De Novo design of protein kinase inhibitors by in silico identification of hinge region-binding fragments

Article abstract of DOI:10.1021/cb300729y

Protein kinases constitute an attractive family of enzyme targets with high relevance to cell and disease biology. Small molecule inhibitors are powerful tools to dissect and elucidate the function of kinases in chemical biology research and to serve as potential starting points for drug discovery. However, the discovery and development of novel inhibitors remains challenging. Here, we describe a structure-based de novo design approach that generates novel, hinge-binding fragments that are synthetically feasible and can be elaborated to small molecule libraries. Starting from commercially available compounds, core fragments were extracted, filtered for pharmacophoric properties compatible with hinge-region binding, and docked into a panel of protein kinases. Fragments with a high consensus score were subsequently short-listed for synthesis. Application of this strategy led to a number of core fragments with no previously reported activity against kinases. Small libraries around the core fragments were synthesized, and representative compounds were tested against a large panel of protein kinases and subjected to co-crystallization experiments. Each of the tested compounds was active against at least one kinase, but not all kinases in the panel were inhibited. A number of compounds showed high ligand efficiencies for therapeutically relevant kinases; among them were MAPKAP-K3, SRPK1, SGK1, TAK1, and GCK for which only few inhibitors are reported in the literature.

Full text of DOI:10.1021/cb300729y

Articles
pubs.acs.org/acschemicalbiology
De Novo Design of Protein Kinase Inhibitors by in Silico Identification
of Hinge Region-Binding Fragments
Robert Urich,† Grant Wishart,‡ Michael Kiczun,‡ Andre Richters,§ Naomi Tidten-Luksch,† Daniel Rauh,§
́
Brad Sherborne,‡ Paul G. Wyatt,*,† and Ruth Brenk*,∥
†Drug Discovery Unit (DDU), Division of Biological Chemistry and Drug Discovery, College of Life Sciences, University of Dundee,
Sir James Black Centre, DD1 5EH, U.K.
‡Department of Chemistry, MSD, Newhouse, Lanarkshire, ML1 5SH, U.K.
§Fakultat Chemie - Chemische Biologie, Technische Universitat Dortmund, Otto-Hahn-Straße 6, 44227 Dortmund, Germany
̈
̈
∥Institut fur Pharmazie und Biochemie, Johannes Gutenberg-Universitat Mainz, Staudinger Weg 5, 55128 Mainz, Germany
̈
̈
S
* Supporting Information
ABSTRACT: Protein kinases constitute an attractive family of
enzyme targets with high relevance to cell and disease biology.
Small molecule inhibitors are powerful tools to dissect and
elucidate the function of kinases in chemical biology research
and to serve as potential starting points for drug discovery.
However, the discovery and development of novel inhibitors
remains challenging. Here, we describe a structure-based de
novo design approach that generates novel, hinge-binding
fragments that are synthetically feasible and can be elaborated
to small molecule libraries. Starting from commercially
available compounds, core fragments were extracted, filtered
for pharmacophoric properties compatible with hinge-region binding, and docked into a panel of protein kinases. Fragments with
a high consensus score were subsequently short-listed for synthesis. Application of this strategy led to a number of core fragments
with no previously reported activity against kinases. Small libraries around the core fragments were synthesized, and
representative compounds were tested against a large panel of protein kinases and subjected to co-crystallization experiments.
Each of the tested compounds was active against at least one kinase, but not all kinases in the panel were inhibited. A number of
compounds showed high ligand efficiencies for therapeutically relevant kinases; among them were MAPKAP-K3, SRPK1, SGK1,
TAK1, and GCK for which only few inhibitors are reported in the literature.
different kinases than the hinge region, and the differences can
be exploited to achieve selectivity.8
hosphorylation is the most important and widespread
Pcovalent modification of proteins. It is used to control
enzyme activity in cellular processes and thereby plays a major
role in cell signaling and is fundamental to all aspects of cell
behavior and organization.1 Protein kinases catalyze the transfer
of the γ-phosphate group from ATP to recognized amino acids
of proteins. Kinases have implications for many diseases
including cancer, diabetes, and Alzheimer’s disease and
constitute the second most exploited group of drug targets
with many ongoing drug discovery efforts.2 Despite the
extensive research over the past two decades, selective chemical
tools are still needed to dissect the complex nature of kinase
regulation.2,3
A wealth of structural information has revealed the general
architecture of protein kinases, their binding sites, and complex
regulation.4,5 The ATP-binding sites of most protein kinases
share similar features (Figure 1a).6,7 A key recognition motive is
the hinge region that forms hydrogen bonds to the adenine
moiety of ATP and is targeted by many kinase inhibitors.
Often, inhibitors also address one or both of the adjacent
hydrophobic pockets I and II. These are more variable between
Kinase inhibitors are commonly discovered by high-
throughput, virtual or fragment-based screening, often using
compound libraries sourced from commercial suppliers.9−13
While successful in delivering hit compounds, they have only
limited template diversity. In order to tackle this issue, various
research groups have developed approaches to expand their
libraries with proprietary compounds.14−20 Libraries that
contained compounds with heterocycles, which have the
potential to interact with the hinge region of the kinase
binding site but no previous reported activity against kinases,
were of particular high value.14−18 A difficulty in expanding the
kinase libraries was to assess synthetic feasibility of the
suggested compounds, especially if they contained novel
cores.14,17
Received: December 28, 2012
Accepted: March 12, 2013
© XXXX American Chemical Society
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A core fragment was defined as a ring system plus the directly
attached heteroatom containing functional groups.11 Starting
from over two million compounds, about 84,000 unique core
fragments were extracted. In the next step these core fragments
were filtered for fragment-like properties, the absence of
unwanted functionalities, and limited complexity. The resulting
11,000 core fragments were subsequently filtered using a 3D
pharmacophore to remove scaffolds that did not contain a
hinge-binding motif (Supplementary Figure S1). About 6,000
core fragments that passed this filter step were docked into the
binding sites of a panel of 46 different protein kinases
(Supplementary Table S1). These proteins were chosen
based on the availability in the MRC Protein Phosphorylation
Unit in Dundee for compound testing and access to a crystal
structure in the public domain.21 In order to make the docking
scores comparable for the different kinases, they were
normalized relative to the best score for any fragment in the
active site of each kinase in a similar way as carried out
previously.22 Following this approach the top 100 nonselective
core fragments were visually inspected. The vast majority of
these were predicted to form two or three hydrogen bonds with
the kinase hinge region. Six out of the top scoring core
fragments or fragments closely resembling these scaffolds had
been co-crystallized with a kinase as part of a larger compound
(Figure 2). Comparing the docked poses with the binding
modes of these compounds confirmed that they were placed
correctly in the binding site in at least one kinase of the docking
panel (RMSD of maximum common substructure <2 Å). The
novelty of the high-ranking hinge binders was assessed by using
the core fragments as substructure queries for ChEMBL23 and
SciFinder (Chemical Abstracts Service, Columbus, OH). It
turned out that 73 of the top 100 nonselective core fragments
were already reported in the literature as part of known kinase
inhibitors. Six novel fragments out of the remaining 27
fragments were short-listed for library enumeration based on
synthetic considerations (Figure 3). None of the selected core
fragments was available as part of commercial compounds with
either the required substitution pattern or the desired diversity
at the time of the study.
In the final step, suitable substitution points to attach
additional moieties to interact with the hydrophobic pockets I
and II (Figure 3) were assigned. For all short-listed core
fragments, more than one binding mode was predicted for the
kinases in the docking panel. Typically, in the different
orientations several hydrogen bonds with the hinge region
were formed, but the interacting atoms of the cores differed. It
was therefore ensured that after adopting these alternative
binding modes the R-groups would still be placed into desired
regions of the binding site. The libraries were enumerated using
commercially available building blocks. The reaction products
were filtered to remove molecules with unwanted function-
alities and non-drug-like molecules according to Lipinski’s rule
of five.24 A final selection was made based on diversity by visual
inspection and in-house availability of the building blocks. Due
to synthetic considerations, libraries containing the core
fragments A and F were generated by varying either R1 or R2
(Supplementary Table S2, Figure 3), whereas for core
fragments B and D R1 R2 were varied simultaneously. Core
fragments C and E contained only one R-group for
enumeration. In total, 265 compounds were short-listed for
synthesis. All libraries were synthesized using parallel synthesis
in a maximum of six steps. To speed up synthesis the synthetic
routes were designed to introduce diversity as late as possible
Figure 1. (a) ATP binding site of a typical protein kinase (adapted
from ref 7). (b) In silico screening cascade used to design novel kinase
inhibitor libraries.
Here, we report on the structure-based de novo design of
protein kinase inhibitors. The approach is centered on
fragments that have precedence for synthesis but are not
commercially available with the required substitution pattern.
Libraries around six core fragments without previous reported
activity against kinases were synthesized, and selected
compounds were screened against a panel of 117 kinases. In
addition, the crystal structure of one novel inhibitor in complex
with cSrc was determined. Every tested compound was active
against at least one kinase. While predicting general activity
against kinases on a scaffold level was highly successful,
predicting selectivity on a compound level failed. Ligand
efficient inhibitors were identified for a number of kinases,
which have implications in a range of diseases but for which
only a few inhibitors have been reported to date.
RESULTS AND DISCUSSION
■
Structure-Based Design of Novel Protein Kinase
Inhibitor Libraries. An in silico screening cascade was
established for the design of novel kinase inhibitor libraries
(Figure 1b). This approach consisted of the following four
principle steps: core fragment extraction out of commercially
available compounds, selection of candidate core fragments,
docking of core fragments, and fragment expansion.
B
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Figure 2. Docking poses of six high ranking core fragments (green carbon atoms) superimposed on crystallographically determined binding modes
of ligands containing the same or a closely related core fragment (cyan carbon atoms). Putative hydrogen bonds to the hinge region are shown as
dashed lines. RMSD values are given for the maximum common substructure between core fragment and ligand. (The binding sites are oriented as
depicted in Figure 1a.)
Figure 3. Predicted binding modes with respect to the hinge region for six high-ranking core fragments (A−F) for which binding to protein kinases
was not reported in the literature. Only the most frequent binding mode for each core fragment is shown. The substitution points that target the
hydrophobic pockets I and II and that have been selected for diversifying the cores are indicated as R1 and R2, respectively. (The binding sites are
oriented as depicted in Figure 1a.)
(Scheme 1), and 186 compounds representing all six core
fragments were successfully prepared (yield 7−98%, purity
>90%).
Inhibition Profiles of 15 Compounds against a Panel
of 117 Protein Kinases. A subset of library compounds was
tested against a panel of 117 protein kinases as proof of concept
study (Figure 4). The compounds were chosen to cover all six
core fragments and to be fragment-sized (MW < 300 Da),
therefore having a higher probability of inhibiting a kinase
compared to more elaborated library compounds with the
potential draw-back of having only moderate binding affinity.25
Any compounds showing ≥75% inhibition at 100 μM were
defined as active, between 40 and 75% as moderately active,
and below 40% as inactive (Supplementary Table S3).
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a
Scheme 1
a
Reagents and conditions: (a) NBS, DCM, 0 °C; (b) ethoxycarbonyl-isothiocyanate, dioxane, rt; (c) NH2OH·HCl, DIPEA, MeOH/EtOH, 60 °C;
(d) R1B(OH)2, K3PO4, PCy3, Pd2(dba)3, dioxane/water, MW, 130 °C; (e) R2COOH, PCl3, CH3CN, MW, 150 °C; (f) formamide, 200 °C; (g) Br2,
AcOH, rt; (h) R1B(OH)2, K3PO4, PCy3, Pd2(dba)3, dioxane/water, MW, 100 °C; (i) diethylmalonate, 170 °C; (j) POCl3, reflux; (k) HNO3, H2SO4,
rt; (l) R1R′1NH, MeOH, MW, 140 °C; (m) Zn, NH4Cl, MeOH, rt; (n) SOCl2, MeOH, 0 °C−rt; (o) Bredereck’s reagent, toluene, 115 °C; (p) 2-
amino-3-hydroxy-pyridine, NaOAc, AcOH, 90 °C; (q) N-phenylbis(trifluoromethanesulfonimide), K2CO3, THF, MW, 120 °C; (r) R2B(OH)2,
Pd(PPh3)4, 120 °C; (s) TMSI, DCM, rt; (t) 1,2,4-triazol-3-amine, NaOAc, AcOH, 90 °C; (u) 33% HBr−AcOH, 50 °C; (v) R1SO2Cl or R1COCl or
R1NCO or R1NCS, DCM, MW, 110°C; (w) 2-aminoimidazole, NaOAc, AcOH, 90 °C; (x) H2, 10% Pd/C, EtOH, H-Cube; (y) R1SO2Cl or
R1COCl or R1NCO or R1NCS, DCM, MW, 110 °C; (z) PPA, 120 °C; (aa) HClO4, MeOH, rt.
According to these definitions, all assayed compounds were at
least moderately active against at least one kinase (Figure 5a).
The most selective compounds were E1 and F2, which both
inhibited only one kinase with >40% inhibition (MSK1 and
MKK1, respectively). The least selective compounds were B1
and A2, which inhibited 63 and 55 different kinases with >40%
inhibition, respectively.
The kinases presented in the kinase panel were not equally
inhibited by the 15 compounds selected to present the different
core fragments (Figure 5b, Supplementary Tables S3 and S4).
Using a ≥40% inhibition cutoff value, 26 kinases (22%) in the
panel were not inhibited by any of the tested compounds.
When a cutoff of ≥75% inhibition was used, this number
increased to 75 (64%).
Potency Determinations for Selected Compounds. Six
compounds (A1, A2, B1, C2, D1, and F3) with inhibition of
>50% for certain kinases were selected for IC50 determinations
(Table 1). Activity for all compounds was confirmed with IC50
values ranging from 4 to 470 μM. Additionally, all compounds
were characterized by high ligand efficiencies (>0.30 kcal/mol
heavy atom)26 for at least one protein kinase, with B1 showing
the best ligand efficiencies across a range of kinases.
Confirmation of Binding Mode. The binding mode of B1
in complex with cSrc was determined using X-ray crystallog-
raphy. In the most frequent binding mode that was generated
D
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Figure 4. Structures of 15 compounds that were screened against a panel of 117 protein kinases. Core fragments are marked in blue.
Table 1. IC50 Values and Ligand Efficiencies for Compounds
A1, A2, B1, C2, D1, and F3 for Selected Protein Kinases
a
compound
kinase
CK2
IC50 [μM]
LE [kcal/mol heavy atom]
A1
18
21
0.33
0.33
0.26
0.28
0.28
0.26
0.33
0.27
0.32
0.25
0.38
0.30
0.32
0.42
0.46
0.41
0.40
0.41
0.43
0.39
0.41
0.32
0.28
0.33
0.29
0.38
0.40
MAPKAP-K3
RSK2
196
97
Src
SRPK1
Aurora A
CDK2
CK2
114
188
26
A2
131
25
CLK2
FGF-R1
GCK
252
4
IGF-1R
TAK1
CHK2
GCK
47
24
B1
17
6
HER4
IGF-1R
Src
20
25
20
TAK1
VEG-FR
YES1
11
39
21
C2
D1
F3
GSK-3β
SGK1
25
110
158
469
22
EPH-B3
FGF-R1
PIM1
Figure 5. (a) Bar chart showing the number of kinases inhibited to at
least 40% (yellow bars) or 75% (green bars) based on 15 compounds
tested against a panel of 117 kinases. (b) Bar chart showing how many
kinases were inhibited by how many compounds to at least 40%
(yellow bars) or 75% (green bars) based on 15 compounds tested
against a panel of 117 kinases.
PIM3
14
a
Hill slopes range from 0.7 to 1.3.
for core fragment B in the kinases of the docking panel the
exocyclic amino group pointed toward the gatekeeper and the
nitrogen atom bridging the heterocycles was placed next to the
hinge region (Figure 3). This orientation closely matches the
E
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one found in the cSrc-B1 complex structure (Figure 6,
Supplementary Table S5, rmsd = 0.77 Å for non-hydrogen
atoms).
scaffolds for which activity against kinases was not reported
previously were identified, and synthetic routes were developed
to prepare focused libraries around each core. All tested
compounds were active against at least one kinase (Supple-
mentary Table S3). We attribute this success to the following
reasons: (1) Focusing on core fragments that occur in
commercially available compounds but are not available with
the required substitution pattern ensured that the libraries were
synthetically accessible and at the same time novel. (2)
Exploiting the wealth of kinase crystal structures when short-
listing the cores canceled differences in the kinase binding sites
and increased the chances that highly ranked cores would
actually bind to a kinase when part of a larger compound.
Evaluating a subset of the library compounds in a large kinase
panel confirmed some previous findings but also highlighted
differences (Supplementary Table S4). For instance, we
deliberately concentrated our synthetic efforts on predicted
unselective fragments. It turned out that derivatives of each
core displayed distinct selectivity profiles (Figure 5). This
observation is in tune with the notion that kinase selectivity
often does not stem from the core itself but from its
substituents.13,27 Further, we observed inhibition of PIM1
and PIM3 (Table 1). These kinases possess an altered hinge
binding region incompatible with forming the hydrogen-
bonding interactions typically observed in kinase-ligand
complexes (Figure 1a).28 It was speculated that interactions
with different amino acids in the binding site require a similar
pharmacophore as the interactions with the hinge region that
presumably lead to high hit rates of fragment-like kinase
inhibitors for these atypical kinases.13 Our data confirms this
hypothesis. However, Posy et al.27 and Bamborough et al.29
reported low hit rates for ASK1 (0 and 0.2%, respectively). In
contrast, by testing just 15 compounds against this kinase we
found two hits containing two different scaffolds. Anastassiadis
et al.30 found no hits for NEK6 and MAPKAP-K3, whereas in
our exercise two inhibitors containing the same scaffold and
seven inhibitors containing three different scaffolds were
discovered, respectively. One of the MAPKAP-K3 inhibitors
had an IC50 value of 21 μM and a ligand efficiency of 0.33 kcal/
mol heavy atom (Table 1). The previous studies had concluded
that these kinases were less tractable. Our data contradict these
findings, which is another warning that profiling data can be
interpreted only in relation to the chemical space covered by
the screening library.
Molecular docking was very successful when predicting
binding modes of fragments and general activity against kinases
on a core fragment-level but less so when individual
compounds for individual kinases were considered. Six high
ranking core fragments had been co-crystallized with kinases as
part of more elaborated compounds (Figure 2). All of the
observed binding modes for the core fragments were among
the ones generated in the kinase docking panel. Also, the
binding mode of B1 in cSrc was predicted correctly (Figure 6).
Remarkably, 73 out of the top 100 ranked core fragments had
activity against kinases reported in the literature. This unusually
high enrichment was presumably caused by exclusively docking
compounds that fulfilled a pharmacophore required for hinge-
binding fragments (Supplementary Figure S1a) and by using
consensus scoring across a panel of kinase structures
(Supplementary Table S1). This success provided confidence
that also the remaining high ranking fragments for which no
activity against kinases was reported would be suitable hinge-
binding scaffolds. At least for the selected core fragments that
Figure 6. Crystallographically determined binding mode of B1 in
complex with cSrc together with electron density map (2Fo − Fc
contoured at 1σ). The fragment binds to the hinge region of the kinase
domain. The binding site is oriented as depicted in Figure 1a. Putative
hydrogen bonds are indicated as dashed lines. PDB code: 4fic.
Comparison of Predicted and Observed Inhibition
Profiles. To compare the modeling results with the
experimental inhibition data, we docked the 15 compounds
that were profiled in our kinase panel (Figure 4) into the
binding site of the kinases in the docking panel (Supplementary
Table S1). The rank obtained for the least favorable scoring
inhibitor among the 15 tested compounds for each kinase was
compared to the number of identified hits for that target
(Supplementary Table S6). If docking performance was perfect,
both numbers would be identical (e.g., if two hits were
identified for a kinase the ligand with the lowest score should
have rank 2 with the other ligand being on rank 1). While for
some targets the worst rank corresponded closely to the
number of identified hits, for most targets separation between
active and inactive compounds was not possible, both when a
cutoff value of ≥40% (data not shown) or ≥75% inhibition was
used. Similarly, docking failed to predict the selectivity profile
of the inhibitors (Supplementary Table S7). For this
comparison, the scores for all 15 compounds docked into all
46 protein structures were normalized relative to the best score
for any fragment in the active site of each kinase obtained when
docking the library of candidate core fragments. Compounds
were considered to be predicted as active if their normalized
score was ≥1.0 (equal or better than the best score for a core
fragment in a particular kinase). At the chosen cutoff level,
there was only little agreement between predicted and
confirmed activity. For instance, compound B1, the least
selective ligand in the panel, was predicted to be active for only
nine out of the 31 kinases for which activity was found. In
contrast, E1 and F2, the most selective compounds in the panel
were predicted to bind to 10 and 21 kinases, respectively.
However, neither compound demonstrated activity against
these kinases in a biochemical assay. The only compound for
which the profile was predicted correctly was B4, which did not
inhibit any kinase in the docking panel.
Overall, the chosen de novo design strategy (Figure 1b) was
highly successful. Starting with a database of core fragments, six
F
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only carbon atoms or carbon atoms and aromatic sulfur or oxygen
atoms were disregarded.
were chosen for library synthesis and for which examples were
tested in a kinase panel this turned out to be the case. When
trying to predict the selectivity profiles of the tested library
compounds, docking failed to give useful guidance (Supple-
mentary Table S7). This failure is driven by the inability to
correctly rank the tested compounds according to their affinity
for given kinases (Supplementary Table S6). Small changes,
such as adding a nitrogen atom to the heterocycles (E1 vs F1,
Figure 4), which change the selectivity of the compounds are
not accurately captured by the used scoring function, and
furthermore discrimination between more drastic changes, such
as ranking structurally unrelated compounds, failed in most
cases. In addition, predicting the effect of the subtle differences
in the kinase binding sites on compound affinity remains a
challenge.14 In the past, more promising results were obtained
by using structural and inhibition data to train predictors.31−34
However, due to their nature, these approaches do not allow to
make predictions for new compound classes or kinases.
A number of compounds were chosen for IC50 determi-
nations against selected kinases (Table 1). All tested
compounds were characterized by high ligand efficiencies
(≥0.30 kcal/mol heavy atom) for at least one kinase, rendering
them in general promising starting points for drug discovery for
a range of targets with high medical interest.26 Among others,
compounds with high ligand efficiencies were identified for
MAPKAP-K3, SRPK1, SGK1, TAK1, and GCK (Table 1). For
all of these kinases less than 30 compounds with affinities
≤100 μM are reported in ChEMBL Kinase SARfari (as of April
2012).23 They are thought to be targets for the treatment of
cancer, systemic inflammation response syndrome, rheumatoid
arthritis, other inflammatory diseases, and hypertension.35−39
The hits identified by our in silico study can serve as starting
points to further explore these targets.
Summary and Conclusion. A de novo design approach for
novel kinase inhibitors was established that was centered on
core fragments having precedence for synthesis but no reported
activity against kinases. Using a wide range of methods at the
interface of chemistry and biology, e.g., structure-based design,
chemical synthesis, X-ray crystallography and biological
profiling, the approach was validated. Six small molecule
libraries were synthesized. Selected compounds were profiled in
a large kinase panel, and dose−response curves were
determined. In addition, the binding mode of one compound
was confirmed using X-ray crystallography. Whereas predicting
binding modes and general activity against kinases was very
reliable, correctly predicting selectivity solely based on docking
to crystal structures failed. Nevertheless, this study demon-
strated the overall success of the chosen design strategy. In
addition, a number of inhibitors with good binding efficiency
were identified for a range of kinases with therapeutic relevance
and can now serve as starting points for chemical tools to
further explore these targets.
Fragment Selection. Three filters were used to eliminate
inappropriate or undesirable scaffolds from the generated database
of core fragments. First, fragments that contained unwanted
functionalities as described previously were removed.11 Second,
fragments that did not comply with a modified “Rule of Three”
were removed from the database.40 Here, only ring fragments with
MW < 300 Da, number of hydrogen bond donors ≤3, number of
hydrogen bond acceptors ≤6, and clogP ≤ 3 were retained.
Additionally, core fragments with the total charge ≤ −1 or ≥1 were
removed. Finally, compounds containing more than two fused rings or
more than six rotatable bonds were rejected.
Pharmacophore Search. The 3D pharmacophore search was
carried out using the UNITY tool available with the SYBYL-X 1.0
package (Tripos Inc.). The default file sln3d_macros.def that contained
the definition of predefined feature types (macros) such as hydrogen-
bond acceptor or hydrogen-bond donor was modified to also account
for C−H···O hydrogen bonds as often observed in protein kinases
(Supplementary Figure S1b). Otherwise, default settings were used
when converting the filtered core fragments to a 3D UNITY database.
The pharmacophore was generated based on the crystal structure of
CDK2 in complex with an imidazole piperazine inhibitor (PDB code
2w05). The resulting pharmacophore model was made up of four
features (Supplementary Figure S1a). One hydrogen-bond acceptor
and two hydrogen-bond donor features (radius 0.6 Å) were defined to
interact with the hinge region. To consider the directionality of the
hydrogen bonds, the features were linked with their hydrogen-bond
binding partners in the protein. The aromatic feature (radius 1.5 Å)
was added to take into account that the vast majority of protein kinase
inhibitors contain an aromatic ring system that is placed within the
adenine binding region.14 To fulfill the pharmacophore, all hits were
required to contain the aromatic feature and two out of the possible
three hydrogen-bonding features.
Receptor Preparation. Crystal structures of protein kinases that
were available in the MRC Protein Phosphorylation Unit, University
of Dundee, for profiling at the beginning of the study were
downloaded from the PDB (Supplementary Table S1). All crystal
structures representing these kinases exhibit the DFG-in conforma-
tion.6 The structures were aligned with CDK2 (PDB code 2w05)
using the hinge region as matching atoms. Hydrogen atoms of polar
groups were added using MOLOC (Gerber Molecular Design), and
their positions were minimized with the MAB force field as
implemented in MOLOC.41 Subsequently, all nonprotein atoms
were removed from the crystal structures. Compounds were placed
into the binding site and scored using DOCK 3.5.54.42,43 The required
sphere set to define the region with a low dielectric constant was
composed of the bound ligands’ atoms. If necessary, the set was
manually modified to cover the entire buried part of binding site. The
sphere set used as matching points for docking was manually
generated by placing matching atoms into the adenine binding region
close to the hinge region. The same set was used for all protein
kinases. To favor interactions between ligand and hinge region, partial
charges of the carbonyl oxygen atoms in the amide backbone of the
hinge region were decreased by 0.4, and the partial charge of the amide
hydrogen atom was increased by 0.4 (Figure S1a). The total charge
was then balanced by distributing the charge difference among the
remaining hinge region atoms. Grids to store information about
excluded volumes, van der Waals potential, and ligand desolvation
were calculated as described previously.44,45
METHODS
■
Ligand Preparation. Tautomers, stereoisomers, and protonation
states were enumerated and converted to a suitable database format as
described previously.44
Docking Protocol. Multiple conformations and orientations of
each ligand were docked into the kinase binding sites using DOCK
3.5.54.42,43 Ligand and receptor overlap bins were set to 0.4 Å.
Distance tolerance for matching ligand atoms to receptor was set to
1.2 Å. All fragments were docked into the ATP binding pocket, and
each docking orientation was filtered for steric fit. Only fragments that
were able to pass the steric fit filter were scored for electrostatic, van
Core Fragment Extraction. Core fragments were derived from an
in-house database containing more than two million commercially
available compounds using a method described previously.11 In brief,
core fragments were defined as ring atoms plus the atoms of directly
attached polar functional groups. Polar functional groups were
specified as polar hetero atoms (S, N, P, or O) and polar hetero
atoms double or triple bonded to carbon atoms or linked to other
polar hetero atoms or carbonyl groups. Functional groups linking ring
atoms were added to both resulting scaffolds. Fragments containing
G
dx.doi.org/10.1021/cb300729y | ACS Chem. Biol. XXXX, XXX, XXX−XXX

ACS Chemical Biology
Articles
der Waals, and desolvation energies. The best scoring conformation
and representative (tautomer, protonation state) of each compound
was used for final ranking.
Notes
The authors declare no competing financial interest.
To compare fragments between different kinases, the originally
norm
ACKNOWLEDGMENTS
calculated energy scores were normalized by the formula Sij
= Sij/
■
norm
Sjbest where Sij
is the normalized score for fragment i in the active
This work was supported by the Welcome Trust (WT083481)
and through a CASE studentship for R.U., jointly funded by
MSD&Schering-Plough and the Biotechnology and Biological
Sciences Research Council. N.T.-L. was supported by a
fellowship from the German Academic Exchange Service
(DAAD). We thank OpenEye for free software licenses, J.
Downward (University of Dundee) for administration of the
workstations, A. Hinton (MSD&Schering-Plough, Newhouse,
U.K.) for help with Pipeline Pilot, and the staff in the MRC
Protein Phosphorylation Unit at the University of Dundee for
carrying out the kinase assays. D.R. is grateful for funds by the
German Federal Ministry for Education and Research, which
supported this work through the German National Genome
Research Network-Plus (NGFNPlus) (Grant No. BMBF
01GS08104).
site of kinase j, Sij is the original score, and Sjbest is the best score for
norm
any ligand in the active site of the kinase j. All negative Sij
scores
norm
were set to zero. Thus, Sij
= 1 if the fragment scores best of all
norm
docked fragments for a particular kinase, and Sij
= 0 if it scores
worst.
Library Enumeration. The reagents were selected through a web
interface based on Pipeline Pilot (Accelrys Software Inc.). Only in-
house reagents that were commercially available were used for the
enumeration process. Enumeration of libraries was performed using
the “core plus R-groups” method from Pipeline Pilot which was again
presented through a customized web interface. All reaction products
were filtered to remove molecules with unwanted functionalities, >5
hydrogen-bond donors, >10 hydrogen bond acceptors, molecular
weight >500 Da, clogP > 5, and polar surface area >140 Å. Finally, all
remaining reaction products were docked into the binding site of three
kinases (CSK, RSK1, and GSK3β) to exclude those compounds which
did not sterically fit into a typical ATP binding site.
Chemistry. All synthesized compounds had a purity of greater than
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Corresponding Author
*E-mail: brenk@uni-mainz.de; p.g.wyatt@dundee.ac.uk.
H
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