Structure-Based Discovery of a Subtype-Selective Inhibitor Targeting a Transient Receptor Potential Vanilloid Channel

Article abstract of DOI:10.1021/acs.jmedchem.8b01496

Discovery of potent selective inhibitors targeting a protein from a highly conserved family is challenging. Using a strategy combining structural and evolutionary information, we discovered transient receptor potential (TRP) subtype-selective inhibitors (transient receptor potential vanilloid type 2 (TRPV2) inhibitors). We unveiled three ligand-binding sites of TRPV2 and compounds that bind to these sites. Structural optimization of the best-hit compound provided a potent selective TRPV2 inhibitor, SET2. The molecular basis and subtype-selective inhibition mechanism were quantitatively characterized and experimentally verified. Then, as an effective chemical probe, SET2 was used to investigate the function role of TRPV2. SET2-induced inhibition of TRPV2 reduced prostate cancer migration, which indicated TRPV2 as an antimetastasis therapeutic target. In addition, functional assays suggested that TRPV2 was coupled to a validated metastasis mediator, LPAR1. The discovery of the potent selective inhibitor potentially leads to novel avenues for pharmacological applications and therapeutic development targeting the TRPV2 channel.

Full text of DOI:10.1021/acs.jmedchem.8b01496

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Article
Structure-based discovery of a subtype-selective inhibitor
targeting a transient receptor potential vanilloid channel
Hao Chai, Xi Cheng, Bin Zhou, Lifen Zhao, Xianhua Lin, Dongping Huang, Weiqiang
Lu, Hao Lv, Feng Tang, Qiansen Zhang, Wei Huang, Yang Li, and Huaiyu Yang
J. Med. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jmedchem.8b01496 • Publication Date (Web): 08 Jan 2019
Downloaded from http://pubs.acs.org on January 9, 2019
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Structure-based discovery of a subtype-selective inhibitor targeting a
transient receptor potential vanilloid channel
Hao Chai,†,§,‡ Xi Cheng,†,‡ Bin Zhou,†,§,‡ Lifen Zhao, Xianhua Lin, Dongping Huang,
†
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†,§
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†,§,*
Yang Li,†,§,*
Weiqiang Lu, Hao Lv, Feng Tang, Qiansen Zhang, Wei Huang,
&
Huaiyu Yang#,*
†
State Key Laboratory of Drug Research and CAS Key Laboratory of Receptor
Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555
Zuchongzhi Road, Shanghai 201203, China.
#
Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and
School of Life Sciences, East China Normal University, 500 Dongchuan Road, Shanghai
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§
00241, China.
University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049,
China
‡ These authors contributed equally to this work.
*
To whom correspondence should be addressed.
KEYWORDS: cancer, drug design, G-protein coupled receptor, transient receptor
potential channel, lysophosphatidic acid
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ABSTRACT: Discovery of potent selective inhibitors targeting a protein from a highly
conserved family is challenging. Using a strategy combining structural and evolutionary
information, we discovered TRP subtype-selective inhibitors (TRPV2 inhibitors). We
unveiled three ligand-binding sites of TRPV2 and compounds that bind to these sites.
Structural optimization of the best-hit compound provided a potent selective TRPV2
inhibitor, SET2. The molecular basis and subtype-selective inhibition mechanism were
quantitatively characterized and experimentally verified. Then, as an effective chemical
probe, SET2 was used to investigate the function role of TRPV2. SET2-induced
inhibition of TRPV2 reduced prostate cancer migration, which indicated TRPV2 as an
anti-metastasis therapeutic target. And functional assays suggested that TRPV2 was
coupled to a validated metastasis mediator, LPAR1. The discovery of the potent selective
inhibitor potentially leads to novel avenues for pharmacological applications and
therapeutic development targeting TRPV2 channel.
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INTRODUCTION
Subtype-selective compounds are of great therapeutic importance. However, given high
similarity among protein members of a conserved family, development of subtype-
selective compounds represents a very challenging task. As the most widely used
approach in drug development, experimental high-throughput screening only has a hit
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rate less than 0.02% in discovering subtype-selective compounds. On the other hand, the
rational design approach can significantly improve the efficiency of drug development
and reduces the time and cost by reducing the number of compounds that need be
synthesized.2
Transient receptor potential (TRP) ion channels play crucial roles in nociception, taste
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perception, thermosensation, and mechano- and osmolarity sensing. However, due to
high conservation among TRP channels, it is difficult to develop selective compounds
targeting a particular member of this family, which leads to a major disadvantage in the
therapeutic development of TRP channels. The transient receptor potential vanilloid type
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(TRPV2) channel is a TRP channel participating in metastasis of various cancers.4-7
Yet, TRPV2 has no potent selective modulator. Until now, a diphenyl compound, i.e.
tranilast, has been used in several reports as a TRPV2-specific antagonist. Tranilast has a
half-maximal inhibition concentration (IC ) of more than 10 μM and has not been fully
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validated as a direct TRPV2 blocker. Ruthenium red can potently inhibit TRPV2 with an
IC of approximately 0.6 μM, but it is a non-selective blocker of several TRP channels.
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For a long time, the development of TRPV2 selective compounds has been unsuccessful
due to the high structural homology among transient receptor potential vanilloid (TRPV)
subfamily members, especially TRPV1-TRPV4. All of these channels are homotetramers
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with ion pathway located at the four-fold symmetry.9-17 Surrounded by transmembrane
helices S1-S4, the ion pathway of a TRPV channel is formed by the transmembrane
helices S5-S6, pore helices and the intervening loops in the assemble tetramer.
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In this study, using a protocol based on structural and evolutionary information, we
identified three functional ligand-binding sites of the TRPV2 channel and discovered the
inhibitors that bind to these sites. Then, we optimized the best hit and developed a highly
potent selective antagonist SET2. Using SET2 as a probe, we characterized the
interaction between the inhibitor and the TRPV2 channel at atomic level and revealed the
mechanism of subtype selectivity among the TRPV channels. The potential role of
TRPV2 as an anti-metastasis target was investigated with SET2. Furthermore, we found
the functional coupling of the TRPV2 channel to the lysophosphatidic acid receptor 1
(LPAR1) might be critical in cancer progression.
RESULTS
Discovery of druggable sites and antagonists targeting these sites
The study started with the identification and characterization of drug-binding pockets.
Two difficult aspects have to be considered: (i) the identification of candidate pockets
that are likely to bind small subtype-selective drug-like compounds; (ii) the ranking of
candidate pockets, which depends on whether the pockets might regulate the protein
function. Recent tremendous advances in structural biology have provided valuable
information for structure-based pocket detection methods to identify unique pockets that
accept small molecular compounds. The evolutionary analysis methods, such as
conservation analysis, have been widely used to unveil functionally important hotspots,
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especially catalytic sites and ligand-binding sites. Thus, integrating the structural-based
pocket detection method with the evolutionary analysis in virtual screening may facilitate
the development of subtype-selective compounds.
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First, we performed multiple sequence alignment of TRPV1-TRPV6 channels. Since
functionally important residues are more conserved, Jensen-Shannon divergence-based
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conservation analysis was used to locate the top 30% ranked conserved residues of
TRPV2 in multiple sequence alignment. Then, all unique residues of TRPV2 were also
identified in multiple sequence alignment to reveal the hotspots, which might bind to the
subtype-selective compounds. In the second stage, a structure-based pocket detection tool
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Fpocket was used to generate a pool consisting of potential ligand binding pockets on
all available wild-type (WT) full-length TRPV2 structures. Both unique residues and
conserved residues ranked in the top 30% were mapped onto these ligand-binding
pockets. Finally, three pockets (A, B and C) containing the largest numbers of conserved
residues and at least two unique residues were detected (Figure 1A and Supporting
Information Table S1).
We performed virtual screening targeting the selected pockets A, B and C. More than
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00,000 commercial compounds from the Specs database were screened against each site.
Fifty structure-diverse and drug-like compound candidates were selected for bioassay. In
whole-cell voltage clamp experiments on HEK293T cells transiently transfected with
TRPV2, six compounds (SET1, SEA6, SGE9, SGG5, SGH0 and SHB9) displayed
inhibitory effects on the current of TRPV2 (Figure 1b). According to the virtual screening
models, SET1 and SGH0 bound to pocket A, SEA6 and SGG5 bound to pocket B, and
SGE9 and SHB9 bound to pocket C. To validate these models, we designed eight
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mutations involving the following pocket residues: I165A (pocket B), Y330A (pocket B),
S465A (pocket C), F467A (pocket A), L470A (pocket A), E468A (pocket C), Q525A
(pocket A), and I661A (pocket C). The functionality of these mutants remained intact
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(Supporting Information Table S2). Compared with the WT TRPV2 channel, these
mutants were less sensitive to corresponding hits (Supporting Information Figure S1).
Among these six hits, SET1 is the most potent antagonist of the TRPV2 channel (Figure
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b-d). However, because the aqueous solubility of SET1 is poor, we were not able to test
this compound on TRPV2 at high concentrations (more than 10 μM).
Figure 1. TRPV2 inhibitors and their binding sites. (a) Three druggable sites of the
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TRPV2 channel. Two TRPV2 structures (protein data bank (PDB) codes: 5AN8 , 5HI9 )
were employed to identify druggable sites. The protein is shown in cartoon. Ligand
binding pockets A, B and C are displayed in the surface depiction. Four different subunits
of TRPV2 are shown in different colors. (b) Inhibitory effects of the six compounds on
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TRPV2. HEK293T cells overexpressing TRPV2 were treated with 10 μM SET1, SGH0,
SEA6, SGG5, SGE9 or SHB9, respectively (n = 5). The data are shown as the mean ±
standard error of mean (SEM) (c) Dose-dependent inhibition of TRPV2 by SET1 (n = 5).
The data are shown as the mean ± SEM. (d) Chemical structure of SET1.
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Identifying SET2 as a novel selective antagonist of TRPV2
To obtain antagonists with better solubility and potency, we designed and synthesized
ten analogues of SET1 (Figure 2a). The most potent and soluble compound SET2, which
has a tertiary amine instead of the phenyl group in SET1 (Figure 2b-d), inhibited TRPV2
channels with an IC of 0.46 ± 0.01 μM (Figure 2d). We then evaluated the subtype
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selectivity of SET2. TRPV1, TRPV3 and TRPV4 channels are the closet homologs of
TRPV2. Similar to the TRPV2 channel, both TRPV1 and TRPV3 can be activated by 2-
aminoethoxydiphenylborate (2-APB). TRPV4 can be activated by GSK-1016790A.
Using HEK293T cells expressing TRPV1, TRPV3 or TRPV4, we found that none of
TRPV1, TRPV3 or TRPV4 was sensitive to SET2 (Figure 2d and Supporting Information
Figure S2). These results suggested SET2 as a potent selective TRPV2 antagonist. Based
on the activities of SET1-SET11, it seems that the 4-position substituent of the
pyrimidine prefers alkylamino groups rather than rigid ring structures for TRPV2 binding.
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Figure 2. SET2 as a potent selective TRPV2 antagonist. (a) Chemical structures of SET1
and its analogues. (b) Inhibitory effects of 1 μM SET1 or its analogues on TRPV2
channel (n = 4). (c) Dose-dependent inhibition of TRPV2 channel by SET1, SET2 and
SET3 (n = 4). The data are shown as the mean ± SEM. (d) Representative whole-cell
current traces recorded from HEK293T cells overexpressing TRPV1, TRPV2 or TRPV3
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under SET2 treatments. Currents were evoked by 2-APB. (e) Dose-dependent inhibition
of TRPV2 by SET2 (n = 5).
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Characterization of the TRPV2/SET2 binding mode
After discovering a selective potent TRPV2 inhibitor, we paid attentions to
characterization of the TRPV2/SET2 binding mode. We combined several advanced
modeling methods with a mutagenesis approach. First, Glide standard molecular docking
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analysis indicated the insertion of SET2 in pocket A, which is the SET1-binding site.
Then, considering the receptor flexibility and environmental effects, the RosettaLigand
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program and RosettaMembrane energy function were used to build accurate ligand-
binding models (Figure 3a and Supporting Information Figure S3). In these models, the
furan ring of SET2 pointed downward to a cavity between the S4-S5 linker and S5 of an
adjacent subunit, while the pyrimidine group extended upwards between S3-S4 of one
subunit and between S5-S6 of the adjacent subunit (Figure 3a). To identify the key
protein residues interacting with SET2, we decomposed the binding energies of the
models on a per-residue basis. Tyr466, Phe467, Gln525 and Leu470 had low van der
Waals (VDW) energy scores (less than -1.0 in Rosetta energy units (REU)), suggesting
that they might be the main contributors to the binding of SET2 (Figure 3b). We mutated
these four residues into alanine, respectively. Compared with the WT TRPV2, the
TRPV2 mutants F467A, Q525A and L470A were less sensitive to SET2 (Figure 3c). We
could not observe the effects of SET2 on Y466A, because it was not activated by 2-APB.
These results supported the predicted SET2-binding model. In this model, Phe467,
Gln525 and Leu470 stabilized the orientation of the SET2 pyrimidine group in the
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transmembrane pocket (Figure 3a). These mutagenesis studies of TRPV2 validated that
SET2 bound to the site used for virtual screening.
We also used explicit (all-atom) molecular dynamics simulations to simulate the
process of SET2 antagonizing the TRPV2 channel. In the simulations, the dominant pose
of SET2 was similar to the one observed in the docking model (Figure 3a and Supporting
Information Figure S4). We found that SET2 also frequently interacted with the S5 and
S6 helices of the adjacent subunit (Val538, Phe542, Leu627 and Leu631) (Supporting
Information Figure S4). Since the central ion-conductive pore region includes the S5 and
S6 helices, SET2 might stabilize the channel in the resting state and might prevent
channel activation upon binding to the transmembrane pocket (Supporting Information
Table S3).
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Mechanism of the subtype selectivity
Elucidating the subtype selectivity mechanism of homologous proteins is always
challenging. After validating the binding site of SET2 on TRPV2, it is possible to
elucidate the subtype selectivity by comparing TRPV2 with other TRPV channels. None
of TRPV1, TRPV3 or TRPV4 is sensitive to SET2 (Figure 2 and Supporting Information
Figure S2). For TRPV3 or TRPV4, it is most likely that its low similarity to TRPV2 in
the transmembrane domains leads to the distinct channel sensitivity towards SET2. In
contrast, the TRPV1 channel is structurally similar to the TRPV2 channel, with 43%
amino acid sequence identity in the transmembrane domains. We performed sequence
alignment between TRPV1 and TRPV2, and found three unique residues Phe467, Leu505
and Gln525 within the SET2-binding TRPV2 pocket (Figure 3d).
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We first made mutagenesis study on TRPV2. We substituted these residues (Phe467,
Leu505 and Gln525) of TRPV2 with the corresponding residues (Ser513, Thr551 and
Glu571) in TRPV1. Compared with the WT TRPV2, the TRPV2 mutants F467S and
L505T were less sensitive to SET2 (Figure 3c). SET2 had decreased activities on both
F467A and F467S mutants, which suggested the importance of Phe467 in the interaction
with the SET2 molecule. In addition, a hydrophobic leucine was more favorable than a
polar threonine at the residue position 505 for SET2-binding possibly because the
hydrophobic side chain of Leu505 stabilized the pyrimidine group of SET2 (Figure 3a).
We could not observe the effects of SET2 on Q525E, since this mutant was rapidly
desensitized to 2-APB. SET2 did not inhibit the mutant Q525A, as shown above.
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TRPV1 is not sensitive to SET2. We tried to identify TRPV1 mutants that are sensitive
to SET2. Along with the mutations of TRPV2, such mutations of TRPV1 could provide
very important information of the subtype selectivity mechanism. Because Phe467 and
Leu505 are unique and crucial residues for SET2 binding in the TRPV2 channel, we
substituted the corresponding residues in TRPV1 (Ser513 and Thr551) to design a double
mutation of TRPV1, i.e., S513F/T551L. As shown in Figure 3g, the S513F/T551L mutant
was inhibited by SET2, indicating that this ligand bound to the transmembrane pocket of
the TRPV1 mutant. We also tested S513F and T551L single-point mutants in bioassays.
While S513F was not sensitive to SET2, T551L was inhibited by SET2 at high
concentrations (no less than 1 μM) (Supporting Information Figure S5). To further
characterize the structural basis for this gain-of-function mutation, we built models of the
S513F/T551L mutant and performed docking simulations of SET2 to these models. In the
docking models, both Phe513 and Leu551 had low VDW energy scores (less than -1.0
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REU), suggesting that they made significant hydrophobic contributions to SET2 binding.
In the WT TRPV1, the corresponding residues Ser513 and Thr551 have polar side chains,
which might interfere in the interactions with the hydrophobic pyrimidine groups and
furan ring of the SET2 molecule. These identified gain-of-function mutations of TRPV1
further convincingly demonstrate the binding site and the subtype selectivity mechanism.
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Figure 3. Inhibition of WT TRPV2, mutant TRPV2 and mutant TRPV1 channels by
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SET2. (a) Binding of SET2 to the TRPV2 channel (PDB code: 5AN8 ). The protein is
shown in cartoon. SET2 and the residues involved in binding are displayed as sticks. (b)
Distributions of the average VDW interactions between SET2 and TRPV2 (top 10
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docking models). (c) Dose-dependent inhibition of WT and mutant TRPV2 channels by
SET2 (n = 4-6). (d) Sequence alignment of the transmembrane pockets of the TRPV1 and
TRPV2 channels. Unique residues are colored in red. (e) Binding of SET2 to the TRPV1
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S513F/T551L mutant channel (PDB code: 5AN8 ). Residues Phe513 and Leu551 are
highlighted in yellow. (f) Distributions of average VDW interactions between SET2 and
the TRPV1 S513F/T551L mutant channel (top 10 docking models). (g) Dose-dependent
inhibition of the WT and S513F/T551L mutant TRPV1 channels by SET2 (n = 4-5).
Unpaired t-test was used for statistical analysis [t (8) = 3.572 for 0.3 μM SET2-treatment,
t (7) = 8.933 for 0.1 μM SET2-treatment, t (6) = 3.780 for 3.0 μM SET2-treatment, t (8) =
3.174 for 10.0 μM SET2-treatment]; * indicates P < 0.05, ** indicates P < 0.01, ***
indicates P < 0.005. The data are shown as the mean ± SEM.
Functional role of TRPV2 in metastasis revealed by SET2
4
TRPV2 has high expression levels in metastatic prostate cancers. It has been reported
that small-interfering RNA (siRNA) silencing of the TRPV2 reduces cancer cell
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migration. Therefore, TRPV2 is a potential anti-metastasis target. In accordance with
5
previous reports, our semi-quantitative reverse transcription polymerase chain reaction
(RT-PCR) and immunoblotting analysis of the human prostate cancer cell line PC-3M
revealed the expression of TRPV2 (Supporting Information Figure S6a, b). And our
transwell-based cell migration assays showed that the siRNA silencing of TRPV2
reduced PC-3M migration (Supporting Information Figure S6c, d). SET2 treatment had
no significant influence on the migration of the PC-3M that were transfected with siRNA
(siTRPV2) (Supporting Information Figure S6c, d). In contrast, SET2 treatment
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abrogated the migration of PC-3M cells expressing TRPV2 (Figure 4a, b). Remarkably,
SET2 had no significant effect on cell survival at all tested concentrations (Figure 4c).
These results supported that the negative modulation of TRPV2 by small molecules
inhibited the migration of prostate cancer cells, confirming TRPV2 as an anti-metastasis
target.
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Figure 4. Effects of SET2 treatment on the migration of prostate cancer cells. (a)
Representative images showing SET2 inhibition of prostate cancer cell (PC-3M)
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migration. For PC-3M migration assessment, PC-3M cells (8×10 ) cells were allowed to
migrate for 24 hours with the indicated treatments. (b) Migration ratios of PC-3M after
treatment with SET2 at different concentrations (n = 3). One-way ANOVA with
Dunnett’s multiple comparison test was used for statistical analysis [F (4, 15) = 141.2].
The data are shown as the mean ± SEM; ** indicates P < 0.01. (c) Cell viability of PC-
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M after treatments with SET2 for 48 hours (n = 3).
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As an effective chemical tool, SET2 facilitated the mechanism study of TRPV2 in
simulating cancer cell migration. The lysophosphatidic acid (LPA) signaling increases
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cancer cell migration in numerous ways. It has been reported that LPA can indirectly or
directly up-regulate TRPV1.23, 24 Considering high homology between TRPV1 and
TRPV2, LPA might also regulate TRPV2. To validate this assumption, we used SET2
and LPA to treat PC-3M in migration assays. Consistent with previous reports,25, 26 after
treating 0.1 μM LPA, a significant LPA-induced increase in cell migration was observed
(Figure 5a, b). Pretreatment with SET2 reduced the LPA-induced migration of PC-3M,
suggesting that TRPV2 participated in the LPA-induced signal process. Next we studied
whether LPA directly regulate TRPV2. The effects of LPA on TRPV2 were investigated
using patch-clamp recordings. LPA failed to directly activate or potentiate TRPV2
(Supporting Information Figure S7). These observations indicated that LPA indirectly
regulated TRPV2 through an upstream effector expressed in PC-3M cells. In the RT-PCR
and immunoblotting analysis of PC-3M, we found that a G-protein coupled receptor of
LPA, i.e. LPAR1, was highly expressed (Supporting Information Figure S6e, f). We
treated PC-3M with a selective LPAR1 antagonist AM966 in a cell migration assay and
observed that LPA-induced cell migration was abolished by AM966 (Figure 5a, b). These
findings indicated that LPA activated LPAR1 to induce PC-3M cell migration. Altogether,
migration assays suggested that both TRPV2 and LPAR1 participated in LPA-induced
PC-3M cell migration.
We further studied the relationship between LPAR1 and TRPV2 using patch-clamp
recordings. We assumed that LPA potentiated TRPV2 via regulating LPAR1. In the
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recording experiments, we used HEK293T cells transiently co-transfected with TRPV2
and LPAR1. The TRPV2 agonist 2-APB was used to invoke currents. In co-transfected
cells, 2-APB-evoked currents were inhibited by SET2 (Figure 5c and Supporting
Information Figure S8a), indicating that these currents were primarily carried by TRPV2.
LPA potentiated (2-APB-evoked) TRPV2 currents in the TRPV2/LPAR1 co-transfected
cells (Figure 5c and Supporting Information Figure S8b), but it did not potentiate TRPV2
currents in the TRPV2 transfected cells (Supporting Information Figure S7b, c). These
results supported our assumption that LPA potentiated TRPV2 via modulating LPAR1. In
co-transfected cells, the LPA-induced potentiation of TRPV2 currents was blocked by a
LPAR1 antagonist AM966 (Figure 5c and Supporting Information Figure S8c),
indicating that LPA potentiated TRPV2 by activating LPAR1. We also studied the
relationship between LPAR1 and TRPV2 in calcium responses, which are essential in
cancer cell migration. Application of LPA induced a cytoplasmic calcium increase in PC-
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M (Supporting Information Figure S9). The LPA-induced cytoplasmic calcium
increases were inhibited by the TRPV2 antagonist SET2 (Supporting Information Figure
S9).
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Figure 5. Effects of SET2 and AM966 on the LPA-induced migration of PC-3M. (a)
Representative images showing that SET2 and AM966 inhibited LPA-induced PC-3M
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migration. For the LPA-induced PC-3M migration assay, PC-3M cells (4×10 ) were
allowed to migrate for 24 hours with the indicated treatments. (b) Migration ratios of PC-
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M after treatment with dimethyl sulfoxide (DMSO), LPA, AM966 and SET2 (n = 3).
One-way ANOVA with Dunnett’s multiple comparison test was used for statistical
analysis [F (3, 12) = 30.63]. (c) Effects of LPA, AM966 and SET2 on currents of
HEK293T cells, which were co-transfected with LPAR1 and TRPV2. The currents were
evoked by 2-APB. 3 min after 1 μΜ LPA perfusion on the co-transfected cells, the
currents were significantly increased (n = 10). Both AM966 (n = 7) and SET2 (n = 7)
eliminated the LPA-induced potentiation of currents. On-way ANOVA with Dunnett’s
T3 comparison test was used for statistical analysis [F (3, 30) = 59.49]. The data are
shown as the mean ± SEM. ** indicates P < 0.01, *** indicates P < 0.005.
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Discussion
A solid drug target validation requires both genetic evidence and specific chemical
probe. It is more challenging to discover chemical probes than obtaining genetic
evidence. As a result, there might be a massive genetic evidence of a particular protein
suggesting its association with certain diseases, while its target validation could not be
fully performed due to a lack of chemical probes. Despite decades of studies, the
development of potent selective TRPV2 antagonists has been unsuccessful. New
strategies and information for drug development are urgently needed. In this study, we
introduced Jensen-Shannon divergence-based conservation analysis in the pocket
prediction and successfully identified three pockets containing multiple functionally
important residues. New TRPV2 antagonists with different structure types were
discovered via screening against these pockets, which demonstrates the efficiency of the
strategy in drug development. From the molecular mechanistic point of view, it is
interesting to reveal three ligand-binding sites regulating the gating of TRPV2. Pocket A
includes the S4-S5 linker, a domain known to transduce activation conformational
changes in TRP channels.10, 11, 14, 15, 27, 28 Close to pocket A, pocket C is formed by the
transmembrane helices S1-S4 and the TRP helix following the S6 helix. Pocket B is an
intracellular site involving the N-terminal ankyrin repeat domain (ARD), which is
connected to the S1 helix. The twisting motion of the ARD might trigger the TRP domain,
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which pulls the S6 helix and causes the lower gate to open. Interestingly, these three
proposed druggable pockets comprise three pivotal functional elements the S4-S5 linker,
the TRP helix and the ARD, which are interdependent in TRPV2 gating. These findings
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not only provide new hot spots for drug design but also help us understand the TRP
channel machinery.
Many evidence demonstrate that the TRPV2 expression correlates with tumor grades in
various cancers.4, 30 Previous studies have shown that siRNA mediated silencing of
TRPV2 reduces the growth and migration of metastatic cancer cells in vitro and in vivo.5
Thus, TRPV2 is a potential drug target for cancers. Consistent with results of the gene
silencing assays, we found that SET2 effectively blocked the TRPV2 channel and
reduced basal migration of prostate cancer cells. This result supports TRPV2 as an anti-
metastasis target. Considering the efficiency of SET2, it could also be used in preclinical
validation of TRPV2. And new chemical probes may be developed based on SET2.
LPA has gained immense importance due to its excess production in carcinoma,
glioma, ovarian, prostate, and breast cancers, promoting their invasive properties.31-35
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Several studies have reported that LPA and its receptor LPAR1 regulates the motion
dynamics in cancer cells via mediating cell spreading and lamellipodia formation.36
Moreover, LPA modulates adherent junction disassembly, cytoskeletal disorganization
and formation of focal adhesion in ovarian and colon cancers.36, 37 LPA-mediated
signaling is critical in mediating cancer cell migration, but the downstream effectors in
this signaling pathway remain largely unknown. In this work, we showed that LPA
potentiated TRPV2 via activating LPAR1 and identified the LPA/LPAR1/TRPV2
signaling pathway in the migratory process of prostate cancer cells. Since the
autotaxin/LPA axis is essential in cancer cell migration, identification of TRPV2 as a
downstream mediator in this signaling pathway further validates its importance and
potential as a therapeutic target for cancers. Considering that cancer cell migration
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remains one of the less-understood processes leading to cancer progression, further study
of the LPA/LPAR1/TRPV2 pathway may lead to new therapeutic treatments for cancers.
In summary, by applying an advanced strategy of drug development, we designed a
novel compound SET2, which potently selectively inhibited the TRPV2 channel at
submicromolar concentrations. Combining electrophysiology, mutagenesis and
computational modeling, we revealed the molecular basis of the subtype selectivity of
SET2 at the atomic level. Using SET2 as a chemical probe, we unveiled the functional
coupling between LPAR1 and TRPV2 in the physiological processes of cancer metastasis.
These findings not only demonstrate the feasibility of exploiting the TRPV2 channel as a
therapeutic target for metastatic prostate cancer, but also suggest SET2 as a promising
drug lead and an efficient tool for further target validation studies in the future.
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EXPERIMENTAL SECTION
Material and Instrumentation. All reagents and solvents were commercially
purchased from Sinopharm, Bide Pharmatech Ltd. and Shanghai Titan Ltd. (Shanghai,
China) and used without further purification. Analytical thin layer chromatography
(TLC) was performed on TLC plates precoated with silica gel HSGF254 (200   3 μm
thickness). Analytic RP-HPLC analysis was performed on a Beijing Chuang Xin Tong
Heng LC-3000 (analytic model) instrument with a C-18 column (5 μm, 4.6 x 150 mm) at
o
40 C. The column was eluted with a gradient of 2-90% acetonitrile containing 0.1% TFA
in 30 min at a flow rate of 1 mL/min. HPLC analysis showed that the purity of all the
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final products were more than 95%. H-NMR and C-NMR spectra were recorded on a
BRUKER AscendTM 400 MHz or 600 MHz instrument. Chemical shifts were assigned in
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ppm and coupling constants were assigned in Hz. Constant-time H-NMR and HSQC
were recorded on AVANCE III HD BRUKER AscendTM 600 MHz instrument. ESI-MS
spectra were measured with an Agilent 6230 LC-TOF MS spectrometer.
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N-(furan-2-ylmethyl)-3-((4-(4-methoxyphenyl)-6-(trifluoromethyl)pyrimidin-2-
yl)thio)propanamide (SET1) and other compounds applied in virtual screening were
purchased from Specs. We synthesized 10 analogues of SET1, including N-(furan-2-
ylmethyl)-3-((4-(N’-methyl-N’-propylamino)-6-(trifluoromethyl)-pyrimidin-2-
yl)thio)-propanamide (SET2) (Scheme 1).
OH
F
F
O
F
F
F
F
F
F
F
B
or
H R1
or X
2h-2i
HO
R1
HO
SH
2a-2d
2e-2g
i
4
N
N
O
N
ii
Cl
N
Cl
Cl
N
R1
HO
S
N
R1
1
3a-i, R1=2a-i
5a-j
3
j, R =H
1
F
F
F
R2
SET1-SET9, R =2a-i, R =6a
1
2
NH2
a-b
SET10, R =H, R =6a
7, R =2a, R =6b
6
1
2
O
N
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2
iii
R2
iv
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S
N
R1
SET11, R =2a, R =-CH -COOH
H
1
2
2
R1=
R2=
6a
2
a
2b
2c
2d
O
O
O
O
O
2e
2f
N
2g
N
2h
2i
6b
N
N
O
O
S
O
Scheme 1. Synthesis of derivatives SET1-SET11a.
aReagents and conditions: i) for synthesis of 3a-3d and 3h-3i: 2a-2d or 2h-2i, Trans-
o
Dichlorobis-(triphenyl-phosphine)Palladium(II), 1,4-dioxane, sat. Na CO , 75 C; for
2
3
o
synthesis of 3e-3g: 2e-2g, TEA, DCM, 0 C; ii) 1,8-diazabicyclo[5.4.0]undec-7-ene, 1,4-
o
dioxane, 95 C; iii) EDC, HOBt, TEA, DCM, rt; iv) NaOH, THF/MeOH/H O, rt.
2
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5
6
General Procedures for synthesis of intermediates 3a-3d and 3h-3i. To a solution of
2,4-dichloro-6-(trifluoromethyl)-pyrimidine (1, 1g, 1 eq) in 1,4-dioxane (10 mL), 2a-2d
and 2h-2i (1.1 eq), saturated solution of sodium carbonate (5 mL) and Trans-Dichlorobis-
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
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3
4
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8
9
0
1
2
3
4
5
6
7
8
9
0
(triphenyl-phosphine)Palladium(II) (342 mg, 0.1 eq) were added and the mixture was
stirred at 75℃ for 5 h. After cooled to room temperature, the solution was diluted with
dichloromethane (20 mL) and washed with brine and water successively. The organic
layer was dried over anhydrous sodium sulfate, filtered and evaporated in vacuo. The
residue was subject to chromatography purification through a silica gel column and
eluted with petroleum ether/ethyl acetate (20/1) to give the desired product.
General procedures for synthesis of intermediates 3e-3g. To a solution of 2,4-
dichloro-6-(trifluoro-methyl)pyrimidine (1, 1 g, 1 eq) in dichloromethane (30 mL), 2e-2g
(1.1 eq) and triethylamine (1.4 g, 3 eq) were added and the mixture was stirred under ice-
cooling for 5 h. Then, the solution was diluted with dichloromethane (50 mL) and washed
with brine and water successively. The organic layer was dried over anhydrous sodium
sulfate, filtered and evaporated in vacuo. The residue was subject to chromatography
purification through a silica gel column and eluted with petroleum ether/ethyl acetate
(20/1) to give the desired product.
General procedures for synthesis of SET1-SET10 and intermediate 7. To
synthesize SET1-SET10 and intermediate 7, we prepared the intermediates 5a-j via
chlor-substitution of prior intermediates 3a-i and 3-((4-(trifluoromethyl)-pyrimidin-2-
yl)thio)propanoic acid (3j). First, 3a-j (1 g, 1 eq) and 3-mercaptopropanoic acid (4, 1.1 g,
3 eq) were dissolved in 1,4-dioxane (10 mL) and 1,8-diazabicyclo[5.4.0]undec-7-ene
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(
1.58 g, 3 eq) was added. The solution was stirred at 95 °C for 10 h. After cooled to room
temperature, the solution was diluted with dichloromethane (50 mL) and washed with
brine and water successively. The organic layer was dried over anhydrous sodium sulfate,
filtered and evaporated in vacuo. The residue was subject to chromatography purification
through a silica gel column and eluted with petroleum ether/ethyl acetate (2/1) to give
desired product 5a-j. Then, A mixture of 5a-j (1 eq), furfurylamine or glycinemethylester
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
6
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
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5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
hydrochloride
(6a-b,
2
eq),
1-ethyl-3-(3-dimethylaminopropyl)-carbodimide
hydrochloride (550 mg, 2 eq), 1-hydroxybenzotriazole hydrate (377 mg, 2 eq),
triethylamine (423 mg, 3 eq), and dichloromethane (5 mL) was stirred at room
temperature for 10 h. After complete conversion, the solution was diluted with
dichloromethane (20 mL) and washed with brine and water successively. The organic
layer was dried over anhydrous sodium sulfate, filtered and evaporated in vacuo. The
residue subject to chromatography purification through a silica gel column and eluted
with petroleum ether/ethyl acetate (3/1) to give desired products SET1-SET10 and
intermediate 7.
N-(furan-2-ylmethyl)-3-((4-(4-methoxyphenyl)-6-(trifluoromethyl)pyrimidin-2-
1
yl)thio)propanamide (SET1). Yield (final step) 85%. H NMR (400 MHz, Chloroform-
d) δ 8.14 (d, J = 2.2 Hz, 1H), 8.12 (s, 1H), 7.61 (s, 1H), 7.35 (m, 1H), 7.05 (s, 1H), 7.03
(s, 1H), 6.33 (dd, J = 3.2, 1.8 Hz, 1H), 6.25 (d, J = 3.2 Hz, 1H), 5.91 (s, 1H), 4.48 (d, J =
1
3
5.2 Hz, 2H), 3.92 (s, 3H), 3.55 (t, J = 7.1 Hz, 2H), 2.76 (t, J = 7.1 Hz, 2H). C NMR
(101 MHz, CDCl3) δ 173.1, 170.6, 165.9, 163.1, 156.1, 151.1, 142.2, 129.2, 129.23,
1
27.4, 120.6, 114.5, 114.5, 110.4, 107.4, 106.6, 55.5, 36.5, 36.1, 26.9. ESI-HRMS: calcd.
+
for C H F N O S, 438.1099 (M+H) , found, 438.1098.
2
0
18
3
3
3
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2
2
2
2
2
2
3
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5
5
6
N-(furan-2-ylmethyl)-3-((4-(N’-methyl-N’-propylamino)-6-(trifluoromethyl)-
1
pyrimidin-2-yl)thio)-propanamide (SET2). Yield (final step) 80%. H NMR (400
MHz, Chloroform-d) δ 7.35 (m, 1H), 6.41 (s, 1H), 6.32 (m, 1H), 6.24 (d, J = 3.2 Hz, 1H),
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
6
1
.03 (s, 1H), 4.46 (d, J = 6.8 Hz, 2H), 3.65 (m, 1H), 3.39 (t, J = 7.2 Hz, 2H), 3.33 (m,
H), 3.18-3.06 (m, 3H), 2.69 (t, J = 7.2 Hz, 2H), 1.64 (m, 2H), 0.95 (m, 3H). 13C NMR
(
101 MHz, Chloroform-d) δ 171.2, 161.5, 151.1, 142.2, 122.3, 120.5, 110.4, 107.4, 94.7,
5
1.5, 36.8, 36.5, 35.9, 26.6, 20.4, 11.4. ESI-HRMS: calcd. for C H F N O S, 403.1416
1
7
21
3
4
2
+
[
M+H] , found, 403.1477.
N-(furan-2-ylmethyl)-3-((4-(4-methyl-piperazin-1-yl)-6-(trifluoromethyl)-
1
pyrimidin-2-yl)thio)-propanamide (SET3). Yield (final step) 37%. H NMR (400
MHz, Chloroform-d) δ 7.36 (m, 1H), 6.52 (s, 1H), 6.33 (dd, J = 3.2, 1.9 Hz, 1H), 6.24 (m,
1
H), 6.01 (s, 1H), 4.46 (d, J = 5.6 Hz, 2H), 3.74 (s, 4H), 3.39 (t, J = 7.3 Hz, 2H), 2.68 (t, J
1
3
= 7.2 Hz, 2H), 2.50 (t, J = 5.2 Hz, 4H), 2.36 (s, 3H). C NMR (101 MHz, CDCl3) δ
1
3
4
72.0, 170.9, 161.3, 154.6, 151.1, 142.1, 120.8, 110.4, 107.4, 94.9, 54.4, 54.4, 45.9, 43.9,
+
6.7, 36.5, 29.6, 26.8. ESI-HRMS: calcd. for C H F N O S, 430.1525 [M+H] , found,
1
8
22
3
5
2
30.1542.
N-(furan-2-ylmethyl)-3-((4-(phenyl)-6-(trifluoromethyl)-pyrimidin-2-yl)thio)-
1
propanamide (SET4). Yield (final step) 65%. H NMR (400 MHz, Chloroform-d) δ
8
.14 (m, 2H), 7.68 (s, 1H), 7.62 – 7.57 (m, 1H), 7.57 – 7.51 (m, 2H), 7.35 (m, 1H), 6.33
(dd, J = 3.3, 1.9 Hz, 1H), 6.24 (m, 1H), 5.95 (s, 1H), 4.48 (d, J = 5.5 Hz, 2H), 3.56 (t, J =
13
7
.1 Hz, 2H), 2.76 (t, J = 7.1 Hz, 2H). C NMR (101 MHz, CDCl3) δ 173.5, 170.7, 166.6,
1
56.4, 151.0, 142.2, 135.1, 132.2, 129.2, 129.2, 127.5, 127.5, 120.5, 110.5, 107.6, 107.5,
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+
3
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6.6, 36.1 27.0. ESI-HRMS: calcd. for C H F N O S, 408.0994 [M+H] , found,
19 16 3 3 2
08.1065.
N-(furan-2-ylmethyl)-3-((4-(3,4-dimethoxyl-phenyl)-6-(trifluoromethyl)-
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
6
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
pyrimidin-2-yl)thio)-propanamide (SET5). Yield (final step) 88%. H NMR (400
MHz, Chloroform-d) δ 7.76 (d, J = 2.1 Hz, 1H), 7.71 (dd, J = 8.4, 2.1 Hz, 1H), 7.61 (s,
1
5
2
1
H), 7.35 (m, 1H), 6.99 (d, J = 8.5 Hz, 1H), 6.32 (dd, J = 3.3, 1.9 Hz, 1H), 6.24 (m, 1H),
.90 (s, 1H), 4.47 (d, J = 5.5 Hz, 2H), 4.02 (s, 3H), 3.99 (s, 3H), 3.55 (t, J = 7.2 Hz, 2H),
1
3
.76 (t, J = 7.2 Hz, 2H). C NMR (101 MHz, CDCl3) δ 173.1, 170.6, 165.9, 156.0,
52.7, 151.0, 149.6, 142.2, 127.7, 121.1, 120.6, 111.1, 110.4, 109.8, 107.5, 106.8, 56.1,
+
56.1, 36.5, 36.1, 26.9. ESI-HRMS: calcd. for C H F N O S, 468.1205 [M+H] , found,
2
1
20
3
4
4
4
68.1211.
N-(furan-2-ylmethyl)-3-((4-(4-methyl-phenyl)-6-(trifluoromethyl)-pyrimidin-2-
1
yl)thio)-propanamide (SET6). Yield (final step) 56%. H NMR (400 MHz, Chloroform-
d) δ 8.03 (s, 1H), 8.01 (s, 1H), 7.63 (s, 1H), 7.34 (d, J = 1.8 Hz, 2H), 7.32 (s, 1H), 6.32
(
dd, J = 3.2, 1.9 Hz, 1H), 6.23 (d, J = 3.2 Hz, 1H), 6.07 (t, J = 5.6 Hz, 1H), 4.46 (d, J =
1
3
5
.5 Hz, 2H), 3.53 (t, J = 7.1 Hz, 2H), 2.75 (t, J = 7.1 Hz, 2H), 2.45 (s, 3H). C NMR
(
101 MHz, CDCl3) δ 173.3, 170.6, 166.4, 156.23, 151.1, 143.0, 142.2, 132.3, 129.9,
1
29.94, 127.4, 127.4, 120.5, 110.4, 107.5, 107.21, 36.58, 36.1, 26.9, 21.6. ESI-HRMS:
+
calcd. for C H F N O S, 422.1150 [M+H] , found, 422.1157.
20 18
3
3
2
N-(furan-2-ylmethyl)-3-((4-(morpholin-4-yl)-6-(trifluoromethyl)-pyrimidin-2-
1
yl)thio)-propanamide (SET7). Yield (final step) 40%. H NMR (400 MHz, Chloroform-
d) δ 7.36 (m, 1H), 6.51 (s, 1H), 6.33 (dd, J = 3.2, 1.9 Hz, 1H), 6.24 (m, 1H), 5.98 (s, 1H),
4.46 (d, J = 5.5 Hz, 2H), 3.80 (m, 4H), 3.70 (s, 4H), 3.39 (t, J = 7.3 Hz, 2H), 2.67 (t, J =
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2
2
2
2
2
2
2
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3
3
3
3
3
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3
3
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4
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4
4
4
4
4
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5
5
5
5
5
5
5
5
5
6
13
7
1
.3 Hz, 2H). C NMR (101 MHz, CDCl3) δ 172.1, 170.8, 161.6, 154.7, 151.1, 142.2,
20.7, 110.4, 107.4, 94.8, 94.7, 66.3, 66.3, 44.3, 36.6, 36.6, 26.7. ESI-HRMS: calcd. for
+
C H F N O S, 417.1208 [M+H] , found, 417.1241.
1
7
19
3
4
3
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
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0
1
2
3
4
5
6
7
8
9
0
N-(furan-2-ylmethyl)-3-((4-(thiophen-2-yl)-6-(trifluoromethyl)-pyrimidin-2-
1
yl)thio)-propanamide (SET8). Yield (final step) 46%. H NMR (400 MHz, Chloroform-
d) δ 7.86 (dd, J = 3.8, 1.2 Hz, 1H), 7.61 (dd, J = 5.0, 1.1 Hz, 1H), 7.50 (s, 1H), 7.36 (m,
1
1
2
H), 7.21 (dd, J = 5.0, 3.8 Hz, 1H), 6.34 (dd, J = 3.2, 1.9 Hz, 1H), 6.26 (d, J = 3.2 Hz,
H), 5.93 (s, 1H), 4.49 (d, J = 5.5 Hz, 2H), 3.52 (t, J = 7.2 Hz, 2H), 2.76 (t, J = 7.2 Hz,
1
3
H). C NMR (101 MHz, CDCl3) δ 173.4, 170.6, 161.2, 156.1, 151.1, 142.2, 140.8,
132.1, 129.3, 128.8, 120.3, 110.4, 107.5, 105.9, 36.6, 36.1, 27.0. ESI-HRMS: calcd. for
+
C H F N O S , 414.0558 [M+H] , found, 414.0613.
1
7
14
3
3
2 2
N-(furan-2-ylmethyl)-3-((4-(furan-2-yl)-6-(trifluoromethyl)-pyrimidin-2-yl)thio)-
1
propanamide (SET9). Yield (final step) 78%. H NMR (400 MHz, Chloroform-d) δ
7
6
.64 (m, 1H), 7.55 (s, 1H), 7.40 (m, 1H), 7.33 (m, 1H), 6.62 (dd, J = 3.6, 1.7 Hz, 1H),
.31 (dd, J = 3.3, 1.9 Hz, 1H), 6.23 (m, 1H), 5.95 (s, 1H), 4.46 (d, J = 5.5 Hz, 2H), 3.49
1
3
(
t, J = 7.2 Hz, 2H), 2.71 (t, J = 7.2 Hz, 2H). C NMR (101 MHz, CDCl3) δ 173.2, 170.6,
1
3
57.4, 156.2, 151.0, 150.6, 146.3, 142.2, 120.3, 114.8, 113.1, 110.4, 107.5, 105.7, 36.5,
+
6.1, 27.0. ESI-HRMS: calcd. for C H F N O S, 398.0786 [M+H] , found, 398.0891.
1
7
14
3
3
3
N-(furan-2-ylmethyl)-3-((6-(trifluoromethyl)-pyrimidin-2-yl)thio)-propanamide
1
(SET10). Yield (final step) 85%. H NMR (400 MHz, Chloroform-d) δ 8.76 (d, J = 4.9
Hz, 1H), 7.36 (m, 1H), 7.30 (d, J = 5.0 Hz, 1H), 6.34 (dd, J = 3.2, 1.9 Hz, 1H), 6.28 –
6
.14 (m, 1H), 5.92 (s, 1H), 4.48 (d, J = 5.5 Hz, 2H), 3.49 (t, J = 7.1 Hz, 2H), 2.71 (t, J =
1
3
7.1 Hz, 2H). C NMR (101 MHz, CDCl3) δ 173.8, 170.4, 159.5, 155.8, 151.0, 142.3,
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20.2, 111.9, 110.5, 107.7, 36.6, 35.9, 26.9. ESI-HRMS: calcd. for C H F N O S,
1
3
12
3
3
2
+
32.0681 [M+H] , found, 332.0813.
N-(hydroxycarbonylmethyl)-3-((4-(4-methoxyl-phenyl)-6-(trifluoromethyl)-
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
6
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
pyrimidin-2-yl)thio)-propanamide (SET11). To a solution of SET11 precursor 7 (300
mg, 1 eq) in the mixture of tetrahydrofuran, methanol and water (3:1:1, 5 mL), a proper
amount of 1 M sodium hydroxide solution was added to adjust pH to 12 and the mixture
was stirred for 4 h at room temperature. Then, the solution was diluted with
dichloromethane (10 mL) and washed with brine and water successively which was
furtherly concentrated under reduced pressure. After that, the residue was subject to
chromatography purification through a silica gel column and eluted with petroleum
1
ether/ethyl acetate (2/1) to give SET11 (275 mg, final-step yeild 95%). H NMR (400
MHz, DMSO-d6) δ 8.35 (s, 1H), 8.33 (d, J = 2.1 Hz, 1H), 8.28 (t, J = 5.8 Hz, 1H), 8.17
(s, 1H), 7.14 (d, J = 2.0 Hz, 1H), 7.12 (d, J = 2.1 Hz, 1H), 3.88 (s, 3H), 3.78 (d, J = 5.8
13
Hz, 2H), 3.42 (t, J = 6.9 Hz, 2H), 2.70 (t, J = 7.0 Hz, 2H). C NMR (101 MHz, DMSO) δ
1
5
4
72.6, 171.7, 171.1, 166.1, 163.3, 155.5, 130.2, 130.2, 127.4, 121.0, 115.1, 115.1, 107.9,
+
6.0,41.1, 34.7, 26.8. ESI-HRMS: calcd. for C H F N O S, 416.0892 (M+H) , found,
17 16
3
3
4
16.0834.
Molecular biology and cell transfection. Complementary DNA (cDNA) of the mouse
TRPV1, TRPV2, TRPV3 and TRPV4 channels were subcloned into the pEGFPN1
expression vector (Invitrogen), respectively. cDNA of TRPV2 and cDNA of LPAR1
were co-transfected at a 1:5 ratio. cDNA encoding green fluorescent proteins were used
to facilitate identification of transfected cells. Mutations were introduced into TRPV1 or
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TRPV2 by PCR using the QuickChange XL sitedirected mutagenesis kit (Agilent
Technologies) and were subsequently confirmed by DNA sequencing.
Human embryonic kidney 293T (HEK293T) cells were provided by the Cell Bank of
Chinese Academy of Sciences (Shanghai, China). HEK293T cells were maintained in
Dulbecco’s modified Eagle’s medium/high glucose (Gibco) supplemented with 10% fetal
bovine serum (FBS) (Gibco) and 100 μgml−1 penicillin-streptomycin (Cellgro) in a
0
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humidified incubator at 37 °C (5% CO ). For electrophysiology experiments, cells were
2
plated in 35 mm tissue culture dishes (Corning Incorporated) were transiently transfected
with the plasmids using Lipofectamine 2000 (Life Technologies) following the
manufacturer's protocol. Primers used in this study are listed in Supporting Information
Table S4.
The human prostate cancer cell lines PC-3M were obtained from American Type Cell
Culture (Manassas, Virginia, USA). PC-3M cell line was a metastasis-derived variant of
PC3. The cells were maintained in 1640 medium (Gibco) supplemented with 10% FBS
(
Gibco). PC-3M was cultured in a humidified incubator (5% CO ) at 37 °C.
2
Small interfering RNA transfection. PC-3M, the human prostate cancer line, was
used in the experiment. These cells were grown in Roswell Park Memorial Institute
(RPMI) 1640 Medium (GIBCO, USA) supplemented with 10% FBS in humidified room
air containing 5% CO at 37℃. The day before transfection, PC-3M cells were seeded in
2
6
cm cell culture dishes (Corning, USA) at a density of 106 cells/dish. Cells were
transfected with siRNA (negative control, positive control, TRPV2) and Lipofectamine
RNAi MAX (Invitrogen, USA) according to the manufacturer's protocol. The siRNA
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Page 29 of 44
Journal of Medicinal Chemistry
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sequence were list: siRNA-TRPV2: 5’-UAAGAGUCAACCUCAACUTT-3’, negative
control siRNA: 5’-UUCUCCGAACGUGUCACGUTT-3’, positive control siRNA
(siRNA-β-actin): 5’-UGAAGAUCAAGAUCAUUGCTT-3’. 36 h post-transfection,
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Cells were used.
Electrophysiology. All electrophysiological recordings were obtained using patch-
clamp recordings for macroscopic current dose-response curves. All patch-clamp
recordings were conducted 36-96 h after transfection. Patch-clamp recordings were
performed with Axopatch-200B amplifier and Axon Digidata 1550A driven by
Clampex10 software (Molecular Devices). Membrane potential was held at -60 mV. The
microelectrodes fashioned from 1.5 mm thin-walled borosilicate glass with filament were
pulled from Flaming/Brown type micropipette puller (P-97; SUTTER INSTRUMENT)
with the resistances of 3-7 MΩ for whole-cell recordings. The bath solutions contained
1
65 mM NaCl, 10 mM HEPES, pH 7.3. The pipette solutions contained 140 mM KCl, 10
mM HEPES, pH 7.3. All recordings were performed at room temperature (approximately
5 °C). Temperature variation was less than 1 °C. The current signals were filtered at 1
2
kHz and digitized at a 10 kHz sampling frequency. The bath level was kept as low as
possible to reduce noise.
To apply 2-APB or other drugs during patch-clamp recording, a rapid solution changer
with a gravity-driven perfusion system was used (RSC-200, Bio-Logic). Each solution
was delivered through a separate tube so there was no mixing of solutions. Pipette tip
with a membrane patch or a whole-cell patch was placed right in front of the perfusion
outlet during recording to ensure the solution exchange was complete.
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