Somatostatin receptor subtype 2 (sstr2) is a G-protein-coupled receptor (GPCR) that is overexpressed in neuroendocrine tumors. The homology model of sstr2 was built and was used to aid the design of new somatostatin analogues modified with phosphonate-containing cross-bridged chelators for evaluation of using them as PET imaging radiopharmaceuticals. The new generation chelators were conjugated to Tyr3-octreotate (Y3-TATE) through bioorthogonal, strain-promoted alkyne azide cycloaddition (SPAAC) to form CB-TE1A1P-DBCO-Y3-TATE (AP) and CB-TE1K1P-PEG4-DBCO-Y3-TATE (KP) in improved yields compared to standard direct conjugation methods of amide bond formation. Consistent with docking studies, the clicked bioconjugates showed high binding affinities to sstr2, with Kd values ranging from 0.6 to 2.3 nM. Selected isomers of the clicked products were used in biodistribution and PET/CT imaging. Introduction of the bulky dibenzocyclooctyne group in AP decreased clearance rates from circulation. However, the additional carboxylate group and PEG linker from the KP conjugate significantly improved labeling conditions and in vivo stability of the copper complex and ameliorated the slower pharmacokinetics of the clicked somatostatin analogues.
Somatostatin receptor subtype 2 (sstr2) is a G-protein-coupled receptor (GPCR) that is overexpressed in neuroendocrine tumors. The homology model of sstr2 was built and was used to aid the design of new somatostatin analogues modified with phosphonate-containing cross-bridged chelators for evaluation of using them as PET imaging radiopharmaceuticals. The new generation chelators were conjugated to Tyr3-octreotate (Y3-TATE) through bioorthogonal, strain-promoted alkyne azide cycloaddition (SPAAC) to form CB-TE1A1P-DBCO-Y3-TATE (AP) and CB-TE1K1P-PEG4-DBCO-Y3-TATE (KP) in improved yields compared to standard direct conjugation methods of amide bond formation. Consistent with docking studies, the clicked bioconjugates showed high binding affinities to sstr2, with Kd values ranging from 0.6 to 2.3 nM. Selected isomers of the clicked products were used in biodistribution and PET/CT imaging. Introduction of the bulky dibenzocyclooctyne group in AP decreased clearance rates from circulation. However, the additional carboxylate group and PEG linker from the KP conjugate significantly improved labeling conditions and in vivo stability of the copper complex and ameliorated the slower pharmacokinetics of the clicked somatostatin analogues.
Copper
radionuclides, such as 60Cu, 61Cu, 62Cu, 64Cu, and 67Cu, have applications
in nuclear medicine for SPECT, PET, and/or targeted radiotherapy.
Copper-64, with a half-life of 12.7 h, and its unique decay profile
(β+: 18%; β–: 38%; electron
capture: 44%), is well suited for radiolabeling biomolecules.[1] However, due to the presence of copper-chelating
proteins in vivo, a challenge of developing copper-based radiopharmaceuticals
is the in vivo stability.[2] There is interest
in developing new copper chelators for improved copper radiopharmaceuticals.[3,4] Our laboratory has a long history of developing copper chelators,
with CB-TE2A being one of the gold standards for forming kinetically
stable chelates with Cu(II).[5] Concomitant
with its high in vivo stability is the challenge of radiolabeling
under mild conditions. The phosphonate-pendant-armed cross-bridged
chelator, CB-TE1A1P, can be labeled with Cu-64 at ambient temperature
in high specific activity.[6] However, when
the carboxylate pendant arm in CB-TE1A1P was utilized for conjugation
to the sstr2 analogue, Y3-TATE, the requirements for room temperature
labeling were compromised, and the synthesis yield was very low.[7] With an aim to further optimize peptide conjugates
with phosphonate-based cross-bridged chelators, CB-TE1K1P was synthesized
with a homolysine pendant arm replacing the carboxylate pendant arm
of CB-TE1A1P, which conserved the carboxylate and phosphonate pendant
arms after conjugation to biomolecules.[8] Because of the challenges of conjugating the phosphonate-based chelators
with biomolecules directly through peptide bond formation, including
low yields and requirement of higher temperatures for labeling, click
chemistry was applied as the bioconjugation method.The Huisgen
1,3-dipolar cycloaddition, also called copper-catalyzed
alkyne–azide cycloaddition (CuAAC) click chemistry,[9] has been applied extensively in the development
of radiopharmaceuticals since its introduction to this field.[10,11] Struthers et al. reviewed the development of metal chelating systems
using this strategy.[12] Strain-promoted
copper-free click chemistry (also called strain-promoted alkyne azide
cycloaddition, SPAAC) is especially attractive for conjugating copper
chelators, because there is no need to remove copper from the clicked
products, which constitutes a significant problem for unprotected
copper chelators.[13] Baumhover et al. pioneered
the application of this chemistry in copper-based radiopharmaceuticals
by functionalizing DOTA and NOTA with monofluorocyclooctyne, which
was then conjugated with an azide-modified peptide.[14] Another advantage of using SPAAC chemistry is that the
prelabeled clickable chelators can be conjugated to the biomolecules
almost quantitatively at equal equivalency under mild and bioorthogonal
conditions. This is especially important for labeling biomolecules
using chelators that require harsh labeling conditions that the biomolecules
cannot tolerate.Modification of this new generation of cross-bridged
chelators
with the commercially available dibenzocyclooctynes (DBCO)[15] allows facile conjugation of them to other biomolecules
through SPAAC. However, a concern of this approach is the influence
of the bulky and hydrophobic DBCO on the binding affinity, internalization,
and pharmacokinetics of the clicked products. While the influence
of the DBCO group is relatively small when conjugated with macromolecules
such as viruses,[16] nanoparticles,[17,18] or antibodies, there is a high likelihood that DBCO will have a
greater impact on the pharmacokinetics of smaller molecules, such
as peptides and peptidomimetics. It was previously shown that a 18F-labeled peptide targeting integrin αvβ6 containing a DBCO prosthetic group had considerable lipophilicity
that contributed to increased hepatobiliary clearance.[19]We hypothesized that the higher hydrophilicity
of the cross-bridged
macrocyclic chelators with pendant carboxylate and/or methane phosphonate
arms in combination with DBCO would retain the high target-to-background
contrast of the clicked products. Recently, Chen et al. synthesized
a 64Cu-labeled RGD peptide from a DBCO-modified, PEG-linked
DiAmSar chelator which showed high contrast between tumor and nontargeted
uptake in the U87MGhumanglioblastoma xenograft model.[20] Inspired by these results, we set out to explore
the effects of our newly developed DBCO-modified chelators on binding
affinities and pharmacokinetics of the clicked somatostatin analogues
and to demonstrate the potential utility of these chelators on 64Cu-based PET imaging of neuroendocrine tumors.As radiolabeled
somatostatin analogues showed promise for both
imaging and therapy of neuroendocrine tumors,[21] the sstr2 agonist Tyr3-octreotate (Y3-TATE) was chosen
as the model peptide for this study.[22,23] A 3-D atomic
structure model of sstr2 based on the crystal structure of the opioid
receptors was used to explore the effects of the DBCO-cross-bridged
chelator moieties on the receptor targeting of the new bioconjugates.[24] The synthesis, in silico, in vitro, ex vivo,
and in vivo evaluation of 64Cu-CB-TE1A1P–DBCO–Y3-TATE
(64Cu-AP) and 64Cu-CB-TE1K1P–PEG4–DBCO–Y3-TATE
(64Cu-KP) derived from two DBCO-modified chelators are
reported here (Figure 1). The results are compared
with CB-TE1A1P directly conjugated to Y3-TATE, 64Cu-CB-TE1A1P–Y3-TATE
(64Cu-1A1P), in a structure–pharmacokinetic relationship
analysis.[7]
Figure 1
Structures of Tyr3-octreotate
(Y3-TATE) analogues.
Structures of Tyr3-octreotate
(Y3-TATE) analogues.
Results
Homology Modeling of sstr2
To the best of our knowledge,
there is no reported crystal structure for somatostatin receptor subtype
2 (sstr2). It is known that somatostatin receptors have about 40%
sequence homology similarity to the opioid receptors.[25] In the present work, we constructed 3D sstr2 structural
model using our established sequence homology modeling approach[26] based on the known crystal structures of opioid
receptors to construct the 3D structures of sstr2. Subsequently, molecular
dynamics (MD) and molecular mechanics (MM) calculations were performed
using SYBYL-X 1.32. Three dimensional sstr2 structural and conformation
evaluation analyses were performed using proSA-web for Z-scores and
PROCHECK for Ramachandran plots (Figures S7 and
S8, Supporting Information). Furthermore, root mean squared
deviation (RMSD), superimposition of query and template structure,
and visualization of generated ssrt2 structural models were performed
using UCSF Chimera 1.8.1. The model with the lowest RMSD based on
the nociceptin/orphanin FQ receptor (NOP, 4EA3) was selected as the
candidate structure for further ssrt2 studies.
Molecular Docking
3D docking was performed by the Tripos
Surflex-dock module with different binding poses or conformations
of each ligand and sstr2 structural models generated. The binding
pocket was rendered with the molecular surface generated by Sybyl
MOLCAD.[27] The docking poses and ligand/receptor
interactions were analyzed by the PyMol program, including intermolecular
H-bonds and hydrophobic and hydrophilic interactions within 4.0 Å.Docking of Y3-TATE with the defined sstr2 structure model revealed
hydrogen bond interactions of the peptidomimetic with amino acid residues,
including Asn196, Trp197, Tyr205, Asn276, Asn119, Gln88, and Thr212
of sstr2 (Figure 2). The binding site of Y3-TATE
is located deep inside sstr2. Data from the docking model also revealed
an unoccupied pocket next to the N-terminus of Y3-TATE, suggesting
that substitution at this position should be well tolerated. The docking
score, which correlates with the predicted binding affinity (pKd value) of the ligand to the receptor, was
12.9. Docking of 1A1P and AP with this model showed similar docking
scores of 10.1. 1A1P interacts with amino acid residues Trp188, Ser192,
Lys291, Asn276, Tyr302, Thr174, Val173, Ile177, and Phe208 of sstr2
through hydrogen bonds (Figure 3). The docking
pose of AP binding to sstr2 indicates hydrogen bond interactions with
Asn276, Cly216, Cys193, Gln126, Ile209, Phe127, Phe208, and Gln102
of sstr2 (Figure 4).
Figure 2
A: Overview of the docking
mode of Y3-TATE in the binding pocket
of sstr2. B: Molecular interactions between the Y3-TATE and specific
amino acid residues of sstr2.
Figure 3
A: Overview of the docking mode of CB-TE1A1P–Y3-TATE (1A1P)
in the binding pocket of sstr2. B: The detailed molecular interactions
between 1A1P and specific amino acids of sstr2.
Figure 4
A: Overview of the docking mode of DBCO–CB-TE1A1P–N3-Y3-TATE (AP) in the binding pocket of sstr2. B: The detailed
molecular interaction between the AP and specific amino acids in sstr2.
A: Overview of the docking
mode of Y3-TATE in the binding pocket
of sstr2. B: Molecular interactions between the Y3-TATE and specific
amino acid residues of sstr2.A: Overview of the docking mode of CB-TE1A1P–Y3-TATE (1A1P)
in the binding pocket of sstr2. B: The detailed molecular interactions
between 1A1P and specific amino acids of sstr2.A: Overview of the docking mode of DBCO–CB-TE1A1P–N3-Y3-TATE (AP) in the binding pocket of sstr2. B: The detailed
molecular interaction between the AP and specific amino acids in sstr2.Docking of KP with the sstr2 model
showed that KP fits the binding
pocket even with the flexible PEG linker between the chelator and
DBCO (Figure 5A), with a predicted score of
13.2. It interacts with amino acid residues Trp197, Ile195, Thr206,
Gly123, Asp122, Asn276, Gln126, Thr212, and Lys291 of sstr2 through
hydrogen bonds (Figure 5B).
Figure 5
A: Overview of the docking
mode of CB-TE1K1P–PEG4–DBCO–Y3-TATE
(KP) in the binding pocket of sstr2. B: The detailed molecular interactions
between KP and specific amino acids in sstr2.
A: Overview of the docking
mode of CB-TE1K1P–PEG4–DBCO–Y3-TATE
(KP) in the binding pocket of sstr2. B: The detailed molecular interactions
between KP and specific amino acids in sstr2.
Synthesis and Radiolabeling of Peptide Conjugates
The
precursor Y3-TATE was synthesized via standard solid-phase Fmoc-based
peptide synthesis on a microwave peptide synthesizer.[28] After cleavage and HPLC purification, 30% of the product
was isolated and was used for strain-promoted click chemistry with
DBCO–CB-TE1A1P and DBCO–CB-TE1K1P (Figure S1, Supporting Information).CB-TE1A1P–Y3-TATE
(1A1P) was synthesized following a published procedure.[7] Consistent with the previously published result,
less than 10% of pure 1A1P was isolated after HPLC purification. CB-TE1A1P–DBCO–Y3-TATE
(AP) was synthesized by mixing DBCO–CB-TE1A1P and N3-Y3-TATE in H2O and t -BuOH, with stirring
at 40 °C for 1.5 h. Because of the lack of regioselectivity of
SPAAC, three isomers were separated on a semiprep reversed-phase HPLC
column. The total isolated yield of the three isomers was 72%. KP
was synthesized by the same procedure described above for AP. Because
of the lack of regioselectivity of SPAAC, two regioisomers were separated.
The total isolated yield of the two regioisomers was 43%.The
radiolabeling conditions for the three chelator–peptide
conjugates were optimized. The optimal buffer solution was 0.1 M NH4OAc (pH 8.1). All of the isomers of AP were labeled at 70
°C in 30 min, while both isomers of KP were labeled within 5
min at 70 °C. Radio-HPLC was used to validate the radiochemical
purities and the labeling yields. The ease of labeling of KP may be
attributed to the extra carboxylate pendant arm and/or the PEG linker
that reduces the steric hindrance. The relatively mild labeling conditions
achievable with these chelators is consistent with previously published
phosphonate containing chelators such as CB-TE1A1P.[7] For the purpose of comparison, 1A1P, AP-1, and KP-1 were
all labeled at 90 °C for 5 min in the same S.A. in >98% radiolabeling
yields and were used without further purification for in vitro and
in vivo studies.
Cellular Internalization
Internalization
studies were
done with sstr2-transfected HCT116 cells (Figure
S2, Supporting Information).[29] All
three isomers of 64Cu-AP were internalized rapidly within
2 h after administration of the radiotracers. The internalization
was blocked with Y3-TATE administered 10 min before the tracer, indicating
receptor-specific uptake of the agents. The two isomers of 64Cu-KP also showed receptor-specific uptake into sstr2-transfected
HCT116 cells, albeit the internalization was not as rapid as 64Cu-AP. For 64Cu-AP-1, the maximum internalized
tracer (45 ± 3%ID/mg) occurred after 2 h at 37 °C; the internalized 64Cu-AP-2 peaked at after 2 h at 37 °C (73 ± 7%ID/mg).
Interestingly, 64Cu-AP-3 showed slower internalization
which was not saturated after 4 h at 37 °C. The more rapid internalization
of isomers of AP could be due to the favorable interactions between
the DBCO with the hydrophobic core of sstr2. In contrast to the rapid
internalization of the isomers of AP, the isomers of KP internalized
more slowly, especially at early time points, which could be due to
the hydrophilic PEG linker repelling the hydrophobic sstr2 core.
Saturation Binding Assay and Log D Measurements
Saturation binding assays of 64Cu-AP, and 64Cu-KP were performed using a modified protocol because of high nonspecific
binding of these bioconjugates to the 96-well plates. The Bmax, Kd, and log D values of these tracers are summarized in Table 1. There is an increasing trend of Bmax with increased isomer hydrophobicity, suggesting aggregation
of the more hydrophobic isomers of the tracers (Figure S3, Supporting Information).
Table 1
Saturation Binding Assay and Log D of Different Isomers of 64Cu-AP and 64Cu-KP
tracers
Bmax (fmol/mg)
Kd (nM)
log Da
RT (min)b
64Cu-AP-1
2740 ± 180
0.6 ± 0.2
–1.8 ± 0.06
19.0
64Cu-AP-2
5680 ± 390
0.9 ± 0.2
–1.7 ± 0.17
21.1
64Cu-AP-3
8930 ± 390
2.3 ± 0.3
–1.7 ± 0.03
22.6
64Cu-KP-1
1910 ± 230
0.8 ± 0.3
–2.3 ± 0.08
17.4
64Cu-KP-2
6230 ± 570
1.4 ± 0.3
–1.8 ± 0.04
19.2
Log D was measured
at pH 7.2.
See Experimental
Section for detailed HPLC conditions.
The log D values of these tracers were determined by the traditional
shake flask method using neutral PBS buffer and octanol. The log D values of three isomers of AP were −1.8 ±
0.06, −1.7 ± 0.17, −1.7 ± 0.03, respectively,
while the log D of the two isomers of KP were −2.3
± 0.08 and −1.8 ± 0.04, respectively. The values
of log D showed the same trend as the retention times
of these tracers on reversed-phase HPLC (Table 1).Log D was measured
at pH 7.2.See Experimental
Section for detailed HPLC conditions.
Biodistribution
The most hydrophilic isomers of 64Cu-AP and 64Cu-KP were chosen for in vivo evaluations,
based on their higher affinity to sstr2 and lower tendency for aggregation
in buffered aqueous solution. The uptake of all tracers was high in
sstr2-expressing tissues (tumor, pancreas). Co-injected Y3-TATE blocked
63%, 84%, and 95% of the tumor uptake of 64Cu-AP-1, 64Cu-KP-1, and 64Cu-1A1P, respectively, showing
the high specificity of these probes for sstr2.The tracers
were excreted mainly through the kidneys, resulting in high kidney
uptake at earlier time points. The higher kidney uptake of 64Cu-AP-1 might be a result of the additional positive charge of the
molecule, which could be attracted by the negatively charged basement
membrane and the podocytes in the kidneys. The higher liver uptake
of 64Cu-AP-1 at 1 h postinjection (p.i.) reflected its
greater hydrophobicity. At 24 h p.i., less than 1% ID/g activity remained
in the liver for both 64Cu-AP-1 and 64Cu-KP-1,
which suggests in vivo stability of the copper chelates (Figure 6). At 24 h p.i., 64Cu-KP-1 showed lower
liver uptake than 64Cu-AP-1 and 64Cu-1A1P, suggesting
that the additional carboxylate group further stabilized the copper
chelate. There was no significant difference in the tumor-to-blood
and tumor-to-muscle ratios for 64Cu-AP-1 and 64Cu-KP-1 at 1, 4, and 24 h p.i. (Figure 7);
however, tumor-to-blood ratio of 64Cu-1A1P was significantly
higher than both 64Cu-AP-1 and 64Cu-KP-1 at
all time points. Tumor-to-muscle ratios of 64Cu-1A1P were
significantly higher than both 64Cu-AP-1 and 64Cu-KP-1 at 1 and 24 h p.i. (P < 0.001); however,
there was no significant difference at 4 h p.i. (P > 0.05). At 1 h p.i., the tumor-to-kidney ratio of 64Cu-1A1P was significantly higher than those of both 64Cu-AP-1 and 64Cu-KP-1 (P < 0.001).
The tumor-to-kidney ratio of 64Cu-AP-1 and 64Cu-KP-1 were not significantly different (P >
0.05)
at 1 h. At 4 h, 64Cu-1A1P and 64Cu-KP-1 had
similar tumor-to-kidney ratios (P > 0.05), which
were significantly higher than 64Cu-AP-1 (P < 0.05). At 24, tumor-to-kidney ratios were not significantly
different for the three tracers. At 1 and 24 h, the tumor-to-liver
ratios of the three tracers followed the trend, 64Cu-1A1P > 64Cu-KP-1 > 64Cu-AP-1. At
4 h,
the tumor-to-liver ratio of 64Cu-KP-1 was significantly
higher than for 64Cu-AP-1 (P < 0.05),
while there was no significant difference between 64Cu-KP-1
and 64Cu-1A1P (P = 0.32, Figure 8).
Figure 6
Biodistribution of 64Cu-1A1P, 64Cu-AP-1,
and 64Cu-KP-1 in sstr2-transfected HCT116 tumor-bearing
female nu/nu mice at 1 and 24 h (A), and at 4 h with and without 20
μg of Y3-TATE co-injected as a blocking agent (B). N = 4 for each time point.
Figure 7
Tumor-to-organ ratios of 64Cu-1A1P, 64Cu-AP-1,
and 64Cu-KP-1 with sstr2-transfected HCT116 tumor-bearing
female nu/nu mice. ***: significantly different (P < 0.001). **: significantly different (0.001 < P < 0.01). *: significantly different (0.01 < P < 0.05). ns: no significant difference (P >
0.05). n = 4 mice per time point.
Figure 8
Clearance profiles of 64Cu-1A1P (green dots), 64Cu-AP-1 (red dots), and 64Cu-KP-1 (blue dots).
***: significantly
different (P < 0.001). **: significantly different
(0.001 < P < 0.01). *: significantly different
(0.01 < P < 0.05). ns: no significant difference
(P > 0.05).
Biodistribution of 64Cu-1A1P, 64Cu-AP-1,
and 64Cu-KP-1 in sstr2-transfected HCT116tumor-bearing
female nu/nu mice at 1 and 24 h (A), and at 4 h with and without 20
μg of Y3-TATE co-injected as a blocking agent (B). N = 4 for each time point.Tumor-to-organ ratios of 64Cu-1A1P, 64Cu-AP-1,
and 64Cu-KP-1 with sstr2-transfected HCT116tumor-bearing
female nu/nu mice. ***: significantly different (P < 0.001). **: significantly different (0.001 < P < 0.01). *: significantly different (0.01 < P < 0.05). ns: no significant difference (P >
0.05). n = 4 mice per time point.The blood clearance of 64Cu-AP-1 and 64Cu-KP-1
was similar from 1 to 4 h p.i., which was significantly slower than
the blood clearance of 64Cu-1A1P (P <
0.001, Figure 8). By 4 h, all three tracers
showed similar uptake in the blood (P = 0.16). The
slower blood clearance of 64Cu-AP-1 was possibly due to
the increased hydrophobicity of the tracer; while the slower blood
clearance of 64Cu-KP-1 was also possibly due to the PEG
linker. At 1 h, the liver uptake of 64Cu-AP-1 was significantly
higher than that of 64Cu-KP-1 and 64Cu-1A1P
(P < 0.001), while that of 64Cu-KP-1
and 64Cu-1A1P were similar. At 4 and 24 h, 64Cu-KP-1 showed lower uptake in the liver than 64Cu-AP-1
and 64Cu-1A1P (P < 0.01). At early
time points, the kidney clearance rate followed the trend, 64Cu-1A1P > 64Cu-KP-1 > 64Cu-AP-1. At 1
h, all
three tracers showed similar tumor uptake (P = 0.62).
At 4 and 24 h, 64Cu-1A1P showed significantly higher tumor
uptake than 64Cu-KP-1 and 64Cu-AP-1 (P > 0.01, Figure 8). Compared
with 64Cu-AP-1, the addition of an extra carboxylate group
and the
PEG linker dramatically improved the pharmacokinetic profile of 64Cu-KP-1.Clearance profiles of 64Cu-1A1P (green dots), 64Cu-AP-1 (red dots), and 64Cu-KP-1 (blue dots).
***: significantly
different (P < 0.001). **: significantly different
(0.001 < P < 0.01). *: significantly different
(0.01 < P < 0.05). ns: no significant difference
(P > 0.05).
Small Animal PET/CT Imaging
Small animal PET/CT imaging
after administration of the three tracers in the sstr2-transfected
HCT116tumor-bearing mice was performed at 2 h p.i. In one group of
mice, Y3-TATE was co-injected with the radiotracers to block the sstr2-specific
binding of the tracers. At 2 h, the tumor SUVs for 64Cu-AP-1, 64Cu-KP-1, and 64Cu-1A1P were 4.6 ± 0.8 (n = 2), 3.2 ± 0.2 (n = 2), and 2.8
± 0.4 (n = 2), respectively. Consistent with
the biodistribution data, the PET/CT images of the tracers showed
high tumor uptake at 2 h p.i. with more than 90% of the uptake blocked
by co-injected Y3-TATE (Figures 9 and S4, Supporting Information).
Figure 9
Small animal PET/CT imaging
of 64Cu-AP-1 (SUV = 4.6
± 0.8, n = 2), 64Cu-KP-1 (SUV = 3.2
± 0.2, n = 2), and 64Cu-1A1P (SUV
= 2.8 ± 0.4, n = 2) at 2 h p.i. The images of
mice injected with the three tracers are scaled the same (from 0 to
10%ID/cc). Mice injected with unlabeled Y3-TATE to block specific
uptake of the tracers had tumor SUVs for 64Cu-AP-1, 64Cu-KP-1, and 64Cu-1A1P of 0.47 ± 0.18, 0.21
± 0.06, and 0.19 ± 0.02, respectively (Figure S4, Supporting Information).
Small animal PET/CT imaging
of 64Cu-AP-1 (SUV = 4.6
± 0.8, n = 2), 64Cu-KP-1 (SUV = 3.2
± 0.2, n = 2), and 64Cu-1A1P (SUV
= 2.8 ± 0.4, n = 2) at 2 h p.i. The images of
mice injected with the three tracers are scaled the same (from 0 to
10%ID/cc). Mice injected with unlabeled Y3-TATE to block specific
uptake of the tracers had tumor SUVs for 64Cu-AP-1, 64Cu-KP-1, and 64Cu-1A1P of 0.47 ± 0.18, 0.21
± 0.06, and 0.19 ± 0.02, respectively (Figure S4, Supporting Information).
Discussion
G-protein-coupled receptors are the most
targeted proteins for
currently used drugs. Among the five subtypes of somatostatin receptors
which share common signaling pathways in inhibiting adenylate cyclase,
modulating mitogen-activated protein kinase, and activating phosphotyrosine
phosphatase, sstr2 has been most widely investigated due to its overexpression
in many neuroendocrine tumors, its inhibition of cell growth regulation,
suppressive effect on pancreatic cancer,[30] and antiproliferative effect on medullary thyroid carcinoma.[31] Because to the best of our knowledge there is
no available crystal structure for sstr2, targeting this GPCR for
drug discovery has revolved around modifications of its native ligands.
Theoretical modeling has emerged as a powerful approach to simulate
the native structures of GPCRs, which can aid in the rational design
of ligands at the molecular level. Because somatostatin receptors
are about 40% identical to the opioid receptors,[25] we used the crystal structures of opioid receptors to construct
the 3D structures of sstr2. After the structures were evaluated and
stereochemistry analyzed, the most reliable model was selected for
the ligand design based on molecule docking and validated with known
sstr2 ligands (Figure S9, Supporting Information).
The docking result of the agonist, Y3-TATE, showed that this ligand
was located deep inside the receptor and revealed an unoccupied pocket
next to the d-phenylalanine of Y3-TATE. Although it is known
that substitution at this position is well tolerated, the size of
the moiety that can be accommodated at this position has not been
widely investigated. The somatostatin analogues were designed based
on modifications at N-terminus of Y3-TATE to introduce different phosphonate-containing
cross-bridged chelators through bioorthogonal SPAAC, which incorporates
larger linkers than have previously been investigated.The docking
of the designed ligands (1A1P, AP, KP) showed binding
affinity similar to that of sstr2 (docking scores higher than 10),
suggesting that all ligands were worthy of further investigation.
Notably, our docking studies revealed a common amino acid residue
of sstr2, Asn276, which interacts with all of the peptidomimetics
that were docked through hydrogen bonding. This is consistent with
previous reports that indicated the importance of this amino acid
residue on the selectivity of octreotide for sstr2.[32] The consistency of the computational docking for the reported
site-directed mutagenesis data indirectly validated our model and
the docking method, which may be an effective tool for future sstr2
ligand design and structure–activity studies even in the absence
of a crystal structure.Neuroendocrine tumors have been clinically
imaged with sstr2 specific
ligands labeled with 111In, 68Ga, 18F, and 64Cu for diagnosis and selection of patients for
peptide receptor radionuclide therapy.[33]177Lu- and 90Y-labeled sstr2 ligands had been
successful used clinically and showed great promise as radiotherapeutic
agents.[23]64Cu-labeled sstr2
specific ligands are unique in that they are potentially theranostics
agents, allowing for diagnosis and therapy using the same radiotracer
and providing accurate and direct dosimetry measurement to plan therapeutic
doses of tracers for each individual patient. Alternatively, targeted
radiotherapy could be achieved with 67Cu (100% β–, t1/2 = 62 h),[34,35] which is advantageous in having a longer half-life, higher abundance
of β–, and less radiation from gamma photons
compared to 64Cu.As the commonly used copper chelator,
DOTA, suffers from significant
in vivo dissociation of copper ion, better copper chelators have been
designed to improve the in vivo stability of the copper complex. CB-TE2A-conjugated
somatostatin analogue formed kinetically stable chelate with Cu(II).[28,36] However, the extended labeling time at high temperature for 64Cu-labeled CB-TE2A conjugate is not optimal for future clinical
use. More recently, we reported CB-TE1A1P–Y3-TATE that can
be labeled under milder conditions.[7] The
caveat of this agent is that the synthesis is challenging, with long
reaction time and low chemical yield.Click chemistry is among
the most efficient ways of conjugating
chelators with biomolecules. Although clickable chelators have been
synthesized and conjugated with biomolecules through Cu-catalyzed
click chemistry, there are fewer reported biological evaluations on
these bioconjugates.[37] For copper-64-based
radiopharmaceuticals, SPAAC has advantages over CuAAC, because SPAAC
obviates the need to remove copper ion from the final product when
unprotected copper chelators are applied.[14,38] Commercially available DBCO derivatives have been used in SPAAC;
however, DBCO may significantly change the binding affinity, solubility,
and pharmacokinetics of the imaging probe.[19] Presumably, the smaller the targeting molecule, the more severe
its influence will be. Therefore, modeling was performed to determine
whether modifications to the N-terminus with the bulky DBCO group
would be tolerated. The in silico docking supported that the modifications
were unlikely to cause drastic changes in binding affinities. A PEG
linker was incorporated into KP to lessen the impact of the hydrophobic
DBCO on the pharmacokinetics of the tracer.The lack of regioselectivity
of SPAAC must be considered when using
this approach in the design of molecular imaging agents. Unlike the
copper-catalyzed click chemistry which generally forms only a single
1,4-regioisomer,[39] or Ru-catalyzed click
chemistry which generally forms the 1,5-regioisomer,[40] because of the lack of regioselectivity, SPAAC produces
both 1,4- and 1,5-regioisomers, complicating the purification and
potentially complicating future regulatory approval for translation
to the clinic. In addition to the two regioisomers produced by SPAAC,
the cross-bridged clam chelators have two enantiomers, producing a
total of four possible isomers after conjugation to the peptidomimetic.
Here we evaluated all the HPLC-separated isomers in vitro. Although
we found that the more hydrophobic isomers bound more receptor sites
(higher Bmax), they also easily aggregated
in aqueous solution. Therefore, we chose the most hydrophilic tracers
for in vivo studies to explore the feasibility of using DBCO-modified
cross-bridged phosphonate-based chelators for imaging sstr2 by PET.Another concern of introducing the bulky hydrophobic DBCO to the
biomolecule is the likelihood of increased nonspecific binding and
slower clearance profile of the bioconjugate. This was not a major
problem for hydrophilic biomolecules such as galacto-RGD peptide.[20] The log D values of the sstr2-targeted
regioisomers, which reflect the hydrophilicity of the molecule, were
also considered for choosing agents for in vivo evaluation. The most
hydrophilic isomers of AP and KP were evaluated in PET/CT imaging
and biodistribution studies.Copper ion accumulation in the
liver at later time points has been
proposed to reflect the in vivo stability of copper complexes and
their biomolecule conjugates.[36] The lower
liver uptake of 64Cu-KP-1 compared to 64Cu-AP-1
and 64Cu-1A1P at 24 h p.i. suggests that the extra carboxyl
group of KP increased the in vivo stability. This was consistent with
the in vivo studies comparing CB-TE2A with its analogue bearing an
extra carboxyl group, CB-TE2A-PA.[41] The
chelator CB-TE1K1P has an advantage over the recently reported CB-TE2A-PA
in that it can be labeled at much milder conditions (70 °C, 5
min vs 95 °C, 30 min). Future studies include comparing the in
vivo stability of the CB-TE1K1P-based tracers with the CB-TE2A-PA-based
tracers. Future plans are to investigate other nonclick chemistry
type linking groups between CB-TE1K1P and receptor-targeted peptides.
Conclusion
Here we demonstrate the application of in silico analysis to predict
the successful application of SPAAC to design sstr2-targeted agents
that can be readily synthesized in high yields with phosphonate-based
cross-bridged chelators for labeling with 64Cu under mild
conditions. DBCO–CB-TE1A1P (AP) and DBCO–CB-TE1K1P (KP)
were conjugated to azide-modified Y3-TATE efficiently in 72% and 43%
isolated yields, which is in significantly higher yield than direct
conjugation through peptide bond formation (7% isolated yield).[7] PET/CT imaging of sstr2-positive tumors in mice
showed specific tumor uptake and good contrast of tumor to background
for both 64Cu-AP-1 and 64Cu-KP-1; however, 64Cu-1A1P, where the chelator is directly conjugated to Y3-TATE,
showed higher tumor to nontumor ratios than the clicked bioconjugates.
With the rapid development of the SPAAC reagents, further improvement
on the pharmacokinetics of the bioconjugates derived from our new
generation chelators could arise from using more hydrophilic strained
alkynes as the coupling partner.[44] These
results demonstrate the potential for using SPAAC chemistry in conjugation
of copper chelators to biomolecules for molecular imaging.
Experimental Section
Unless otherwise
specified, all reagents and solvents were purchased
from Sigma-Aldrich Chemical Co. (St. Louis, MO). Matrigel was purchased
from BD Biosciences, Bedford, MA. Reactions were monitored by TLC
on 0.25 mm silica gel glass plates containing F-254 indicator. Visualization
by TLC was monitored by UV light, KMnO4, or radioactivity.
Flash chromatography was performed using 200 mesh silica gel. 1H NMR spectra were recorded on a Bruker DRX 400 MHz NMR spectrometer
(Billerica, MA). 13C NMR spectra were obtained at 100 MHz.
ESI-MS were obtained on a Waters LCT-Premier XE LC-MS station (Milford,
MA). 64CuCl2 was purchased from Washington University
School of Medicine (St. Louis, MO) and University of Wisconsin—Madison
(Madison, WI). Aqueous solutions were prepared using ultrapure water
(resistivity, 18 MΩ). The Wang resin (loading, 0.61 mmol/g)
and all Fmoc-protected amino acids were purchased from Chem-Impex
International, Inc. (Wood Dale, IL). Reversed-phase high-performance
liquid chromatography (HPLC) were performed either on a Waters 600E
(Milford, MA) chromatography system with a Waters 991 photodiode array
detector and an Ortec model 661 (EG&G Instruments, Oak Ridge,
TN) radioactivity detector, or a Waters 1525 Binary HPLC pump (Milford,
MA) with a Waters 2489 UV/visible detector and a model 105-S-1 (Carroll&Ramsey
Associates; Berkeley, CA) radioactivity detector. HPLC samples were
analyzed on an analytical C18 column (Phenomenex, Torrance, CA) and
purified on a semipreparative C18 column (Phenomenex, Torrance, CA).
H2O (0.1% TFA; solvent A) and acetonitrile (0.1% TFA; solvent
B) were used as mobile phase. All final compounds were at least 95%
pure by HPLC analysis. Radioactive samples were counted using an automated
well-type gamma-counter (8000; Beckman, Irvine, CA). PET/CT data were
acquired using an Inveon preclinical PET scanner (Siemens Medical
Solutions, Erlangen, Germany).
Animal Model
All animal studies
were conducted according
to the procedures outlined by the University of Pittsburgh and Washington
University Institutional Animal Care and Use Committees (IACUC). Human
colorectal HCT116 cells (kindly provided by Dr. Bert Vogelstein, Johns
Hopkins University) were transfected with sstr2 as previously described.[29] Cell media (Iscove’s) was obtained from
Gibco (Carlsbad, CA) and supplemented with 10% fetal bovine serum
(FBS, Gibco) and 1 mM Zeocin (Gibco). Female, mice 4–6 weeks
old athymic nude from Taconic (Hudson, NY) were injected with 0.8–1.2
million sstr2-transfected HCT116tumor cells mixed with Matrigel and
were allowed to grow for 9–12 days.
3D Protein Structure Prediction
for sstr2
The known
crystal structures of opioid receptors were used to construct the
3D structures of sstr2. These receptors and their structures used
in our studies are nociceptin/orphanin FQ receptor (NOP, PDB entry: 4EA3, resolution: 3.01),
μ-opioid receptor (MOR, PDB entry: 4DKL, resolution: 2.80), κ-opioid receptor
(KOR, PDB entry: 4DJH, resolution: 3.01), and δ-opioid receptor (DOR, PDB entry: 4EJ4, resolution: 3.40).
These structures were retrieved from the Protein Data Bank (http://www.pdb.org/pdb/) and were then prepared by SYBYL-X 1.3. The whole sequence of sstr2
was retrieved from the UniProtKB/Swiss-Prot (http://www.uniprot.org/uniprot/P30874).Sstr2 belongs to class A family of GPCRs, which shares high
sequence similarities with other GPCR structures. Sequence alignments
of sstr2 and the known crystal structure of GPCR revealed that sstr2
has a moderate sequence identity similarity: ∼40% to nociceptin/orphanin
FQ receptor (NOP, PDB entry: 4EA3, resolution: 3.01), ∼44% to μ-opioid
receptor (MOR, PDB entry: 4DKL, resolution: 2.80), ∼41% to κ-opioid
receptor (KOR, PDB entry: 4DJH, resolution: 3.01), 42% to δ-opioid receptor
(DOR, PDB entry: 4EJ4, resolution: 3.40), ∼34% to chemokine receptor CXCR4 (PDB
entry: 3ODU,
resolution: 2.50), ∼28% todopamine D3 receptor (D3R, PDB entry: 3PBL, resolution: 2.89),
27% to humanbeta2-adrenergic receptor (PDB entry: 2RH1, resolution: 2.40),
∼28% to chemokine receptor CXCR1 (PDB entry: 2LNL, solid-state NMR),
∼22% to human A2A receptor (A2AAR, PDB entry: 2YDO, resolution: 3.00),
∼26% to humanhistamine H1 receptor (H1R, PDB entry: 3RZE, resolution: 3.10),
∼25% to sphingosine 1-phosphate receptor (S1P, PDB entry: 3V2W, resolution: 3.35),
and ∼31% to humanbeta1-adrenergic receptor (PDB entry: 2Y00, resolution: 2.50).Moreover, as one disulfide bridge/bond between Cys115 and Cys193
in sstr2 was suggested by the UniProtKB/Swiss-Prot (http://www.uniprot.org/uniprot/), we adjusted the alignments of sequence of the extracellular loop
2 (ECL2) part manually. For example, for the alignment of sstr2 and
NOP (4EA3), we adjusted the Pro5.50 in sstr2 to align the Pro5.50
in NOP (4EA3). Meanwhile, we also assured that alignments of TMs and
conserved motifs such as “D/ERY” in TM3, “CWFPV″in
TM6, and “NPxxY” in TM7 were reasonable.We used
four crystal structures of opioid receptors to build the
3D structure of sstr2 by using Modeller9.12.1. The protocols in Modeller9.12
for constructing the 3D structures of sstr2 were the following: (1)
downloaded these four structures from Protein Data Bank (PDB); (2)
aligned the templates with the sequence of sstr2; (3) constructed
a 3D structure of sstr2. Once the 3D models were generated, energy
minimization was performed using SYBYL-X 1.32. Powell was used as
the modeling method, with a gradient of 0.5 kcal/mol, 5000 maximum
iterations, in MMFF94s force field with MMFF94 charges.Structural
evaluation and stereochemical analyses were performed
by using proSA-web for Z-scores and PROCHECK for Ramachandran plots
(Figures S7 and S8, Supporting Information).
Root mean squared deviation (RMSD), superimposition of query and template
structure, and visualization of generated models were performed using
UCSF Chimera 1.8.1. The model with lowest RMSD was selected as the
candidate structure for sstr2.Molecular docking was performed using
the Tripos Surflex-docking program to investigate the detailed interaction
between our compounds and sstr2.[22,32] The initial
binding pocket of this peptide was subsequently characterized to be
nearby Asn276 and Phe294 according to site-directed mutagenesis data.
Molecular surface analysis was performed by MOLCAD to find a solvent-accessible
cavity around these two key residues. Model validation was performed
by docking with known sstr2 ligands and comparing the docking score
with experimental Ki values (Figure 9S, Supporting Information).
Synthesis of
DBCO–CB-TE1A1P, and DBCO–PEG4–CB-TE1K1P
CB-TE1A1P was synthesized as previously reported with minor modifications.[6] The synthesis of DBCO–CB-TE1A1P, CB-TE1K1P,
and DBCO–PEG4–CB-TE1K1P was performed following our
recently published procedure.
Synthesis of N3-Y3-TATE
Y3-TATE on resin
was synthesized by standard Fmoc solid-phase peptide synthesis on
a CEM microwave peptide synthesizer (Matthews, NC). 6-Azidohexanoic
acid was incorporated as the last “amino acid” by a
standard peptide coupling protocol, with HBTO and DIEA used as activator
and base, respectively. The peptide was cleaved with a cocktail comprising
TFA/TIPS/PhOH/H2O (85:5:5:5), precipitated with diethyl
ether, and purified with semipreparative HPLC under isocratic conditions
(30% ACN in H2O, with 0.1% TFA). The isolated yield was
30%. ESI-MS [M + H]+: observed, 1188.2; calculated, 1188.5.
Synthesis of CB-TE1A1P–DBCO–Y3-TATE (AP)
N3-Y3-TATE (0.31 μmol) was mixed with DBCO–CB-TE1A1P
(0.31 μmol) in 1 mL of t-BuOH/H2O (1:1). The mixture was heated at 40 °C for 1.5 h. Reversed-phase
analytical HPLC of a small aliquot of the crude reaction mixture showed
complete conversion. The crude reaction product was diluted with water
and purified with reversed-phase semipreparative HPLC under isocratic
conditions (30% ACN in H2O with 0.1% TFA). The isolated
yield was 72%. Three peaks were resolved and separated. ESI-MS [M
+ H] +: observed, 1824.8; calculated, 1825.0.
Synthesis of
CB-TE1K1P–PEG4–DBCO–Y3-TATE
(KP)
N3-Y3-TATE (0.98 μmol) was mixed with
CB-TE1K1P–PEG4–DBCO (0.75 μmol) in 1 mL of t-BuOH/H2O (1:1). The mixture was heated at 40
°C for 1.5 h, diluted with water, and purified by reversed-phase
semipreparative HPLC, using isocratic conditions (30% ACN in H2O, with 0.1% TFA). HPLC showed complete conversion. Two peaks
were resolved and separated. The isolated yield was 43%. ESI-MS [M
+ H] +: observed, 2216.4; calculated, 2216.8.
Radiolabeling
of CB-TE1A1P–Y3-TATE (1A1P), CB-TE1A1P–DBCO–Y3-TATE
(AP), and CB-TE1K1P–PEG4–DBCO–Y3-TATE (KP)
64Cu-1A1P, 64Cu-KP, or 64Cu-AP
(1 nmol) was labeled with 64Cu(OAc)2 (30–37
MBq) by incubation in 100 μL of 0.1 M NH4OAc (pH
8.1) for 5 min at 90 °C. Radiochemical purity was confirmed by
radio-TLC or radio-HPLC. The labeling kinetics of 64Cu-KP
and 64Cu-AP at lower temperatures were also measured (Figures S5, Supporting Information).
Cell Internalization
Cell internalization assays were
performed as previously described.[7] Briefly,
aliquots of sstr2-transfected HCT116 cell suspension were placed in
12-well plates. 64Cu-1A1P, 64Cu-KP, or 64Cu-AP was added to a final concentration of 4 nM. A 1000-fold
excess of Y3-TATE was used as blocking agent to determine nonspecific
binding and internalization. At 15, 30, 60, 120, 240 min after addition
of radiotracers, the surface-bound and internalized radioactivity
was measured with a gamma counter (Packard II gamma counter). Total
protein concentration in the cell lysate was determined using the
BCA Protein assay (Pierce Biotechnology, Rockford, IL). Results were
normalized to the administered activity and content of protein.
Saturation Binding Assay
Cell membrane was prepared
from sstr2-transfected HCT116 cells and was used for binding assays.
Saturation binding assays were performed using freshly prepared cell
membrane in Eppendorf tubes, following the previously described protocol
with some modifications.[45] Briefly, Eppendorf
tubes were saturated with binding buffer containing 0.1% BSA for 30
min. 64Cu-1A1P, 64Cu-KP, or 64Cu-AP
were added in increasing concentrations (0.1–10 nM), followed
by the addition of 15 μg of sstr2-transfected HCT116 membranes.
After 2 h incubation at room temperature, the pellets were precipitated
and washed twice with 300 μL of binding buffer, followed by
centrifuging at 7000 rpm for 4 min. The pellets were transferred to
tubes for counting in a gamma counter (Packard II gamma counter).
Log D Measurements
Radiolabeled bioconjugates
(5 μL) were added to 1 mL of PBS (pH 7.4) and 1 mL of octanol.
The mixture was vortexed for 10 min and then centrifuged for 10 min.
Both layers were counted in an automated gamma counter. The log D was calculated based on formula of log D = log([M]oct/[M]aq). Data are presented as
mean of triplicate measurements.The biodistribution studies were carried
out as previously described.[28] The tracers
(1.85 MBq) were injected into sstr2-transfected HCT116tumor-bearing
female nu/nu mice via the tail vein. The most hydrophilic isomers
of 64Cu- AP and 64Cu- KP were evaluated and
compared to 64Cu- 1A1P. At 1, 4, and 24 h p.i., mice were
sacrificed, and selected organs were removed, weighed, and counted
on a gamma counter (PerkinElmer Wizard2, Waltham, MA). A blocking
study was conducted at 4 h postinjection to confirm the specificity
of the tracers for binding to sstr2 by co-injecting 20 μg of
Y3-TATE with the radiotracers.Small animal PET/CT imaging
was performed as previously described.[28] Briefly, the radiotracers (3.7 MBq) were injected via tail vein
and imaged at 2 h p.i. A blocking study was performed by co-injecting
20 μg of Y3-TATE with the radiotracers. Static imaging was performed
on an Inveon PET/CT scanner[46,47] with 10 min PET scanning
followed by 5 min CT. Inveon Research Workplace (IRW) from Siemens
Healthcare Global was used for coregistration of PET/CT images and
quantification of regions of interest (ROI). PET/CT images were reconstructed
with maximum a posteriori (MAP), 3D ordered-subset expectation maximization
(OSEM3D), 2D ordered-subset expectation maximization (OSEM2D), and
filtered back projection (2DFBP). Standard uptake values (SUV) were
generated by measuring ROI from PET/CT images and calculated with
the formula: SUV = [nCi/ml] × [animal weight
(g)]/injected dose [nCi].
Statistical Methods
All of the data were presented
as mean ± standard deviation. Two-tailed unpaired t tests were performed using GraphPad Prism to generate P values. When comparing more than two columns, one-way ANOVA analysis
with Tukey post-test was performed with α = 0.05 (95% confidence
intervals), α = 0.01 (99% confidence intervals), and α
= 0.001 (99.9% confidence intervals).
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Authors: Federico Tagliati; Maria Chiara Zatelli; Arianna Bottoni; Daniela Piccin; Andrea Luchin; Michael D Culler; Ettore C Degli Uberti Journal: Endocrinology Date: 2006-04-06 Impact factor: 4.736
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Authors: Brian M Zeglis; Christian Brand; Dalya Abdel-Atti; Kathryn E Carnazza; Brendon E Cook; Sean Carlin; Thomas Reiner; Jason S Lewis Journal: Mol Pharm Date: 2015-08-31 Impact factor: 4.939