Design, Synthesis, and Evaluation of Dasatinib–Amino Acid and Dasatinib–Fatty Acid Conjugates as Protein Tyrosine Kinase Inhibitors

Article abstract of DOI:10.1002/cmdc.201600387

Derivatives of the tyrosine kinase inhibitor dasatinib were synthesized by esterification with 25 carboxylic acids, including amino acids and fatty acids, thereby extending the drug to interact with more diverse sites and to improve specificity. The dasatinib–l-arginine derivative (Das-R, 7) was found to be the most potent of the inhibitors tested, with IC₅₀values of 4.4, <0.25, and <0.45 nm against Csk, Src, and Abl kinases, respectively. The highest selectivity ratio obtained in our study, 91.4 Csk/Src, belonged to compound 18 (Das-C₁₀) with an IC₅₀value of 3.2 μm for Csk compared with 35 nm for Src. Furthermore, many compounds displayed increased selectivity toward Src over Abl. Compounds 15 (Das–glutamic acid) and 13 (Das–cysteine) demonstrated the largest gains (10.2 and 10.3 Abl/Src IC₅₀ratios). Das-R (IC₅₀=2.06 μm) was significantly more potent than the parent dasatinib (IC₅₀=26.3 μm) against Panc-1 cells, whereas both compounds showed IC₅₀<51.2 pm against BV-173 and K562 cells. Molecular modeling and binding free energy simulations revealed good agreements with the experimental results and rationalized the differences in selectivity among the studied compounds. Integration of experimental and computational approaches in the design and biochemical screening of dasatinib derivatives facilitated rational engineering and diversification of the dasatinib scaffold, providing useful insight into mechanisms of kinase selectivity.

Full text of DOI:10.1002/cmdc.201600387

Accepted Article
Title: Design, Synthesis, and Evaluation of Dasatinib-Amino Acid and
Dasatinib-Fatty Acid Conjugates as Protein Tyrosine Kinase
Inhibitors
Authors: Rakesh K Tiwari, Alex Brown, Amir Nasrolahi Shirazi, Jared
Bolton, Amanda Tse, Gennady Verkhivker, Keykavous
Parang, and Gongqin Sun
This manuscript has been accepted after peer review and appears as an
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of the final Version of Record (VoR). This work is currently citable by
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the VoR from the journal website shown below when it is published
to ensure accuracy of information. The authors are responsible for the
content of this Accepted Article.
To be cited as: ChemMedChem 10.1002/cmdc.201600387
Link to VoR: http://dx.doi.org/10.1002/cmdc.201600387
A Journal of
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ChemMedChem
10.1002/cmdc.201600387
Design, Synthesis, and Evaluation of Dasatinib-Amino Acid and
Dasatinib-Fatty Acid Conjugates as Protein Tyrosine Kinase
Inhibitors
[
b]
[a]
[b]
[b]
Rakesh K. Tiwari,* Alex Brown, Neda Sadeghiani, Amir Nasrolahi Shirazi, Jared
[
a]
[c]
[c]
[b]
[a]
Bolton, Amanda Tse, Gennady Verkhivker,* Keykavous Parang,* and Gongqin Sun*
[
[
[
a]
Dr. A. Brown, J. Bolton, Prof. G. Sun
Department of Cell & Molecular Biology
389 CBLS Building, 120 Flagg Road
University of Rhode Island
Kingston RI 02881, (USA)
E-mail address: gsun@uri.edu
b]
Prof. R. K. Tiwari, Dr. Neda Sadeghiani, Dr. A. N. Shirazi, Prof. K. Parang
Department of Biomedical and Pharmaceutical Sciences
Chapman University School of Pharmacy
9401 Jeronimo Road, Irvine, CA 92618, (USA)
E-mail address: tiwari@chapman.edu
E-mail address: parang@chapman.edu
c]
Amanda Tse, Prof. G. Verkhivker
Schmid College of Science and Technology Physics
Computational Science and Engineering
Chapman University, Orange, CA, 92866, (USA)
E-mail address: verkhivk@chapman.edu
Supporting Information for this article is given via a link at the end of the document.
1
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10.1002/cmdc.201600387
TITLE RUNNING HEAD. Fatty acyl and amino acyl derivatives of dasatinib: synthesis,
evaluation, and molecular modeling studies.
2
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ChemMedChem
10.1002/cmdc.201600387
Abstract
Derivatives of dasatinib were synthesized via esterification with 25 carboxylic acids including
amino acids and fatty acids by extending the inhibitor to interact with more diverse sites and to
improve specificity. Dasatinib-L-arginine derivative (Das-R, 7) was the most potent of the
inhibitors tested with IC50 values of 4.4 nM, <0.25 nM, and <0.45 nM against Csk, Src, and Abl
kinases, respectively. The highest selectivity ratio obtained in our study, 91.4 Csk/Src belonged
to compound 18 (Das-C10) with an IC50 of 3.2 µM for Csk compared to 35 nM for Src.
Furthermore, many compounds displayed increased selectivity toward Src, as compared with
Abl. Compounds 15 (Das-E) and 13 (Das-C) demonstrated the largest gains (10.2 and 10.3
Abl/Src IC50 ratios). Das-R (IC50 = 2.06 µM) was significantly more potent than Das (IC50 = 26.3
µM) against Panc-1 cells while they both showed an IC50 < 51.2 pM against BV-173 and K562
cells. Molecular modeling and binding free energy simulations revealed a good agreement with
the experimental results and rationalized differences in selectivity of the studied compounds.
Integration of experimental and computational approaches in the design and biochemical
screening of dasatinib derivatives facilitated rational engineering and diversification of dasatinib
scaffold, providing useful insights into mechanisms of kinase selectivity.
3
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10.1002/cmdc.201600387
Introduction
Protein tyrosine kinases (PTKs) are involved in numerous pathologies, including many
cancers. Furthermore, PTK inhibitors have proven to be invaluable research and therapeutic
tools. Ideally, such molecules would be able to target the aberrant kinases without interfering
with normal physiological kinase signaling. Current PTK inhibitors as ATP-binding site inhibitors
1
have limited specificity , most likely due to the high degree of conservation within their targets’
ATP binding pockets. This problem stems from a lack of structural diversity in the ATP binding
pocket, similar in all kinases. The potent tyrosine kinase inhibitor (TKI) dasatinib, N-(2-chloro-6-
methylphenyl)-2-((6-(4-(2-hydroxyethyl)piperazin-1-yl)-2-methylpyrimidin-4-yl)amino)thiazole-
5-carboxamide (BMS-354825), is a case in point. It binds to the ATP binding site of many PTKs
and is a potent broad spectrum PTK inhibitor.2
The discovery of dasatinib was announced by Bristol-Myers Squibb in 2004 as an orally
3
administered anticancer compound. In 2006, the company was granted FDA tentative approval
4
for dasatinib, via the accelerated review process. Initially, approved indications for use applied
only to adult patients diagnosed with either Philadelphia chromosome-positive (Ph+) chronic
myeloid leukemia (CML) in the chronic phase, or Ph+ acute lymphoblastic leukemia (ALL), who
were intolerant or resistant to standard imatinib (Gleevec, by Novartis) treatment. In 2010, full
approval was granted for the treatment of imatinib-resistant Ph+ ALL/CML, once further safety
and efficacy were established. This extended the approved indications to include less developed
Ph+ CML, still in the accelerated or blast phases.5
The Ph+ profile of many ALL/CML cancers is readily observed via standard karyotype,
6
as it involves a large and very specific translocation between chromosomes 9 and 22. This
chromosomal aberration induces abnormal expression of a BCR (Breakpoint Cluster Region,
22q11.21) – Abl (9q34.12) fusion-protein. The fusion of the two proteins disrupts the normal
regulatory mechanisms of each. In particular, the loss of the N-terminal domains of Abl removes
key components of substrate recognition, cellular localization, and catalytic inactivation. The
4
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ChemMedChem
10.1002/cmdc.201600387
truncated kinase is responsible for creating a highly distorted pattern of phosphorylation,
upsetting normal cell signaling dynamics, and leading to the oncogenic progression of ALL or
CML. TKIs, such as imatinib and dasatinib, inhibit cancer progression by blocking the kinase
activities of BCR-Abl and/or other kinases that are known to contribute oncogenic signaling,
such as Src Family Kinases (SFK).
Dasatinib inhibits SFKs, BCR-Abl, c-KIT, EphA2, PDGFR-beta kinases with nanomolar
or sub-nanomolar IC50.5 It has also been crystalized as a bound ligand to the Abl, BMX, BTK,
EphA4, Lyn, p38alpha, p38MAP, and Src kinases.7-14 The common manner in which it binds to
each of these kinases, suggests it should be similar for many other kinases, too. This may, in
part, explain side-effects of the compound at clinical dosage. Moreover, the clinical dosage,
itself, may be limited by toxicity due to off-target kinase inhibition. This can lead to the
persistence of cancer in small, drug-resistant populations and, ultimately relapse of patients who
were previously in remission. In some patients, mutations arise during the course of treatment,
or before. In all of these cases, where resistance has developed, alternative therapies must be
sought.
The problems associated with balancing toxicity with effective dosage are not unique to
dasatinib. All currently available TKIs are expected to lose effectiveness at some point to restart
disease progression. From this perspective, it seems obvious that greater kinase specificity
should be a top priority in the development of novel therapeutic inhibitors. However, it seems
likely that many kinases share too much similarity to reasonably expect true specificity from ATP
analogs, even from drugs with the potency of a molecule like dasatinib.
Outside of the ATP-binding cleft of PTKs there are several regions of great variability
amongst kinases, as demonstrated in Figure 1. We reasoned that by extending dasatinib from
the ATP binding pocket into these variable regions, the derivatives may obtain new kinase-
specific interactions, which would lead to inhibitory specificity toward a given kinase. This
concept is further strengthened by the finding that the loop that connects α-helixes D and E in
5
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ChemMedChem
10.1002/cmdc.201600387
Csk harbors the key residues of a substrate-docking site that is unique to the Csk family kinases,
Csk and Chk.15-16 Conveniently, dasatinib binds to the kinase in such a way that its hydroxyl
group is located just outside of the ATP-binding cleft and very close to the Csk substrate-docking
site. This observation led to the strategy of modifying the hydroxyl group of dasatinib with various
functional groups in the hope that some of them will interact with the substrate docking site or
nearby kinase-specific motifs, resulting in inhibitory specificity. It has been demonstrated
previously that the hydroxyl group can be modified without affecting the interaction of dasatinib
with the ATP-binding site, it can be used to facilitate attachment to chromatographic resins for
affinity purification.17-19
By the addition of small molecules to the dasatinib scaffold, it may be possible to extend
the binding site to include regions of the kinase that are more diverse in order to impart greater
potential PTK specificity. We hypothesized that specificity may be developed by extending the
inhibitor out from the traditional ATP-binding pocket to interact with more diverse sites.
Figure 1. Dasatinib inhibition of kinase activity is mediated by molecular interaction with highly conserved residues
from the ATP-binding cleft of the catalytic domain. (A) The MUSCLE aligned protein sequences from the catalytic
6
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ChemMedChem
10.1002/cmdc.201600387
domains of Abl, Csk, Src, and Lyn illustrate the level of conservation throughout various regions of the catalytic
domain among these diverse PTKs. The darker shaded portions of the alignMent indicate greater conservation.
The ligand-bound crystal structure of Lyn (B) demonstrates how dasatinib is docked within the catalytic domain.
The inhibition of kinase activity is achieved via molecular interaction with amino acids of the ATP-binding cleft.
These residues are displayed in stick form in the structure and also indicated by black arrowheads within the
alignMent. The region of the catalytic domain between the end of αD-helix and the beginning of αE-helix is boxed
within the alignMent and structure to highlight its variability and proximity to the binding site.
We sought to evaluate this strategy by linking dasatinib to a series of amino acids and
fatty acids via esterification reactions. The selection of amino acids and fatty acids for
conjugation with dasatinib was based on their diverse structures and physicochemical
properties, and the presence of different functional groups. Following favorable molecular
modeling results, we employed this technique to build a small library of 25 compounds (Figure
2
and Figures S1, S2, Supporting Information). Three non-receptor PTKs (Csk, Abl, and Src)
were used for evaluating these compounds in terms of their potency and specificity. Several
selected compounds were then further explored to reveal some unique properties and potential
applications of these novel inhibitors.
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10.1002/cmdc.201600387
Figure 2. Dasatinib was used as a scaffold for the attachment of various amino acids and fatty acids.
Results
Chemistry
Schemes 1 and 2 depict the synthesis of amino acid and fatty acid conjugates of
dasatinib by using an ester linkage. In brief, dasatinib was coupled to Boc-protected amino acids
using
N-(3-dimethylaminopropyl)-N′-ethylcarbodiimide
hydrochloride
(
EDC)/hydroxybenzotriazole (HOBt) and N-methylmorpholine (NMM) as coupling and activating
reagents under an anhydrous condition using DMF as a solvent. The conjugation of fatty acids
with dasatinib was conducted with under a similar condition using the same coupling and
activating reagents. However, in the case of long-chain fatty acids, such as stearic acid and
8
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ChemMedChem
10.1002/cmdc.201600387
eicosanoic acid, the use of dichloromethane was needed to improve the solubility of fatty acids
during the coupling reaction. Furthermore, for long chain fatty acids, more time (24-72 h) was
required in the coupling reaction. The Boc protection group from the coupled amino acids
derivatives was removed in the presence of p-toluenesulfonic acid (pTsOH) in acetonitrile. The
crude products were purified by flash silica gel column chromatography. All synthesized
compounds were characterized by using H and 13C nuclear magnetic resonance (NMR)
spectroscopy and high-resolution time-of-flight electrospray mass spectrometry. The purity of
final products (≥95%) was confirmed by reverse phase analytical HPLC. Synthesis yields ranged
1
80 to 91% for fatty acid conjugates and 20-84% for amino acid conjugates.
Me
N
N
Me
N
H
N
N
HOOC
HNBoc
N
S
H
N
O
Cl
OH
X
Dasatinib (1)
Me
N
N
Me
N
H
N
O
N
EDC.HCl/HOBt/NMM/DMF
4 h at 25 C
N
S
H
N
HNBoc
O
2
Cl
N
O
Me
X
N
N
Me
H
N
pTsOH/CH CN
N
3
O
N
S
H
N
2h, 25 C
O
NH2
Cl
O
X
Dasatinib-amino acid derivatives (2-15)
X = -H, -CH , -(CH ) NH-C(NH )=NH, -CH(CH )-(CH )-CH , -CH CH(CH ) , -CH Ph-OH,
3
2 3
2
3
2
3
2
3 2
2
-CH OH, -CH CH SH, -CH CH COOH, -CH CH SCH , -CH CONH , -CH CH CONH ,
2 2 2 2 2 2 2 3 2 2 2 2 2
-
CH CH -3-Indole ring
2
2
Scheme 1. Synthesis of dasatinib-amino acid conjugates (2-15).
9
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10.1002/cmdc.201600387
Scheme 2. Synthesis of dasatinib-fatty acid conjugates (16-25).
Modeling to Establish the Theoretical Feasibility of Binding and Rule Out Steric
Hindrance of Dasatinib Derivatives. In order to establish the theoretical feasibility of modeling
experiments, we first conducted control docking simulations of dasatinib with the protein
conformations obtained from the crystal structures of dasatinib complexes with Abl (pdb id
2GQG), Csk (pdb id 3QLG), Src (pdb id 3G5D), Lyn (pdb id 2ZVA), Btk (pdb id 3K54, 3OCT),
Bmx (pdb is 3SXR), EphA4 (pdb id 2Y6O), and P38 kinase (pdb id 3KFA). The lowest energy
docked poses of dasatinib complexes reproduced crystallographic inhibitor conformations within
RMSD = 1.5 Å (root mean square deviation). The predicted structures of dasatinib complexes
were subjected to 200 ns molecular dynamics (MD) simulations, and the obtained trajectories
were subsequently used in MM-GBSA calculations of binding free energies (Figure S3,
Supporting Information). For consistency of comparison with the experiment, we utilized the
results of kinase inhibitors screening in in vitro competition binding assays that were followed
by determination of quantitative dissociation constants K
for high-affinity inhibitors.20-21
d
Molecular docking and binding free energy simulations validated the utility of the
computational approach in rational design of dasatinib analogs by reproducing the experimental
1
0
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10.1002/cmdc.201600387
binding affinities of dasatinib across a spectrum of kinase targets. In particular, the computed
binding affinities correctly discriminated weak Dasatinib binding to p38α kinase from significantly
stronger binding with Abl, Src, and Lyn kinases.
Equipped with a good agreement with experimental results for a range of known crystal
structures of dasatinib complexes, we embarked on modeling of the selected derivatives with
Abl, Csk, and Src kinases to evaluate binding propensities of dasatinib derivatives and rule out
a potential steric hindrance. In docking of all derivatives, we used the crystal structures of
dasatinib complexes with Abl, Csk, and Src. As a control, the selected dasatinib derivatives were
1
0
also docked into the crystal structure of the Lyn kinase , which is a member of the clinically
relevant SFK family. The resolution and completeness of the crystal structure of the Lyn kinase
outside of the dasatinib binding pocket was important in our modeling, given that the additions
to the core compound could potentially interact with a region outside the traditional binding
pocket. We chose to model each of the 20 common amino acids, along with the addition of
phosphotyrosine, as carboxyesters of dasatinib to establish the feasibility of our approach.
Combining accuracy and ease of use, we chose Autodock Vina to perform our in silico
modeling. Autodock Vina’s performance in dockings has been relatively well established, and
its algorithms require no assumptions to be made concerning the ionization of side-chains.22-23
The first feature that the models predict is the preferred orientation of the compounds that were
attached to dasatinib. Despite allowance to rotate freely, almost all of the simulated dockings
favor interaction with the region surrounding αD-helix, rather than the equally proximal ATP
binding lobe of the kinase (Figure 3).
1
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Figure 3. The predicted docked poses of dasatinib derivatives DAS-A (3), DAS-E (15), and DAS-R (7) were
superimposed with the crystallographic conformation of dasatinib. Crystal structure of dasatinib-bound Abl kinase
(
pdb id 2GQG, blue). The docked conformations of dasatinib derivatives to Abl are shown in sticks colored
according to the atom type, and the crystallographic conformation of dasatinib bound to Abl is shown in cyan sticks.
All of the compounds were docked, and the top hits for each compound (Figure S4,
Supporting Information) were subsequently subjected to 200 ns MD simulations. MM-GBSA
calculations using the obtained trajectories provided binding free energies and compound
ranking as reported in Figure S5 (Supporting Information).
The core dasatinib portion of each derivative was nearly identical and showed only small
deviation from the original crystallized ligand after structural superposition. The binding free
energies of dasatinib (compound 1) with Abl, Csk and Src were in good agreement with the
experimental binding constants. The computed binding energetics of all derivatives were within
1
2
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10.1002/cmdc.201600387
0
.9 kcal/mol of the dasatinib biding free energy, indicating that the proposed chemical
modifications could be well tolerated. The favorable binding energies of dasatinib derivatives
Figure S5, Supporting Information) suggested that these small molecules may potentially
(
enhance dasatinib binding by maintain scaffold interactions andf making additional favorable
contacts outside the ATP binding pocket.
Design and Synthesis. By utilizing computational predictions in rational design of dasatinib
analogues, we explored chemical esterification with various amino acids as these adducts were
predicted to extend out from the ATP binding pocket while preserving the crystallographic mode
of dasatinib scaffold. Alongside these compounds, additional derivatives were synthesized by
esterification with several fatty acids. These particular derivatives were chosen to evaluate their
potential use as linkers to sites more distal to the ATP binding pocket. Using his approach, 25
compounds were successfully synthesized and purified including 14 amino acid and 10 fatty
acid adducts of dasatinib (compounds 2-25). Compound 26 was later synthesized according to
the previously reported procedure24 as a fluorescein-glycine ester to demonstrate further the
utility of such chemical derivatives.
Compound Screening. Each of the amino acid and fatty acid conjugates of dasatinib was
screened at a fixed concentration: 250 pM against Abl, and Src, and 8 nM against Csk. The
respective concentrations were selected based on IC50 of dasatinib against each enzyme. Their
percent inhibition relative to dasatinib was then determined. The results of this screening (Figure
4) offered insight as to the potency of each adduct, relative to dasatinib. Moreover, this relative
profile could be compared between Abl, Csk, and Src kinases. Thus, this screening helped to
highlight potential patterns of enhanced or diminished inhibition relating to the type of adduct.
1
3
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In general, fatty acyl-derived compounds (16-25) dramatically decreased inhibitor
potency. Among all of these compounds, only compound 16 (Das-C ) inhibited comparably to
dasatinib. Each of the other fatty acid derivatives (17-25) exhibited less than 60% of dasatinib’s
inhibition toward each kinase. Figure 4 shows that Das-C10, Das-C12, and Das-C11SC have
2
2
H
5
inhibitor potencies in a similar range as compound 24. This screening profile suggests that
hydrophobicity, not size, accounts for much of these inhibitors’ reduced potency. The size of
compound 24 with the amino group is similar, in particular, to that of Das-C10 and Das-C12 which
do not have polar groups. Furthermore, losses in potency due to long, hydrophobic chains may
be recovered, at least in part, by linkage to a polar functional group (like –NH ).
2
The amino acid derived compounds (2-15) showed significantly greater potency over fatty
acyl derivatives, with the exception of compound 13 with a cysteine residue (Das-C). Compound
15 containing a glutamic acid (Das-E) also displayed a significantly reduced potency when
compared to other amino acid derivatives. Compound 7 containing an arginine residue (Das-R)
appeared to be the most potent of the inhibitors tested against all three kinases (Figure 4).
Interestingly, the side-chain guanidinium group of compound 7 (Das-R) was predicted to form a
hydrogen bond with the backbone of the kinase, just outside the ATP-binding cleft.
1
4
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ChemMedChem
10.1002/cmdc.201600387
Figure 4. Results of screening of compounds at a fixed concentration against each of the panel PTKs. The activity
of uninhibited enzyme was compared to dasatinib-inhibited enzyme activity to establish a baseline of inhibition.
Each of the compounds were then compared to dasatinib inhibition for each enzyme. Bars above the x-axis show
increased potency while those below indicate a decreased capacity to inhibit the kinase, relative to dasatinib. The
error bars represent the SEM of at least three determinations.
The major changes in potency by our derivatives are interesting and perhaps informative
but are not the main focus of our study. Since we endeavor to identify an active agent with
altered kinase selectivity, the compounds’ variable potency between kinases was our greatest
concern. Compounds 21 (Das-C16), 24 (Das-C11NH
decreased capacity to inhibit Abl, as compared to the other kinases (Figure 4). Compound 7
Das-R), however, demonstrated its potency gains were greatest for Abl. Additionally, compound
6 (Das-C ) displayed significantly increased potency toward Csk when compared to Abl and
2
), and 23 (Das-C20) showed a significantly
(
1
2
1
5
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ChemMedChem
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Src. The screening assay’s sensitivity, however, limited the extraction of further selectivity
results.
IC50 determination. The screening, while relatively rapid, is not incredibly sensitive and, thus,
is limited in the task of identifying changes in kinase specificity. We further characterized the
inhibition of selected compounds via IC50 assays toward each of the kinases. Compound 7 (Das-
R) was chosen because it was one of the best compounds screened for each of the kinases in
terms of potency and selectivity. We then chose compounds 3, 13, and 15 (Das-A, Das-C, Das-
E) to use as a basis for comparison and to tease out potential differences in selectivity. For the
fatty acid-derived compounds, we again chose to compare the most potent compound, 16 (Das-
C
2
), one longer chained derivative (21, Das-C16), two moderately long-chained compounds
17/Das-C , 18/Das-C10), and the potential linker compound 24 (Das-C11NH ) for further
investigation.
(
8
2
The results of the IC50 assays, summarized in Table 1, reflect the potency of the
compounds toward each of the PTKs. As predicted by the screenings, compound 7 (Das-R)
displayed increased potency against all kinases with an average 37% decrease in IC50
compared to dasatinib. The greatest gain in potency was observed for Abl by compound 7 (-R)
with an IC50 of <0.45 nM as compared to the <0.75 nM value for dasatinib, representing a 42%
decrease. Conversely, compound 13 (Das-C) was the worst performing of the amino acid
derivatives with IC50’s ranging from 1.7-5.3x higher than dasatinib toward our PTK panel.
Interestingly, compound 15 (Das-E) performed about as well as compound 3 (Das-A), despite
the latter showing possible signs of greater potency in the screenings.
1
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Table 1. Selected compounds were evaluated against each of the enzymes in our panel. Potency was measured via IC50 in standard P32 kinase assay with
appropriate substrate. Selectivity is represented as the ratio of IC50 for one enzyme over another. The change in IC50, as compared to dasatinib, is calculated and
shown in the right-most columns to illustrate how potency was affected.
IC50 [nM]#
Csk
7
Selectivity
C/S
Net change in IC50 (%Dasatinib)
Compd Name
No.
Abl
<0.78
<0.45
2.1
Src
C/A
9.0
A/S
2.1
Abl
Csk
--
Src
--
Avg
--
1
7
Dasatinib
<0.37
<0.25
<0.33
<0.39
<0.43
1
18.9
--
Das-R
Das-C
4.4
9.8
17.6
1.8
6.4
-42
-37
-32
-11
5
-37
1
6
2
5.5
2.6
16.7
169
285
464
528
8618
6438
28105
-21
46
3
Das-A
3
21
7.0
53.8
7.7
200
186
329
7043
8471
45614
163
222
342
5782
5612
27693
1
5
4
3
7
8
Das-E
4.4
20
4.5
46.5
10.2
4.9
16
2
1
1
1
Das-C11-NH
Das-C
2
4.9
30
6.1
30.0
170
1684
1927
9359
68
500
600
3200
6.6
7.4
75.8
10.3
6.8
Das-C
8
51
7.5
11.8
14.5
80.0
Das-C10
220
35
91.4
6.3
1
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2
1
Das-C16
680
5100
75
7.5
68.0
9.1
87079
72757
20170
60002
#The standard errors were in the range of 0.034-0.095 nM for Src, 0.041-0.242 nM for Csk, and 0.041-0.109 nM for Abl. All kinase inhibition assays were
performed in duplicate at least three times.
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To garner more quantitative insight into potential gains or losses in enzyme selectivity,
the IC50 of each compound toward a particular kinase can be compared to the IC50 of the same
compound for another kinase, in the form of a ratio. The IC50 of dasatinib was 7 nM, <0.37 nM,
and <0.78 nM against Csk, Src, Abl, respectively, giving a ratio of 18.9 Csk/Src and a ratio of
2.1 Abl/Src clearly indicating inhibiting both Abl and Src kinases in rather non-selective fashion.
When comparing Abl and Src, however, a ratio of 2.1 A/S for dasatinib implies that the
compound inhibits both kinases in rather non-selective fashion. In this manner, ratios greater
than 10 or less than 0.1 reflect IC50s that differ by more than an order of magnitude, and the
inhibitor is generally considered to be selective or specific for the kinase with the lower IC50. Our
approach generated numerous inhibitory compounds with enhanced kinase selectivity.
Comparisons of the specificities for each of the compounds toward Csk shows that two
compounds, 7 (Das-R) and 16 (Das-C ), showed little change in their preference for Src (17.6
2
A/S and 16.7 C/S, respectively). However, each of the remaining compounds increased their
preference for Src dramatically with C/S IC50 ratios of 30.0 or higher. The highest selectivity ratio
obtained in our study, 91.4 C/S, was from this group and belonged to compound 18 (Das-C10
)
with an IC50 for Csk = 3.2 µM compared to 35 nM for Src. This marks a difference of almost two
orders of magnitude between the IC50 values. Additionally, each of these compounds displayed
increased selectivity toward Src, as compared with Abl. Of particular note, compound 15 (Das-
E) and compound 13 (Das-C) demonstrated the largest gains (10.2 and 10.3 A/S IC50 ratios).
These two dasatinib derivatives represent the only bona-fide Src specific inhibitors in our
dataset, as they possess IC50’s at least an order of magnitude higher for both Abl and Csk, and
present a significant increase in kinase specificity when compared to dasatinib.
Modeling to Rationalize Differences in Specificity. We used computational modeling to
evaluate binding energetics and differences in selectivity for the panel of studied compounds
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10.1002/cmdc.201600387
(Table 1). In this analysis, 200 ns MD simulations followed by MM-GBSA binding free energy
computations were performed separately for each of these 10 compounds with Abl, Csk, and
Src kinases respectively. We focused our analysis on compounds 3, 7, and 15 (Das-A, Das-R,
Das-E) as a basis for comparison. In agreement with the experimental data, the results indicated
that compound 7 (Das-R) has a better affinity with Abl and Src kinases. Moreover, we noticed
that compound 15 (Das-E) displayed a reduced potency when compared to other amino acid
derivatives as was observed in the experiments, whereas compound 7 (Das-R) exhibited the
strongest binding affinity against all three kinases. In addition, we also observed that the Csk/Src
selectivity is markedly improved for compounds 7 and 15. This is also consistent with the
experimental data, albeit the experimental Csk/Src selectivity ratio is greater for compounds 3
and 15. By extracting binding constants from the IC50 data using Cheng-Prusoff equation25-26
,
we correlated the experimental and computed binding free energies (Figure 5). Because the
enzyme concentrations necessary for the assays were significantly higher than the true Ki’s,
extracting Ki’s from IC50 values results in at best an estimate.
Figure 5. (A) The computed binding free energies for a selected panel of compounds that were evaluated against
Abl, Csk, and Src kinases. The original potencies that was measured in inhibition constants IC50 were converted
into K
values with the aid of Cheng-Prusoff equation.23,24 In these calculations, the enzyme concentration was set
i
2
0
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ChemMedChem
10.1002/cmdc.201600387
to 0.4 nM. (B) The correlation between experimental binding constants and computed binding free energies. The
data for Abl are shown in blue squares, for Csk in red triangles-up, and for Src in green triangles-down.
A strong correspondence between computation and experiment with a correlation
coefficient R ~ 0.892 provided support to modeling results and allowed for a preliminary analysis
of structural basis underlying binding affinity and selectivity profiles of studied compounds. The
computational analysis suggested that high-affinity dasatinib derivatives may benefit from
forming favorable interactions with the αD-helix residues (Figure S6, Supporting Information).
For instance, we observed that Das-A may approach the αD-helix in Abl and form stable
hydrogen bonding with E329 and Y326 residues (Figure S6, Supporting Information). Similarly,
Das-R appeared to maintain stable hydrogen bonding with the carbonyl oxygen of E329.
Although only structural determination could provide the ultimate verification of these
predictions, the binding energetics analysis based on the predicted docked poses and MD
simulations reproduced experimental binding constants with an excellent accuracy (Figure 5).
Particularly, computational analysis successfully predicted the Csk/Src selectivity trend seen in
the studied compounds. According to our analysis, the observed differences in Csk/Src binding
affinity can be partly attributed to a cumulative effect of the side-chain interactions with the αD-
helix of the kinases. For instance, the differences in specific interactions with the αD-helix
residues may be among important determinants underlying the observed Csk/Src selectivity of
compound 7 (Das-R). Indeed, the side-chain guanidinium group of this dasatinib derivative may
form strong and stable hydrogen bond interactions with E349 and E353 in Src kinase, whereas
only some of these interactions may be preserved in Csk kinase (Figure S7, Supporting
Information). According to our results, the αD-helix residues may contribute to the structural
stability and favorable binding affinities of dasatinib derivatives with the panel of all studied
kinases. The importance of the αD-helix residues in binding of dasatinib derivatives may also
arise from their proximity and involvement in stabilization of the catalytic spine (C-spine)
residues (V394, I392, and L346) (Figure S7, Supporting Information). The C-spine is involved in
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ChemMedChem
10.1002/cmdc.201600387
the positioning of the adenine ring of ATP that arranges the two lobes so that the catalytic
residues are aligned optimally for catalysis.27-28
To explore the role of complementarity in determining the binding free energy differences
we computed the average complementarity determined by the LPC program29 as
complementarity function CF defined as:
CF = S
l
- S - E
i
Normalized complementarity is defined as CF divided by the solvent-accessible surface
of the uncomplexed ligand. In this equation, S is the sum of all surface areas of all “desirable”
1
atomic contacts between ligand and receptor. S
i
is the sum of all surface areas of all
“
undesirable” atomic contacts and E is the repulsion term as defined in reference.29
In general, energetically favorable contacts (e.g., hydrophobic-hydrophobic) are
classified as legitimate contact, whereas energetically unfavorable contacts (e.g., hydrophobic-
hydrophilic) are classified as illegitimate ones. More specifically, according to the LPC program,
the “desirable” contacts include hydrophobic-hydrophobic, hydrophobic-aromatic, hydrophobic-
neutral, donor-acceptor and other typical classes of favorable intermolecular contacts. A more
2
8
complete description of this approach has been published and references therein. Normalized
complementarity is defined as CF divided by the solvent-accessible surface of the uncomplexed
ligand.
We observed that the complementarity of dasatinib and compound 7 (Das-R) is greater
as compared to other compounds. Additionally, the Csk/Src differences in the normalized
complementarity are greater than between Abl and Src kinases (Figure S8, Supporting
Information).
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Assaying the dynamic nature of dasatinib esters. Given the profound influence of drug
metabolism on inhibitor efficacy, we sought to characterize how our synthesis strategy may
impart a unique and favorable stability profile. In vivo, numerous carboxylesterases have been
shown to hydrolyze ester bonds of compounds (similar to those in the dasatinib derivatives).
Mouse plasma contains relatively high concentrations of carboxylesterases and frequently serve
as proxies for the stability studies. Selected compounds, Das-C
2
and Das-C were pre-treated
8
with mouse plasma at 0, 15, 30, 60, and 120 min. If the derivative is a suitable substrate for one
or more carboxylesterase, the products of the subsequent reaction should include the core
dasatinib molecule. We used LC/MS/MS to monitor the formation of dasatinib. The assays relied
upon the careful consideration of proper compound concentration and a significant difference in
potency between the derivative and dasatinib.
As the dasatinib derivatives vary substantially in size and chemical properties, it is worth
noting that stability of the derivatives likely differs between compounds, according to variations
in substrate specificities of carboxylesterases. With this dynamic in mind, we chose
representative compounds for the assays, namely 16 (Das-C
results, summarized in Supporting Information (Table S1 and Figure S9), it appears that
compound 17 (Das-C ) is remarkably unaffected by carboxylesterases, even after 2 h pre-
treatment. The stability of 17 (T1/2 > 480 min) was a high contrast to that of 16 (Das-C ), which
showed to be less stable T1/2 < 5 min). Compound 16 (Das-C ) was completely metabolized in
mouse plasma by the 15 min time point, and rapid dasatinib formation was also monitored from
this compound by using HPLC and mass spectrometry. In contrast, Das-C (17) was observed
to be stable in mouse plasma (and no dasatinib formation was seen at specified time). The
difference can be due to the presence of larger fatty acyl chain in Das-C (17) that generated
2
) and 17 (Das-C
8
). From the
8
2
2
8
8
sterical hindrance. The dynamic offered by these esterified derivatives can be quite
advantageously applied toward engineering a unique drug metabolic profile.
2
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Development of a Fluorescent Dasatinib Derivative. To expand upon the vast potential
offered by dasatinib derivatives, we sought to construct a fluorescent probe for in vitro
characterization of kinases. Tethered to dasatinib by a glycine linker, a fluorescein-conjugated
derivative was synthesized (compound 26) (Figure 2). The compound was assayed against Src,
finding an IC50 of 1 nM. The affinity of the dasatinib-fluorescein compound was then measured
using a fluorescence polarization binding assay.
In such an assay, polarized light of a specific wavelength is used to excite the fluorescein
molecule, which in turn emits light at a higher wavelength. The degree to which the emitted light
is depolarized depends on the free rotation of fluorescein, which is inversely correlated with
ligand binding. Thus, the binding affinity of a fluorescein-ligand conjugate for a given receptor
can be measured by recording the polarization of light in a serial dilution of the receptor and
fitting the data to a standard ligand-binding curve.
We sought to measure the affinity of our ligand for a form of Src that is deficient in kinase
activity (kdSrc). This mutant kinase is often able to be purified to significantly higher
concentrations than active kinase, which adds to the convenience of the assay and broadens
its potential application (as discussed later). The binding curve generated from these assays
(shown in Figure S10A, Supporting Information) reveals an affinity of 15 nM toward kdSrc by our
fluorescein-dasatinib conjugate (compound 26). This value was higher than expected and may
reflect differences between active/inactive kinase forms or limitations of the assay’s lowest
detection limit.
To explore the utility of this fluorescent probe, we employed a variation of this assay to
determine the binding affinity of unlabeled dasatinib via a competitive binding assay. In this
assay, fixed concentrations of the fluorescent probe and kinase were used to produce a high
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ChemMedChem
10.1002/cmdc.201600387
polarization signal. The reactions were then titrated with unlabeled dasatinib while recording the
change in polarization. The resulting data was graphed and curve fitting analysis provided a
binding constant of 3 nM for dasatinib (Figure S10B, Supporting Information).
The results of these fluorescence polarization binding assays with the kinase-deficient
enzyme are fairly consistent with the IC50’s derived from the radio-ligand kinase assays. The
difference between the measured affinities of the fluorescent probe and dasatinib accurately
predict the relative potency of the compounds as kinase inhibitors. Combined with the ease of
polarization binding assays, the utility of compound 26 (-G-Flu) as a probe for inhibitor
development is clear.
Cytotoxicity cell-based assays were conducted in human B leukemia cell lines (BV-
173, Creative Bioarray # CSC-C0203) and bone marrow lymphoma (K652, ATTC # CCL-243),
and pancreatic epithelioid carcinoma (Panc-1, ATCC # CRL-1469) cell lines. BV-173 cell line
1
is an example of Philadelphia chromosome (Ph )+ chronic myeloid leukemia derived from the
peripheral blood of a 45-year-old man with CML in blast crisis in 1980. K562 is an example of
3
0
bone marrow leukemia cells . Since, dasatinib has been shown previously potency in treating
3
1
pancreatic cancer . We also tested the activity of selected compounds against Panc-1 cell
lines. Thus, the IC50 values of selected compounds 1 (Das), 7 (Das-R), 13 (Das-C), 15 (Das-
E), 16 (Das-C
2
), 21 (Das-C16), 24 (Das-C11NH ), and staurosporine (as control drug) were
2
obtained after 72 h incubation (Table 2; Figure S11 (Supporting Information)). The IC50 values
were obtained in the range of 26.3 µM to <51.2 pM. Das-R (IC50 = 2.06 µM) and Das-C16 (IC50
=
0.72 µM) were significantly more potent than Das (IC50 = 26.3 µM) against Panc-1 cells while
they showed an IC50 < 51.2 pM against BV-173 and K562 cells. All Das conjugates were
significantly more potent in BV-173 and K562 cells than Panc-1 cells. Indeed, Das-C was not
active (IC50 >100 µM) against Panc-1 cells while it showed IC50 values of 658 nM and 1330
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nM against BV-173 and K562 cells, respectively. A similar pattern was observed for Das-C2
that exhibited no activity against Panc-1 while was very potent against BV-173 and K562.
Table 2. IC50 values of representative compounds using MTT cell viability assay in three cancer
cell lines.*
Compound
IC50 (M)
K562
BV-173
<51.2 pM
<51.2 pM
1.33E-09
6.07E-11
<51.2 pM
<51.2 pM
<51.2 pM
4.77E-09
Panc-1
2.63E-05
2.06E-06
100 M
6.41E-05
N/A
1
(Das)
(Das-R)
3 (Das-C)
5 (Das-E)
6 (Das-C
1 (Das-C16)
4 (Das-C11NH
Staurosporine
<51.2 pM
<51.2 pM
6.58E-10
<51.2 pM
<51.2 pM
<51.2 pM
<51.2 pM
2.35E-07
7
1
1
1
2
)
2
7.16E-07
5.92E-06
1.55E-08
2
2
)
N/A indicates the IC50 value is not available because the data values did not fit any IC50 curve. * All the data points
are average of duplicate experiments.
Discussion
Library construction. Based upon the wealth of available structural data and past successes
of dasatinib modifications for affinity-based interaction studies, we hypothesized that the
exceptional potency of dasatinib would support its use as a molecular scaffold for the synthesis
of novel kinase inhibitors with enhanced specificity. The solved crystal structures of dasatinib in
complex with several PTK catalytic domains demonstrate the common manner in which the
inhibitor binds PTK active sites. Particularly intriguing to us, is a hydroxyl group of dasatinib that
extrudes from the binding pocket to the surface of the kinase. In literature, there are numerous
examples of dasatinib (and other kinase inhibitors, as well) that have been modified at this
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position through the coupling of compounds to agarose resin or other molecules.17, 32-34 These
modifications enabled efficient extraction of PTKs that are potential dasatinib targets from
various cancer cells and tissues. These affinity-driven applications rely upon specific interaction
or recognition of kinases, which suggests that the inhibitor portions of these compounds retain,
at least in part, their ability to bind PTK active sites. We reasoned that if large resin attachment
does not abolish the affinity of dasatinib, then smaller chemical adducts should be well tolerated,
too.
In the present study, we sought to take advantage of this feature of dasatinib by attaching
a series of small molecules in an effort to impart novel inhibitor characteristics. In the spirit of
rapid library development, we designed a synthesis strategy that was efficient, convenient, and
easily employed to obtain derivatives with a wide range of chemical properties. To meet these
criteria, we opted for the synthesis directly from dasatinib (free base) by esterification of its
hydroxyl group with carboxylic acid containing compounds (amino acids and fatty acids).
A potential drawback to any conjugation, of course, is the potential destruction of key
features of the original molecule. The hydroxyl group was reported to extend out towards the
8
solvent –exposed protein in the crystal structure of dasatinib with Abl kinase. Upon review of
the crystallized ligand, it seems likely that the proper binding orientation of the core molecule is
stabilized by energetically favoring exclusion of the hydroxyl group from the binding pocket.
Docking studies of this molecule without the hydroxyl group support this idea, as calculated
binding energies rise and predicted conformation deviates substantially from the known crystal
structures. Additionally, this polar group’s inclusion probably enhances the solubility or
bioavailability of hydrophobic dasatinib core molecule. In a recent report, dasatinib was
conjugated with a number of hydrophobic compounds and showed promising angiostatic
activity.35 Thus, our conjugation of dasatinib, which targets this position for modification,
threatens to disturb proper binding conformation and solubility-related characteristics. The
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ChemMedChem
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potency with which the derivatives inhibit the PTKs in our panel suggests proper orientation is
likely achieved by most, if not all compounds.
Conjugation alters kinase selectivity. The structural diversity of target kinases is a central
element to this study, as we endeavor to identify the different types of inhibitor interactions that
confer specificity. For this reason, we chose three kinases that represent divergent non-receptor
PTK families, distinct in structure and function. An ideal inhibitor would target just one of these
kinases through recognition of one or more of its distinct structural features, not found in more
distantly related PTKs. Therefore, our diverse panel of kinases serves to increase our chances
of identifying novel compounds that more closely resemble an ideal inhibitor.
With that idea in mind, it is important to recognize that our kinase inhibitor scaffold,
dasatinib, already has a built-in bias toward certain kinases, particularly the Abl and Src families,
as compared to others, like Csk. This suggests two things: first, that dasatinib recognizes
structural elements common to all three kinases, and second, that Csk possesses features that
limit this interaction. It is, therefore, reasonable to assume that complete reversal in this pattern
of specificity is unlikely to occur without a major change in binding mode. The inhibitor would
not only have to overcome its previously limited interaction with Csk, but also would have to
develop some new interaction that is not tolerated by Abl and Src. Therefore, when starting from
a biased inhibitor, altered selectivity is probably most likely to occur as a result of either the
elimination or exaggeration of an inherent bias.
From this line of reasoning, it makes sense that our library of derivatives displays no signs
of dramatic reversals in kinase selectivity pattern. All of the compounds showed better inhibit
Src than Abl, and Abl was always inhibited more than Csk. This apparent limitation aside, our
measures of selectivity do change dramatically for a number of inhibitors, simply by enhancing
a pre-existing bias of dasatinib for or against a given kinase. In one of the most dramatic
examples, the IC50 of compound 15 (Das-E) increased only mildly for Src (+16%) but greatly for
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Csk (+186%) and even more so for Abl (+464%). While other compounds such as 13 (Das-C)
and 18 (Das-C10) also possessed significantly altered kinase selectivity, compound 15 (-E) was
particularly unique for its minimal loss of potency toward Src.
The changes in kinase inhibitor specificity are quite remarkable considering the limited
size of the library generated. Compound 15 (Das-E) demonstrates the ease with which dasatinib
derivatives can be developed to alter significantly kinase selectivity. An IC50 for Src that is more
than a magnitude lower than for other kinases is certainly quite notable and, we believe,
represents a major step in the development of truly specific PTK inhibitors. Furthermore, this
success can be built upon by expanding this strategy to include many new dasatinib derivatives
for study and comparison to compound 15 (Das-E).
Compound 17 (Das-C8) is low nanomolar inhibitor that displays enhanced specificity for
Abl and Csk compared to dasatinib. The highest selectivity ratio obtained in our study, 91.4
Csk/Src belonged to compound 18 (Das-C10) with an IC50 of 3.2 μM for Csk compared to 35 nM
for Src. Moreover, each of these compounds displayed increased selectivity toward Src, as
compared with Abl.
Compound 7 containing an arginine residue (Das-R) appeared to be the most potent of
the inhibitors tested against all three kinases (Figure 4). The results of docking and MD
simulations have supported structural models in which compound 7 could indeed form additional
hydrogen bonds with Abl and Src kinases, just outside the ATP-binding cleft. More specifically,
compound 7 formed hydrogen bonding with the carbonyl oxygen of E329 and strengthened the
inhibitor coupling to stable C-spine. Although only structural determination could provide the
ultimate verification of these predictions, the binding energetics analysis based on the predicted
docked poses and MD simulations reproduced experimental binding constants with an excellent
accuracy (Figure 5). Particularly, computational analysis successfully predicted the Csk/Src
selectivity trend seen in the studied compounds, including compound 7. In addition, the
experimental data supported our predictions as compound 7 increased potency against all
2
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