Jasuja et al., 2009) and DHT-induced conformational changes (30 s1) were significantly faster than the observed rates of sensitized FRET. To examine if the FRET kinetic curves included any component from the diffusional transfer to D11-FxxLLF, we performed kinetic experiments in the presence of increasing D11-FxxLF concentrations (50 nM to 1 lM). The rate constant for the FRET was found to be independent of coactivator peptide concentration (Fig. 1B) ruling out diffusion as a possible contributor. These findings therefore indicate that the FRET increases originated from the intra-complex conformational rearrangement. 3.2. The energetic characteristics of the coactivator binding are best described by a two stage binding model As discussed earlier, previous studies that assumed a monophasic model, utilized assumptions of cooperativity and Hill equation to fit the coactivator association data while maintaining the inference that stoichiometry is 1:1(He and Wilson, 2003). The combination of steady-state and kinetic data allowed us to ascertain that

Fig. 1. Interaction of AR-LBD with DHT. (A) The change of emission at 520 nm when 20 lL of 2 lM DHT was injected into a solution containing 20 lL of a mixture of 8 nM AR-LBD, 8 nM Tb antibody, and 500 nM coactivator peptide (upper curve). Data were smoothed by Savitzky–Golay 5-point filter. To calculate rate constant, the kinetic traces were fit by a first order exponential rise curve using the nonlinear regression curve fit (kconf = 0.21 ± 0.02 s1 at room temperature). Injection happened at t = 570 ms, measurement is shown starting at t  1.8 s, where 2 s is dead time of mixing. Lower curve is a negative control generated using buffer injection. Upper curve fit is extrapolated back to the injection time (t = 0) to elicit that the sensitized FRET is not a monophasic process. (B) Independence of the reaction rate, calculated as described above, on the coactivator concentration. All measurements were done at room temperature. The results are representative of three to five independent experiments performed in duplicates. Each data point is the mean of all replicates and error bars represent standard error of the mean.

coactivator:AR-LBD association is not a single step simple bimolecular reaction. Binding equations derived in this study from the law of mass action (Supporting material S1), where binding and conformational rearrangement were explicitly accounted for, allowed much better data fits without the assumption of cooperativity. The experiments were conducted in a plate reader equipped with Peltier stage that allowed alteration of experimental temperature. By monitoring steady-state association at varying temperatures, Van’t Hoff plots were constructed to derive enthalpic and entropic contributions to coactivator interactions. The sensitized FRET emission for different temperatures is shown in Fig. 2. Experiments are performed with varying coactivator concentration in excess of DHT. Necessary corrections were applied. After this adjustment, the data (Fig. 2) were fit by Eq. (S1), using parameters from (Hur et al., 2004) as a starting point for the fits. After this adjustment the dissociation constant Kd for coactivator binding was found to be 484 ± 5 nM at room temperature, which is consistent with (Ozers et al., 2007), using similar constructs. Van’t Hoff

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A

±

Fig. 2. Evaluation of the steady state energetics of peptide binding to AR-LBD. The dose–response curves for D11-FxxLF coactivator titration change with temperature. Fluorescein labeled coactivator was titrated against 5 lM DHT, 10 nM AR-LBD GST tagged with 10 nM Tb-anti-GST antibody in a 384 well plate. Upon titration, the plate was incubated for 45 min. TR-FRET was measured at 520 nm at temperatures ranging from 300 to 315 °K. Parallel titration was run in the absence of DHT to correct for the diffusion-enhanced FRET. Difference between the acceptor emission at 520 nm in the absence and the presence of DHT is plotted against D11 concentration. Each data point is a mean of 3 replicates. Data were fit using a twostage binding model (Eq. (S1)). (inset) The temperature dependence of the equilibrium constant. Natural logarithm of the association constant was plotted against the inverse temperature to derive enthalpy change (DH) and entropy change (DS) from the slope and intercept of the linear fit to the Van’t Hoff plot, respectively. DH was calculated to be 9.5 ± 1.9 kJ/mol and DS 87.3 ± 7.1 J/(K mol).

plot was generated from the binding isotherms (Fig. 2, inset). The linear regression fits of the Kd dependence on temperature allowed us to find the entropic and enthalphic contributions: DH = 9.5 ± 1.9 kJ/mol and DS = 87.3 ± 7.1 J/(K mol), respectively. These values suggest that overall coactivator association is both enthalpically (decreased energy of products) and entropically favorable (increased overall entropy of system). Since these are steady state calculations, the free energy, enthalphy and entropy changes include contributions from both D11-FxxLF binding and conformational rearrangement after association. Another important parameter that regulates the rates of conformational change in protein systems is activation energy barrier. Accordingly, the activation energy of coactivator-induced rearrangement of the AR-LBD complex was determined by Arrhenius analysis of coactivator binding. The time dependent TR-FRET experiments were conducted at 6 different temperatures ranging from 290 °K to 307 °K T (Fig. 3A), and in the excess of D11-FxxLF coactivator (1 lM) premixed with 8 nM AR-LBD and 8 nM Tb-donor conjugate. The mixture was equilibrated at each temperature for 30 min before 1 lM DHT, maintained at the same temperature, was injected. The temporal evolution of conformational change was followed and three representative curves are shown in Fig. 3A. The rate constant kconf of the coactivator induced rearrangement increased at higher temperatures. The Arrhenius plots were constructed to examine the relationship between ln(kconf) and the inverse temperature (Fig. 3B). The activation energy barrier of coactivator-induced rearrangement of AR-LBD was found to be 29.8 ± 4.2 kJ/mol. Together, the steady state and time resolved data demonstrate that coactivator interaction include at least two discrete steps; binding and conformational relaxation within the ternary complex. While we cannot fully exclude the possibility of additional phases, the kinetic and steady-state FRET data are accurately and adequately fit by a parsimonious two state model. Use of appropriately derived equations based on the two phase model

B

Fig. 3. Arrhenius analysis of the coactivator binding. (A) The change in emission at 520 nm upon DHT injection, measured at different temperatures. 20 lL of DHT (1 lM) was injected into the assay plate containing 20 lL of a mixture containing 8 nM Tb labeled anti GST antibody (donor), 8 nM GST-tagged AR, and 500 nM fluorescein labeled D11-FxxLF (acceptor). The donor was excited at 340 nm and the FRET signal was monitored at 520 nm for the acceptor emission. Data are smoothed by the Savitzky–Golay 5-point filter. The assay was conducted at different temperatures and the fluorescence kinetic trace was fit by the first order exponential rise using non-linear curve fit. Exemplary curves at 3 temperatures are offset vertically for clarity. (B) Arrhenius plot of the peptide D11-FxxLF binding and the rate of peptide-induced conformational change. The logarithm of the observed rate constant for the peptide-induced conformational changes (kconf) was plotted against inverse of the temperature. The activation energy, Ea (29.8 ± 4.2 kJ/ mol) was estimated from Arrhenius equation k = A exp(Ea/RT). Data points represent the mean and SEM of 3 to 5 independent measurements.

also obviates the need to assume cooperativity in known stoichiometry of 1:1 in these systems. 3.3. ARA70, SRC3-1 and D11-FXXLF based coactivator peptides induce distinct conformations in AR-LBD It has long been speculated that cell and tissue selectivity of androgen action is caused by differences in coactivator expression patterns. We examined if the coactivator sequences belonging to two major families LXXLL and FXXLF induce distinct conformations in solution. The high sensitivity of the efficiency of resonance energy transfer allowed us to determine separation between fluorophores, thus characterizing the conformational change. An independent titration of DHT was performed to monitor the quenching of Tb emission (Fig. 4A) and to derive the absolute quenching efficiency (E) in Eq. (S4). From these parameters, the

M.N. Zakharov et al. / Molecular and Cellular Endocrinology 341 (2011) 1–8

A

3.4. Computational modeling of AR-LBD backbone flexibility show long-range coactivator-specific rearrangements distant from the binding site

Demission D11 (RFU) x10 -4

3.6

3.4

3.2

3.0 1E-4

1E-3

0.01

0.1

1

10

100

1000 10000

[DHT](nM)

B

4

4x10

3x10

Distance, A

Acceptor Intensity (RFU)

110

4

100 90 80

D11Fxx

2x10

5

LFARA70

SRC3-1

4

1E-3

0.01

0.1

1

10

100

1000

DHT (nM) Fig. 4. Evidence of different conformational changes occurring upon interaction of different physiologically relevant coactivators. (A) Terbium chelate emission quenching in the process of coactivator binding. Donor emission change (Demission D11) vs. DHT concentration in presence of 5 nM GST-tagged AR-LBD, 500 nM coactivator D11-FxxLF, and 5 nM antibody is shown. Donor was excited at 328 nm (bandwidth 20 nm) and donor emission was monitored at 490 nm (bandwidth 7 nm). Experiment was performed at room temperature. (B) Fluorescence intensity of the acceptor change vs. concentration of DHT. Experiment is done in presence of 5 nM GST-tagged AR-LBD, 500 nM of each of the coactivators, and 5 nM Tb antibody. Emission for D11-FxxLF (squares), ARA70 (circles), SRC3-1 (triangles) at 520 nm is plotted vs. concentration of DHT. Inset shows effective distances between Tb-labeled GST antibody (donor) and fluorescein-labeled coactivator peptides (acceptor) for different peptides.

effective distance between the Tb-donor and D11-FxxLF acceptor was found to be 91 Å. From the published expression pattern of coactivators in NURSA, we identified that (Mangelsdorf, 2007) ARA70 and SRC3-1 display clearly distinct relative expressions between the skeletal muscle and prostate. ARA70 possesses an FxxLF motif with a flanking sequence that is different from D11-FxxLF (a consensus peptide representing SRC-1, GRIP1, AIB-1) containing FxxLF motif obtained from a phage screen (He et al., 2002), while SRC3-1 contains an LxxLL motif. Interestingly, we found that the sensitized emissions for D11-FxxLF, ARA70, and SRC3-1 elicit significantly different saturation values, reflecting differences in FRET even though they are coupled with identical donor/acceptor pairs (Fig. 4B). These data provide direct evidence that effective distances between donor and acceptor differ for different consensus peptides, and therefore support the inference that distinct conformations are induced by these consensus peptides from coactivator classes (Fig. 4B insert).

Protein backbone flexibility computations are an important tool to examine the alterations in the equilibrium distribution of protein conformations. The intrinsic conformational flexibility parameters have long been recognized as the contributors to the protein function and are calculated by relaxing the atomic environment starting from the static crystal structure. While these calculations may not directly explain the origin of the differences in the solution conformations, they provide complementary characterization of the perturbations in the coactivator bound states of AR-LBD. Instead of overlaying and limiting the analysis to side chain perturbations, calculations were performed to examine alteration in flexibility of the protein backbone which may modulate the subsequent binding partners. We superimposed the DHT-bound AR-LBD crystal structure on the structure of AR-LBD bound to DHT plus LxxLL motif (Fig. 5A). Fig. 5B shows the backbone flexibility profile calculated for the following structures: (i) AR-LBD with only DHT bound (PDB id: 1T7T); (ii) AR-LBD with DHT and LxxLL bound (PDB id: 1T7F); (iii) AR-LBD with DHT and FxxLF bound (PDB id: 1T7R) (Hur et al., 2004), as described in methods section. Results are shown in Fig. 5B by black, red and green curves, respectively. The backbone flexibility analysis shows that even the residues that are distant from the immediate binding pocket are perturbed in a sequence specific manner subsequent to the coactivator binding. The computations revealed several distinct differences in the modes of LxxLL and FxxLF interactions. The backbone flexibility of many residues directly interacting with the coregulator (indicated by vertical lines in the figure) was reduced upon coactivator binding. Interestingly, the residues – 894, 897, and 898 – located in helix 12, displayed lower flexibility in DHT and DHT/LxxLL bound state when compared to the DHT/FxxLF bound state. Within the computational constraints of modeling, it appears that the binding of FxxLF not only involved these residues but also resulted in a structural distortion that freed them, thereby increasing their flexibility. For residues 683–695, 850–863, 869–880, the flexibility was the greatest in the DHT-only bound state and decreased upon binding of either of the two coactivators. In contrast, the flexibility of residues 843–848 was unaffected by the binding of LxxLL compared to DHT alone, but was significantly decreased upon binding of FxxLF. Together with the experimental evidence of distinct perturbations in the AR-LBD conformations, backbone flexibility calculations demonstrated that not only flexibility profile in the vicinity of the coactivator binding pocket was altered but the residues distant from the pocket also showed coactivator sequencespecific conformational rearrangement.

4. Discussion The present study, utilizing state-of-the-art biophysical tools, uncovered several novel aspects of the coactivator interaction with AR. First, our data provide evidence that coactivator:AR-LBD association is a biphasic process. The kinetics and thermodynamics of coactivator interaction with AR are best described by a biphasic model in which the data fits explicitly incorporate the binding and conformational rearrangement steps. Further, we find that, in solution, coactivators induce sequence-specific perturbations distant from the binding pocket in AR-LBD. These distinct conformational states and associated alterations in backbone flexibility may then regulate the downstream components of transcriptional machinery including DNA response elements in tissues. D11-FxxLF coactivator binding is described by a 2-phase model in which an initial association of coactivator with AR is followed by

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Fig. 5. The molecular modeling was performed to characterize the intramolecular alterations in conformational flexibility in the AR backbone that were associated with the coactivator binding. Molecular simulation highlights the difference between conformations assumed by AR upon binding to LxxLL coactivators in contrast to that assumed upon binding to FxxLF coactivators. (A) Superposition of the models of the two AR LBD crystal structures: one with DHT bound only (pale green, PDB id: 1T7T) and another with DHT + LxxLL(D11) bound (light pink, PDB id: 1T7F). Side chains at the coregulator binding interface are shown as sticks; side chains that significantly changed conformation are highlighted by green and red coloring. (B) Predicted AR LBD backbone flexibility profiles in the absence and presence of coactivators. DHT only, PDB id: 1T7T (black); DHT + LxxLL, PDB id: 1T7F (red), DHT + FxxLF, PDB id: 1T7R (green). Horizontal lines show helices that are in contact with the coactivator, and vertical lines show individual important residues. Thus, coactivator interaction with AR was associated with perturbations in the AR backbone distant from the site of coactivator association. Furthermore, the intramolecular rearrangements in the AR upon binding to LxxLL coactivators and FxxLF coactivators were different. These data provide evidence of sequence specificity in the coactivator-AR interaction and support the inference that coactivators impart specificity in the transcriptional machinery by inducing rearrangements and altering the flexibility of the regions distant from the immediate binding pocket. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)

a conformational rearrangement. By following kinetics of TR-FRET data, we find that rapid binding is followed by a rearrangement within the ternary complex (0.21 ± 0.02 s1). By performing kinetic measurements in varying D11-FXXLF peptide concentration, we confirmed that sensitized emission is neither diffusion limited process nor involved a convolution of the coactivator binding step. Increasing peptide concentration (50 nM to 1 lM) in excess of the DHT (5 lM DHT with 5 nM AR-LBD) did not alter the rates of sensitized emission. These data provide further evidence that the sensitized FRET is the result of intra-molecular conformational change. This study also resolves an apparent inconsistency in previous reports (He and Wilson, 2003; Ozers et al., 2007) where steady state TR-FRET and isothermal titration calorimetry (ITC) data fits

for the coactivator association with AR-LBD were performed by varying the Hill slope. The data model that utilizes variable slope assumes cooperative behavior and therefore is not appropriate for this system since the coactivator:AR-LBD association stoichiometry is 1:1. In the present study we demonstrate that by rederiving equations to explicitly account for the two steps without the assumption of cooperativity, we are able to consistently fit the data while constraining the stoichiometry to 1:1. Coactivator interaction data obtained using surface plasmon resonance techniques are also consistent with a two-stage model (Hur et al., 2004). Temperature dependence of steady state binding isotherms demonstrated that the D11-FXXLF coactivator motif binding process is both enthalpically and entropically favored. The transition state of conformational rearrangement within the AR-LBD:D11-

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FxxLF complex is associated with an activation energy barrier of 29.8 ± 4.1 kJ/mol. These data suggest that overall, this process is energetically favored. It is well known that tissues display distinct coactivator expression profiles. Motivated by the evidence that D11-FxxLF caused a structural rearrangement, we searched the Nuclear Receptor Signaling Atlas (NURSA) database for AR coactivator protein expression levels in the prostate and the skeletal muscle. Two specific coactivators, ARA70 and SRC3-1, whose expression was strikingly regulated in a tissue-specific manner, were selected to further examine perturbations in AR-LBD. Interestingly, we find that peptides based on the consensus sequences derived from ARA70 and SRC3-1 induce distinct conformational states in the DHT:AR-LBD:coactivator complex. The steady-state data demonstrates that AR-DLBD:coactivator interactions follow an ‘‘induced-fit’’ mechanism where the conformation of the complex is formed after coactivator recruitment. However, differences in the backbone flexibility analysis of the ternary complexes suggest that there are distinct conformational ensembles available for the binding partners depending on the co-activator bound to the receptor. These differences, while difficult to capture experimentally (primarily accessible by NMR, limited to smaller sequences), can elicit profound functional consequences in proteins with multiple binding partners like AR. These data raise an interesting possibility that although the receptor may be occupied by the same ligand in multiple tissues, the transcriptionally active conformation could be distinct, depending on the relative coactivator expression profile within those tissues. This may afford an additional level of tissue-specific modulation of downstream steps, including the response element association. The inferences from experiments that use coactivator-based consensus peptides and purified LBD, such as those used in this study, are constrained by the caveat that these may not fully reflect the interactions of full length proteins. The isolation of full length AR or the AR-LBD in an absence of the ligand has been proven difficult; consequently, the crystal structure of unliganded AR-LBD has not been determined. Nonetheless, consensus sequences based on the coregulator peptides have served as powerful tools to elucidate the signaling events associated with steroid hormone receptors (He and Wilson, 2003; Ozers et al., 2005, 2007). For example, the studies using FxxLF- and LxxLL-containing peptides and AR-LBD have yielded insights into the specificity of the binding (Chang and McDonnell, 2002). Subsequent studies, where charged residues, flanking the consensus motif were mutated, demonstrated that LxxLL and FxxLF motif interactions with steroid hormone receptors are a coupled response of oppositely charged residues flanking the motifs and charge clusters bordering AF2 (He and Wilson, 2003). A more recent study (Ozers et al., 2007) utilized fluorescently labeled peptides to demonstrate that consistent with the in vivo and cellular data, hydroxyflutamide bound mutant T877A AR-LBD interacts with coactivators differently than the wild type. Similarly, LxxLL-containing peptides have been used to study coactivator docking on the ER (Chang et al., 1999; Paige et al., 1999; Norris et al., 1999; Hall et al., 2000; McDonnell et al., 2000). Thus, a variety of cellular, biophysical and molecular studies have established the utility and appropriateness of the use of coactivator peptide to study such interactions. Importance of ligand and coactivator-induced conformational perturbations has been identified in other steroid hormone receptors (Margeat et al., 2001; Germain et al., 2009; Tamrazi et al., 2005; Duda et al., 2004; Pfaff and Fletterick, 2010). Tamrazi et al. (2005) reported that a ternary complex of E2:ER:coactivator peptide elicits distinct conformational differences in the tripartite complex, which correlated with the transcriptional output. Similarly, in HNF-4a, the presence of both the ligand and the coactivator was required to attain an active conformation (Duda et al., 2004). Our data on the interactions of AR with coactivators further

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highlight the significance of functionally important conformational changes in these interactions. It has been reported that over expression of SRC3 alone can accelerate the prostate cancer progression and amplify the response to circulating androgens (Henke et al., 2004; Zhou et al., 2005). These in vivo and in vitro data suggest that changes in the tissue-specific expression of coactivator proteins in disease states could modify AR activity. Further study of coactivator binding process together with subsequent steps of AR-mediated transcriptional activation including residence time on DNA response elements should allow us to develop an integrated numerical model of a multi-stage, AR signal amplification. In conclusion, coactivator binding process is not a single step process, it involves binding and reorganization. AR occupies distinct conformational states even in the presence of the same ligand depending on the presence of specific coactivator proteins. We posit that the resulting distinct conformations of the protein complexes may dictate tissue specificity by altering interaction/affinity for the downstream proteins and DNA-response elements. The net effect of this regulation is manifested in the amplification of the transcriptional output. Acknowledgements The work was supported by Evans Foundation grant 01346002591, NIH grant U01 AG014369-S, ACS grant IRG-72001-33-IRG, NIH grant R01 AG037193, NIH grant P20 GM076221 (JCMM). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.mce.2011.03.003. References Askew, E.B., Gampe Jr., R.T., Stanley, T.B., Faggart, J.L., Wilson, E.M., 2007. Modulation of androgen receptor activation function 2 by testosterone and dihydrotestosterone. J. Biol. Chem. 282, 25801–25816. Bevan, C.L., Hoare, S., Claessens, F., Heery, D.M., Parker, M.G., 1999. The AF1 and AF2 domains of the androgen receptor interact with distinct regions of SRC1. Mol. Cell. Biol. 19, 8383–8392. Bohl, C.E., Gao, W., Miller, D.D., Bell, C.E., Dalton, J.T., 2005. Structural basis for antagonism and resistance of bicalutamide in prostate cancer. Proc. Natl. Acad. Sci. U.S.A. 102, 6201–6206. Bohl, C.E., Wu, Z., Miller, D.D., Bell, C.E., Dalton, J.T., 2007. Crystal structure of the T877A human androgen receptor ligand-binding domain complexed to cyproterone acetate provides insight for ligand-induced conformational changes and structure-based drug design. J. Biol. Chem. 282, 13648–13655. Brinkmann, A.O., Jenster, G., Kuiper, G.G., Ris, C., van Laar, J.H., van der Korput, J.A., Degenhart, H.J., Trifiro, M.A., Pinsky, L., Romalo, G., 1992. The human androgen receptor: structure/function relationship in normal and pathological situations. J. Steroid Biochem. Mol. Biol. 41, 361–368. Brinkmann, A.O., Klaasen, P., Kuiper, G.G., van der Korput, J.A., Bolt, J., de Boer, W., Smit, A., Faber, P.W., van Rooij, H.C., Geurts van Kessel, A., 1989. Structure and function of the androgen receptor. Urol. Res. 17, 87–93. Chang, C., Norris, J.D., Gron, H., Paige, L.A., Hamilton, P.T., Kenan, D.J., Fowlkes, D., McDonnell, D.P., 1999. Dissection of the LXXLL nuclear receptor-coactivator interaction motif using combinatorial peptide libraries: discovery of peptide antagonists of estrogen receptors alpha and beta. Mol. Cell. Biol. 19, 8226–8239. Chang, C.Y., McDonnell, D.P., 2002. Evaluation of ligand-dependent changes in AR structure using peptide probes. Mol. Endocrinol. 16, 647–660. Dubbink, H.J., Hersmus, R., Pike, A.C., Molier, M., Brinkmann, A.O., Jenster, G., Trapman, J., 2006. Androgen receptor ligand-binding domain interaction and nuclear receptor specificity of FXXLF and LXXLL motifs as determined by L/F swapping. Mol. Endocrinol. 20, 1742–1755. Dubbink, H.J., Hersmus, R., Verma, C.S., van der Korput, H.A., Berrevoets, C.A., van Tol, J., Ziel-van der Made, A.C., Brinkmann, A.O., Pike, A.C., Trapman, J., 2004. Distinct recognition modes of FXXLF and LXXLL motifs by the androgen receptor. Mol. Endocrinol. 18, 2132–2150. Duda, K., Chi, Y.I., Shoelson, S.E., 2004. Structural basis for HNF-4alpha activation by ligand and coactivator binding. J. Biol. Chem. 279, 23311–23316. Duff, J., McEwan, I.J., 2005. Mutation of histidine 874 in the androgen receptor ligand-binding domain leads to promiscuous ligand activation and altered p160 coactivator interactions. Mol. Endocrinol. 19, 2943–2954.

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