jbc papers in press. published on april 19, 2004 as ... · jamie m. r. moore1, sarah j. galicia1,4,...

Quantitative Proteomics of the Thyroid Hormone Receptor Coregulator

Interactions

Jamie M. R. Moore1, Sarah J. Galicia1,4, Andrea C. McReynolds1, Ngoc-Ha

Nguyen1, Thomas S. Scanlan1,2, R. Kiplin Guy1,2,3

Departments of Pharmaceutical Chemistry1 and Molecular & Cellular

Pharmacology2, University of California at San Francisco, Genentech Hall,

Mission Bay San Francisco, 600 16th Street Box 2280 CA 94143-2280

3To whom reprint requests should be addressed: Departments of Pharmaceutical

Chemistry1 and Molecular & Cellular Pharmacology2, University of California at

San Francisco, Genentech Hall, Mission Bay San Francisco, 600 16th Street Box

2280 CA 94143-2280, [email protected]

4Current Address:

600 University Avenue Samuel Lunenfeld Research Institute Mount Sinai

1

JBC Papers in Press. Published on April 19, 2004 as Manuscript M403453200

Copyright 2004 by The American Society for Biochemistry and Molecular Biology, Inc.

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Hospital Toronto, Ontario M5G 1X5

Running Title: thyroid hormone receptor-coregulator interactions

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SUMMARY

The thyroid hormone receptor regulates a diverse set of genes that control

processes from embryonic development to adult homeostasis. Upon binding of

thyroid hormone, thyroid receptor releases corepressor proteins and undergoes a

conformational change that allows for the interaction of coactivating proteins

necessary for gene transcription. This interaction is mediated by a conserved

motif, termed the NR box, found in many coregulators. Recent work has

demonstrated that differentially assembled coregulator complexes can elicit

specific biological responses. However, the mechanism for the selective

assembly of these coregulator complexes has yet to be elucidated. To further

understand the principles underlying thyroid receptor-coregulator selectivity, we

designed a high-throughput in vitro binding assay to measure the equilibrium

affinity of thyroid receptor to a library of potential coregulators in the presence of

different ligands including the endogenous thyroid hormone T3, synthetic thyroid

receptor β-selective agonist GC-1, and antagonist NH-3. Using this

homogenous method several coregulator NR boxes capable of associating with

thyroid receptor at physiologically relevant concentrations were identified

including ones found in traditional coactivating proteins such as SRC1, SRC2,

TRAP220, TRBP, p300 and ARA70; and those in coregulators known to repress

gene activation including RIP140 and DAX-1. In addition, it was discovered

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that the thyroid receptor-coregulator binding patterns vary with ligand and that

this differential binding can be used to predict biological responses. Finally, it is

demonstrated that this is a general method that can be applied to other nuclear

receptors and can be used to establish rules for nuclear receptor-coregulator

selectivity.

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INTRODUCTION

Thyroid hormone (3,5,3’-triido-L-thyronine, T3) regulates multiple physiologic

processes in development, growth, and metabolism (1,2). Most T3 actions are

mediated through the thyroid hormone receptors (TR), which regulate

transcription of target genes either positively or negatively in response to

hormone binding. There are two different genes that express different TR

subtypes, TRα and TRβ. Each transcript can be alternatively spliced generating

different isoforms (TRα1, TRα2, TRβ1, TRβ2,) (3,4). While most of these

isoforms are widely expressed, there are distinct patterns of expression that vary

with tissue and developmental stage. In particular, TRβ2 is found almost

exclusively in the hypothalamus, anterior pituitary, and developing ear. In

addition, mice deficient in either TRα or TRβ display unique phenotypes

suggesting that the different TR isoforms have unique regulatory roles (5-10).

The thyroid hormone receptors belong to a superfamily of proteins known as the

nuclear hormone receptors (NR). Like other members of the NR superfamily, TR

has three functional domains; an amino-terminal transactivation domain (NT), a

central DNA-binding domain (DBD), and a carboxy-terminal ligand-binding

domain (LBD) (11). The DBD of TR recognizes short, repeated sequences of

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DNA found in T3-responsive genes, termed the thyroid hormone response

elements (TREs). TR can bind to a TRE as a monomer, homodimer, or

heterodimer with the retinoid X receptor (RXR) (12). However, receptor

activation from the heterodimer complex is the best characterized to date. Both

liganded and unliganded TR bind to TREs. In the absence of T3, TR associates

with corepressor proteins at the TRE maintaining the chromatin in a compact

state and therefore repressing gene activation. Upon binding of T3, TR

undergoes a conformational change, releasing corepressor proteins and allowing

for the interaction with coactivator proteins that enhance TRE driven gene

transcription.

Structural, biochemical, and genetic studies have provided a considerable

amount of information about NR-coregulator interactions. The best-studied

coregulators belong to the p160 protein family of steroid receptor coactivators

(SRC) (13). Members of this family include SRC1, SRC2 (GRIP1/TIF2), and

SRC3 (AIB1/TRAM1/RAC3/ACTR). These proteins contain several functional

domains including the nuclear receptor interaction domain (NID) and two

activation domains which interact with other coregulatory proteins CBP/p300

(AD-1) and CARM-1 (AD-2) (Figure 1A). Within the NID there are three

repeated motifs with the consensus sequence LXXLL, often termed the NR box.

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In addition there is a unique fourth LXXLL motif found in the extreme carboxy-

terminus of an alternatively spliced variant of SRC1, SRC1-a. Several

investigations have shown that the LXXLL motif is necessary and sufficient for

interaction with NR (14,15). Further structural work with a coregulator NR box

peptide and liganded TR has revealed that the LXXLL binds to a hydrophobic

groove in the TR-LBD as an α-helix (16). Other coregulators include CREB

binding protein (CBP)/p300 (17,18), thyroid receptor activating protein (TRAP)/

vitamin D receptor interacting protein (DRIPs)/peroxisome proliferating activated

receptor binding protein (PBP) (19,20), androgen receptor activator 70/55

(ARA70/55) (21,22), receptor interacting protein 140 (RIP140) (23), PPARγ

coactivator 1 (PGC-1) (24), thyroid receptor binding protein (TRBP)/PPAR

interacting protein (PRIP) (25,26), DAX-1(27), and small heterodimer partner

(SHP) (28). The interaction of these coregulators with nuclear receptors is also

mediated by LXXLL motifs. An analogous motif, I/LXXII, has been identified in

corepressors such as nuclear receptor corepressor (NCoR) and silencing

mediator of retinoic acid (SMRT) and structural studies have shown that the

binding sites for coactivators and corepressors partially overlap (29).

There is a large pool of coregulators available for interaction with TR. Although

there appears to be some functional redundancy within the SRCs, there is also

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evidence that SRCs have distinct biological regulatory roles. While mice deficient

in SRC1 exhibit resistance to thyroid hormone (RTH), the phenotypes for mice

deficient in SRC2 and SRC3 are distinct with no evidence of RTH (30-32).

These studies, along with recent work with the progesterone and glucocorticoid

receptors, have demonstrated that interaction with specific coregulators can elicit

specific biological responses (33). However, it remains unclear how NRs

discriminate between different coregulators. In this study we sought to define

rules that govern TR-coregulator selectivity.

Combinatorial peptide libraries have been used to define NR-coregulator

specificity, and have revealed that the sequences immediately flanking the NR

box are critical for specificity (34,35). However the peptides in these studies

were generated from random libraries that do not represent the true NR box

sequences. Other investigations focused on defining SRC NR box selectivity

using a subset of coregulator NR boxes from the SRCs. This work has shown

that ligands can allosterically modulate the coregulator binding pocket and

therefore differentially alter specific SRC recruitment and NR box usage (36-38).

However, to date there has been no comprehensive study of the interactions of

TR and natural coregulator NR boxes. To address this issue, we designed an in

vitro binding assay to measure the equilibrium binding of TRβ to a library of

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potential coregulators in a high-throughput manner using fluorescence

polarization. With this method, binding constants for TRβ to coregulator NR

boxes were determined in a consistent format, including NR boxes from SRCs

and 9 other known coregulators. In addition the TRβ -coregulator binding

patterns for three different ligands including T3, the synthetic TRβ-selective

agonist GC-1, and the T3 antagonist NH-3 were defined. This quantitative

information can be used to establish rules for TRβ coregulator selectivity and

these rules can be used for predicting biological responses.

EXPERIMENTAL PROCEDURES

Ligand Synthesis -GC-1 and NH-3 were synthesized as previously described

(39),(40).

Protein Expression and Purification- Human TRβ LBD (His6; residues E202-

D461) was expressed from a pET28a construct (Novagen) in BL21(DE3) (20°C,

0.5 mM IPTG added at OD600 = 0.6) as previously described (15). Cells were

harvested, resuspended in sonication buffer (20 mM Tris, 300 mM NaCl, 0.025%

tween, protease inhibitors, 10 mg lysozyme, pH 7.5, 30 minutes on ice), and

sonicated for 3x3 minutes on ice. The lysed cells were centrifuged at 100,000 x

g for 1 hr and the supernatant was loaded onto Talon resin (Clonetech).

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Liganded-protein was eluted with 500 mM imidazole plus ligand (3,3’,5-triiodo-

L-thyronine, Sigma; GC-1; or NH-3;). Protein purity was assessed by SDS-

PAGE and HPSEC and protein concentration measured by coomassie protein

assay.

Peptide Library Synthesis -Coregulator peptides consisting of 20 amino acids

with the general motif of CXXXXXXXLXXL/AL/AXXXXXXX were constructed,

where C is cysteine, L is leucine, A is alanine, and X is any amino acid. The

sequences of all the coregulator peptides were obtained from human isoform

candidate genes (SRC1/AAC50305, SRC2/Q15596, SRC3/Q9Y6Q9, PGC-

1/AAF19083, TRAP220/Q15648, TRBP/Q14686, TRAP100/Q75448,

ARA70/Q13772, ARA55/NP_057011, p300/Q92831, RIP140/P48552, DAX-

1/P51843, SHP/Q15466). The peptides were synthesized in parallel using

standard fluorenylmethoxycarbonyl (Fmoc) chemistry in 48 well synthesis blocks

(FlexChem System, Robbins) (41). Preloaded Wang (Novagen) resin was

deprotected with 20% piperidine in dimethylformamide. The next amino acid was

then coupled using 2-(1H-Benzotriazole-1-yl)-1,1,3,3-tetramethyluronium

hexafluorophosphate (2.38 equiv. wt.), Fmoc-protected amino acid (2.5 equiv.

wt.), and diisopropylethylamine (5 equiv.wt.) in anhydrous dimethylformamide.

Coupling efficiency was monitored by the Kaiser Test. Synthesis then proceeded

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through a cycle of deprotection and coupling steps until the peptides were

completely synthesized. The completed peptides were cleaved from the resin

with concomitant side chain deprotection (81% TFA, 5% phenol, 5% thioanisole,

2.5% ethanedithiol, 3% water, 2% dimethylsulphide, 1.5% ammonium iodide) and

crude product was dried down using a speedvac (GeneVac). Reversed-phase

chromatography followed by mass spectrometry (MALDI-TOF/ESI) were used to

purify the peptides. The purified peptides were lyophilized. A thiol reactive

fluorophore, 5-iodoacetamidofluorescein (Molecular Probes), was then coupled

to the amino terminal cysteine following the manufacturer’s protocol. Labeled

peptide was isolated using reversed-phase chromatography and mass

spectrometry. Peptides were quantified using UV spectroscopy. Purity was

assessed using LCMS (Supplemental Information).

Direct Binding Assay-Using a BiomekFX in the Center for Advanced Technology

(CAT), hTRβ-LBD was serially diluted from 70 µM to 0.002 µM in binding buffer

(50 mM Sodium Phosphate, 150 mM NaCl, pH 7.2, 1 mM DTT, 1 mM EDTA,

0.01% NP40, 10% glycerol) containing 140 µM ligand (T3, GC-1, or NH-3) in 96

well plates. Then 10 µL of diluted protein was added to 10 µL of fluorescent

coregulator peptide (20 nM) in 384 well plates yielding final protein

concentrations of 35-0.001 µM and 10 nM fluorescent peptide concentration.

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The samples were allowed to equilibrate for 30 minutes. Binding was then

measured using fluorescence polarization (excitation λ 485 nm, emission λ 530

nm) on an Analyst AD (Molecular Devices). Two independent experiments were

assayed for each state in quadruplicate. Data were analyzed using SigmaPlot

8.0 (SPSS, Chicago, Il) and the Kd values were obtained by fitting data to the

following equation (y=min+(max-min)/1+(x/Kd)^Hillslope).

RESULTS

Coregulator Peptide Library-A library of known coregulator peptides consisting of the

LXXLL sequence plus 7-8 additional flanking residues at each terminus was synthesized

(Figure 1B). Previous screens with coactivator peptides established amino acid residues

at +6 to +12 as critical for binding (38,42). To capture these specificity determinants,

peptides of 20 amino acid length were generated. Additionally, negative control peptides

were made for each coregulator NR box by replacing L+4 and L+5 with alanine

(LXXAA), as this substitution has been shown to abolish interactions with NR (38). A

thiol reactive fluorescent probe was covalently attached to each peptide via a cysteine

positioned at the amino terminus of each peptide. The coregulator peptides are listed in

the far left column of Figure 1B, where SRC1-1, SRC1-2, SRC1-3 represent the first,

second and third NR boxes in SRC1, respectively. This nomenclature, first proposed by

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O’Malley, is applied to all of the coregulator peptides studied throughout this paper (30).

All peptide probes were synthesized in parallel using the Fmoc strategy and purified by

RP-HPLC. Identity and purity were confirmed using HPLC and MALDI-TOF or

LCMS(Supplemental Information). Seven targeted coregulator NR boxes, TRAP100-1,

TRAP100-5, RIP140-2, RIP140-4, TRAP220-1(-), TRBP-1(-), and TRAP100-6(-),

are omitted as they could not be synthesized or purified after several attempts.

Coregulator Peptides Bind to hTRβ-LBD in Four Different Binding Modes-Initial

peptide binding studies were carried out with SRC2-2 and the ligand binding

domain of the human thyroid hormone receptor β (hTRβ-LBD) in the presence

of T3. As shown in Figure 2A, SRC2-2 binds to TRβ in a saturable dose-

dependent manner with a measured Kd of 0.7 µM, consistent with literature

reports (0.8 µM) (15). We also confirmed that this interaction was specific by

carrying out binding studies with a mutated SRC2-2 peptide (LXXAA, SRC2-2(-

)). The trace observed in Figure 2A reveals that SRC2-2(-) does not interact

with TRβ in the presence of T3.

To further elucidate the coregulator binding pattern of TRβ in the presence of T3,

direct binding assays were carried out with the entire coregulator peptide library.

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This set of experiments was executed by maintaining a constant concentration of

coregulator peptide (10 nM) and varying the TRβ concentration from 0.001-35

µM in the presence of saturating amounts of T3 (90 µM). The results revealed

that the 34 different coregulator peptides bound to liganded TR with varying

degrees of affinity. Individual Klotz plots were constructed for each coregulator

peptide. This analysis revealed four different binding modes. Example

equilibrium affinity curves are summarized in Figure 2 (A-D) and Kd value

ranges are reported in Figure 3A. In no case did the negative peptide controls

bind to liganded TRβ.

The first binding mode consisted of peptides that bound in a dose dependent and

saturable manner (Figure 2A) where a clear plateau was reached within the

protein concentration range studied. Eight coregulator peptides exhibited this

mode: SRC2-1, SRC2-2, SRC2-3, TRAP220-1, TRBP-1, p300, RIP140-5, and

DAX1-3. The Kd values for this class ranged from 0.7 to 10 µM.

The next binding mode included peptides where binding appeared to be reaching

saturation but did not have a clear plateau, as defined by at least two points with

indistinguishable y-ordinates (Figure 2B). This assumption is based on previous

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binding studies conducted with these coregulator peptides where similar changes

in polarization values were observed for saturating binding isotherms (data not

shown). These peptides bound to TRβ with a Kd range of 10-30 µM and

included SRC1-2, SRC1-3, SRC3-2, TRAP220-2, TRBP-2, and ARA70. To

accurately obtain Kd values, however, the binding studies would need to be

carried out at protein concentrations varying from1-300 µM as this would give

the widest range of polarization values. Working with TRβ protein concentrations

higher than 100µM is problematic due to protein aggregation and decreased

protein stability. In order to reflect the inability to obtain an unambiguous Kd

value, we report a Kd range,10-30 µM, for coregulator peptides that exhibit this

binding mode.

The third binding mode is one in which polarization increases with protein concentration

but does not seem to be reaching saturation. This mode is exemplified by SRC3-3

(Figure 2C) where the polarization of SRC3-3 slowly increases with TRβ

concentration. Other coregulators included in this category are SRC1-1, SRC3-

1, SRC3-3, RIP140-3, RIP140-8, and SHP. The binding isotherms for this

group suggest that the coregulator peptides are binding non-specifically or that

they bind with a Kd value significantly above the working assay range, (e.g. >30

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µM). This class of coregulator peptides is distinguished from the final group of

peptides where no binding is observed (Figure 2D).

T3 Recruitment of Coregulators-We report here the first comprehensive

investigation of coregulator recruitment to liganded TRβ with 12 different

coregulators and 32 unique NR boxes as well as appropriate negative controls

(LXXAA). Of the 32 coregulator peptides tested, 20 appear to interact with TRβ

in the presence of T3 with varying degrees of affinity. The strongest recruitment

observed was with SRC2-2 which exhibited a Kd of 0.7 µM ± 0.2. This was

followed by TRBP-1 (Kd=1.8 µM ± 0.1), RIP140-5 (Kd=2.5 µM ± 0.4),

TRAP220-1 (Kd=2.7 µM ±1.1), DAX1-3 (Kd=3.6 µM ± 2.3), SRC2-3 (Kd=4.5 µM

± 1.5), SRC2-1 (Kd=6.0 µM ± 2.0), and p300 (Kd=9.2 µM ± 2.8). The coregulator

peptides that clearly did not interact with T3 liganded TRβ included ARA55, all of

the TRAP100 peptides, and some of the RIP140 and DAX1 NR box peptides.

The remaining coregulator peptides bound to TRβ weakly with Kd values ranging

from10-30 µM or > 30 µM as discussed above.

The SRCs are a family of coregulators whose interaction with TRβ have been

extensively studied using non-quantitative methods (15,38,43,44). Our data are

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consistent with previously published work where it was determined that TRβ has

a strong preference for SRC2 NR box peptides with the overall observed

preference being SRC2-2>SRC2-3>SRC2-1 (15). The next family member,

SRC1, bound to liganded TRβ to a lesser extent with SRC1-2~SRC1-3>SRC1-

1. Only weak interactions were observed for SRC3 where affinity has been

reported as SRC3-2>SRC3-1=SRC3-3.

The TRAP coactivator complex has been shown to associate with NRs and help

initiate transcription (19,20). Two single subunits TRAP220 and TRAP100 were

investigated for their ability to interact with liganded TRβ. TRAP220 has two NR

boxes and in this report it was determined that the first NR box, TRAP220-1,

interacted more strongly than the second NR box, TRAP220-2. This is the

opposite of what has been reported for TRα, supporting the notion that TR

isoforms can differentially recruit coactivator NR boxes (20,45). The TRAP100

protein contains 7 NR boxes, 5 of which were studied here. As previously

reported, none of these NR boxes interact with liganded TRβ (19).

Another coregulator that has been shown to interact with TRβ is TRBP. This

coactivator is ubiquitously expressed and appears to be a general coactivator

that can associate with NR including TR, ER, PPAR, as well as other

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transcriptional proteins such as AP-1, CRE, and NFκB-response element(25).

There are two LXXLL motifs in TRBP and both can interact with TRβ. Our

studies indicate that TRBP-1 is preferentially recruited to TRβ in the presence of

T3.

RIP140 is a coregulator that contains 9 LXXLL motifs and has been shown to

interact with many NRs including TRβ (23). It has been suggested that RIP140

directly competes with other coregulators (23). Unlike traditional coregulators,

however, RIP140 represses transcription upon binding to NR (46-49). Here we

show liganded TRβ has a clear preference for three of the NR boxes in RIP140,

RIP140-3, RIP140-5, and RIP140-8. One NR box peptide in particular,

RIP140-5, bound fairly tightly with a Kd of 2.5 µM ± 0.4.

Three additional coactivators, p300, ARA70, and DAX1, were also shown in this

report to associate with TRβ with varying degrees. ARA70 and DAX1 had not

previously been investigated for their interaction with TRβ .

Ligands Alter Coregulator Recruitment-To investigate ligand effects on

coregulator recruitment, binding studies were performed in the presence of the

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TRβ selective agonist, GC-1. GC-1 is a halogen-free thyromimetic that is

approximately 10-fold selective for binding to TRβ vs. TRα (39). It has been

shown that the oxyacetic acid at the carbon-1 position (Figure 3A) is responsible

for the selective TRβ binding of GC-1 (50). Additionally, crystallographic studies

have confirmed that the oxyacetic acid group participates in a hydrogen bonding

network in the TRβ LBD polar pocket (51). We sought to determine how these

interactions might alter coregulator specificity.

In the presence of GC-1 the coregulator peptides bound to TRβ with varying

degrees of affinity and all four binding modes were observed. Overall the

coregulator binding patterns for GC-1 and T3 were similar in terms of which

coregulator peptides were recruited. However, the degree to which they bound

varied. In most cases, the coregulator peptides bound with similar or slightly

lower affinity to TRβ·GC-1 than TRβ·T3. Several NR boxes, particularly those of

the SRC family, exhibited significant differences in affinity to TRβ·GC-1 relative

to TRβ·T3. All of the SRC2 NR boxes bound TRβ·T3 in a measurable Kd range,

whereas in the presence of GC-1 a saturated binding curve was only observed

for SRC2-2. Additionally, SRC1-2 appears to be much more strongly recruited

by TRβ·T3, whereas the opposite is true for SRC3-3. Other notable differences

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between T3 and GC-1 were seen with TRAP220 and TRBP where recruitment

decreased in the presence of GC-1.

In addition to studying agonist induced coregulator recruitment, we wanted to

explore how antagonists may affect coregulator binding. The recently reported T3

antagonist NH-3 (Figure 3A) was tested against the entire coregulator peptide

library (40). In the presence of saturating concentrations of NH-3, no

coregulators from the library were recruited to the TRβ·NH-3 complex (Figure

3A).

DISCUSSION

The NRs show a clear preference for particular NR boxes. One factor that drives this

specificity is the amino acid residues immediately flanking the NR box (15,34,36-38).

Most prior work focused on individual coregulators or the p160/SRC coregulator family

(15,19,23,25,38,43-45,52). To expand our understanding of coregulator recruitment, we

investigated the ability of TRβ to bind to a library of known coregulator NR boxes

using a homogenous equilibrium binding assay. The results from this screen

demonstrate that the coregulator binding pattern for TRβ is distinct from other NR

(ERα, ERβ, AR, data not shown) and new TRβ -coregulator peptide interactions,

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including RIP140-5 (Kd=2.5 µM), ARA70 (Kd=10-30 µM), and DAX1-3 (Kd=3.6

µM) were identified. The NR box peptides that interacted with TRβ revealed

specificity elements including a propensity for hydrophobic groups at the 1

position and for proline at the –2 position as seen in TRAP220 and TRBP-1

(20,45). Additional trends included histidine at –3, glutamine at +6, and the

presence of a serine in the carboxy-terminal positions +7-+10 (Figure 3B).

Previous phage display studies isolated non-natural peptides with similar

specificity determinants.(35)

Ligands are another factor that can impact the recruitment of coregulators to NR

(36-38,53). In this study, the ability of both agonists and antagonists to modulate

the coactivator binding pocket of TRβ was investigated. As predicted, the NR

box binding patterns for TRβ·T3 and TRβ·GC-1 were different, and no

coregulators were recruited in the presence of the T3 antagonist NH-3. Based

on the differential NR box recruitment observed for the GC-1 ligand, specificity

determinants that are distinct from T3 can be defined. While there is still a high

propensity for hydrophobic amino acids at the –1 position and for serine at

positions +7-+10, proline at -2 and histidine at -3 do not seem to be important

for specificity in the presence of GC-1 (Figure 3B). In addition, the specificity

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determinants for TRβ·T3 and TRβ·GC-1 are distinct from those observed for the

estrogen receptor with its cognate ligand (ERα·E2)(36, Chang, 1999 #36).

The differential binding patterns for TRβ·T3, TRβ·GC-1, and TRβ·NH-3 may be

used to predict biological responses. In hypothyroid and euthyroid

hypercholesterolemic mice, GC-1 behaves like T3 to potently reduce serum

cholesterol (54). Additionally, while T3 potently induces positive inotropic and

chronotropic cardiac effects, GC-1 is devoid of significant cardiac effects through

a wide dose range. Although these observations may be partially explained by

the selective binding of GC-1 to TRβ as well as preferential liver vs. heart uptake

(54), coregulator selectivity may also play a role. In the presence of T3 there is a

stronger preference for the recruitment of SRC1 and SRC2 coregulator peptides

to TRβ, whereas SRC2 and SRC3 NR boxes are more strongly recruited to

TRβ·GC-1. Recent investigations focusing on SRC1s role in regulating T3 responsive

genes have revealed that SRC1 is important for the pituitary-hypothalamus-

thyroid axis and for T3 affects in the heart but not for regulation of hepatic genes

that regulate cholesterol levels (55-57). This suggests that SRC2 and SRC3

regulate cholesterol modulating genes in the liver. In support of this argument,

studies have shown that SRC2 and SRC3 liver expression is increased in

hypothyroid mice while there is a slight decrease in SRC1 expression (58).

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Studies utilizing cDNA microarrays have revealed that thyroid hormone can both

positively and negatively regulate genes (59). One mechanism of T3 driven

repression may involve the recruitment of coregulators that repress transcription,

such as RIP140 and DAX1. In our studies we find that both TRβ·T3 and

TRβ·GC-1 strongly interact with RIP140-5 and DAX1-3, but TRβ·NH-3 fails to recruit

these coregulators. From these observations, it can be predicted that T3 and

GC-1 can repress gene transcription but NH-3 lacks this ability. Thus NH-3

treatment may result in partial activation of genes that are normally repressed by

TRβ·T3. If this is the case, then NH-3 would display unique pharmacology by

blocking ligand activation of positively regulated T3-responsive genes and

causing derepression of negatively regulated T3-responsive genes.

Presumably there are additional factors that influence NR recruitment of

coregulators such as post-translational modifications, structural determinants

arising from specific DNA response elements, cooperativity, cellular environment,

and additional interaction surfaces on the NR and coregulator proteins. To fully

dissect NR-coregulator interactions, more complex models will need to be

developed. The use of full-length molecules for determining NR-coregulator

binding affinities has been employed with the estrogen receptors and members of

the SRC family (60). Although this work demonstrated that the binding affinities

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are 3-5 fold higher than predicted with coregulator peptides and NR-LBD, the

overall selectivity of ER isoforms for SRC members was consistent with previous

investigations. This emphasizes the utility of a simple affinity model as a first

step for establishing rules of NR-coregulator selectivity.

NR signaling is a multivariant complex process that utilizes differences in NR, NR

isoforms, a diverse set of coregulators, ligands, tissue variability, and unique

DNA response elements. It remains unclear how this protein network can

potentiate signals for specific biological responses. However one point of

regulation may derive from specific NR-coregulator interactions. Using an

equilibrium binding assay, the binding affinities of TRβ for a large set of NR

boxes in the presence of multiple ligands were quantitatively determined and

some rules were defined that account for the specificity of these interactions.

Additionally, it was shown that these binding patterns could be used to predict

biological responses. Finally, we believe that this method may be generalized to

other nuclear receptors to establish patterns of NR-coregulator selectivity.

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FIGURE LEGENDS

Figure 1. Coregulator Peptides

A block diagram of SRC1 identifying some of the functional domains. The nuclear

interaction domain (NID) contains three nuclear receptor interaction domains (NR boxes)

that are known to interact with NR (SRC1-1, SRC1-2, SRC1-3). The activation

domains AD-1 and AD-2 interact with other known coregulators including p300/CBP

and CARM-1. SRC1 has two isoforms, SRC1a and SRC1e. SRC1-a has an additional

NR box at the carboxy terminus designated SRC1-4 that has been shown to interact with

some NR. B. Sequence alignment of the coregulator peptides tested in this study. The

conserved NR box, LXXLL, is enclosed in a box. Negative control peptides were also

synthesized with leucine +4 and +5 replaced with alanines (LXXAA). * denotes omitted

peptide sequences that were not recovered after synthesis.

Figure 2. TRβ↑Coregulator Binding Isotherms in the presence of T3

Panel A. The binding of TRβ SRC2-2 is plotted in dark green to signify that this

is a saturable binding curve where a measurable Kd=0.7 µM is extracted by

fitting to the equation (y=min+(max-min)/1+(x/Kd)^Hillslope). The binding of TRβ

to the negative control SRC2-2 peptide is also shown in red. Panel B. The

binding curve for SRC1-3 is shown in light green. This binding curve appears to

be reaching saturation, but no visible plateau is observed. The Kd is reported as

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10.1-30 µM. Panel C. The binding curve for SRC3-3 is shown in gray.

Polarization is increasing with TRβ concentration but does not appear to be

reaching saturation. The Kd is reported as >30 µM. Panel D. The binding curve

for TRAP220-2 is plotted in red indicating that no binding is observed. The solid

circles denote the native NR box peptides, solid lines represent fitted curves for

native NR box peptides, open red circles represent negative NR box peptides

(LXXAA), and dashed red line is fitted curve for negative NR box peptide.

Figure 3. Coregulator Binding Patterns and Specificity Determinants.

A. The structure of the TRβ ligands tested; endogenous thyroid hormone T3,

synthetic TRβ-selective agonist GC-1, and T3 antagonist NH-3. The

equilibrium binding constants for TRβ↑coregulator NR boxes are reported for

each ligand. The coregulator peptides are listed in the left column where SRC1-

1, SRC1-2, SRC1-3, SRC1-4 represent the first, second, third, and fourth NR

box in SRC1, respectively. Each color represents a unique Kd range as defined

by the legend on the left. Significant differences between TRβ·T3 and TRβ·GC-1

are boxed in black. B. A representative coregulator peptide is listed for TRβ·T3,

TRβ·GC-1, ERα·E2 with amino acids highlighted in green representing amino

acids that convey specificity for each NR·ligand state. The information for

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ERα·E2 was extracted from two sources for comparative purposes 1) a time-resolved

fluorescence assay conducted with SRCs (36) and 2) a phage peptide library

screen with ERα·E2 (35). Φ denotes hydrophobic amino acids and ζ represents

hydrophilic amino acids.

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ACKNOWLEDGEMENTS

The authors wish to thank the DOD (DAMD17-01-1-0188), the Sandler

Research Foundation, and the NIH (DK-52798 and DK-58390) for financial

support. The Center for Advanced Technology and Genomics and Proteomics

center for support.

ABBREVIATIONS

AR, androgen receptor; ARA70, androgen receptor activator; DBD, DNA binding

domain; DRIP, vitamin D receptor interacting protein; ER, estrogen receptor; LBD,

ligand binding domain; NID, nuclear interaction domain; NR, nuclear receptor, PPAR,

peroxisome proliferating activated receptor; PBP, PPAR binding protein; PGC1, PPAR

gamma coactivator; PRIP, PPAR interacting protein; RIP140, receptor interacting protein

140; RTH, resistance to thyroid hormone; RXR, retinoid x receptor; SHP, small

heterodimer partner; SRC steroid receptor coactivator; T3, 3,3’,5,-triiodo-Lthyronine;

TR, thyroid hormone; TRAP, thyroid receptor activating protein; TRBP, thyroid receptor

binding protein; TRE, thyroid receptor response element

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Quantitative Proteomics of the Thyroid Hormone Receptor Coregulator

Interactions

Jamie M. R. Moore1, Sarah J. Galicia1,4, Andrea C. McReynolds1, Ngoc-Ha

Nguyen1, Thomas S. Scanlan1,2, R. Kip Guy1,2,3

Departments of Pharmaceutical Chemistry1 and Molecular & Cellular

Pharmacology2, University of California at San Francisco, Genentech Hall,

Mission Bay San Francisco, 600 16th Street Box 2280 CA 94143-2280

SUPPLEMENTAL MATERIALS


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Table 1. Dissociation Constants for NR box peptides for TRβ

Kd (µM) ± standard deviation Ligand

Coregulator-Peptides T3 GC-1 NH-3SRC1-1 > 30 > 30 NBSRC1-2 10.1-30 > 30 NBSRC1-3 10.1-30 10.1-30 NBSRC1-4 NB NB NBSRC2-1 6.0 ± 2.0 10.1-30 NBSRC2-2 0.7 ± 0.2 3.8 ± 0.1 NBSRC2-3 4.5 ± 1.5 10.1-30 NBSRC3-1 > 30 > 30 NBSRC3-2 10.1-30 10.1-30 NBSRC3-3 > 30 10.1-30 NBPGC-1 NB NB NB

TRAP220-1 2.7 ± 1.1 10.1-30 NBTRAP220-2 10.1-30 10.1-30 NB

TRBP-1 1.8 ± 0.1 2.7 ± 0.1 NBTRBP-2 10.1-30 NB NB

TRAP100-2 NB NB NBTRAP100-3 NB NB NBTRAP100-4 NB NB NBTRAP100-6 NB NB NBTRAP100-7 NB NB NB

ARA70 10.1-30 10.1-30 NBARA55 NB NB NBp300 9.2 ± 2.8 10.1-30 NB

RIP140-1 NB NB NBRIP140-3 > 30 > 30 NBRIP140-5 2.5 ± 0.4 4.1 ± 0.1 NBRIP140-6 NB NB NBRIP140-7 NB NB NBRIP140-8 > 30 > 30 NBRIP140-9 NB NB NBDAX1-1 NB NB NBDAX1-2 NB NB NBDAX1-3 3.6 ± 2.3 3.4 ± 0.9 NB

SHP > 30 > 30 NB


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Table 2. Mass Accuracy, Purity, and Yields for Fluorescently Labeled NRBox Peptides

Methods

LCMSThe purity of the coregulator NR box peptides was assessed using LCMS(Alliance 2695, Micromass ZQ, Waters). Approximately 10 µg of peptide wasloaded onto a Xterra MSC18, 3.5µM, 2.1x50mm (Waters). A gradient of 10%-100% acetonitrile/0.05% trifluoroacetic acid was ramped over 10 minutes andheld for 1 minute. Peaks were integrated at 214 nm and 280 nm using Masslynx(Waters).

Reversed Phase HPLC (RP-HPLC)/MALDI-TOFThe purity of the coregulator NR box peptides that did not ionize by electrospraywere assessed using HPLC (Alliance 2695, Waters) and MALDI-TOF (Voyager-EE STR, Applied Biosystems). Approximately 10 µg of peptide was loaded onto aXterra RPC18, 3.5µM, 4.6x50mm (Waters). A gradient of 10%-100%acetonitrile/0.05% trifluoroacetic acid was ramped over 10 minutes and held for 1minute. Peaks were integrated at 214 nm and 280 nm using Millenniumsoftware (Waters). The collected peaks were identified using MALD-TOF.


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Figure 1. SRC2-2-. A. The bottom spectra is the TIC for SRC2-2. Themiddle panel displays the diode array detection at 280nm. The top panel isthe TIC at 907.21, the expected mass (z=+3). B. The observed mass forSRC2-2, 907.46 (z=+3) and 1360.68 (z=+2, expected 1360.32).


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Scanlan and R. Kiplin GuyJamie M. R. Moore, Sarah J. Galicia, Andrea C. McReynolds, Ngoc-Ha Nguyen, Thomas S.

Quantitative proteomics of the thyroid hormone receptor coregulator interactions

published online April 19, 2004J. Biol. Chem.

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