Sinefungin derivatives as inhibitors and structure probes of protein lysine methyltransferase SETD2

Article abstract of DOI:10.1021/ja307060p

Epigenetic regulation is involved in numerous physiological and pathogenic processes. Among the key regulators that orchestrate epigenetic signaling are over 50 human protein lysine methyltransferases (PKMTs). Interrogation of the functions of individual PKMTs can be facilitated by target-specific PKMT inhibitors. Given the emerging need for such small molecules, we envisioned an approach to identify target-specific methyltransferase inhibitors by screening privileged small-molecule scaffolds against diverse methyltransferases. In this work, we demonstrated the feasibility of such an approach by identifying the inhibitors of SETD2. N-propyl sinefungin (Pr-SNF) was shown to interact preferentially with SETD2 by matching the distinct transition-state features of SETD2's catalytically active conformer. With Pr-SNF as a structure probe, we further revealed the dual roles of SETD2's post-SET loop in regulating substrate access through a distinct topological reconfiguration. Privileged sinefungin scaffolds are expected to have broad use as structure and chemical probes of methyltransferases.

Full text of DOI:10.1021/ja307060p

Article
pubs.acs.org/JACS
Sinefungin Derivatives as Inhibitors and Structure Probes of Protein
Lysine Methyltransferase SETD2
Weihong Zheng,†,⊥ Glorymar Ibanez,†,⊥ Hong Wu,‡,⊥ Gil Blum,†,§ Hong Zeng,‡ Aiping Dong,‡
́
̃
Fengling Li,‡ Taraneh Hajian,‡ Abdellah Allali-Hassani,‡ Maria F. Amaya,‡ Alena Siarheyeva,‡ Wenyu Yu,‡
Peter J. Brown,‡ Matthieu Schapira,‡ Masoud Vedadi,‡ Jinrong Min,*,‡,∥ and Minkui Luo*,†
†Molecular Pharmacology and Chemistry Program, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, United
States
‡Structural Genomics Consortium, University of Toronto, 101 College Street, Toronto, Ontario, Canada M5G 1L7
§Tri-Institutional Training Program in Chemical Biology, Memorial Sloan-Kettering Cancer Center, New York, New York 10065,
United States
∥Department of Physiology, University of Toronto, Toronto, Ontario, Canada M5S 1A8
S
* Supporting Information
ABSTRACT: Epigenetic regulation is involved in numerous
physiological and pathogenic processes. Among the key
regulators that orchestrate epigenetic signaling are over 50
human protein lysine methyltransferases (PKMTs). Inter-
rogation of the functions of individual PKMTs can be
facilitated by target-specific PKMT inhibitors. Given the
emerging need for such small molecules, we envisioned an
approach to identify target-specific methyltransferase inhibitors
by screening privileged small-molecule scaffolds against diverse
methyltransferases. In this work, we demonstrated the
feasibility of such an approach by identifying the inhibitors of SETD2. N-propyl sinefungin (Pr-SNF) was shown to interact
preferentially with SETD2 by matching the distinct transition-state features of SETD2’s catalytically active conformer. With Pr-
SNF as a structure probe, we further revealed the dual roles of SETD2’s post-SET loop in regulating substrate access through a
distinct topological reconfiguration. Privileged sinefungin scaffolds are expected to have broad use as structure and chemical
probes of methyltransferases.
concentration (IC50) of 0.3 nM. The difference between
DOT1L and other PKMTs also allowed Yao et al.12 to design
5′-aziridine-based SAM analogues as DOT1L-selective inhib-
itors. Apart from the rational design approach, medium- or
high-throughput screening led to the identification of inhibitors
of SET-domain PKMTs, such as chaetocin for Drosophila
melanogaster SU(VAR)3−9 (likely human SUV39H1), BIX-
01294 for G9a (likely its homologue GLP), and AZ505 for
SMYD2.3,13−15 However, the handful of inhibitors cannot
satisfy the increased need for PKMT chemical probes directed
toward understanding the epigenetic roles of more than 50
human PKMTs.3 Since most PKMTs rely on the highly
conserved SET domain for SAM binding and less-structured
regions for substrate recognition, it seems challenging to
develop PKMT inhibitors with both selectivity and potency in a
rational manner.3 In this work, we envisioned an approach to
screen diverse methyltransferases against privileged small-
molecule scaffolds to identify target-specific PKMT inhibitors.
INTRODUCTION
■
Epigenetics involves heritable phenotypic changes that do not
alter the genotype.1,2 Among the essential epigenetic regulators
are diverse post-translational modifiers such as protein lysine
methyltransferases (PKMTs).1−3 The human genome encodes
more than 50 PKMTs, which use S-adenosylmethionine (SAM)
as the cofactor and transfer its sulfonium methyl group to the ε-
amino group of lysine side chains of specific protein substrates.3
PKMT-mediated methylation regulates numerous biological
functions, such as signal transduction, gene transcription, and
protein stabilization.1,2,4 The dysregulation of these events has
been linked to various diseases, including cancer.5,6 In view of
the physiological and pathological relevance of the emerging
epigenetic targets, there is an urgent need for small-molecule
probes to investigate the biochemical properties of individual
PKMTs and to manipulate them pharmacologically.3,5,6
With the exception of DOT1L, which contains a distinct
catalytic domain,7 PKMTs harbor a canonical 130 amino acid
SET domain for SAM binding and enzymatic catalysis.8−10 By
exploiting the distinct SAM-binding motif of DOT1L, Daigle et
al.11 developed the SAM analogue EPZ004777 as a potent
inhibitor of DOT1L with an in vitro half-maximal inhibitory
Received: July 19, 2012
Published: October 8, 2012
© 2012 American Chemical Society
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Figure 1. Structures of a proposed transition state of protein lysine methylation and sinefungin analogues as the transition-state mimics. The
transition state features classical hydrophobic interactions/hydrogen bonds with the lysine side chain of the substrate and nonclassical C−O
hydrogen bonds with the sulfonium methyl moiety of SAM. Sinefungin (2) and its analogues 3a−d are expected to capture certain transition-state
characters of specific PKMTs.
Scheme 1. Synthesis of Sinefungin Analogues 3a−d
Enzymatic transition-state theory argues that even closely
related enzymes may adopt distinct transient structures along
the reaction path of enzymatic catalysis and thus could be
selectively inhibited by structurally matched small mole-
cules.16,17 Molecular dynamics modeling and static structures
of PKMTs suggest that transition-state stabilization at
substrate−cofactor interfaces of PKMTs involves both classical
hydrophobic interactions/hydrogen bonds with the lysine side
chain of substrates and nonclassical C−O hydrogen bonds with
the sulfonium methyl moiety of SAM (Figure 1).18,19 Here we
envisioned the development of N-alkyl sinefungins as PKMT
inhibitors by capturing certain transition-state characters
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Figure 2. Inhibition profile of sinefungin and its analogues 3a−d against a panel of methyltransferases. (a) The magnitude of IC50 of sinefungin and
its analogues 3a−d is presented against 15 phylogenetically arrayed methyltransferases (their IC50 values are listed in Table S1). The increased
diameters and darkness of the circles reflect higher potency (lower IC50) and larger sizes of the inhibitors, respectively. (b) Representative IC50
curves of sinefungin and its analogues 3a−d against SETD2 with the values of 28.4 1.5, >100, 8.2 1.2, 0.80 0.02, and 0.48 0.06 μM for
sinefungin and 3a−d, respectively. (c) IC50 curves of Pr-SNF 3c against representative methyltransferases with the values of 0.80 0.02 μM for
SETD2, 2.2 0.4 μM for SET7/9, 3.0 0.3 μM for CARM1, 9.5 0.4 μM for PRMT1, >100 μM for SET8, G9a, and GLP.
(Figure 1). To achieve high affinity to specific PKMTs, such
sinefungin analogues are expected to position their secondary
amines at the substrate−cofactor interface and the N-alkyl
chains at the lysine-binding pocket for optimal interactions
(Figure 1).
corresponding haloalkanes (methyl/ethyl iodide, benzyl bro-
mide) to afford 5a, 5b, and 5d, respectively. In contrast to the
ready alkylation of 4 to 5a, 5b, and 5d, the reaction of 4 with
iodopropane was sluggish (<15% yield), likely because of the
low reactivity of the haloalkane. To circumvent this problem
and achieve the preparation of 3c, we adopted an alternative
strategy involving ozonolysis of the terminal alkene of 4
followed by Me2S workup in the presence of methanol to yield
6,34 which was then alkylated using more reactive allyl iodide to
furnish 7 (the allyl group served as the precursor of Pr-SNF’s
N-propyl moiety). Primary alcohols 8a−d were obtained via
ozonolysis of terminal-alkene-containing 5a, 5b, and 5d and I2-
facilated acetal deprotection of 7,35 followed by hydride
reduction. Mesylation of 8a−d and subsequent iodination
afforded 9a−d. The chiral amino acid moiety of 3a−d was
Human SETD2 is a tumor-suppressing PKMT implicated in
p53-dependent gene regulation, transcription elongation, and
intron−exon splicing.20−26 Aberrant activities of SETD2 and its
homologues NSD1/2/3 have also been implicated in various
developmental syndromes and cancers.20,27−32 Here we report
that N-alkyl sinefungin analogues act as SETD2-specific
inhibitors by matching distinct transition-state characters of
SETD2. With the aid of N-propyl sinefungin (Pr-SNF, 3c;
Figure 1), we further revealed that the post-SET loop of
SETD2 goes through a remarkable reconfiguration for inhibitor
binding, substrate recognition, and enzymatic catalysis. Since
structurally diverse sinefungin variants can be examined in a
similar manner, the sinefungin-based scaffolds are expected to
display broad utility as structure or pharmacological probes of
protein methyltransferases.
introduced using the Schollkopf bis-lactim ether chiral auxiliary
̈
in the synthesis of 10a−d.36,37 These intermediates were
processed into 11a−d and then 12a−d after hydrolytic removal
of the pyrazine and isopropylidene, protection of the amino
moiety with a benzyloxycarbonyl (Cbz) group, acetylation of
the ribosyl hydroxyl moieties, and then incorporation of N6-
benzoyladenine under Vorbruggen conditions.33 Further
RESULTS
̈
■
conversion of 12a−d by sequential treatments with K2CO3
(to remove acetates), hydrazine (to remove the methyl ester
and N6-benzoyl group), and Pd-catalyzed hydrogenolysis (to
remove Cbz selectively and reduce the allyl group) yielded the
desired final products 3a−d in overall yields of 7−11% from 4
(Scheme 1; also see the Supporting Information).
Synthesis of Sinefungin Analogues 3a−d. With
sinefungin as a privileged small-molecule scaffold to screen
PKMT inhibitors, sinefungin analogues 3a−d were prepared
from the reported D-ribose derivative 4 (Scheme 1).33 To
access N-alkyl (alkyl = methyl, ethyl, benzyl) analogues 3a, 3b,
and 3d, the common precursor 4 was alkylated with the
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Figure 3. Structures of SETD2 in complex with SAH and Pr-SNF. (a) Overall crystal structures of SETD2 in complex with SAH (left) and Pr-SNF
3c (right). Here the catalytic domain of human SETD2 (residues 1435−1711) contain the N-terminal extension motif, AWS domain (orange), SET
domain (light green), and post-SET motif (cyan) with the ligands (SAH or Pr-SNF) highlighted. (b) Superposition of the binary complexes of
SAH−SETD2 (blue-yellow, PDB code 4H12), Pr-SNF−SETD2 (green-white, PDB code 4FMU), and H3K9me2−GLP (mauve-magenta, PDB code
2RFI). Overlaid structures between SAH−SETD2 and H3K9me2−GLP show that the autoinhibitory loop in the SAH−SETD2 complex and its
R1670 (blue) bind the site that would be otherwise occupied by the substrate (magenta) of GLP. In contrast, the loop and its characteristic R1670
are repositioned in the structure of Pr-SNF−SETD2 (green) and overlaid with the post-SET helix (mauve) for binding substrate. (c) Superposed
structures of the inactive binary complex SAH−SETD2 (blue, PDB code 4H12) and its homologues, ASH1L (green, PDB code 3OPE) and NSD1
(orange, PDB code 3OOI). The three PKMTs have the similar autoinhibitory topology with their post-SET loops. (d) The key residues to stabilize
the alternative configuration of the post-SET loop and interact with Pr-SNF’s N-propyl chain. In the SETD2−Pr-SNF (right) but not SETD2−SAH
(left) binary complex, SETD2’s post-SET loop is glued at a hydrophobic core consisting of Tyr1604, Tyr1666, Phe1668, Leu1689, and the
hydrocarbon side chain of Arg1670. In the SETD2−Pr-SNF, the N-propyl moiety was buried in the hydrophobic binding pocket formed by SETD2’s
Tyr1579, Tyr1605, Met1627, Phe1650, Phe1664, and Tyr1666.
Pr-SNF (3c) and N-Benzyl Sinefungin (3d) as Potent,
Selective Inhibitors of SETD2. With sinefungin and its
derivatives 3a−d, we examined their inhibition profile against a
panel of human methyltransferases, including 10 SET-domain
PKMTs (SET7/9, SET8, EZH2, MLL, GLP, G9a, SUV39H2,
SETD2, SUV420H1, and SUV420H2) as well as 5 non-SET-
domain PKMTs (PRMT1, PRMT3, CARM1, DOT1L, and
DNMT1) (Figure 2). Among the 5 × 15 panel of small
molecules and enzymes, 3c (Pr-SNF) and 3d displayed 2−200-
and 10−100-fold preferences, respectively, to SETD2 over
other examined methyltransferases (Figure 2a and Table S1).
The potency of 3c and 3d against SETD2 (apparent IC50 of 0.8
0.2 and 0.48 0.06 μM, respectively) is more than 10-fold
higher than that of sinefungin 2, 3a, and 3b (Figure 2b and
Table S1). This structure−activity relationship (SAR) indicated
that the N-propyl/benzyl moieties of 3c and 3d, in contrast to
the free amine of sinefungin 2 and N-methyl/ethyl groups of 3a
and 3b, contribute to the tight interaction with SETD2. For
other examined methyltransferases in the 5 × 15 assay panel
against 3a−d, only SET7/9 and CARM1 show modest μM
range IC50 of 1.4−3.0 μM, which are not significantly different
from IC50 of the parent compound sinefungin 2, a pan-
methyltransferase inhibitor (Figure 2c and Table S1).3 With the
exception of SETD2 among the examined 15 methyltrans-
ferases, appending the small alkyl moieties (e.g., methyl/ethyl/
propyl groups) to sinefungin deteriorates or has no effect on its
IC50 (Table S1). In contrast, the strong preference of 3c and 3d
against SETD2, together with their well-correlated SAR,
presents the two sinefungin derivatives as SETD2-specific
inhibitors with decent potency and selectivity.
Pr-SNF as a Structure Probe Specific for SETD2’s
Active Conformer. To elucidate the molecular mechanism of
the potency and selectivity of the sinefungin derivatives as
SETD2 inhibitors, we solved the structures of the binary
complexes of SETD2’s catalytic domain (AWS, SET, and post-
SET motifs) with S-adenosyl-L-homocysteine (SAH, which was
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Figure 4. Effects of SETD2’s enzyme catalysis. Methylation activities of SETD2 and its mutants were measured through the filter paper assay with
[3H-Me]-SAM as cofactor. The F1668A, Q1669A, R1670G/A/V/L/I/F/P/W/K/Q, and Y1671A mutations are within SETD2’s post-SET loop,
which regulates substrate access. The barely detectable methylation activities of SETD2’s F1668A. Q1669A and Y1671A mutants are consistent with
their roles on either stabilizing SETD2’s active open conformer or interacting with substrate. SETD2’s 1670 site can tolerate modest hydrophobic
substitutions (e.g., A/V/I/L/F) but not extreme ones (e.g., G/P/W).
degraded from SAM under the crystallization condition,
Methods section) and Pr-SNF 3c (Figure 3a). In the presence
of SAH, SETD2 adopts a compact configuration with its AWS
motif and post-SET motif interwoven with the central SET
domain. The SAH molecule is located within a deep pocket
formed between SETD2’s SET and post-SET domains, as
conserved among all known SET-domain PKMTs (e.g., SET7/
9, SET8, G9a, GLP, MLL, SUV39H2, SUV420H1, and
SUV420H2).9,38,39 However, the SETD2−SAH binary complex
is distinct by its autoinhibitory post-SET loop, which is
positioned to prevent substrate binding, and its characteristic
Arg1670 residue located in the pocket that is otherwise
occupied by substrate lysine (Figure 3b). Such autoinhibitory
topology has also been reported for NSD1 and ASH1L, two
closely related homologues of SETD2, and proposed to
regulate the access of substrates to the PKMTs (Figure 3c,
S2).10,40−42
Although the overall structure of the binary complex of
SETD2 with Pr-SNF 3c is similar to that with SAH, a
remarkable difference was revealed at the post-SET motif of
SETD2 in complex with Pr-SNF (Figure 3b,d). The overlaid
structures of SETD2 with Pr-SNF and SAH showed that the
Pr-SNF’s propyl group partially extends into the lysine-binding
pocket (Figure 3b,d). To accommodate this N-propyl moiety,
which would otherwise clash with the Arg1670 residue in the
SETD2−SAH complex, SETD2 orients this arginine 15 Å away
from the lysine-binding pocket by flipping the otherwise
autoinhibitory post-SET loop (Figure 3d). This reconfiguration
also vacates SETD2’s catalytic site for the entry of substrates
(this site is occupied by the post-SET loop in the SETD2−SAH
complex). To stabilize this substrate-accessible configuration in
the SETD2−Pr-SNF binary complex, SETD2’s post-SET loop
is glued at a newly formed hydrophobic core through Tyr1604,
Tyr1666, Phe1668, Leu1689, and the hydrocarbon side chain of
Arg1670 (Figure 3d). The structure overlay with the substrate-
bound GLP further revealed that Gln1669/Tyr1671 in the
SETD2’s post-SET loop and the helix between SETD2’s
Glu1588−Asn1599 region are topologically comparable to
GLP’s Arg1214/Ile1218 and GLP’s Ser1132−Glu1138 helix
region (Figure 3b).43,44 Given that these residues of GLP play
the key role on substrate recognition,43,44 the comparable
regions of SETD2 (Gln1669/Tyr1671 in the post-SET loop;
the helix of aa 1588−1599) are expected to participate in
substrate binding in a similar manner. Comparing the overlaid
structures of Pr-SNF−SETD2 and SAH−SETD2 also revealed
a 45° rotation of Tyr1666 residue, although its biological
relevance remains unknown. Collectively, these results showed
that SETD2’s methyltransferase domain can adopt at least two
alternative conformations through flipping its post-SET loop:
an autoinhibitory close conformation and a substrate-accessible
open conformation. Here Pr-SNF 3c plays a key role as a
structure probe through its preferential interaction with the
latter.
Effects of Mutations of SETD2’s Post-SET Loop on
Enzyme Catalysis. Structural analysis of SETD2 underscored
the importance of SETD2’s post-SET loop to receive substrate.
To confirm the role of SETD2’s post-SET loop, we mutated
SETD2’s F1668, Q1669, R1670, and Y1671 residues to alanine
(Figure 4). The barely detectable methylation activities of
SETD2’s F1668A and Q1669A/Y1671A mutants are consistent
with their proposed roles in stabilizing SETD2’s active open
conformer and interacting with substrate, respectively. In
contrast, SETD2’s R1670A mutant partially retains the
methylation activity. To further examine the role of this
residue in enzyme catalysis, Arg1670 was systematically
replaced with nonpolar/hydrophobic amino acids G/V/I/L/
P/F/W as well as polar amino acids K/Q. The overall activity
profile indicated that SETD2’s Arg1670 site can tolerate
modest (e.g., A/V/I/L/F) but not extreme hydrophobic
substitutions (e.g., G/P/W) (Figure 4). This observation is
consistent with the role of the hydrocarbon portion of
Arg1670s side chain to stabilize SETD2’s active open
conformer by interacting with the nearby hydrophobic core.
Such interaction is expected to be partially maintained by
replacing the arginine with certain hydrophobic residues
(Figure 3d). The complete loss of activity of SETD2’s
R1670Q mutant versus partial loss of the activity of the
R1670K/A/V/I/L/F mutant also suggests that both the charge
and the hydrophobic side chain of SETD2’s Arg1670 play
certain roles on the enzyme catalysis (Figure 4). These
mutagenesis results therefore confirm the roles of SETD2’s
post-SET loop and its Arg1670 on substrate interaction, as
revealed above by SETD2’s structures.
Characterization of Pr-SNF as a SETD2 Inhibitor via
Enzyme Kinetics. The structure of the Pr-SNF−SETD2
binary complex suggests that, to accommodate Pr-SNF, SETD2
needs to adopt the catalytically active open configuration with
its post-SET loop aligned for substrate entry. Given the present
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Figure 5. Methylation kinetics of SETD2. The kinetic analysis was carried out with varied concentrations of substrate and cofactor in the absence (a)
or presence (b) of Pr-SNF. (a) Initial velocities for SETD2-mediated methylation were measured to generate the Lineweaver−Burk curve versus the
concentration of the SAM cofactor (0.25−1.5 μM) (left) or the concentration of the H3K36 peptide substrate (0.25−1.5 μM) (right). The linear
regressions, which converge on the x axis in both cases, suggest a random sequential mechanism. Km,SAM = 1.21 0.05 μM, Km,Substrate = 0.42 0.02
μM, α = 1, and kcat = 0.14
0.1 min−1 were obtained by plotting the slopes of the Lineweaver−Burk double reciprocal curves against the
concentrations of SAM and substrate (Figure S1a and SI). (b) Double reciprocal plots of initial velocities of SETD2-mediated methylation versus the
concentration of substrate or SAM in the presence of Pr-SNF (0−1.5 μM) were generated by varying the concentration of substrate (0.25−5 μM)
(left) in the presence of the fixed concentration of SAM (0.8 μM) or by varying the concentration of cofactor (0.5−4 μM) in the presence of the
fixed concentration of the substrate (4 μM) (right). The linear regressions, converging on the negative x axis against substrate and on the y axis
against SAM, are consistent with a noncompetitive mechanism between Pr-SNF and substrate and a competitive mechanism between Pr-SNF and
SAM. Kd = 360 15 nM and βKd = 43 4 nM (β = 0.12 0.01) were obtained by plotting the slopes of the double reciprocal curves against the
concentration of Pr-SNF (Figure S1b and SI). (c) Overall mechanisms and kinetic parameters of SETD2-mediated methylation in the absence or
presence of Pr-SNF. SETD2-mediated methylation goes through a random sequential mechanism and can be inhibited by Pr-SNF via forming either
the Pr-SNF−SETD2 binary or the Pr-SNF−SETD2−substrate ternary complexes.
difficulty to obtain the structure of the SETD2−substrate
complex, such topological switch was validated through
analyzing the kinetics of SETD2-catalyzed methylation in the
absence or presence of Pr-SNF (Figure 5). The initial velocities
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Figure 6. Structural insights of Pr-SNF’s selectivity on SETD2 over other PKMTs. Pr-SNF ligand in the Pr-SNF−SETD2 binary complex (PDB
code 4FMU) was overlaid with SAM or SAH in complex with SET7/9 (PDB code 1O9S), SETD2’s autoinhibitory conformer (PDB code 4H12),
SET8 (PDB code 1ZKK), MLL (PDB code 2W5Z), G9a (PDB code 3RJW), GLP (PDB code 2RFI), SUV39H2 (PDB code 2R3A), SUV420H1
(PDB code 3S8P), and SUV420H2 (PDB code 3RQ4) with ICM version 3.7-2b (Molsoft, San Diego). The overlaid structures of GLP and
SUV420H2 were omitted given their similarity to those of G9a and SUV420H1, respectively. The optimal hydrogen-bonding distances between Pr-
SNF’s secondary amine and main-chain carbonyls observed in the SETD2 structure may contribute to the high selectivity of the inhibitor.
of SETD2-catalyzed methylation were monitored with the H3
peptide (20−50 amino acid) as H3K36 substrate and [3H-Me]-
SAM as cofactor. The plots of the initial velocities versus
concentrations of peptide substrate or SAM cofactor were first
generated in the absence of Pr-SNF. The linear regression did
not converge on the y axis (Figure 5a) and thus ruled out an
ordered sequential mechanism: the ordered SAM/substrate or
substrate/SAM binding along the reaction path of SETD2-
catalyzed methylation.45 The converged initial velocities on the
x axis versus the concentrations of peptide substrate or SAM
further argue that SETD2-catalyzed methylation goes through a
random sequential mechanism, and the binding of either SAM
or substrate does not affect the sequential binding of the other
(α = 1, Figure 5c).45 Plotting the slopes of the double
reciprocal kinetics against the concentrations of SAM or
substrate gives SETD2’s Km,SAM of 1.21 0.05 μM, Km,Substrate
of 0.42 0.02 μM, and kcat = 0.14 0.1 min−1 (Figure 5c,
S1a). The similar results were obtained via nonlinear regression
of the same set of kinetic data (Figure S1b).
To accurately determine the dissociation constant Kd of 3c
on SETD2, we measured initial velocities of SETD2-catalyzed
methylation versus concentrations of peptide substrate and
SAM cofactor as the function of the concentration of Pr-SNF
3c. In the presence of the varied amount of 3c and the fixed
amount of SAM, the double-reciprocal kinetics of SETD2-
catalyzed methylation versus peptide substrate converged in the
negative region of x axis (Figure 5b left).45 This result
implicated a noncompetitive character between Pr-SNF and
peptide substrate, featured as coexistence of the inhibitor−
enzyme binary and inhibitor−enzyme−substrate ternary
complexes (Figure 5c).45 Given that Pr-SNF’s N-propyl moiety
and the H3K36 lysine chain could clash if simultaneously
occupying SETD2’s lysine-binding pocket, the formation of the
inhibitor−enzyme−substrate complex is intriguing and can be
better elucidated upon solving the structure of the ternary
complex.
The converged linear regression in the negative region of y
axis further revealed that the initial binding of either Pr-SNF 3c
or substrate facilitates the following binding of the other (β <
1) (Figure 5b, left and c). In contrast, in the presence of the
varied amount of Pr-SNF and the fixed amount of peptide
substrate, the double-reciprocal kinetics of SETD2-catalyzed
methylation versus SAM cofactor converged on y axis,
consistent with the competitive character between Pr-SNF 3c
and SAM cofactor (Figure 5b, right and c). Upon fitting these
kinetics with Km,SAM = 1.21 0.05 μM, Km,Substrate = 0.42 0.02
μM, and α = 1, Kd = 360 15 nM, and βKd = 43 4 nM (β =
0.12 0.01) were obtained for Pr-SNF to bind SETD2 in the
absence and presence of substrate, respectively (Figures 5c and
S1b). These values are consistent with the IC50 of 3c against
SETD2 as measured with sub-Km concentrations of SAM
cofactor and peptide substrate (calculated IC50 of 0.60 μM
versus experimental IC50 of 0.80 μM shown in Figure 2). Our
kinetic data together with SETD2’s structures thus concluded
that SETD2-catalyzed methylation goes through a random
sequential mechanism and that Pr-SNF 3c inhibits this process
through the formation of either a Pr-SNF−SETD2 binary
complex or a Pr-SNF−SETD2−substrate ternary complex
(Figure 5c). The small β value of 0.12 further argues that the
binding of Pr-SNF to SETD2 significantly facilitates the
subsequent recruitment of substrate to form the inhibitor−
SETD2−substrate ternary dead complex (Km,Substrate = 0.42
0.02 μM versus βKm,Substrate = 0.050 0.005 μM, Figure 5c).
The high affinity of the Pr-SNF−SETD2 binary complex to
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substrate peptide, as reflected by small βKm,Substrate of 0.050
0.005 μM, also recapitulates the prior finding that 3c
preferentially interacts with SETD2’s active open conformer
and thus position SETD2’s post-SET loop in a ready
configuration to bind substrate.
group. These findings therefore substantiate the importance of
the matched lysine-binding pocket, besides the two well-
positioned backbone carbonyls (Figure 6), for Pr-SNF’s
selectivity on SETD2 over other PKMTs.
DISCUSSION
Selective Inhibition of Pr-SNF 3c on SETD2 versus
Other SET-Domain PKMTs. To further explore the origin of
the selectivity of Pr-SNF 3c on SETD2 versus other SET-
domain PKMTs, we superimposed SETD2-bound Pr-SNF to
SAM or SAH in complex with SETD2’s autoinhibitory close
conformer and other PKMTs. The secondary amine of Pr-SNF
3c is expected to be protonated at physiological pH and thus
carries two hydrogen atoms. In SETD2’s active open
conformation, Pr-SNF’s secondary amine moiety is ideally
positioned to form the two hydrogen bonds with the backbone
carbonyl of SETD2’s R1625 and Y1604 (N−O distances of 2.8
and 2.9 Å, respectively) (Figure 6). The comparable carbonyl
groups of SET7/9 have also been proposed to participate in
transition-state stabilization and enzymatic catalysis at the
substrate−cofactor interface by forming nonclassic oxygen−
carbon hydrogen bonds with SAM’s sulfonium methyl
moiety.18 In contrast, such carbonyl residues in SETD2’s
inactive conformer (SETD2 in complex with SAH) and the
prior SET domain structures (e.g., SET8, MLL, GLP, G9a,
SUV39H2, SUV420H1, and SUV420H2) are not well
positioned with the less optimally docked N−O distances of
>3.1 Å for the carbonyl groups (Figures 3 and 6). In these
cases, the formation of the optimal hydrogen bonds would
require the PMTs to alter ground-state conformations and thus
pay additional energy penalty. Despite the near-optimal N−O
distances of 3.1 Å in the structures of SETD8, SUV420H1, and
SUV420H2 (Figure 6), Pr-SNF shows even lower affinity in
contrast to MLL and SUV39H2 (Table S1). This observation
indicates that additional factors may further contribute to the
altered affinity of Pr-SNF on PKMTs. In the case of SET7/9,
the amide oxygen of the side-chain of N265 can form an
alternative hydrogen bond, which may compensate the less
optimal carbonyl hydrogen bond and thus cause the modest
cross-inhibition observed (Figures 2 and 6). This analysis
therefore suggests that SETD2’s active open conformer
contains the two well-positioned backbone carbonyls to form
the hydrogen bonds with Pr-SNF, and these interactions in part
account for its selective inhibition on SETD2 over other
PKMTs.
Here we further argue that the N-propyl moiety of Pr-SNF
also plays a positive role on its preferential interaction with
SETD2’s active open conformer, because sinefungin and its N-
methyl derivative 3a do not show such selectivity (Table S1).
In the structure of the SETD2−Pr-SNF binary complex, Pr-
SNF’s N-propyl moiety was located in the hydrophobic binding
pocket of substrate lysine formed by SETD2’s Tyr1579,
Tyr1605, Met1627, Phe1650, Phe1664, and Tyr1666 (Figure
3d). The readiness of the lysine-binding pocket to accom-
modate N-alkyl groups is thus essential for Pr-SNF’s selectivity
on SETD2. Here SETD2’s lysine-binding pocket can be
explored with the N-alkyl sinefungin analogues 3a−d as
structure probes (Figure 2 and Table S1). The gradually
reduced IC50 of 100, 8.2 1.2, 0.80 0.20, and 0.48 0.06
μM from 3a−d on SETD2 indicates that the lysine-binding
pocket of SETD2 is flexible enough to accommodate bulky
propyl or benzyl moiety. In contrast, 10−50-fold drop in
potency from 3c to 3d suggests that the lysine-binding pockets
of SET7/9 and SUV39H2 are not sufficient for 3d’s benzyl
■
Synthesizing the privileged N-alkyl sinefungin derivatives and
screening them against a panel of methyltransferases allowed us
to identify Pr-SNF 3c and N-benzyl sinefungin 3d as inhibitors
of SETD2. Among the examined 10 SET domain PKMTs
(SET7/9, SET8, EZH2, MLL, GLP, G9a, SUV39H2, SETD2,
SUV420H1, and SUV420H2) and 5 non-SET domain
methyltransferases (PRMT1, PRMT3, CARM1, DOT1L, and
DNMT1), Pr-SNF 3c and N-benzyl sinefungin 3d showed the
best inhibition on SETD2 with apparent IC50 of sub-μM (Kd =
0.36 0.02 μM for Pr-SNF). Further characterization of Pr-
SNF revealed that the presence of SETD2’s substrate enhances
its Kd by additional 8-fold (βKd = 0.043 0.004 μM). SETD2
is solely responsible for H3K36 trimethylation and has been
characterized as a tumor suppressor of multiple cancers.22,24,46
Here we present Pr-SNF 3c (likely N-benzyl sinefungin 3d as
well) as a SETD2-specific inhibitor.
Pr-SNF was further demonstrated to be a valuable structure
probe of human SETD2. Pr-SNF 3c preferentially interacts
with SETD2’s catalytically active open conformer. Compared
with SETD2’s autoinhibitory close conformer, the active open
conformer is featured by a distinct reconfiguration of a post-
SET substrate-recognizing loop. In particular, SETD2’s
Arg1670 residue plays dual roles by orienting the loop to
block the substrate entry in the inactive close conformer but
readily receive the substrate in the active open conformer. The
configuration switch also positions SETD2’s backbone carbonyl
groups to form two optimal hydrogen bonds with Pr-SNF’s
secondary amine. The presence of Pr-SNF 3c therefore favors
the equilibrium to SETD2’s catalytically active open conformer.
Remarkably, NSD1 and ASH1L were also reported to contain
similar autoinhibitory loops to prevent free access of
substrates.40−42,47 SETD2, NSD1, and ASH1L are more closely
related among the SET-domain-containing PKMTs on the basis
of their primary sequence (Figure S2) and their ability to
recognize H3K36 as a substrate.40−42,47 The autoinhibitory
topology may be adapted by the subfamily of PKMTs as a
general mechanism to regulate substrate recognition. The
switch from the autoinhibitory to catalytically active config-
uration of the subfamily of PKMTs could be modulated by
their binding partners in cellular contexts and thus account for
their context-specific substrate recognition.48
Pr-SNF’s preference for SETD2 over 14 other methyl-
transferases is striking given the overall structural similarity
between the 10 examined SET-domain-containing PKMTs.38,39
Structural analysis and enzyme kinetics of SETD2, together
with the results of mutagenesis and molecular docking,
indicated that such selectivity relies on the existence of the
matched lysine-binding pocket and unique catalytically active
conformer of SETD2. To rationally design inhibitors of protein
methyltransferases, several prior efforts focused on conjugating
a portion of substrates to a 5′-azo-SAM analogue (bisubstrate-
type inhibitors).3,12,49,50 With exception of the 5′-aziridine-
based inhibitor of DOT1L, whose structural topology is
different from other protein methyltransferases,12 most
bisubstrate-type inhibitors only showed modest IC50.49,50
More mechanistic studies appear to be necessary to understand
their low potency. It has been noticed that protein
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trifluoroacetic acid (0.1%) in 10 min and a flow rate of 10 mL/min.
The fractions containing Pr-SNF were collected. The volatile solvents
were removed by SpeedVac. The resultant solution was lyophilized to
give the desirable product 3c with overall 7% from compound 4. Pr-
SNF was dissolved in water and stored at −20 °C before use. The
compounds 3a, 3b, and 3d were obtained in a similar manner
(Supporting Information).
methyltransferases, though structurally similar in terms of
conversed SAM-binding motifs, can display a broad range of
affinity to the same ligand (e.g., SAM and sinefungin) and this
variation, even between closely related methyltransferases,
could not be readily justified according to their static
structures.3,8−10 This observation therefore argues that
individual protein methyltransferases may achieve tight
interaction with specific ligands by adopting alternative but
better matched conformations. Our current success in
identifying the N-alkyl sinefungin analogues as SETD2
inhibitors presents the utility and power of using privileged
scaffolds to probe these distinct conformations in the course of
developing PKMT inhibitors. Given that only a limited number
of sinefungin analogues and PKMTs are examined here, we
envision a promising use of structural variants of sinefungin as
structure and chemical probes to elucidate functions of protein
methyltransferases.
1
3a. R = Me, 52% yield. H NMR (600 MHz, MeOD): δ 1.96−
2.03(m, 2H), 2.05−2.08(m, 2H), 2.25−2.29(m, 2H), 2.64(s, 3H),
3.43−3.45(m, 1H), 3.99−4.03(m, 1H), 4.19−4.22(m, 1H), 4.36(t, 1H,
J = 5.9 Hz), 4.65(dd, 1H, J = 5.4 Hz, 3.7 Hz), 6.01(d, 1H, J = 3.7 Hz),
8.35(s, 1H), 8.36(s, 1H); 13C NMR (150 MHz, MeOD): δ 26.54,
27.60, 31.43, 33.55, 53.59, 58.23, 74.86, 75.01, 80.92, 91.85, 117.99(q,
J = 289.7 Hz), 121.15, 143.44, 149.45, 150.10, 154.64, 162.57(q, J =
35.5 Hz),171.52; MS(ESI) m/z: 396 [M+H]+; HRMS: calcd for
C17H28N7O5 ([M+H]+): 396.1995; found: 396.1982.
3b. R = Et, 56% yield. 1H NMR (600 MHz, MeOD): δ 1.11(t, 3H,
J = 7.2 Hz), 1.93−1.97(m, 2H), 1.99−2.07(m, 2H), 2.23−2.27(m,
1H), 2.28−2.32(m, 1H), 3.05(q, 2H, J = 7.2 Hz), 3.46−3.48(m, 1H),
3.97(t, 1H, J = 6.0 Hz), 4.19−4.22(m, 1H), 4.37(t, 1H, J = 6.0 Hz),
4.70(dd, 1H, J = 5.4 Hz, 3.8 Hz), 5.99(d, 1H, J = 3.8 Hz), 8.30(s, 2H);
13C NMR (150 MHz, MeOD): δ 11.53, 26.99, 27.71, 33.51, 41.92,
53.75, 56.89, 74.57, 75.17, 80.91, 91.78, 118.09(q, J = 289.2 Hz),
121.12, 142.79, 150.26, 151.64, 156.02, 162.70(q, J = 35.4 Hz),171.77 ;
MS(ESI) m/z: 410 [M+H]+; HRMS: calcd for C17H28N7O5 ([M
+H]+): 410.2152; found: 410.2142.
CONCLUSION
■
In this work, we outlined an approach, apart from the
conventional high-throughput screening, to identify target-
specific methyltransferase inhibitors by screening privileged
small-molecule scaffolds against diverse methyltransferases.
Among the small set of sinefungin derivatives synthesized
here, Pr-SNF and N-benzyl sinefungin were identified as
SETD2-specific inhibitors with decent potency and selectivity.
The preferential interaction between the N-alkyl sinefungin
analogues and SETD2 attributes to the distinct transition-state
features of SETD2’s catalytically active conformer. With Pr-
SNF as a structure probe, we further revealed a dual role of
SETD2’s post-SET loop on regulating substrate access through
a distinct topological reconfiguration. The current work further
argues that even closely related SET-domain-containing
PKMTs, which contain almost identical SAM-binding motifs,
can adopt distinct configurations and thus be selectively
inhibited by well-designed small molecules. Although sinefun-
gin was regarded as a pan-inhibitor of methyltransferases, we
demonstrated that well-designed sinefungin variants can go
beyond the pan-inhibitor category and thus stand as lead
compounds for further optimization. Given sinefungin contains
rich structural motifs including primary amine, carboxylic acid,
adenine and ribosyl moieties and thus can be subject to further
derivatization, privileged sinefungin scaffolds are expected to
show broad use in the course of developing inhibitors and
interrogating functions of methyltransferases.
3c. R = Pr, 57% yield. 1H NMR (500 MHz, MeOD): δ 0.83(t, 3H, J
= 7.4 Hz), 1.42−1.49(m, 1H), 1.52−1.59(m, 1H), 1.94−2.09(m, 4H),
2.21−2.26(m, 1H), 2.29−2.35(m, 1H), 2.92(t, 2H, J = 8.0 Hz) 3.44−
3.48(m, 1H), 4.01(t, 1H, J = 6.0 Hz), 4.19−4.22(m, 1H), 4.40(t, 1H, J
= 6.0 Hz), 4.67(dd, 1H, J = 5.4 Hz, 3.4 Hz), 6.02(d, 1H, J = 3.4 Hz),
8.35(s, 1H), 8.36(s, 1H); 13C NMR (150 MHz, MeOD): δ 11.20,
20.77, 27.05, 27.64, 33.32, 48.23, 53.54, 57.29, 74.83, 75.16, 80.91,
91.90, 117.92 (q, J = 289.4 Hz),121.11, 143.47, 149.35, 150.09, 154.55,
162.44(q, J = 35.8 Hz),171.50; MS(ESI) m/z: 424 [M+H]+; HRMS:
calcd for C18H30N7O5 ([M+H]+): 424.2308; found: 424.2296.
1
3d. R = Bn, 30% yield. H NMR (600 MHz, MeOD): δ 1.97−
2.10(m, 4H), 2.31 (ddd, 1H, J = 15.8 Hz, 5.8 Hz, 3.2 Hz), 2.40−
2.45(m, 1H), 3.57−3.59(m, 1H), 3.99(t, 1H, J = 6.0 Hz), 4.12(d, 1H, J
= 13.0 Hz), 4.20(d, 1H, J = 13.0 Hz), 4.41(t, 1H, J = 6.0 Hz), 4.70(dd,
1H, J = 5.8 Hz, 4.0 Hz), 5.49(s, 2H), 5.99(d, 1H, J = 3.8 Hz), 7.10(d,
2H, J = 7.2 Hz), 7.23(t, 2H, J = 7.2 Hz), 7.31(t, 1H, J = 7.2 Hz),
8.20(s, 1H), 8.33(s, 1H); 13C NMR (150 MHz, MeOD): δ 27.09,
27.87, 32.45, 53.71, 54.96, 57.08, 74.33, 74.84, 80.98, 91.88, 121.22,
130.22, 130.55, 130.68, 132.26, 142.88, 150.14, 151.49, 155.86,
162.55(q, J = 35.4 Hz), 171.75; MS(ESI) m/z: 472 [M+H]+;
HRMS: calcd for C22H30N7O5 ([M+H]+): 472.2308; found: 472.2299.
Protein Expression and Purification for the Assays of
Enzymatic Activities. Full-length SET7/9, SET8 (residues 191−
395), SETD2 (residues 1347−1711, native and mutants), GLP
(residues 951−1235), G9a (residues 913−1193), SUV39H2 (residues
112−410), PRMT1 (residues 10−352), PRMT3 (residues 211−531),
and CARM1 (residues 19−608) were expressed and purified as
previously reported (see the Supporting Information). DOT1L
(residues 1−420), SUV420H1 (residues 69−335), and SUV420H2
(residues 2−248) containing an N-terminal His tag were overex-
pressed in E. coli BL21 (DE3) V2R-pRARE (SGC) and purified by Ni-
NTA column (Qiagen). The EZH2 complex containing EZH2
(residues 1−751), EED (residues 1−441), and SUZ12 (residues 1−
739) and the MLL complex containing MLL (residues 3745−3969),
WDR5 (residues 1−334), and RBBP5 (residues 1−538) were cloned
in a pFastBac Dual vector (Invitrogen) with an N-terminal His6-tag on
MLL or EZH2. Both complexes were expressed in SF9 cells and
purified by a Ni-NTA column. Additional purification steps were used
if needed.
METHODS
■
Synthesis and Characterization of Pr-SNF 3c. To a stirred
solution of 12c (0.02 mmol) in methanol (10 mL) was added
potassium carbonate (14 mg, 0.1 mmol). The resultant mixture was
stirred at ambient temperature for 8 h, concentrated to dryness, and
then redissolved in 10 mL water. To the mixture was added hydrazine
monohydrate (5 μL, 0.1 mmol). The reaction was stirred for 8 h at
ambient temperature, neutralized with 1 M aqueous HCl, and then
concentrated under reduced pressure. This mixture was then dissolved
in 6 mL ethanol:water (5:1). To this solution was added 20 μL acetic
acid and palladium on activated carbon (15 mg, 10 wt %, wet Degussa
type). The subsequent hydrogenation reaction was carried out with
hydrogen balloon for 12 h. The reaction mixture was filtered through a
short pad of Celite and washed out with 20 mL MeOH and then 20
mL 0.1% TFA/water. The combined filtrates were concentrated under
reduced pressure. The resultant crude products were purified by
preparative reversed-phase HPLC (XBridge Prep C18 5 μm OBD 19
× 150 mm) with 0−15% gradient of acetonitrile in aqueous
Biochemical Assays of Methylation Activities. Three assays
(the filter paper assay, scintillation proximity assay (SPA), and the fiber
filterplate assay) were used to determine the activities of
methyltransferases according to the readiness of assay reagents and
3
the characters of enzymes. The filter paper assay, in which H-Me of
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[3H-Me]-SAM is transferred to peptide substrates, followed by filter
binding, and then quantification with a scintillation counter, was used
to examine the activities of G9a, GLP, SUV39H2, SET7/9, SET8,
SETD2 (wild type and mutants), PRMT1, PRMT3, and CARM1. The
AUTHOR INFORMATION
Corresponding Author
jr.min@utoronto.ca; luom@mskcc.org
■
3
SPA, in which H-Me of [3H-Me]-SAM is transferred to biotinylated
Author Contributions
⊥These authors contributed equally.
substrates, followed by immobilization onto SPA plate and topcount
plate reading, was applied to determine the activities of SUV420H1,
SUV420H2, EZH2 and MLL complexes, and DNMT1. The fiber
Notes
3
filterplate assay, in which H-Me of [3H-Me]-SAM is transferred to a
The authors declare no competing financial interest.
protein substrate, followed by acid precipitation, immobilization to
fiber filterplate and topcount plate reading, was used for DOT1L. The
IC50 values were obtained by fitting inhibition percentage versus
inhibitor concentration using GraphPad Prism5 or SigmaPlot software.
Crystallization, Data Collection, and Structure Determina-
tion (See the SI for Details). Human SETD2 (residues 932−1208)
with an N-terminal 6 × histidine tag was overexpressed in E. coli BL21
(DE3) codon plus RIL strain (Stratagene) and purified by HiTrap
chelating column (GE Healthcare), Superdex200 column (GE
Healthcare), and then ion-exchange chromatography. Purified
SETD2 protein (10 mg/mL) was complexed with SAM (Sigma),
which was degraded into SAH during crystallization, at a 1:10 protein
to ligand molar ratio, and crystallized using sitting drop vapor diffusion
method. One μL of the protein solution was mixed with 1 μL of the
reservoir solution containing 30% PEG 2K MME and 0.1 M KSCN at
20 °C. For the complex of SETD2 with Pr-SNF, the purified SETD2
was incubated with the inhibitor at a 1:5 protein to inhibitor molar
ratio and crystallized using a sitting drop vapor diffusion method.
Protein solution 1 μL was mixed with 1 μL of reservoir solution
containing 20% PEG4000, 10% isopropanol, and 0.1 M HEPES (pH
7.5) at 20 °C. X-ray diffraction data for the SETD2−SAH complex was
collected at 100 K at beamline19ID of Advanced Photon Source
(APS). The methyltransferase domain structure of SETD2 in complex
with SAH was solved by molecular replacement with human
SUV39H2 (PDB code 2R3A) as the search model. The SEDT2−
SAH structure was subsequently used as model to solve the structure
of the Pr-SNF−SETD2 complex. Contoured omission electronic
density maps for SAH, Pr-SNF, and the autoinhibitory post-SET loops
were simulated to confirm the ligand binding or loop reconfiguration.
Molecular Docking. To compare the SETD2−Pr-SNF complex
with SAH-bound SETD2 and other PKMTs, the Pr-SNF ligand was
overlaid with the SAM or SAH in complex with the structures of
SETD2 (PDB code 4H12), SET8 (PDB code 1ZKK), MLL (PDB
code 2W5Z), GLP (PDB code 2RFI), G9a (PDB code 3RJW),
SUV39H2 (PDB code 2R3A), SUV420H1 (PDB code 3S8P), and
SUV420H2 (PDB code 3RQ4) with ICM version 3.7-2b (Molsoft, San
Diego).
Kinetics Analysis. The filter paper assay was used to determine the
initial velocities of SETD2 in the presence of varied concentrations of
H3 peptide substrate (residues 20−50) and [3H-Me]-SAM cofactor.
Km,SAM, Km,Substrate, and kcat were obtained from the secondary double-
reciprocal plots of the initial velocities versus the concentrations of
substrate or cofactor according to eqs S1 and S2.45 The kinetic
parameters (Km,SAM, Km,Substrate, and kcat) were further confirmed upon
fitting the same set of initial velocities versus the concentrations of
SAM and peptide substrate via nonlinear regression (Figure S1b). To
obtain the inhibition constant Kd (Ki) of Pr-SNF on SETD2, the
methylation kinetics were measured with the filter paper assay in the
presence of varied amounts of the inhibitor. The secondary double-
reciprocal plots of the initial velocities versus the concentration of the
inhibitor were the generated and further processed according to eqs
S3−S6 to give Kd.45
ACKNOWLEDGMENTS
■
The atomic coordinates and structure factors reported in this
paper have been deposited in the Protein Data Bank, www.pdb.
org (PDB codes 4H12 and 4FMU). This work is supported by
Mr. William H. Goodwin and Mrs. Alice Goodwin
Commonwealth Foundation for Cancer Research (M.L.), The
Experimental Therapeutics Center of Memorial Sloan-Ketter-
ing Cancer Center (M.L.), NIGMS (1R01GM096056, M.L.),
NINDS (R21NS071520, M.L.), and the Structural Genomics
Consortium (J.M.), which is a registered charity (1097737) that
receives funds from the Canadian Institutes for Health
Research, the Canadian Foundation for Innovation, Genome
Canada through the Ontario Genomics Institute, GlaxoSmithK-
line, Karolinska Institute, The Knut and Alice Wallenberg
Foundation, the Ontario Innovation Trust, the Ontario
Ministry for Research and Innovation, Merck & Co., the
Novartis Research Foundation, the Swedish Agency for
Innovation Systems, the Swedish Foundation for Strategic
Research, and the Wellcome Trust.
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ASSOCIATED CONTENT
■
S
* Supporting Information
Reagents, assays, crystallography, molecular docking, synthesis,
the full author list of refs 20, 21, and 26, Figures S1−S3, and
Tables S1−S3. This material is available free of charge via the
Internet at http://pubs.acs.org.
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