Computer-aid drug design, synthesis, and anticoagulant activity evaluation of novel dabigatran derivatives as thrombin inhibitors

Article abstract of DOI:10.1016/j.ejps.2019.104965

In this study, computer-aided drug design techniques were adopted to explore the structural and chemical features for dabigatran and design novel derivatives. The built 3D-QSAR models demonstrated significant statistical quality and excellent predictive ability by internal and external validation. Based on QSAR information, 11 novel dabigatran derivatives (12a–12k) were designed and predicted, then ADME prediction and molecular docking were performed. Furthermore, all designed compounds were synthesized and characterized by ¹H NMR, ¹³C NMR and HR-MS. Finally, they were evaluated for anticoagulant activity in vitro. The activity results showed that the 10 obtained compounds exhibited comparable activity to the reference dabigatran (IC₅₀ = 9.99 ± 1.48 nM), except for compound 12i. Further analysis on molecular docking was performed on three compounds (12a, 12c and 12g) with better activity (IC₅₀ = 11.19 ± 1.70 nM, IC₅₀ = 10.94 ± 1.85 nM and IC₅₀ = 11.19 ± 1.70 nM). MD simulations (10 ns) were carried out, and their binding free energies were calculated, which showed strong hydrogen bond and pi–pi stacking interactions with key residues Gly219, Asp189 and Trp60D. The 10 novel dabigatran derivatives obtained can be further studied as anticoagulant candidate compounds.

Full text of DOI:10.1016/j.ejps.2019.104965

Accepted Manuscript
Computer-aid drug design, synthesis, and anticoagulant activity
evaluation of novel dabigatran derivatives as thrombin inhibitors
Shanshan Huang, Yujie Ren, Xiuxiu Peng, Pingping Qian,
Lingwei Meng
PII:
DOI:
Article Number:
Reference:
S0928-0987(19)30228-3
https://doi.org/10.1016/j.ejps.2019.104965
104965
PHASCI 104965
To appear in:
European Journal of Pharmaceutical Sciences
Received date:
Revised date:
Accepted date:
15 April 2019
3 June 2019
20 June 2019
Please cite this article as: S. Huang, Y. Ren, X. Peng, et al., Computer-aid drug design,
synthesis, and anticoagulant activity evaluation of novel dabigatran derivatives as
thrombin inhibitors, European Journal of Pharmaceutical Sciences, https://doi.org/
10.1016/j.ejps.2019.104965
This is a PDF file of an unedited manuscript that has been accepted for publication. As
a service to our customers we are providing this early version of the manuscript. The
manuscript will undergo copyediting, typesetting, and review of the resulting proof before
it is published in its final form. Please note that during the production process errors may
be discovered which could affect the content, and all legal disclaimers that apply to the
journal pertain.

ACCEPTED MANUSCRIPT
Computer-aid Drug Design, Synthesis, and Anticoagulant Activity Evaluation of
Novel Dabigatran Derivatives as Thrombin Inhibitors
Shanshan Huang, Yujie Ren*, Xiuxiu Peng, Pingping Qian and Lingwei Meng
College of Chemical and Environmental Engineering, Shanghai Institute of
Technology, 100 Haiquan Road, Shanghai 201418, China.
*Correspondence: Yujie Ren,
E-mail: clab@sit.edu.cn
Tel.: +021-60877231
Abstract: In this study, computer-aided drug design techniques were adopted to explore
the structural and chemical features for dabigatran and design novel derivatives. The
built 3D-QSAR models demonstrated significant statistical quality and excellent
predictive ability by internal and external validation. Based on QSAR information, 11
novel dabigatran derivatives (12a-12k) were designed and predicted, then ADME
prediction and molecular docking were performed. Furthermore, all designed
1
13
compounds were synthesized and characterized by H NMR, C NMR and HR-MS.
Finally, they were evaluated for anticoagulant activity in vitro. The activity results
showed that the 10 obtained compounds exhibited comparable activity to the reference
dabigatran ((IC50 = 9.99 ±1.48 nM), except for compound 12i. Further analysis on
molecular docking was performed on three compounds (12a, 12c and 12g) with better
activity (IC50 = 11.19 ±1.70 nM, IC50 = 10.94 ± 1.85 nM and IC50 = 11.19 ±1.70 nM).
MD simulations (10 ns) were carried out, and their binding free energies were
calculated, which showed strong hydrogen bond and pi–pi stacking interactions with
key residues Gly219, Asp189 and Trp60D. The 10 novel dabigatran derivatives
obtained can be further studied as anticoagulant candidate compounds.
Key words: Computer-aided drug design; dabigatran derivatives; synthesis;
anticoagulant activity
1. Introduction
Cardiovascular diseases (CVDs) are the leading causes of mortality and morbidity
worldwide. According to the World Health Organization, CVD mortality may be
expected to reach about 25 million by 2030(Chaudhari et al., 2014). Thrombin, a
multifunctional serine protease, is an important effector protease in CVD
processes(Ahmad and Lip, 2012). Thrombin exhibits procoagulant and anticoagulant
1

ACCEPTED MANUSCRIPT
properties in the blood coagulation cascade(De Candia, 2012). It activates platelets and
catalyzes the conversion of fibrinogen to fibrin, which promotes the stability of blood
clots and causes the blood to coagulate(B. et al., 2007). Therefore, thrombin is an
important target in the treatment of CVDs.
To date, several thrombin inhibitors, including indirect thrombin inhibitors and direct
thrombin inhibitors (DTIs), have been developed. DTIs with high specificity for
thrombin have been the focus of anticoagulant drug development(Kam et al., 2005; Lee
and Ansell, 2011). Several direct thrombin inhibitors (Figure 1), such as
Ximelagatran(Gustafsson et al., 1998), Apixaban(Curto and Albaladejo, 2016),
Argatroban(Berry et al., 1994) and Dabigatran etexilate(Eriksson et al., 2008), have
been reported. Ximelagatrans is the first oral DIT and has significant inhibitory effect
on thrombin in clinical. Later, ximelagatran was withdrawn from the market because it
causes increased hepatic enzyme levels(WEITZ and BATES, 2005). Apixaban can
significantly reduce the risk of thromboembolic disease. But it also increase the risk of
anemia, bleeding and other adverse reactions(Granger et al., 2011). Argatroban is the
first clinical direct thrombin inhibitor (DTI). However, after oral administration, it
becomes unstable or even inactivated in the human body(Kim et al., 2015). Thus,
dabigatran etexilate became the only orally available DTI in the market. In March 2008,
the use of dabigatran etexilate for the prevention of venous thromboembolic events for
patients who had undergone total hip and knee replacement surgery was approved by
the European Medicines Administration(Eriksson et al., 2008). Dabigatran etexilate has
been used to prevent stroke among patients with atrial fibrillation in phase III
trials(Savelieva and Camm, 2014). Unlike other anticoagulants, dabigatran etexilate has
several advantages, such as a wide therapeutic window, a fixed dose without monitoring
Figure 1. Chemical structures of some known thrombin inhibitors.
2

ACCEPTED MANUSCRIPT
and less drug-drug interactions(Blommel and Blommel, 2011; Dahl, 2008; Sanford and
Plosker, 2008). However, there are still unavoidable high-dose bleeding risks and
expensive drawbacks(Haas, 2008; Pollack et al., 2015). In 2015, the monoclonal
antibody Idarucizumab was approved for market in the United States. Idarucizumab
can rapidly and safely reverse the anticoagulant effect to control the bleeding risk
caused by dabigatran etexilate(Traynor, 2015). Still, dabigatran etexilate cannot be
accepted by most patients because of its relatively high price caused by the patent
protection and complex synthesis process. Therefore, it is meaningful to find new
thrombin inhibitors with comparable activity to the dabigatran for preventing and
treating CVDs.
Computer-aided drug design (CADD) is extensively applied in drug design. As a
powerful design tool, CADD can improve the success rate of drug research and
development (R&D), reduce R & D costs and shorten the R&D cycle. The approach
has accelerated the lead optimization process by studying 3D features of
chemicals(Huang et al., 2019). 3D-QSAR tools have been successfully applied in the
discovery of inhibitors, such as HO-1 inhibitors(Amata et al., 2017), 5-lipoxygenase
inhibitors(Ul-Haq et al., 2016) and antiviral drugs(Tu et al., 2017). In this work, based
on the compounds and activities obtained from our previous work(Ren et al., 2016;
Wang et al., 2016; Yang et al., 2017), the appropriate groups were introduced to design
novel dabigatran derivatives from the aspects of QSAR information and chemical
properties. The flow of this study are shown in Figure 2.
Figure 2. Flowchart of the study for the discovery of novel dabigatran derivatives
3

ACCEPTED MANUSCRIPT
The above results lay an important foundation for the discovery of new anticoagulant
candidates, and methods combining theory with practice can also provide the reference
for the discovery of other drugs.
2. Results and discussion
2.1 Analysis of CoMFA and CoMSIA
The statistical results for the CoMFAand CoMSIAmodels were summarized in Table
1. In the CoMFA model, the PLS regression analysis obtained the q2 of 0.705 and the
ONC of 8. Then, the non-cross validation gave the satisfactory r2 of 0.971 with the SEE
of 0.090 and the F-statistic value of 114.648. The contributions of steric and
electrostatic fields to the CoMFA model were 31.1% and 68.9%, respectively. In the
CoMSIA model, the PLS regression analysis showed the q2 of 0.707, the ONC of 10,
the r2 of 0.966, the SEE of 0.102 and the F value of 71.471. The contributions of steric,
electrostatic, hydrophobic, H-bond acceptor and H-bond donor fields were 11.2%,
36.4%, 26.7%, 9.6% and 16.2%, respectively. It can be found that the electrostatic and
hydrophobic field made major contributions among the five fields. As listed in Table 1,
the r2pred value of CoMFA was 0.722 and the CoMSIA r2pred value was 0.699. The
CoMFA R2 value was 0.704 and the CoMSIA R2 value was 0.790. The slopes k values
2
(1.000 for CoMFA, 1.004 for CoMSIA) were both close to 1. R0 values (0.756 for
CoMFA, 0.881 for CoMSIA) were both close to R2 values. For the CoMFA and
2
CoMSIA model, the rm2 values were 0.544 and 0.552, the (R2-R0 )/R2 values were
Table 1. The statistical results of 3D-QSAR models
Parameter
CoMFA CoMSIA
q2
0.705
8
0.707
10
ONC
r2
0.971
0.090
0.966
0.102
SEE
F
114.648 71.471
2
Rpred
0.722
0.839
0.704
1.000
0.756
0.544
-0.074
0.107
0.699
0.889
0.790
1.004
0.881
0.552
-0.115
0.098
R
R2
k
2
R0
2
rm
(R2-R0 )/R2
2
MAETest
4

ACCEPTED MANUSCRIPT
-0.074 and -0.115, respectively. The MAEtext values (0.107 for CoMFA, 0.098 for
CoMSIA) were both less than the 0.1 × training set range (0.215). All the internal and
external validation parameters of 3D-QSAR models were in an acceptable limit. The
plots showing the actual and predicted pIC50 values for the total set in the CoMFA and
CoMSIA approaches were represented in Figure 3. Most points were evenly distributed
along the line Y = X, suggesting that predicted pIC50 values were in good agreement
with the actual pIC50 values and the 3D-QSAR models were of satisfactory predictive
capability.
Figure 3. Plots of actual versus predicted pIC50 values for all the molecules based on
CoMFA (A) and CoMSIA (B) models
2.2 CoMFA and CoMSIA contour maps
To visualize the field effects in 3D space, the information which provides by
CoMFA and CoMSIA contour maps, offers theoretical support for designing novel
and potent compounds. For the convenience of the analysis, the compound 26
(dabigatran) was employed to illustrate the key structural features. The default values
of the favorable and unfavorable contours represented 80% and 20% level contribution.
The Figure 4A was the contour map of the steric field in CoMFA model. The green
contours indicated that the bulky groups are conducive to activity, whereas yellow ones
meant the bulky groups can result in the decreased activity. On the pyridine ring, there
was a medium-sized green contour, which indicates that the large group is beneficial to
the improvement of activity. In the electrostatic contour map of the CoMFA model, the
electrostatic favorable and unfavorable regions were represented by blue and red
contours, respectively. In Figure 4B, it can be found that the 3-, 4- and 5- position in
the A location were surrounded by a large blue contour, indicating that the positive
electricity group is advantageous for the improvement of activity.
Figure 4. Steric and electrostatic contour maps of the CoMFA model
The steric and electrostatic contour maps of CoMSIA model were shown in Figure
5

ACCEPTED MANUSCRIPT
5AB. Not surprisingly, the information of contour maps were basically similar to those
of CoMFA model, hence they were not discussed. In the hydrophobic field of CoMSIA
model (Figure 5C), hydrophobic favorable and unfavorable areas were exhibited by
yellow and white contours, respectively. The A position was surrounded by a large
yellow contours, which indicates the hydrophobic property in this place may increase
its activity. The H-bond donor/acceptor fields of the CoMSIA model were described in
Figure 5D and Figure 5E. The favorable and unfavorable regions in H-bond donor field
were represented by cyan and purple contours, and in the H-bond acceptor field, they
were revealed by magenta and red contours. As shown in Figure 5D and 5E, the red
contours of the H-bond acceptor field almost coincide with the cyan contours of the H-
bond donor field, which indicated the consistency of the established models.
Figure 5. Steric (A), electrostatic (B), hydrophobic (C), H-bond acceptor (D) and
H-bond donor (E) contour maps of the CoMSIA model.
2.3 Design of new dabigatran derivatives
According to the contour maps of CoMFA/CoMSIA models, some meaningful
information about dabigatran derivatives as thrombin inhibitors was obtained, as shown
in Figure 6. In general, the site of the compound was affected by several fields rather
than a single field, so the field effects should be taken into account when designing the
compound. Dabigatran was taken as a template to design new inhibitors. Combining
with the structure-activity relationship in Figure 6, increased electron density on
aromatic rings is beneficial to activity, hence the benzene ring replaces the pyridine ring
to increase the electron density. At the A position, the large and hydrophobic groups
favor activity. Then the -Cl group was designed at the 2-, 3-, and 4- position on the
benzene ring. In the N-1 of benzimidazole at the B position, large but not huge and
hydrophobic groups are beneficial for activity. In addition, the research(Li et al., 2015)
also reported that ethyl group at N-1 of benzimidazole exhibites better anticoagulant
activity against thrombin. Hence, the ethyl group with appropriate size and
hydrophobicity was introduced. On the benzene ring at the C position, the F group was
6

ACCEPTED MANUSCRIPT
Table 2 The predicted pIC50 values of the newly designed compounds
No.
Structure
PIC50
Preda
Predb
Refc
8.837 8.887
8.298 8.351
12a
12b
8.240 8.251
12c
12d
12e
12f
12g
8.338 8.424
8.178 8.214
8.203 8.355
8.405 8.324
8.340 8.256
12h
12i
12j
12k
8.222 8.252
8.168 8.200
8.196 8.196
8.127 8.057
Preda: predicted by CoMFA model
Predb: predicted by CoMSIA model
Refc: reference compound, dabigatran
7

ACCEPTED MANUSCRIPT
introduced. With the introduction of fluorine group, the physical and chemical
properties of drug molecules could be changed, which, in turn, alters the
pharmacokinetic properties of drug molecules. Finally, 11 novel dabigatran derivatives
(12a-12k) were designed and synthesized. The structures and the predicted pIC50 values
of 12a-12k based on CoMFAand CoMSIAmodels were listed in Table 2. Table 2 shows
that the pIC50 values of all designed new molecules within an order of magnitude, were
comparable to dabigatran. It is suggested that they have good potential inhibitory
activity, and further synthesis and bioactivity studies could be conducted.
Figure 6. Structure–activity relationships derived from 3D-QSAR studies.
2.4 Molecular docking
Molecular docking explores the binding affinities of ligand and receptor, which helps
us to further understand the quantitative structure-activity relationship. Before
molecular docking, dabigatran was redocked to validate the docking reliability. As
shown in Figure 7, the re-docking results showed that the conformations of dabigatran
and the original ligand (red) almost overlapped in the active site (PDB code: 1KTS,
resolution: 2.4 Å). The aromatic ring of A position was positioned in the D-pocket
which were similar to the results in literature(Hauel et al., 2002), indicating that the
position in the receptor cavity was correct. Subsequently, the 11 designed compounds
Figure 7. The re-docking result of dabigatran
8

ACCEPTED MANUSCRIPT
Figure 8. Docking results of all the compounds in thrombin protein (1KTS)
in this study were docked into thrombin receptor to analyze the bonding patterns. As
shown in Figure 8, all the compounds maintained the similar U-shaped configurations
and were buried deeply in the receptor cavity. H-bond interactions were found between
the dabigatran derivatives and several key residues, such as Gly219, Asp189, Ala190
and Gly216. Figure 9A illustrates the interactions between dabigatran and surrounding
residues in the active site. A total of six hydrogen bonds were formed. The observed
hydrogen bond distances are 1.75 Å (Gly219-O···H-), 1.74 Å (Asp189-O···H-),
Figure 9. Docking result of compound dabigatran (A), 12a (B), 12c (C) and 12g (D).
9

ACCEPTED MANUSCRIPT
2.17 Å (Asp189-O···H-), 2.42 Å (Asp189-O···H-), 2.75 Å (Ser195-O···H) and 2.08 Å
(Thr172-O···H-), respectively. The amidine formed electrostatic interactions with
amino acids Gly219, Asp189, Cys191, Ala190, Cys220, Asp221, Gly193. It was in
agreement with the red contours of electrostatic field in the 3D-QSAR model. Pyridine
rings produced van der Waals interaction with surrounding residues Asn98, Glue97A,
Leu99, Trp215, which corresponds to the yellow contours of hydrophobic field. These
results suggested that the molecular docking was agreement with the generated
CoMFA/CoMSIA model.
In order to identify the more detailed interacting mode, three newly designed
compounds (12a, 12c, and 12g) with better activity, were selected for an in-depth
analysis. As showed in Figure 9B, a total of four hydrogen bonds were formed for 12a.
The observed hydrogen bond distances are 1.89 Å (Gly219-O···H-), 2.09 Å (Asp189-
O···H-), 2.45 Å (Asp189-O···H-) and 2.50 Å (Ala190-O···H-), respectively. Similarly,
compounds 12c and 12g were docked into the same active site as shown in Figure 9C
and 9D. A total of five hydrogen bonds were formed for 12c. The observed hydrogen
bond distances are 2.33 Å (Gly219-O···H-), 2.02 Å (Asp189-O···H-), 2.25 Å (Asp189-
N···H-), 2.47 Å (Ser214-O···H-) and 2.19 Å (Gly216-O···H-), respectively. For the
Table 3. Results of molecular docking for compounds 12a-12k
Com. Total
score
Crash
Polar
NHBa
Residuesb
12a 8.4464 -2.1978 2.1626
12b 9.766 -1.7153 3.2848
4
6
5
5
3
8
3
4
6
4
5
6
Gly219, Asp189, Ala190
Gly219, Asp189, Ser195, Glu97A, Tyr60A
Gly219, Asp189, Gly216, Ser214
Gly219, Asp189, Glu217, Ser214
Asp189, Tyr60A
12c 9.5733 -2.9443 2.5557
12d 9.6787 -3.2373 3.3423
12e 8.1093 -2.5831 2.9361
12f
9.0084 -2.4020 3.0288
Gly219, Asp189, Ala190, Gly216, Glu97A
Gly219, Asp189
12g 7.8091 -2.1289 2.5458
12h 8.9843 -2.4749 2.2878
Gly219, Asp189, Gly216
12i
12j
8.8057 -2.2709 3.0486
8.0391 -1.6329 1.9081
Gly219, Asp189, Gly216, Glu97A, Tyr60A
Phe227, Trp215,Ser214, Pro60C
Gly219, Asp189, Glu217, Ser214
Gly219, Asp189, Ser195, Thr172
12k 7.9979 -3.0466 2.6556
Refc 8.1128 -3.1800 2.1172
NHBa: Number of hydrogen bonds
Residuesb: Residues and hydrogen bonding interaction
Refc: reference compound, dabigatran
10

ACCEPTED MANUSCRIPT
12g, there are three hydrogen bonds. The observed hydrogen bond distances are 2.00 Å
(Gly219-O···H-), 1.89 Å (Asp189-O···H-) and 2.36 Å (Asp189-N···H-), respectively.
By comparing the three docking compounds with the dabigatran, it is found that they
all have hydrogen bonding with the common residues Gly219 and Asp189, and pi-pi
interaction with the residue Trp60D. These results contribute to the identification of key
residues that affect the activity and stability of ligands. At the same time, comparing
the docking results of 12a, 12c, 12g and dabigatran, it can be found that they all
maintain the similar U-shaped conformation with the receptor, but the C-ring positions
of 12a, 12c and 12g have changed in conformation compared with the dabigatran, which
makes them hard to interact with other key residues. The six number of hydrogen bonds
were formed between the dabigatran and the receptor, which maintained its stability in
the receptor. This may be the reason why their activity are slightly lower than the
dabigatran. Figure 8 showed that the substituents of benzene ring are encapsulated by
hydrophobic D-pockets, which shows that hydrophobic groups on benzene ring are
crucial to the affinity of receptors and ligands. Meanwhile, it was found that the amidine
formed stable hydrogen bonds with residues Gly219 and Asp189, and electrostatic
interaction with residues Ala190, ASP189, Cys220, Asp221 and Ser195. The
benzimidazole ring forms pi–pi stacking interactions with conserved Trp60D, and Van
Der Waals interaction with residues Leu99, Tyr60A, Trp60D and Ser214. These
interactions were very significant to improve the activity and stability of the inhibitor.
Moreover, the binding interaction patterns were complementary to those of CoMFAand
CoMSIA contour maps.
2.5 Analysis of MD simulation
Figure 10. The root-mean-square deviation (RMSD) of dabigatran (black), 12a (red)
12c (blue) and 12g (green) in complexes obtained from 10 ns MD simulation.
11

ACCEPTED MANUSCRIPT
In this study, the dynamics simulation of the dabigatran complex was initially carried
out. The 10 ns MD simulations were performed on compounds dabigatran, 12a, 12c
and 12g to further understand the detailed dynamic binding mode. The system overall
convergence and stability of MD simulations were monitored by root-mean-square
deviation (RMSD) of backbone atoms (C, Cα, N, and O) with respect to the initial
docking structure. As show in Figure 10, the RMSD value of the four complexes was
stable after 6 ns of simulation time. The fluctuations of dabigatran, 12a, 12c and 12g
maintained at average 2.6 Å, 2.4 Å, 3.0 Å and 2.4 Å, suggesting the stability of the
complex conformation. Thus, the subsequent MD simulations discussions would be
reasonable to analyze the conformations that extracted from last 2 ns of MD trajectories.
The superposition of the final structure of complex extracted from MD simulation (red)
and the original docked structure (blue) was showed in Figure 11. The final simulation
structure and the initial docked structure were in the same binding pocket from MD
simulation (red) of dabigatran (A), 12a (B), 12 (C) and 12g (D), excepting for a slight
drift. The H-bond distances of dabigatran (Figure 12A) were 2.39 Å (Gly219-O···H-),
2.91 Å (Asp189-O···H-) and 1.99 Å (Glu216-O···H-), respectively. After MD
simulation, the conformation of dabigatran was extended in the pocket, which made it
contact more residues and formed an additional H-bond with the residue Glu217.
However, due to the extension of the conformation, the H-bond distance with the
residues Asp189 and Gly219 becomes longer, which may increase the instability of the
ligand in the receptor. The H-bond distances of 12a (Figure 12B) were 1.99 Å (Ser195-
H···N-), 2.09 Å (Asp189-O···H-), 2.20 Å (Glu217-O···H-), 2.01 Å (Asn98-H···O-)
and 1.90 Å (Arg93-O···H-), respectively. The H-bond distances of 12c (Figure 12C)
was 2.35 Å (Asp189-O···H-). The H-bond distances of 12g (Figure 12D) were 2.42 Å
(Gly219-H···N-), 1.89 Å (Glu217-O···H-), 2.70 Å (Asp186A-O···H-) and 2.37 Å
(Trp60D-H···O-), respectively.
Figure 11. Structural comparison between initial (blue) and representative snapshots
12

ACCEPTED MANUSCRIPT
Figure 12. The binding mode of dabigatran (A), 12a (B), 12c (C) and 12g (D) after MD
simulation.
Comparing the molecular dynamics results of 12a, 12c, 12g and dabigatran, it can be
found that some distortions and changes occur in the spatial conformation after 10 ns
of dynamics simulation. Dabigatran still maintains hydrogen bonding with key residues
Gly219 and Asp189, while 12a, 12c and 12g have some extensions in space and cannot
produce hydrogen bonding with key residues Gly219 and Asp189.
Based on the MD simulation, the binding free energy calculations for the four
inhibitors of the last 2 ns trajectory were performed and are listed in Table 4. MM/PBSA
and MM/GBSA were both used in free energy calculations. It can be seen from the
Table 4 that van der Waals energy ∆퐸푣푑푤 is the most important contribution to the
overall binding energy, followed by electrostatic energy ∆퐸푒푙푒. The binding free energies
∆퐺푏푖푛푑 of the inhibitors dabigatran, 12a, 12c and 12g via MM-GBSA were predicted to
be -16.36, -23.94, -20.66, -19.66 kcal/mol, respectively, and via MM-PBSA were
predicted to be -25.38, -28.24,-29.86 and -29.00 kcal/mol, respectively. From the two
calculation methods of binding free energy ∆퐺푏푖푛푑, it can be found that the ∆퐺푏푖푛푑 of
the dabigatran complex was higher than that of 12a, 12c, and 12g, indicating that the
stability of the three designed compound may be better than dabigatran. Although both
MM/PBSA and MM/GBSA methods were adopted to calculate the binding free energy,
in general, the MM/PBSA performs better than MM/GBSA in calculating binding free
energy(Hou et al., 2011). In addition, the order of the binding energy of compounds
12c > 12g > 12a, was also consistent with the activity measured in our experiments. So,
13

ACCEPTED MANUSCRIPT
the three designed compounds 12a, 12c and 12g could be used as good potential
thrombin inhibitors.
Table 4. Average binding free energy (kcal mol-1, last 2 ns) of complexes along
with the different energy (kcal mol-1, last 2 ns) contributions
∆퐺푠표푙
∆퐺푏푖푛푑
(퐺퐵)
∆퐺푠표푙
∆퐺푏푖푛푑
(푃퐵)
∆퐺푔푎푠
NO.
da
∆퐸푣푑푤 ∆퐸푒푙푒
∆퐺퐺퐵
∆퐺푆퐴
(퐺퐵)
∆퐺푃퐵
∆퐺푆퐴
(푃퐵)
-47.37 -35.15 -82.52 71.20 -5.05 66.15
-45.02 -46.79 -91.81 72.36 -4.49 67.87
-46.99 -40.91 -87.90 72.12 -4.88 67.24
-46.67 -31.99 -78.65 63.92 -4.93 58.99
2.6 ADME prediction
-16.36
-23.94
-20.66
-19.66
63.10 -5.97 57.13
69.29 -5.72 63.57
62.19 -4.15 58.04
55.25 -5.60 49.66
-25.38
-28.24
-29.86
-29.00
12a
12c
12g
In the R&D process for new drugs, ADME and bioavailability analysis played
significant roles in drug-likeness. The ADME parameters calculated by the
SwissADME web tool for the designed compounds were summarized in Table 5. The
results showed that the log P values of the synthesized compounds and dabigatran were
in the range of -0.7 and 5.0, and the log S values were less than or equal to 6, indicating
that they have the reasonable absorbency and good solubility in the body. With the
introduction of the F group in the C ring, the water solubility predicted by ADME will
increase. This is because F group has high electronegativity, and its attachment to
benzene ring will increase electron cloud of benzene ring and polarization of adjacent
NH bond, so the corresponding water solubility will increase.
Figure 13. The bioavailability radars for dabigatran (A), 12a (B), 12c (c) and 12g (d).
14

ACCEPTED MANUSCRIPT
Ligand lipophilicity efficiency (LLE) is the single parameter which considers the
activity and lipophilicity of the compounds. It can be observed from Table 5 that the
LLE values of most compounds were within the ideal range, except for compounds
(12h and 12k) with LLE values of less than 5. Among the synthesized compounds, 12a
had highest LLE value, indicating that it has potential beneficial activity in vivo.
The HIA and BBB values show that they had low intestinal absorption and no brain
penetration. Compared with dabigatran, the eleven synthetic compounds have the
inhibitory effect on cytochrome CYP1A2. It indicates that these compounds could
prolong the action time of the drug, increase the blood concentration, and enhance the
therapeutic effect of the drug by inhibiting cytochrome CYP1A2. At the same time, the
incidence of side effects may also increase. Moreover, their Log Kp values were higher
than that of dabigatran, indicating that the synthesized compounds have better
permeability to the skin. Good skin permeability suggests that the compounds could
easily penetrate the skin tissue when it is made into the external preparation. At the
same time, they conformed to the Lipinski rules of druglikeness. The three highest
bioactivity compounds (12c, 12a and 12g) and the reference dabigatran were further
analyzed. The bioavailability radars of the four inhibitors were analyzed intuitively in
Figure 13. The pink areas meant the optimum range of six properties, namely,
lipophilicity, size, polarity, insolubility, instauration and flexibility. It can be seen from
the Figure 13 that compounds 12c, 12a and 12g were almost within the range of
conformity, except for the inconsistency of instauration and flexibility. Compared with
dabigatran, the three designed compounds performed better in polarity. In short, the
pharmacokinetic properties of eleven designed compounds are acceptable, and
compounds 12a, 12c, and 12g have further research significance.
Table 5. ADME prediction of newly synthesized compounds
TPSA
(Å2)
Fraction
Csp3
0.15
0.15
0.19
0.19
0.15
0.15
0.19
0.19
Rotatable
bonds
10
CYP1A2
inhibition
Yes
Log
Kp
Lipinski
filter
Yes
No.
12a
12b
12c
12d
12e
12f
12g
12h
Log P
3.02
3.33
3.45
3.61
3.07
3.42
3.36
3.67
Log S
-4.67
-4.83
-4.87
-5.03
-4.67
-4.83
-4.87
-5.03
LLE
6.081
5.559
5.561
5.058
5.657
5.193
5.140
4.667
HIA
Low
Low
Low
Low
Low
Low
Low
Low
BBB
No
No
No
No
No
No
No
No
137.33
137.33
137.33
137.33
137.33
137.33
137.33
137.33
-7.21
-7.25
-7.08
-7.12
-7.21
-7.25
-7.08
-7.12
10
Yes
Yes
11
Yes
Yes
11
Yes
Yes
10
Yes
Yes
10
Yes
Yes
11
Yes
Yes
11
Yes
Yes
15

ACCEPTED MANUSCRIPT
12i
12j
3.02
3.32
3.36
1.94
137.33
137.33
137.33
150.22
-4.67
-4.83
-4.87
-3.62
0.15
0.15
0.19
0.16
10
10
11
10
5.231
5.234
4.986
7.940
Low
Low
Low
Low
No
No
No
No
Yes
Yes
Yes
No
-7.21
-7.25
-7.08
-7.97
Yes
Yes
Yes
Yes
12k
dabigatran
2.7 Chemistry
Scheme 1. Synthesis of compounds 12a-k. Reagents and conditions: (a) TfOH (10 mol%), 12 h,
100°C, yields: 38-82%; (b) amine, 80°C, 5 h; AcOH, pH 4–5, yields: 90%-95%; (c) DCM, SOCl2,
rt, 2 h, yields: 100%; (d) DCM, Et3N, rt, 3 h, yields: 24-76%; (e) Zn, AcOH, THF/H2O, rt, yields:
59-78%; (f) H2O, 100°C; (g) EDCI, HOBt, DMF/THF; AcOH, ammonium hydroxide, yields: 45–
82%; (h) NH2OH·HCl, Et3N, anhydrous ethanol; Pd/C, HCOONH4, AcOH, N2, yields: 50-79%; (i)
NaOH, H2O/EtOH, rt, 2 h, yields: 72-87%.
The reaction route of dabigatran derivatives was presented in the Scheme 1. First,
intermediate compounds (2a-2k) were prepared from aniline (1) and ethyl acrylate with
trifluoromethanesulfonic acid (TfOH) (10% mol) as a catalyst. The reaction mixtures
was heated and refluxed for 12 h under N2 atmosphere. Reaction of 4-chloro-3-
16

ACCEPTED MANUSCRIPT
nitrobenzoic acid (3) and the readily available amine solution yielded 4-substituted-3-
nitrobenzoic acids (4a-4k) in good yield. Compounds 4a-4k were converted to 5a-5g
by chlorination. Acylation of compound 2a-k with chlorides 5a-5k under alkaline
conditions gave 6a-6k. Reaction of the nitro compounds 6a-6k with the reducing agent
Zn/AcOH furnished amino compounds 7a-7k. Compounds 8 and bromoacetic acid
were mixed and stirred at 100℃ to obtain compound 9. 7a-7k were reacted with
compounds 9 in the presence of 1-(3-dimethylaminopropyl)-3-ethylcarbodiimide
hydrochloride (EDCI) and 1-hydroxybenzotriazole (HOBt) to afford the imidazole
compounds 10a-10k. 10a-10k were reacted with hydroxylamine hydrochloride in
triethylamine (TEA) to obtain compounds 11a-11k. The target compounds 12a-12k
were obtained from 11a-11k via hydrolysis. The structures of the synthesized
1
13
compounds were determined from their H NMR, C NMR and HR-MS data before
the biological evaluation.
2.8 Anticoagulant activity in vitro
The inhibitory activity of compounds 12a-12k against thrombin were evaluated by
chromogenic assays. Argatroban and dabigatran were used as positive control. The IC50
values of compounds 12a-12k were evaluated and the corresponding data were listed
in Table 6. The results of activity test showed that the inhibitory rate of all compounds
were above 95%, which indicated that the designed compounds had good inhibitory
Table 6. Thrombin inhibitory activity (IC50) of new dabigatran derivatives.
Inhibition
NO. compound
IC50(nM)
11.19±1.70
14.16±1.87
10.94±1.85
13.25±3.78
11.84±1.33
13.10±1.69
11.49±2.57
12.96±1.30
31.55±4.81
11.91±1.38
16.36±1.70
pIC50
7.951
7.849
7.961
7.878
7.927
7.883
7.940
7.887
7.501
7.924
7.786
8.000
8.119
rate(%)
96.58
97.67
99.70
100.00
97.59
97.05
100.00
96.96
96.75
97.72
96.97
99.10
-
1
2
12a
12b
12c
12d
12e
12f
12g
12h
12i
3
4
5
6
7
8
9
10
11
12
12j
12k
Dabigatran 9.99±1.48
13 Argatroban 7.61±0.81
17

ACCEPTED MANUSCRIPT
Figure 14. The thrombin inhibition rate of compound 12a-12k (Refc: reference
compound, dabigatran).
activity. The results also showed that the designed compounds exhibited moderate to
good thrombin inhibitory activity compared to dabigatran. Especially, compounds 12a-
12h, 12j and 12k showed similar equivalent inhibitory activity to the references, with
IC50 values of 11.19 ±1.70 nM, 14.16 ± 1.87 nM, 10.94 ± 1.85 nM, 13.25 ± 3.78 nM,
11.84 ± 1.33 nM, 13.10 ± 1.69 nM, 11.49 ± 2.57 nM, 12.96 ± 1.30 nM, 11.91 ± 1.38
nM and 16.36 ± 1.70 nM, respectively. Furthermore, compound 12c was found to be
the most potent thrombin inhibitor among all these new compounds, which was
comparable to dabigatran (IC50 value: 9.99 ± 1.48 nM). Comparing the predicted pIC50
values and measured values of the synthesized compounds, it could be found that the
measured pIC50 values are comparable to or not much different from dabigatran, which
is similar to the predicted results. Moreover, the measured values of 12a, 12C and 12g
were higher, while the 12i and 12k were lower, which was consistent with the predicted
results. These findings validated the reliability and predictive ability of our QSAR
models.
The positions of the substituent groups exerted some impact on activity. It can be
observed from the bioactivity results that the -Cl groups at the 2- position of the A
location have higher bioactivity than 3- and 4-position. And when the -Cl group is at
the 4-position, the -F group introduced at the C location will increase its bioactivity.
Moreover, when the -Cl group is at the 2- and 3-position of the A location, the ethyl
group introduced at benzimidazole ring will raise its bioactivity than that of methyl
group. Compounds with ortho-substituents on benzene rings have anticoagulant activity.
From the perspective of contour maps, the adjacent substituent -Cl on benzene ring
corresponded to the green contour in the steric field of CoMFA/CoMSIA model. Ethyl
substitution at N-1 of benzimidazole, which can fill the active pocket and have
hydrophobic interactions with the surrounding residues, exhibited improved
anticoagulant activity. The good activity of substituted ethyl on benzimidazole was also
18

ACCEPTED MANUSCRIPT
consistent with the result discussed by our previous research group(Li et al., 2015), that
is, ethyl substituents were beneficial to the improvement of inhibitor activity. From the
molecular docking point of view, compound 12c produced two additional hydrogen
bonds with the thrombin receptor, the N atom of benzimidazole formed one hydrogen
bonding interaction with the residue Ser214 at distance of 2.47 Å, and hydrogen atom
at carboxyl was hydrogen bonded to the residue Gly216 at distance of 2.19 Å. These
effects have an impact on the improvement in the activity and stability of the inhibitor.
3. Conclusion
In this study, 42 dabigatran derivatives reported by our group as thrombin inhibitors
were analyzed using computer-aided drug design methods, including 3D-QSAR,
molecular docking and MD simulations. 3D-QSAR models with high reliability and
predictive abilities were developed to discover the key structural factors that influence
the anticoagulant activities. Reliable CoMFA (q2 = 0.705, r2 = 0.971) and CoMSIA (q2
= 0.707, r2 = 0.966) models were established and assisted with the internal and external
validation. Molecular docking and MD simulations indicated that strong hydrogen bond
and pi–pi stacking interactions with key residues Gly219, Asp189 and Trp60D played
a key role in ligand binding with the receptor. Results showed that the 3D-QSAR,
molecular docking and MD simulations were consistent with each other. Based on the
above results, 11 novel candidate compounds (12a-12k) were designed and synthesized.
13
The structures of the compounds were characterized by 1H NMR, C NMR and HR-
MS. The results of the anticoagulant activity showed that the bioactivity of all the
designed compounds were comparable to that of the reference dabigatran (IC50 =
9.99±1.48 nM). The order is 12c > 12a > 12g > 12e > 12j > 12h > 12f > 12d > 12b >
12k > 12i. The -Cl groups in the A location have higher bioactivity than 3- and 4-
position, and when the -Cl group is at the 4-position, the -F group introduced at the C
location will obviously increase its bioactivity. Moreover, when the -Cl group is at the
2- and 3-position of the A location, the ethyl group introduced at benzimidazole ring
will raise its bioactivity than that of methyl group. Compounds with ortho-substituents
on benzene rings have anticoagulant activity. In particular, 12a, 12c and 12g showed
better anticoagulant activities with IC50 values of 11.19 ± 1.70, 10.94 ± 1.85 and 11.49
± 2.57 nM, respectively, which were equivalent to the dabigatran. Compounds 12a, 12c
and 12g are candidates for further exploration of potential novel anticoagulant drugs.
4. Experimental section
4.1 Chemistry
All chemicals and solvents were purchased from Darui and Titan Corporation and
19

ACCEPTED MANUSCRIPT
used without further purification. Melting points were determined on WRS-1B and
were uncorrected. NMR spectra were recorded on a Bruker Avance 500 MHz NMR
spectrometer using TMS as internal reference. Chemical shifts are reported in δ scale
(ppm). Mass spectra were acquired on a Solari X-70FT-MS apparatus. Thin-layer
chromatography (TLC) was performed on silica gel plates (GF254) with visualization
of components by UV light (254 nm). Column chromatography was carried out on silica
gel (200–300 mesh). A series of novel dabigatran analogues were synthesized by the
method described in Scheme 1)
4.1.1 3-(2-(((4-carbamimidoylphenyl)amino)methyl)-N-(2-chlorophenyl)-1-methyl-1H-
benzo[d]imidazole-5-carboxamido)propanoic acid(12a)
White solid; yield; 72.4%; mp: 223.1-224.3℃; 1H NMR (500 MHz, DMSO-d6+2HCl) δ (ppm) 9.09
(s, 1H), 8.78 (s, 1H), 7.72 (d, J=7.2 Hz, 2H), 7.56 (d, J= 7.6 Hz, 2H), 7.51 (m, 1H), 7.34 (d, J = 7.5
Hz, 2H), 7.22 (d, J = 7.2 Hz, 2H), 6.89 (s, 2H), 4.80 (s, 2H), 4.19 (t, J=7.2 Hz, 2H), 3.84 (s, 3H),
2.62 (t, J = 7.4 Hz, 2H); 13C NMR (125 MHz, DMSO-d6) δ (ppm) 172.98, 170.12, 164.72, 153.90,
153.09, 140.33, 136.68, 136.65, 135.81, 131.98, 131.68, 130.71, 130.20, 128.82, 124.28, 122.96,
116.91, 114.31, 112.48, 111.13, 45.79, 32.43, 31.25, 29.79; HR-MS: calcd for C26H25ClN6O3
(M+H)+, 505.17494, found 505.17415.
4.1.2 3-(2-(((4-carbamimidoyl-2-fluorophenyl)amino)methyl)-N-(2-chlorophenyl)-1-methyl-1H-
benzo[d]imidazole-5-carboxamido)propanoic acid (12b)
White solid; Yield: 87.2%; m.p. 239.8-241.2℃;1H NMR (500 MHz, DMSO-d6+2HCl) δ (ppm) 9.08
(s, 1H), 8.79 (s, 1H), 7.73 (t, J = 11.5 Hz, 2H), 7.63-7.50 (m, 2H), 7.40 (d, J = 9.4 Hz, 3H), 7.28 (d,
J = 7.8 Hz, 1H), 7.24 (d, J = 8.0 Hz, 1H), 7.02 (t, J = 8.7 Hz, 1H), 4.92 (s, 2H), 4.05 (t, J= 7.2Hz,
2H), 3.89 (s, 3H), 2.61 (t, J = 7.8 Hz, 2H); 13C NMR (125 MHz, DMSO-d6+2HCl) δ (ppm) 173.03,
172.99, 169.76, 164.12, 153.34, 151.15, 149.24, 141.51, 141.42, 143.31 ,139.24 , 135.60, 129.38,
128.61, 128.03, 126.46, 125.81, 124.69, 114.89, 114.41, 112.16, 111.07, 46.83, 32.64, 31.14, 21.27;
HR-MS: calcd for C26H24ClFN6O3 (M+H)+, 523.16552, found 523.16408.
4.1.3 3-(2-(((4-carbamimidoylphenyl)amino)methyl)-N-(2-chlorophenyl)-1-ethyl-1H-
benzo[d]imidazole-5-carboxamido)propanoic acid (12c)
White solid; Yield: 74.5%; m.p. 266.4-267.2℃; 1H NMR (500 MHz, DMSO-d6+2HCl) δ (ppm) 9.08
(s, 1H), 8.87 (s, 1H), 7.73 (d, J = 8.5 Hz, 2H), 7.68 (d, J = 10.1 Hz, 2H), 7.57 (d, J = 7.7 Hz 1H),
7.45-7.39 (m, 1H), 7.29 (t, J = 7.9 Hz , 1H), 7.24 (s, 2H), 6.91(d, J = 8.5Hz,2H), 5.01 (s, 2H), 4.48
(m, 2H), 4.20(t, J= 7.2 Hz, 2H), 2.60 (t, J = 7.4 Hz, 2H), 1.33 (t, J = 7.2Hz, 3H); 13C NMR (125
MHz, DMSO-d6+2HCl) δ (ppm) 172.93, 169.92, 164.70, 164.88, 156.00, 153.28, 152.92, 150.00,
148.65, 134.54, 132.81, 130.24, 125.01, 123.30, 122.57, 117.05, 114.52, 113.37, 112.44, 111.75,
56.43, 45.26, 33.03, 20.83, 18.91; HR-MS: calcd for C27H27ClN6O3 (M+H)+, 519.19059, found
20

ACCEPTED MANUSCRIPT
519.19428.
4.1.4 3-(2-(((4-carbamimidoyl-2-fluorophenyl)amino)methyl)-N-(2-chlorophenyl)-1-ethyl-1H-
benzo[d]imidazole-5-carboxamido)propanoic acid (12d)
White solid; Yield: 77.0%; m.p. 232.3-234.1℃; 1H NMR (500 MHz, DMSO-d6+2HCl) δ (ppm) 9.43
(s, 1H), 9.21 (s, 1H), 7.96 (s, 1H), 7.90 (d, J = 8.6 Hz, 1H), 7.80 (d, J = 14.3 Hz, 1H), 7.67 (s, 1H),
7.58 (d, J = 7.6 Hz 1H), 7.50 (d, J = 8.5Hz, 1H), 7.42 (d, J = 7.7 Hz , 1H), 7.30 (t, J = 6.1Hz,1H),
7.26(d, J = 8.1Hz, 1H), 7.09(s, 1H), 5.01 (s, 2H), 4.45(m, 2H), 4.09 (t, J = 7.4Hz, 2H), 2.61 (t, J =
7.4 Hz, 2H), 1.33 (t, J = 7.2Hz, 3H);13C NMR (125 MHz, DMSO-d6+2HCl) δ(ppm) 173.09, 171.02,
164.75, 162.45, 160.11, 160.00, 153.44, 153,18, 141.16, 136.37, 132.04, 130.15, 129.33, 122.88,
119.36, 112.84, 112.62, 112.15, 110.09, 105.43, 105.17, 104.92, 46.29, 38.88, 32.78, 21.52, 15.28;
HR-MS: calcd for C27H26ClFN6O3 (M+H)+, 537.18117, found 537.18009.
4.1.5 3-(2-(((4-carbamimidoylphenyl)amino)methyl)-N-(3-chlorophenyl)-1-methyl-1H-
benzo[d]imidazole-5-carboxamido)propanoic acid (12e)
1
White solid; Yield: 85.3%; m.p. 277.5-279.3℃; H NMR (500 MHz, DMSO-d6+2HCl) δ 9.05 (s,
1H), 8.82 (s, 1H), 7.73 (t, J = 8.2 Hz, 3H), 7.64 (s, 1H), 7.40 (d, J = 8.7 Hz, 1H), 7.24 (d, J = 7.3
Hz, 3H), 7.15 (d, J = 6.9 Hz, 1H), 6.91 (d, J = 8.5 Hz, 2H), 4.94 (s, 2H), 4.06 (t, J = 7.4 Hz, 2H),
3.80 (s, 3H), 2.55 (t, J = 7.5 Hz, 2H); 13C NMR (125 MHz, DMSO-d6+2HCl) δ 173.00, 169.97,
169.75, 164.15, 153.29, 151.15, 149.24, 141.51, 140.88, 136.49, 136.41, 130.21, 128.27, 128.24,
126.45, 124.75, 114.89, 114.72, 112.14, 111.04, 46.76, 32.64, 31.13, 20.91; HR-MS: calcd for
C26H25ClN6O3 (M+H)+, 505.17494, found 505.17103.
4.1.6 3-(2-(((4-carbamimidoyl-2-fluorophenyl)amino)methyl)-N-(3-chlorophenyl)-1-methyl-1H-
benzo[d]imidazole-5-carboxamido)propanoic acid (12f)
White solid; Yield: 76.3%; m.p. 274.9-275.6℃; 1H NMR (500 MHz, DMSO-d6+2HCl) δ (ppm) 9.25
(s, 1H), 8.95 (s, 1H), 7.78 (d, J = 7.2 Hz, 1H), 7.63 (s, 1H), 7.56 (s, 2H), 7.28 (m, 1H), 7.25 (d, J =
8.5 Hz, 4H), 7.12 (m, 1H), 7.04 (s, 1H), 4.88 (s, 2H), 4.04 (t, J=7.2 Hz, 2H), 3.85 (s, 3H), 2.54 (s,
2H); 13C NMR (125 MHz, DMSO-d6+2HCl) δ (ppm) 173.01, 169.89, 166.02, 164.02, 155.43,
151.13, 149.21, 143.32, 141.45, 135.64, 132.17, 129.74, 128.44, 127.36, 126.52, 124.72, 117.52,
114.91, 114.74, 113.92, 112.11, 111.11, 46.77, 32.62, 31.22, 26.87; HR-MS: calcd for
C26H24ClFN6O3 (M+H)+, 521.16244, found 521.16284.
4.1.7 3-(2-(((4-carbamimidoylphenyl)amino)methyl)-N-(3-chlorophenyl)-1-ethyl-1H-
benzo[d]imidazole-5-carboxamido)propanoic acid (12g)
White solid; Yield: 76.5%; m.p. 267.1-267.9℃; 1H NMR (500 MHz, DMSO-d6+2HCl) δ (ppm) 9.03
(s, 1H), 8.81 (s, 1H), 7.71 (d, J=8.5 Hz, 2H), 7.72 (d, J = 8.8 Hz, 2H), 7.51 (s, 1H), 7.45 (d, J = 8.6
Hz, 1H), 7.24 (s, 2H), 7.17 (d, J = 6.4 Hz, 1H), 6.91 (d, J =8.3 Hz, 2H), 4.98 (s, 2H), 4.47 (m, 2H),
4.04 (t, J = 7.4 Hz, 2H), 2.56 (t, J = 7.3 Hz, 2H), 1.34 (t, J = 7.1 Hz,3H); 13C NMR (125 MHz,
21

ACCEPTED MANUSCRIPT
DMSO-d6+2HCl) δ (ppm) 173.04, 170.58, 164,72, 154.03, 153.35, 153.22, 149.19, 139.03, 136.26,
131.26, 130.50, 130.33, 130.17, 123.64, 122.06, 119.57, 113.73, 113.30, 112.19, 110.36, 56.47,
45.00, 33.13, 18.87, 15.25; HR-MS: calcd for C27H27ClN6O3 (M+H)+, 519.19059, found 519.19132.
4.1.8 3-(2-(((4-carbamimidoyl-2-fluorophenyl)amino)methyl)-N-(3-chlorophenyl)-1-ethyl-1H-
benzo[d]imidazole-5-carboxamido)propanoic acid (12h)
White solid; Yield: 80.2%; m.p. 236.3-237.5℃; 1H NMR (500 MHz, DMSO-d6+2HCl) δ (ppm) 9.26
(s, 1H), 9.03 (s, 1H), 7.83 (d, J = 13.5 Hz, 2H), 7.67 (d, J = 16.5 Hz, 2H), 7.50 (s, 1H), 7.45 (s, 1H),
7.15 (s, 1H), 7.07 (d, J = 8.6 Hz, 2H), 6.94 (dd, J = 21.0, 7.8 Hz, 2H), 5.06 (s, 2H), 4.49 (m, 2H),
4.02 (t, J = 7.5 Hz, 2H), 2.54 (t, J = 14.8 Hz, 2H), 1.33 (t, J=7.2 Hz, 3H); 13C NMR (125 MHz,
DMSO-d6+2HCl) δ (ppm) 173.02, 170.05, 167.96, 164.88, 160.46, 153.70, 153.31, 151.28, 143.66,
141.95, 136.22, 130.14, 129.67, 128.44, 127.16, 126.14, 124.65, 124.20, 114.18, 112.37, 110.80,
110.52, 52.04, 49.06, 46.79, 32.68, 30.83; HR-MS: calcd for C27H26ClFN6O3 (M+H)+, 537.18117,
found 537.18009.
4.1.9 3-(2-(((4-carbamimidoylphenyl)amino)methyl)-N-(4-chlorophenyl)-1-methyl-1H-
benzo[d]imidazole-5-carboxamido)propanoic acid(12i)
White solid; Yield: 74.3%; m.p. 253.5-254.3℃; 1H NMR (500 MHz, DMSO-d6+2HCl) δ (ppm) 9.08
(s, 1H), 8.77 (s, 1H), 7.72 (d, J = 7.2 Hz, 2H), 7.57 (d, J = 8.5 Hz, 2H), 7.26 (t, J = 7.2 Hz, 3H),
7.21 (m, 2H), 6.89 (s, 2H), 4.81 (s, 2H),4.04 (t, J = 7.4 Hz, 2H), 3.86 (s, 3H), 2.56 (t, J = 7.5 Hz,
2H); 13C NMR (125 MHz, DMSO-d6+2HCl) δ (ppm) 172.86, 171.43, 168.80, 164.89, 153.89,
152.66, 146.55, 144.12, 141.57, 134.42, 133.83, 131.92, 130.44, 130.24, 129.74, 126.20, 121.07,
119.21, 115.03, 114.82, 112.78, 46.58, 32.54, 32.12, 20.24; HR-MS: calcd for C26H25ClN6O3
(M+H)+, 505.17494, found 505.17854.
4.1.10 3-(2-(((4-carbamimidoyl-2-fluorophenyl)amino)methyl)-N-(4-chlorophenyl)-1-methyl-1H-
benzo[d]imidazole-5-carboxamido)propanoic acid (12j)
White solid; Yield: 85.3%; m.p. 277.5-279.3℃; 1H NMR (500 MHz, DMSO-d6+2HCl) δ (ppm) 9.16
(s, 1H), 8.82 (s, 1H), 7.65 (d, J = 7.2 Hz, 3H), 7.50 (m, 1H), 7.25 (d, J=7.4 Hz, 2H), 7.09 (d, J = 8.7
Hz, 2H), 6.98 (m, 1H), 6.87 (t, J = 7.2 Hz, 2H), 4.93 (s, 2H), 4.05 (t, J = 7.4 Hz, 2H), 3.85 (s, 2H),
2.54 (t, J = 7.5 Hz, 2H); 13C NMR (125 MHz, DMSO-d6+2HCl) δ (ppm) 177.66, 173.64, 167.94,
163.02, 159.93, 158.11, 154.16, 149.17, 147.31, 145.59, 138.94, 138.44, 136.64, 135.17, 134.60,
133.29, 131.28, 119.51, 116.53, 50.94, 41.02, 37.23, 36.91; HR-MS: calcd for C26H24ClFN6O3
(M+H)+, 523.16552, found 523,16514.
4.1.11 3-(2-(((4-carbamimidoylphenyl)amino)methyl)-N-(4-chlorophenyl)-1-ethyl-1H-
benzo[d]imidazole-5-carboxamido)propanoic acid (12k)
White solid; Yield: 80.2%; m.p. 235.8-236.3℃; 1H NMR (500 MHz, DMSO-d6+2HCl) δ (ppm) 9.33
(s, 1H), 9.06 (s, 1H), 7.84 (d, J = 7.2 Hz, 2H), 7.66 (d, J=7.2 Hz, 2H),7.43 (m, 1H), 7.29 (d, J = 8.5
22

ACCEPTED MANUSCRIPT
Hz, 2H), 7.22 (s, 3H), 7.14 (s, 1H),7.06 (s, 1H), 5.17 (s, 2H), 5.08 (m, 2H),4.04 (t, J=7.2 Hz, 2H),
3.16 (s, 2H), 2.54 (t, J = 7.4 Hz, 2H), 1.32 (t, J = 7.2 Hz, 3H); 13C NMR (125 MHz, DMSO-d6+2HCl)
δ (ppm) 175.54, 172.89, 168.79, 164.26, 160.72, 153.01, 152.45, 150.13, 131.96, 130.39, 130.31,
129.85, 129.76, 128.54, 118.86, 114.57, 112.65, 106.31, 46.32, 41.07, 38.73, 32.49, 14.47; HR-MS:
calcd for C27H27ClN6O3 (M+H)+, 518.18277, found 518.18377.
4.2. Anticoagulant assay in vitro
The anticoagulant activities of the target compounds were tested in vitro with
argatroban as reference.The lyophilized human thrombin (national standard) (5.4
μg/mL) , was purifed from human blood with the test compounds dissolved in DMSO
in different dilutions added and pre-incubated for 10 min at 37 °C. Subsequently, Ac-
FVR-AMC (5 μM), as a specifc fluorogenic thrombin substrate, was added to the
system. Then Envision microplate reader (PerkinElmer) to detect the dynamic changes
in relative fluorescence intensity for 10 min at room temperature. During the initial
stage of the reaction, the slope of the linear enzyme dynamics curve was referred to as
the initial velocity of enzyme reaction. Instrument settings: excitation wavelength, 355
nm; emission wavelength, 460 nm. Each well was measured 20 times every 20 s for 10
min. Then the change in fluorescence within a predetermined time was measured with
these conditions. The reaction kinetic curve slope (Vmax) was served as an activity
indicator. The concentration was calculated with a 50 % inhibition of thrombin activity
(IC50) by following formulas:
Inhibition rate (%) = [VDMSO-Vsample]/VDMSO × 100%
Vsample: initial velocity of compound group; VDMSO: initial velocity of blank group,
treated with DMSO alone.
Inhibition rate (%) = 100/[1+10(Log IC50-X)h
]
h: Hill coeffcient
Lyophilized human thrombin: The National Institute for the Control of Pharmaceutical
and Biological Products,China.
Ac-FVR-AMC: Calbiochem.
All measurements were performed in duplicate; the mean values of both determinations
are presented.
Acknowledgments
This work was support by Shanghai Natural Science Foundation (No.19ZR1455400).
23

ACCEPTED MANUSCRIPT
Conflict of Interest
The authors declare no conflict of interest.
Reference
Ahmad, Y., Lip, G.Y.H., 2012. Dabigatran etexilate for the prevention of stroke and
systemic embolism in atrial fibrillation: NICE guidance. Heart 98, 1404–1406.
https://doi.org/10.1136/heartjnl-2012-302101
Amata, E., Marrazzo, A., Dichiara, M., Modica, M.N., Salerno, L., Prezzavento, O.,
Nastasi, G., Rescifina, A., Romeo, G., Pittalà, V., 2017. Heme Oxygenase
Database (HemeOxDB) and QSAR Analysis of Isoform 1 Inhibitors.
ChemMedChem 12, 1873–1881. https://doi.org/10.1002/cmdc.201700321
B., C.J.T., S., Z., K., C.C.K.N., A., L.D., 2007. The central role of thrombin in
hemostasis. J. Thromb. Haemost. 5, 95–101. https://doi.org/10.1111/j.1538-
7836.2007.02500.x
Berry, C.N., Girard, D., Lochot, S., Lecoffre, C., 1994. Antithrombotic actions of
argatroban in rat models of venous, ‘mixed’ and arterial thrombosis, and its
effects on the tail transection bleeding time. Br. J. Pharmacol. 113, 1209–1214.
https://doi.org/10.1111/j.1476-5381.1994.tb17126.x
Blommel, M.L., Blommel, A.L., 2011. Dabigatran etexilate: A novel oral direct
thrombin inhibitor. Am. J. Heal. Pharm. 68, 1506–1519.
https://doi.org/10.2146/ajhp100348
Chaudhari, K., Hamad, B., Syed, B.A., 2014. Antithrombotic drugs market. Nat. Rev.
Drug Discov. 13, 571–572.
Curto, A., Albaladejo, A., 2016. Implications of apixaban for dental treatments,
Journal of Clinical and Experimental Dentistry, 8, e611–614.
https://doi.org/10.4317/jced.53004
Dahl, O., 2008. Dabigatran etexilate: An oral direct thrombin inhibitor, Therapy, 5,
685–695. https://doi.org/10.2217/14750708.5.5.685
De Candia, E., 2012. Mechanisms of platelet activation by thrombin: A short history.
Thromb. Res. 129, 250–256.
https://doi.org/https://doi.org/10.1016/j.thromres.2011.11.001
Eriksson, B.I., Smith, H., Yasothan, U., Kirkpatrick, P., 2008. Dabigatran etexilate.
Nat. Rev. Drug Discov. 7, 557–558.
Granger, C., H Alexander, J., Mcmurray, J., D Lopes, R., Hylek, E., Hanna, M., R Al-
Khalidi, H., Ansell, J., Atar, D., Avezum, A., Cecilia, M., Bahit, R., Donald
Diaz, J., A Easton, J., Ezekowitz, M., Ch, B., Flaker, G., Garcia, D., Geraldes,
M., Wallentin, L., 2011. Apixaban versus Warfarin in Patients with Atrial
Fibrillation. N Engl J Med. 365, 981–992.
https://doi.org/10.1056/NEJMoa1107039)
Gustafsson, D., Antonsson, T., Bylund, R., Eriksson, U., Gyzander, E., Nilsson, I.,
Elg, M., Mattsson, C., Deinum, J., Pehrsson, S., Karlsson, O., Nilsson, A.,
Sörensen, H., 1998. Effects of melagatran, a new low-molecular-weight
24

ACCEPTED MANUSCRIPT
thrombin inhibitor, on thrombin and fibrinolytic enzymes. Thromb. Haemost. 79,
110–118.
Haas, S., 2008. New oral Xa and IIa inhibitors: updates on clinical trial results. J.
Thromb. Thrombolysis 25, 52–60. https://doi.org/10.1007/s11239-007-0108-7
Hauel, N.H., Nar, H., Priepke, H., Ries, U., Stassen, J.-M., Wienen, W., 2002.
Structure-Based Design of Novel Potent Nonpeptide Thrombin Inhibitors. J.
Med. Chem. 45, 1757–1766. https://doi.org/10.1021/jm0109513
Hou, T., Wang, J., Li, Y., Wang, W., 2011. Assessing the Performance of the
MM/PBSA and MM/GBSA Methods. 1. The Accuracy of Binding Free Energy
Calculations Based on Molecular Dynamics Simulations. J. Chem. Inf. Model.
51, 69–82. https://doi.org/10.1021/ci100275a
Huang, S., Feng, K., Ren, Y., 2019. Molecular modelling studies of quinazolinone
derivatives as MMP-13 inhibitors by QSAR, molecular docking and molecular
dynamics simulations techniques. Medchemcomm 10, 101–115.
https://doi.org/10.1039/C8MD00375K
Kam, P.C.A., Kaur, N., Thong, C.L., 2005. Direct thrombin inhibitors: Pharmacology
and clinical relevance. Anaesthesia 60, 565–574. https://doi.org/10.1111/j.1365-
2044.2005.04192.x
Kim, S., Tran, N., Schewe, J., Boehm, O., Wittmann, M., Graeff, I., Hoeft, A.,
Baumgarten, G., 2015. Safety and economic considerations of argatroban use in
critically ill patientsꢀ: a retrospective analysis. Journal of Cardiothoracic Surgery,
10, 1–8. https://doi.org/10.1186/s13019-015-0214-0
Lee, C.J., Ansell, J.E., 2011. Direct thrombin inhibitors. Br. J. Clin. Pharmacol. 72,
581–592. https://doi.org/10.1111/j.1365-2125.2011.03916.x
Li, C.L., Dong, M.H., Ren, Y.J., Li, L.H., 2015. Design, synthesis, biological
evaluation and molecular docking of novel dabigatran derivatives as potential
thrombin inhibitors. RSC Adv. 5, 23737–23748.
https://doi.org/10.1039/c5ra01828e
Pollack, C., Reilly, P., Eikelboom, J., Glund, S., Verhamme, P., A Bernstein, R.,
Dubiel, R., V Huisman, M., Hylek, E., W Kamphuisen, P., Kreuzer, J., Levy, J.,
Sellke, F., Stangier, J., Steiner, T., Wang, B., Kam, C.-W., Weitz, J., 2015.
Idarucizumab for Dabigatran Reversal, The New England journal of medicine,
73, 511–520. https://doi.org/10.1056/NEJMoa1502000
Ren, W., Ren, Y., Wang, S., 2016. Design, synthesis, anticoagulant activity
evaluation and molecular docking studies of a class of N-ethyl dabigatran
derivatives, European Journal of Medicinal Chemistry, 120, 148–159.
https://doi.org/10.1016/j.ejmech.2016.05.020
Sanford, M., Plosker, G.L., 2008. Dabigatran Etexilate. Drugs, 68, 1699–1709.
https://doi.org/10.2165/00003495-200868120-00007
Savelieva, I., Camm, A.J., 2014. Practical considerations for using novel oral
anticoagulants in patients with atrial fibrillation. Clin. Cardiol. 37, 32–47.
https://doi.org/10.1002/clc.22204
Traynor, K., 2015. Idarucizumab approved for reversal of anticoagulant effects of
dabigatran, American Journal of Health-System Pharmacy, 72, 2002–2004.
25

ACCEPTED MANUSCRIPT
https://doi.org/10.2146/news150077
Tu, J., Li, J.J., Shan, Z.J., Zhai, H.L., 2017. Exploring the binding mechanism of
Heteroaryldihydropyrimidines and Hepatitis B Virus capsid combined 3D-QSAR
and molecular dynamics. Antiviral Res. 137, 151–164.
https://doi.org/https://doi.org/10.1016/j.antiviral.2016.11.026
Ul-Haq, Z., Khan, N., Zafar, S.K., Moin, S.T., 2016. Active site characterization and
structure based 3D-QSAR studies on non-redox type 5-lipoxygenase inhibitors.
Eur. J. Pharm. Sci. 88, 26–36.
https://doi.org/https://doi.org/10.1016/j.ejps.2016.03.014
Wang, F., Ren, Y.J., Dong, M.H., 2016. Molecular design, synthesis and
anticoagulant activity evaluation of fluorinated dabigatran analogues. Bioorganic
Med. Chem. 24, 2739–2753. https://doi.org/10.1016/j.bmc.2016.04.038
WEITZ, J.I., BATES, S.M., 2005. New anticoagulants. J. Thromb. Haemost. 3, 1843–
1853. https://doi.org/10.1111/j.1538-7836.2005.01374.x
Yang, H., Liu, Q., Gao, X., Ren, Y., Gao, Y., 2017. Novel dabigatran derivatives with
a fluorine atom at the C-2 position of the terminal benzene ring: Design,
synthesis and anticoagulant activity evaluation. Eur. J. Med. Chem. 126, 799–
809. https://doi.org/https://doi.org/10.1016/j.ejmech.2016.12.015
26