Novel phthalamide derivatives as antihypertensive agents: rapid and clean synthesis, in silico and in vivo evaluation

Article abstract of DOI:10.1007/s00044-019-02327-3

Hypertension is a prevalent progressive disorder and a key risk factor for cardiovascular disease, stroke, and kidney disease. Angiotensin-I-converting enzyme (ACE) inhibitors are the first-line drugs for treating hypertension, but they have many side effects. ACE is a zinc dipeptidyl carboxypeptidase that cleaves the decapeptide angiotensin-I to form the vasopressor angiotensin-II. Since the latter molecule is the main bioactive product of the renin–angiotensin system, its inhibition is a key strategy for hypertension therapy. The aim of this study was to conduct an in silico evaluation of a series of new phthalamides as ACE inhibitors, examine the acute toxicity (in mice) of three of these molecules, and test the hypertensive effect of the most promising compound in a spontaneous hypertensive rat (SHR) model. The new phthalamide derivatives were synthesized with a fast, cheap, high-yield green (solventless) procedure. Three molecules (DD-01, DD-13, and DD-14S) from the current series of phthalamides were selected as the most promising ACE inhibitors based on in silico analysis of their physicochemical properties, Gibbs free energy and ADME profile. After synthesis, these three molecules showed low toxicity (LD₅₀ > 1600 mg/kg) in the acute toxicity test (Lorke’s method). Finally, DD-01 significantly decreased systolic, diastolic, and mean arterial pressure in the SHR model, being ～7-fold more potent than captopril (the reference drug). Three novel phthalamide derivatives were synthesized in good yields with a fast and efficient green procedure. They all displayed low toxicity. The one tested in the SHR model proved to be efficient for reducing blood pressure.

Full text of DOI:10.1007/s00044-019-02327-3

MEDICINAL
CHEMISTRY
RESEARCH
Medicinal Chemistry Research
https://doi.org/10.1007/s00044-019-02327-3
ORIGINAL RESEARCH
Novel phthalamide derivatives as antihypertensive agents: rapid
and clean synthesis, in silico and in vivo evaluation
Erik Andrade-Jorge1,2 Jessica E. Rodríguez José Bribiesca-Carlos Itzell A. Gallardo-Ortíz
1 ●
2 ●
1 ●
●
2 ●
1,3
José G. Trujillo-Ferrara Rafael Villalobos-Molina
Received: 22 December 2018 / Accepted: 11 March 2019
©
Springer Science+Business Media, LLC, part of Springer Nature 2019
Abstract
Hypertension is a prevalent progressive disorder and a key risk factor for cardiovascular disease, stroke, and kidney disease.
Angiotensin-I-converting enzyme (ACE) inhibitors are the first-line drugs for treating hypertension, but they have many side
effects. ACE is a zinc dipeptidyl carboxypeptidase that cleaves the decapeptide angiotensin-I to form the vasopressor
angiotensin-II. Since the latter molecule is the main bioactive product of the renin–angiotensin system, its inhibition is a key
strategy for hypertension therapy. The aim of this study was to conduct an in silico evaluation of a series of new
phthalamides as ACE inhibitors, examine the acute toxicity (in mice) of three of these molecules, and test the hypertensive
effect of the most promising compound in a spontaneous hypertensive rat (SHR) model. The new phthalamide derivatives
were synthesized with a fast, cheap, high-yield green (solventless) procedure. Three molecules (DD-01, DD-13, and DD-
1
4S) from the current series of phthalamides were selected as the most promising ACE inhibitors based on in silico analysis
of their physicochemical properties, Gibbs free energy and ADME profile. After synthesis, these three molecules showed
low toxicity (LD > 1600 mg/kg) in the acute toxicity test (Lorke’s method). Finally, DD-01 significantly decreased systolic,
5
0
diastolic, and mean arterial pressure in the SHR model, being ∼7-fold more potent than captopril (the reference drug). Three
novel phthalamide derivatives were synthesized in good yields with a fast and efficient green procedure. They all displayed
low toxicity. The one tested in the SHR model proved to be efficient for reducing blood pressure.
●
●
●
●
Keywords Hypertension Spontaneously hypertensive rats Green chemistry ADME profile Molecular docking
Introduction
Hypertension, a chronic medical condition that affects >1.3
Supplementary information The online version of this article (https://
billion people worldwide (Bloch 2016; Abdel-Rahman et al.
2017), represents the main risk factor for the development
of cardiovascular disease, stroke, and kidney disease. These
three disorders account for 17 million deaths annually,
approximately 31% of all disease-related deaths worldwide
doi.org/10.1007/s00044-019-02327-3) contains supplementary
material, which is available to authorized users.
*
*
José G. Trujillo-Ferrara
jtrujillo@ipn.mx
Rafael Villalobos-Molina
(
2
WHO 2013; Abdel-Rahman et al. 2017; Ben Salah et al.
018).
One in four people suffers from hypertension in Mexico,
villalobos@campus.iztacala.unam.mx
1
2
3
Unidad de Investigación en Biomedicina, Carrera de Enfermería,
Facultad de Estudios Superiores-Iztacala, Universidad Nacional
Autónoma de México, Av. de los Barrios 1, Los Reyes Iztacala,
Tlalnepantla, Estado de México 54090, Mexico
according to ENSANUT 2016 (Campos-nonato and Her-
nández-barrera 2018). The values used for diagnosing
hypertension have changed over time. Since a reduced
range of values for defining this disorder yields better
results in patient therapy and prognosis, new guidelines for
diagnosis, management, and treatment were published in
2017 by the American Heart Association and the American
College of Cardiology (AHA/ACC) (Lloyd-Jones et al.
2017; Magvanjav et al. 2018).
Laboratorio de Investigación en Bioquímica, Sección de Estudios
de Posgrado e Investigación, Escuela Superior de Medicina del
Instituto Politécnico Nacional, Plan de San Luis y Díaz Mirón s/n
Casco de Santo Tomás, Mexico City 11340, Mexico
Departamento de Bioquímica, Facultad de Medicina, Universidad
Nacional Autónoma de México, Ciudad Universitaria, Coyoacán,
Mexico City 04510, Mexico

Medicinal Chemistry Research
The physiopathology of hypertension is still poorly
understood. The known factors that contribute to this mul-
tifactorial disease are high salt (Na ) intake, obesity, insulin
resistance, and improper regulation of the sympathetic
nervous system and the renin–angiotensin system (RAS)
the development of new acetylcholinesterase inhibitors to
treat a wide variety of neurodegenerative diseases such as
Alzheimer’s (Aliabadi et al. 2013; Si et al. 2016; Andrade-
Jorge et al. 2018). Some phthalamides act as selective
inhibitors of COX-2 with high affinity, giving better results
than diclofenac (a nonsteroidal anti-inflammatory drug)
(Alanazi et al. 2015), while others have been administered
as anticonvulsant agents. Moreover, α1A/1D-AR subselective
antagonists have been designed (Xu et al. 2015).
The aim of the present study was to design, characterize
(in silico), synthesize, and evaluate (in vivo) a series of
phthalamides as ACEis. The one molecule from this series
that was tested in a spontaneous hypertensive rat (SHR)
model was more potent than some of the current ACEis
such as captopril.
+
(
2
Luo et al. 2017; Grootaert et al. 2017; Vildmyren et al.
018). One of the most important mechanisms in blood
pressure regulation is the RAS, responsible for controlling
hemodynamic stability, fluid volume, and sodium–potas-
sium balance (Te Riet et al. 2015; Fu et al. 2016).
Renin is synthesized in the kidneys in its inactive form
and released into blood circulation in response to low levels
of intratubular sodium, hypotension in the afferent arterioles
of renal glomerulus, and sympathetic activation. In the
bloodstream, proteolytic and nonproteolytic mechanisms
activate pro-renin (Jan Danser et al. 2007), which hydro-
lyzes angiotensinogen to form angiotensin-I (Ang I). The
latter decapeptide is cleaved by the Ang I-converting
enzyme (ACE, a zinc dipeptidyl carboxypeptidase) to
generate a potent vasoconstrictor, angiotensin-II (Ang II)
Materials and methods
Theoretical calculations
(
EC3.4.15.1) (Lv et al. 2018), the main bioactive product of
the RAS.
In addition to catalyzing the conversion of Ang I into
The in silico calculations for the parameters of the absorp-
tion, distribution, metabolism, and excretion (ADME) pro-
file, physicochemical properties and toxicity were carried
out on the online server Molinspiration (Molinspiration
Cheminformatics 2016), OSIRIS property explorer, and
StarDrop software for all ligands in this job.
Ang II, ACE inhibits the degradation of the vasodilator
bradykinin (Paiva et al. 2017; Fienberg et al. 2018). The
two distinct isoforms of ACE are the somatic and testicular
form. The somatic isoform, the most important, is mainly
expressed on the endothelial surface. It is particularly
abundant in the lungs, intestine, choroid plexus, and
placenta, as well as on the brush border membranes in the
kidney (Sparks et al. 2015).
Docking
All molecules were modeled on GaussView 5.0.9 software
and the protonation state was considered at physiological
conditions (pH 7.4) for all ligands. The conformational
analysis was performed on Gaussian 09 (Frisch et al. 2009)
with a semi-empirical method (PM3). Docking conditions
were programmed with AutoDock tools 1.5.4 and Raccoon
(Forli et al. 2016) by utilizing a hybrid Lamarckian Genetic
Algorithm (Morris et al. 1998), an initial population of 100
randomly placed individuals, Kollmann partial charges for all
protein atoms, and Gasteiger charges for ligands. Ligands
were prepared by adding all rotating bonds, torsional degrees
of freedom, atomic partial charges, and nonpolar H-bonds
with AutoDock tools 1.5.4. (Morris et al. 2009). The crystal
structure of human ACE was downloaded from the Protein
Data Bank (PDB code: 1O86) (Natesh et al. 2003). The grid
box was set at 80 × 60 × 70 with 0.375 Å spacing and the
following coordinates: X = 37.531, Y = 33.432, and Z =
44.336. With AutoDock4 software in a Linux operative
system (Fedora 22), the lowest energy conformations were
obtained for each ligand bound to the enzyme, expressed as
Gibbs free energy (ΔG), and the dissociation constant (Kd)
and the –log(10) dissociation constant (pKd) were ascertained
for the complex showing the highest affinity. The number of
In cases of hypertension, the inhibition of ACE is known
to lower blood pressure and protect organs. Consequently,
ACE inhibitors (ACEis) have been considered the first-line
drugs for hypertension therapy. Recently, many researchers
have been developing new ACEis based on peptides
derived from plants, animals, and eggs (Li et al. 2014; Jenis
et al. 2017; Tai et al. 2018) because they can control blood
pressure and decrease cardiac and pulmonary fibrosis
without producing the secondary effects of other treatments
(
Fienberg et al. 2018).
Ang II receptor blockers are also employed to control
blood pressure, but it has been demonstrated that ACEis
have additional benefits due to their capacity to increase the
concentration of bradykinin and improve endothelial func-
tion (Shen et al. 2017). The main adverse effects of ACEis,
including a dry cough, hyperkalemia, fatigue, dizziness,
headaches, and loss of taste (Parish and Miller 1992; Nawaz
et al. 2017; Yu et al. 2018), could probably be avoided by
the design of new molecules like those proposed in the
current contribution.
Phthalamides are one possible source of new ACEis.
Phthalic anhydride derivatives are an important moiety in

Medicinal Chemistry Research
interactions, the binding distance, and type of binding were
determined with the Visual Molecular Dynamics program
for the production, care and use of laboratory animals
(NOM-062-ZOO-1999, Ministry of Agriculture).
(
VMD v.1.8.6) (Humphrey et al. 1996).
All drugs were suspended in distilled water as the vehicle
(VEH) and administered to rats intragastrically every 24 h
Synthesis and characterization
for 32 days. The WKY rats formed the normotensive con-
trol group (WKY + VEH, n = 4). The SHR were randomly
assigned to one of the following groups (n = 4): the
hypertensive control group (SHR + VEH), reference group
(SHR + CAPTOPRIL at 40 mg/kg), and experimental
group (SHR + DD-01 at 10 mg/kg).
The reagents and solvents were used as received from the
commercial supplier (Sigma-Aldrich, St. Louis, MO, USA).
All reactions were carried out in an oven-dried flask at the
melting point of the starting material, agitating the mixtures
with a stirring bar for a few minutes under solventless
conditions (green chemistry). The solution was purified by
utilizing the appropriate non-toxic solvent and then con-
centrated by means of a standard rotary evaporator. Melting
points were measured on a Stuart® SMP40 automatic
melting point apparatus and are uncorrected. Infrared
spectra (IR) were obtained on a 100 FT-IR spectrometer
Blood pressure monitoring
Blood pressure (BP) was measured by a non-invasive
indirect method by utilizing a tail-cuff device with a sensor
and an inflatable latex ring (IITC Life Science Inc.,
Woodland Hills, CA, USA). During 1 week, rats were
exposed to being inside a plastic restrainer at 37 °C before
the evaluation of BP began. An average of seven BP
readings was employed to establish systolic BP (SBP),
diastolic BP (DBP), and mean arterial pressure (MAP). The
measurements were recorded every week during the
4 weeks of the experiment.
1
13
(
Perkin-Elmer) with a universal ATR accessory. H and
C
1
NMR spectra were recorded on a Varian Mercury 300 ( H,
1
3
3
00 MHz;
C, 75 MHz) spectrometer with tetra-
methylsilane as an internal reference. The parameters
reported are chemical shifts in ppm (δ), the integration area,
multiplicity (s = singlet, d = doublet, t = triplet, q = quar-
tet, m = multiplet) and coupling constants (Hz). Electro-
spray ionization (ESI) high-resolution mass spectrometry
was performed on a Bruker micrOTOf-Q-II instrument.
Lethal dose 50 for mice
The lethal dose 50 (LD ) was determined with Lorke’s
5
0
General procedure for the synthesis of N,N’-
substituted benzene-1,2-dicarboxamides (DD-01
is representative)
method. Briefly, CD1 male mice (20–25 g) were placed in
three groups (n = 3), applying one dose (10, 100, or 1000
mg/kg) to each group of the test compounds (by intraper-
itoneal injection) to each animal per group. Observation of
the animals for 24 h revealed that none had died. Therefore,
three new groups were formed to administer higher doses
(1200, 1400, and 1600 mg/kg), again finding no dead ani-
mals within 24 h (Lorke 1983; Chinedu et al. 2013).
After placing 202.88 mg (1 mmol) of phthalic anhydride
and 328.65 mg (2 mmol) of phenylethylamine in a 50-mL
round-bottom flask, the mixture was agitated with a stirring
bar and heated from 100 to 150 °C for 10–15 min to achieve
gentle melting. The reaction was cooled at room tempera-
ture and monitored by thin layer chromatography. Subse-
quently, ethyl acetate (40 mL) was added and the mixture
was sonicated until a white powder formed. The precipitate
was filtered and washed three times with water (NaOH 0.1
M, pH 13).
Statistical analysis
The data from the in vivo assays are expressed as the mean
± standard error of the mean (SEM). Each treatment group
was compared with the corresponding control group.
Repeated-measures analysis of variance (RM-ANOVA) and
the Bonferroni post-test were carried out on GraphPad
Prism statistical software, with significant differences con-
sidered at p < 0.05.
In vivo evaluation
Ten-week-old male Wistar Kyoto (WKY) and sponta-
neously hypertensive rats (250–300 g) were obtained from
the breeding colony of the Institute of Cell Physiology
(
UNAM). Rats were maintained in a pathogen-free envir-
Results and discussion
onment under controlled conditions (22 ± 2 °C, 40–60%
humidity, 12/12-h light/dark cycle), with food and water
provided ad libitum. All procedures were approved by the
Bioethics Committee of our institution and complied with
the technical specifications of the Mexican Official Norm
Molecular docking and theoretical calculations
Twenty-three phthalamides derived from phthalic anhydride
were proposed (Scheme 1) and their basic structures

Medicinal Chemistry Research
R3
R3
R4
(CH )
(CH )
R4
2 n
2 n
R1
R1
NH
O
O
R2
R2
NH
Molecule
DD-01
DD-02
R
H
H
H
OH
H
1
R
H
H
OH
H
OH
H
H
COOH
H
COOH
CH3
COOH
H
COOCH3
CH3
OH
H
2
n
R
H
OH
OH
OH
H
H
OH
OH
OCH
OCH
OH
OH
OH
3
R
4
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
1
1
1
1
1
0
0
H
OH
OH
OH
H
DD-03R
DD-03S
DD-04R
DD-04S
DD-05R
DD-05S
DD-06R
DD-06S
DD-07R
DD-07S
DD-08R
DD-08S
DD-09
DD-10R
DD-10S
DD-11
DD-12A
DD-12B
DD-13
OH
COOH
H
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
H
H
COOH
H
COOH
CH3
COOCH3
H
3
3
OH
OH
CH3
H
OH
H
H
H
H
H
CH3
OCH3
OCH3
H
OCH3
H
H
H
H
H
CH3
H
CH3
OCH3
H
OCH3
H
DD-14R
DD-14S
H
H
Scheme 1 Proposed structure of the phthalamides
modeled with a semi-empirical method (PM3). They were
then docked with ACE, obtaining ΔG, Kd, and pKd for the
interactions between human ACE and the ligands, the latter
comprising the test compounds and some reference drugs
like benazepril, captopril, enalapril, and lisinopril (Table 1).
Molecular docking results clearly show a high affinity of the
test compounds for the enzyme, exceeding the capacity of
some of the reference drugs. This is not enough for selecting
the best candidate for synthesis and the in vivo test, in order
to define the molecules with high probability to present
in vivo effects, additional theoretical calculations were
carried out with the online servers Molinspiration and
OSIRIS property explorer to examine some physicochem-
ical properties with Lipinski’s rule of five (Lipinski et al.
1997), as well as the ADME profile and some toxicity
parameters using StarDrop software, results are shown in
Tables 2 and 3. The parameters estimated here are discussed
briefly below in order to select the best candidates for the
synthesis.
The octanol/water partition coefficient (LogP) is an
important descriptor of molecular hydrophobicity and
therefore serves as a parameter of absorption and

Medicinal Chemistry Research
Table 1 Gibbs free energy (ΔG), the dissociation constant (Kd), and
(
MW), the number of hydrogen bond acceptors (HBA) and
–
log (10) dissociation constant (pKd) for the interactions between the
the number of hydrogen bond donors (HBD). Lipinski
pointed out that for good absorption, molecules must have a
MW < 500, no >5 HBD and <10 HBA. The few molecules
in accordance with these values were included in the next
screening.
ligands and angiotensin-I-converting enzyme of human
Receptor
Ligand
ΔG (kcal/mol)
Kd (µM)
pKd
DD-01
−9.800
−10.65
−9.660
−9.650
−9.290
−8.990
−8.080
−7.660
−7.760
−8.100
−8.010
−8.010
−8.550
−8.570
−9.750
−9.900
−9.670
−10.60
−10.88
−10.10
−9.900
−9.170
−9.500
−10.67
−7.120
−10.79
−10.81
0.066
0.018
0.082
0.085
0.156
0.258
1.200
2.430
2.050
1.150
1.350
1.350
0.543
0.522
0.072
0.056
0.082
0.017
0.011
0.040
0.055
0.191
0.109
0.015
6.010
0.012
0.012
7.18
7.74
7.08
7.07
6.81
6.59
5.92
5.61
5.69
5.94
5.87
5.87
6.26
6.28
7.14
7.25
7.08
7.77
7.97
7.40
7.26
6.72
6.96
7.82
5.22
7.91
7.93
In drug development, the inclusion of the ADME profile
is obligatory (see Table 3). The first parameter evaluated
was human intestinal absorption (HIA), an indicator of the
passive absorption from the intestine into the hepatic portal
vein (without considering the effect of first pass metabo-
lism). This parameter provided evidence of poor HIA for
most of the test compounds (Table 3). Acceptable HIA
values (absorption ≥ 30%) are desirable but insufficient to
describe a good oral bioavailability. Greater plasma protein
binding (PPB90) reduces the capacity of compounds to
traverse cell membranes and therefore may affect drug
efficiency. Only a few molecules exhibited strong binding
(over 90%) to plasma proteins. Therefore, those molecules
were discarded since the less bound a drug is, the more
efficiently it can traverse cell membranes. Since metabolism
is a crucial parameter of pharmacokinetic studies, two
relevant isoforms of cytochrome P450 were herein tested
for affinity to the ligands using the StarDrop software.
Isoform 2C9 is responsible for the phase I metabolism of up
to 20% of all drugs, mainly through oxidation (Van Booven
et al. 2010). Isoform P450 2D6, located in the liver and
brain (Wang et al. 2009), participates in the metabolism of
up to 25% of the current clinically used drugs. Both of these
isoforms are involved in the metabolism of aromatic rings,
which are present in all the proposed molecules. All
molecules were found to have similar values of affinity for
isoform 2C9, with an average of 5.72. For isoform 2D6,
most of the molecules displayed low affinity (see Table 3).
P-glycoprotein, a protein belonging to the superfamily of
ATP-binding cassette (ABC) transporters, is implicated in
the absorption and disposal of drugs, acting as a pump to
remove xenobiotics from cells (Lin and Yamazaki 2003).
Accordingly, a determination was made as to whether the
compounds in the series of phthalimides are a substrate of
this protein, and if absorption is thus affected. Such was true
for many of the test compounds. Finally, blood–brain bar-
rier penetration (BBB log([brain]:[blood])) and blood–brain
barrier penetration category (BBB category) are two rele-
vant parameters in the development of central nervous
system (CNS) drugs. However, ACEis do not need to cross
the BBB to exert their action, and the present results indi-
cated that they are unlikely to do so. In addition, 57 toxicity
parameters were assessed by using the Derek Nexus module
with StarDrop software (Table 4). The data reveal three
negative properties for some ligands, including the follow-
ing presumptive toxicity: skin sensitization, hepatotoxicity,
and chromosome damage in vitro, such as DD-02, DD-03R/S,
DD-02
DD-03R
DD-03S
DD-04R
DD-04S
DD-05R
DD-05S
DD-06R
DD-06S
DD-07R
DD-07S
DD-08R
DD-08S
DD-09
DD-10R
DD-10S
DD-11
DD-12A
DD-12B
DD-13
DD-14R
DD-14S
Benazepril
Captopril
Enalapril
Lisinopril
bioavailability. Although Lipinski suggested that the value
must not be over 5.0, a negative number also represents low
hydrophobicity and poor absorption, leading to the exclu-
sion of some of the proposed molecules (DD-03R, DD-03S,
DD-07R, and DD-07S, among others see Table 2). LogS
aqueous solubility) refers to solubility measured in mol/L,
where values >−4 are desirable since it has been seen that
80% of all drugs on the market with these values present
good absorption. Therefore, this parameter is a good
descriptor of absorption. Some molecules had values >2.1
and were eliminated (DD-08R, DD-08S, DD-09, DD-10R,
and DD-10S). Polar surface area (PSA) is a descriptor that
has been found to correlate with the passive transport of
molecules through membranes. Based on the recommen-
dation that values should be <120, additional molecules
were discarded (DD-02, DD-03R, DD-03S, and others).
Furthermore, analysis was made of molecular weight
(
>

Medicinal Chemistry Research
Table 2 Physicochemical
properties based on the
Lipinski’s rules of five
LIGAND
LogP < 5
LogS (−5 a 1)
PSA < 120
MW (g/mol) < 500
HBA < 10
HBD < 5
nrotb < 10
DD-01
3.634
1.781
1.08
58.2
139.1
179.6
179.6
98.66
98.66
213.7
213.7
191.7
191.7
220
372.5
436.5
468.5
468.5
404.5
404.5
524.5
524.5
552.5
552.5
556.6
556.6
552.5
552.5
464.5
496.5
496.5
404.5
432.5
432.5
492.6
372.5
372.5
4
2
6
8
8
4
4
8
8
6
6
10
10
6
6
6
6
6
4
2
2
2
2
2
10
10
10
10
10
10
12
12
14
14
12
12
14
14
8
DD-02
2.43
8
DD-03R
DD-03S
DD-04R
DD-04S
DD-05R
DD-05S
DD-06R
DD-06S
DD-07R
DD-07S
DD-08R
DD-08S
DD-09
−0.2098
−0.2098
1.888
3.219
3.219
2.586
2.586
2.553
2.553
2.286
2.286
2.521
2.521
2.318
2.318
2.142
3.004
3.004
1.673
1.51
10
10
6
1.888
6
0.7275
0.7275
1.116
12
12
12
12
12
12
12
12
8
1.116
−1.311
−1.311
1.371
220
191.7
191.7
139.1
157.6
157.6
98.66
76.66
76.66
95.12
58.2
1.371
2.215
DD-10R
DD-10S
DD-11
0.3713
0.3713
2.831
10
10
6
12
12
10
12
12
14
8
DD-12A
DD-12B
DD-13
3.465
6
3.465
1.51
6
3.018
2.023
0.9025
0.9025
8
DD-14R
DD-14S
3.369
4
3.369
58.2
4
8
LogP octanol/water partition coefficient, LogS aqueous solubility, PSA polar surface area, MW molecular
weight, HBA number of hydrogen bond acceptors, HBD number of hydrogen bond donors, nrotb number of
rotatable bonds
Table 3 ADME profile
LIGAND
HIA
PPB90
2C9 pKi
2D6 affinity
P-gp
BBB log([brain]:[blood])
BBB category
DD-01
+
−
−
−
+
+
−
−
−
−
−
−
+
+
−
−
−
+
+
+
−
+
+
High
High
Low
Low
Low
Low
Low
Low
Low
Low
Low
Low
Low
Low
High
Low
Low
High
High
High
low
5.447
5.606
5.620
5.620
5.145
5.145
5.715
5.715
5.915
5.915
5.793
5.793
5.737
5.737
5.904
5.985
5.985
5.65
Medium
Low
Yes
Yes
No
−0.2858
−0.6993
−0.8803
−0.8803
−0.5687
−0.5687
−1.2720
−1.2720
−1.3810
−1.3810
−1.5030
−1.5030
−0.9135
−0.9135
−0.7201
−0.9973
−0.9973
−0.6184
−0.4444
−0.4444
−0.4697
−0.2397
−0.2397
−
−
−
−
−
−
−
−
−
−
−
−
−
−
−
−
−
−
−
−
−
−
−
DD-02
DD-03R
DD-03S
DD-04R
DD-04S
DD-05R
DD-05S
DD-06R
DD-06S
DD-07R
DD-07S
DD-08R
DD-08S
DD-09
Low
Low
No
Low
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Low
Low
Low
Low
Low
Low
Low
Low
Low
High
DD-10R
DD-10S
DD-11
Low
Low
Medium
Medium
Medium
Low
DD-12A
DD-12B
DD-13
5.896
5.852
6.118
5.675
5.675
No
Yes
No
DD-14R
DD-14S
High
High
Medium
Medium
No
HIA: “+” indicates absorption ≥ 30% and “−” absorption < 30%
PPB90: “Low” denotes < 90% and “high” ≥ 90% of the compound bound to plasma protein
D6 affinity: “Low” refers to a pKi < 5, “medium” a pKi in the range 5–6, “high” in the range 6–7, and “very
2
high” > 7
BBB category: “+” means a ratio ≥ −0.5 and “−” a ratio < −0.5
HIA human intestinal absorption, PPB90 plasma protein binding (90% threshold), 2C9 pKi cytochrome P450
CYP2C9 affinity, 2D6 cytochrome P450 CYP2D6 affinity, P-gp P-glycoprotein substrate, BBB log([brain]:
[blood]) blood–brain barrier penetration, BBB category blood–brain barrier penetration category

Medicinal Chemistry Research
Table 4 Properties of toxicity evaluated by using the Derek Nexus
Table 5 Structure of the synthesized phthalamides and analyzed in the
module with StarDrop software
molecular approach with the angiotensin-I-converting enzyme
Nomenclature
DD-01
Structure
Carcinogenicity, irritation of the skin, phototoxicity, kidney
function-related toxicity, photocarcinogenicity, lachrymation,
cholinesterase inhibition, nephrotoxicity, chromosome damage
in vitro, anaphylaxis, neurotoxicity, ocular toxicity, chromosome
damage in vivo, blood in urine, adrenal gland toxicity, pulmonary
toxicity, photo-induced chromosome damage in vitro, cerebral
edema, bladder disorders, splenotoxicity, mutagenicity in vitro,
chloracne, bladder urothelial hyperplasia, thyroid toxicity,
mutagenicity in vivo, cyanide-type effects, bone marrow toxicity,
urolithiasis, photomutagenicity in vitro, high acute toxicity,
cumulative effect on white cell count and immunology,
developmental toxicity, nonspecific genotoxicity in vitro,
methaemoglobinaemia, bradycardia, teratogenicity, nonspecific
genotoxicity in vivo, mitochondrial dysfunction, cardiotoxicity,
testicular toxicity, photo-induced nonspecific genotoxicity
in vitro, uncoupler of oxidative phosphorylation, HERG channel
inhibition in vitro, occupational asthma, photo-induced
DD-13
nonspecific genotoxicity in vivo, oestrogenicity, hepatotoxicity,
respiratory sensitization, eye irritation, peroxisome proliferation,
alpha-2-mu-globulin nephropathy, photoallergenicity, irritation of
the gastrointestinal tract, phospholipidosis, kidney disorders, skin
sensitization, irritation of the respiratory tract.
DD-14S
DD-05R/S, DD-06R/S, DD-12A, DD-12B, and others,
except those molecules selected (DD-01, DD-13, and DD-
1
4S).
As can be appreciated, theoretical analysis is a vital tool
for drug discovery. Three molecules were chosen in
accordance with the best corresponding scores obtained in
the in silico study (docking, physicochemical properties,
ADME profile, and toxicity parameters) (see Table 5),
which indicated a high probability of producing the best
effect in vivo. The next step was the examination of the
binding mode of the three molecules chosen (Table 5) and
also the references molecules with the ACE.
The main amino-acid residues involved in ligand-ACE
recognition for the test compounds and some reference
drugs were identified (Table 6). Some amino-acid residues
are the same for the phthalamides and the reference drugs
like Lys511, His353, Tyr523, His387, and the Zinc atom
It can be concluded that the binding site for the three
selected phthalamides is the catalytic active site of ACE. In
addition, the principal interactions between these phthala-
mides and ACE are very similar to those described for the
reference molecules. All the information above allowed us
to select three molecules for the synthesis, since these
molecules may act as good inhibitors, and estimate their
lethal doses 50.
Chemical characterization
N,N’-bis(2-phenylethyl)phthalamide (DD-01)
(
Zn701), and also the kind of interaction are shown in
Table 7, as well as the binding distances. Thee residues are
very important for the inhibition of ACE (Natesh et al.
A white solid was obtained in 90% yield; mp 167–168 °C;
1
H NMR (CDCl , 300 MHz) δ 2.89 (4H, t, H-10,10’), 3.62
3
2
003). The binding mode with ACE turned out to be very
similar for the three selected test compounds and lisinopril
Fig. 1). Moreover, these test compounds and the reference
(4H, c, H-9,9’), 6.79 (2H, s, NH), 7.24 (6H, m, H-
12,12’,14,14’,16,16’), 7.29 (4H, m, H-13,13’,15,15’), 7.39
1
3
(
(2H, m, H-4,5), 7.46 (2H, m, H-3,6); C NMR (CDCl , 75
3
drugs (benazepril, captopril, enalapril, and lisinopril)
exhibited the same pattern in relation to the binding dis-
tances with the amino-acid residues of the enzyme (Figs. 2
and 3). The validation of the molecular docking was per-
formed by comparison of docked and crystallographic lisi-
nopril, obtaining the same pattern of interaction with the
receptor for both molecules (Fig. 1d).
MHz) δ 134.6 (C-1,2), 128.4 (C-3,6), 130.1 (C-4,5), 169.1
(C-7,8), 41.3 (C-9,9’), 36.5 (C-10,10’), 138.6 (C-11,11’),
128.6 (C-12,12’,16,16’), 128.7 (C-13,13’,15,15’), 126.5 (C-
14,14’). IR (ATR, cm ) ύ: 3254 (N-H), 3076 (C-H,
Aromatic), 2929 (C-H, Aliphatic), 1626 (C=O), 1575
−
1
(C=C), 1442 (CH ), 1313 (C-N). MS (m/z): 395.1713 (M
2
+Na).

Medicinal Chemistry Research
Table 6 Amino-acid residues involved in the interaction between angiotensin-I-converting enzyme of human and the ligands: phthalamides and
reference molecules
Ligand
Residues
DD-01
Zn701, Lys511, His353, Tyr523, His387, Tyr520, His513, Ser513, Glu384, Ala354, Phe457, Glu162, Glu411, His383, Val380
Zn701, Lys511, Tyr523, Tyr520, Phe457, His387, His383, His353, Ala354, Ser355, Glu384, Glu162
Zn701, Lys511, His353, Tyr523, Glu384, His383, Glu162, Phe457, Gln281, Trp279, Tyr520, His513
Zn701, Lys511, His353, Tyr523, Glu384, Ser355, His387, Ala354, His513, Tyr520, Glu162, Gln281
Zn701, Lys511, Tyr523, Gly200, Glu384, Tyr520, His513, Gln281, Phe457
DD-13
DD-14S
Benazepril
Captopril
Enalapril
Lisinopril
Zn701, Lys511, His353, Tyr523, Glu384, Ala356, His387, Glu411, Val518, His513, Tyr520, Phe512, Phe457, Gln281
Zn701, Lys511, His353, Tyr523, His387, Glu384, Arg522, Glu411, His383, Ala354, Tyr520, His513, Phe512, Gln281
Table 7 Binding distances
between amino-acid residues
involved in the interaction and
the selected ligands
Ligand
DD-01
Interactions
4 H-bond:
5 π-π interactions:
His387:C----C:DD-01 to 4.34 Å
His383:C----C:DD-01 to 5.59 Å
His353:C----C:DD-01 to 3.94 Å
Phe457:C----C:DD-01 to 5.27 Å
Tyr523:C----C:DD-01 to 3.32 Å
1 π-cation interactions:
Tyr520:H----O:DD-01 to 1.92 Å
His353:H----O:DD-01 to 2.09 Å
His513:H----O:DD-01 to 2.37 Å
Lys511:H----O:DD-01 to 1.72 Å
2
Hydrophobic interactions:
Val380:C----C:DD-01 to 5.44 Å
Ala354:C----C:DD-01 to 4.61 Å
Zn701:Zn----C:DD-01 to 3.07 Å
2
π-anion interactions:
Glu411:O----C:DD-01 to 4.69 Å
Glu162:O----C:DD-01 to 3.07 Å
3 H-bond:
DD-13
3 π-π interactions:
His383:C----C:DD-13 to 5.67 Å
Phe457:C----C:DD-13 to 4.97 Å
Tyr523:C----C:DD-13 to 3.51 Å
Tyr520:H----O:DD-13 to 1.99 Å
His353:H----O:DD-13 to 2.47 Å
Lys511:H----O:DD-13 to 1.84 Å
3
Hydrophobic interactions:
1 π-cation interactions:
Ala354:C----C:DD-13 to 5.02 Å
His387:C----C:DD-13 to 3.75 Å
Ser355:C----C:DD-13 to 3.36 Å
Zn701:Zn----C:DD-13 to 3.38 Å
2
π-anion interactions:
Glu384:O----C:DD-13 to 3.53 Å
Glu162:O----C:DD-13 to 4.61 Å
4 H-bond:
DD-14S
4 π-π interactions:
His383:C----C:DD-14S to 5.71 Å
His353:C----C:DD-14S to 3.68 Å
Phe457:C----C:DD-14S to 4.93 Å
Tyr523:C----C:DD-14S to 3.35 Å
Tyr520:H----O:DD-14S to 2.16 Å
Gln281:H----O:DD-14S to 2.15 Å
His513:H----O:DD-14S to 2.05 Å
Lys511:H----O:DD-14S to 1.81 Å
1
Hydrophobic interaction:
Trp279:C----C:DD-14S to 3.58 Å
π-anion interactions:
1 π-cation interactions:
Zn701:Zn----C:DD-14S to 2.33 Å
2
Glu384:O----C:DD-14S to 4.68 Å
Glu162:O----C:DD-14S to 2.88 Å

Medicinal Chemistry Research
Fig. 1 Binding mode of the ligands in the catalytic active site of the
human ACE established by molecular docking: a Binding site of DD-
lisinopril (fuchsia); c binding site of DD-14S and lisinopril (fuchsia);
c’ a similar binding mode was observed for DD-14S and lisinopril
(fuchsia); d reproduction of the binding mode of lisinopril obtained by
molecular docking (fuchsia) and by crystal structure (ocher; PDB code
1O86) (color figure online)
0
1 and lisinopril (fuchsia); a’ the binding mode of DD-01 was similar
to that of lisinopril (fuchsia); b binding site of DD-13 and lisinopril
fuchsia); b’ a similar binding mode was found for DD-13 and
(
N,N’-bis[2-(3,4-dimethoxyphenyl)ethyl]phthalamide (DD-13)
(6H, s, H-18,18’), 5.28 (2H, s, NH), 6.77 (6H, m, H-
1
2,12’,15,15’,16,16’), 7.41 (2H, m, H-3,6), 7.45 (2H, m, H-
1
3
The procedure gave a white solid in 92% yield; mp 147–
4,5); C NMR (CDCl , 75 MHz) δ 134.71 (C-1,2), 128.15
3
1
1
48 °C; H NMR (CDCl , 300 MHz) δ 2.83 (4H, t, H-
(C-3,6), 130.19 (C-4,5), 169.14 (C-7,8), 41.56 (C-9,9’),
3
1
0,10’), 3.61 (4H, dd, H-9,9’), 3.83 (6H, s, H-17,17’), 3.84
35.11 (C-10,10’), 131.11 (C-11,11’), 111.30 (C-12,12’),

Medicinal Chemistry Research
Fig. 2 Binding mode and main amino-acid residues in the catalytic
active site of the human ACE when interacting with the ligands
amino-acid residues interacting with DD-13; c binding site of DD-14S;
c’ amino-acid residues interacting with DD-14S; d binding mode of
DD-01 (fuchsia), DD-13 (green), and DD-14S (yellow), each with
great similarity to the others (color figure online)
(
observed by docking simulation): a Binding site of DD-01; a’) amino-
acid residues interacting with DD-01; b binding site of DD-13; b’
1
1
48.94 (C-13,13’), 147.64 (C-14,14’), 111.87 (C-15,15’),
20.62 (C-16,16’), 55.84 (C-17,17’), 55.87 (C-18,18’). IR
N,N’-bis[(1S)-1-phenylethyl)phthalamide (DD-14S)
−
1
(
ATR, cm ) ύ: 3238 (N-H), 3083 (C-H, Aromatic), 2928
The procedure afforded a white solid in 89% yield; mp 218–
1
(
C-H, Aliphatic), 2836 (O-CH , Aliphatic), 1618 (C=O),
219 °C; H NMR (CDCl , 300 MHz) δ 1.37 (6H, d, H-
3
3
1
590 (C=C), 1453 (CH ), 1262 (C-N), 1239 (O-CH ). MS
10,10’), 5.05 (1H, q, H-9,9’), 7.20 (2H, m, H-3,6), 7.27
2
3
(
m/z): 515.2083 (M+Na).
(4H, m, H-13,13’,15,15’), 7.35 (4H, m, H-12,12’,16,16’),

Medicinal Chemistry Research
Fig. 3 Binding mode and main amino-acid residues in the catalytic
active site of the human ACE when interacting with the reference
drugs (observed by docking simulation): a Binding site of benazepril;
a’ amino-acid residues interacting with benazepril; b binding site of
captopril; b’ amino-acid residues interacting with captopril; c binding
site of enalapril; c’ amino-acid residues interacting with enalapril; d
binding site of lisinopril; d’ amino-acid residues interacting with
lisinopril
7
.45 (2H, m, H-14,14’), 7.46 (2H, m, H-4,5), 8.71 (2H, d,
Aliphatic), 1624 (C=O), 1542 (C=C), 1450 (CH ), 1332
(C-N). MS (m/z): 395.1719 (M+Na).
2
1
3
NH); C NMR (CDCl , 75 MHz) δ 136.6 (C-1,2), 126.9
3
(
(
1
C-3,6), 129.6 (C-4,5), 167.7 (C-7,8), 48.7 (C-9,9’), 22.9
Three phthalamide derivate of phenylethylamines were
synthesized based on the green chemistry principles
(Scheme 2). This strategy incorporates almost all reagents
with good yield in very short times (10–15 min) without any
C-10,10’), 145.0 (C-11,11’), 126.4 (C-12,12’,16,16’),
−1
28.6 (C-13,13’,15,15’), 128.1 (C-14,14’). IR (ATR, cm )
ύ: 3291 (N-H), 3029 (C-H, Aromatic), 2976 (C-H,

Medicinal Chemistry Research
R4
R3
R2
(CH2)n
HN
O
R1
R2
R3
Melting point
00-180 °c
O
O
O
H N
2
+
1
R1 (CH2)n
R6
R1
O
HN
(CH2)n
R2
R3
R4
Scheme 2 The synthetic route under solventless conditions for the three molecules selected based on their favorable properties
solvent or catalytic reagent, with this technique we can be
synthesizing up to 5 g each time, and also the purification is
easy just basic water and ethyl acetate. Our new technique
allows complying with at least nine principles of green
chemistry using just the melting point of the reagents.
activity (Herichova and Szantoova 2013). However,
excessive activity of Ang II has been implicated in hyper-
tension and cardiovascular disease.
Ang II elevates BP through several pathways, the most
important ones being vasoconstriction, sympathetic stimu-
lation, and increased aldosterone biosynthesis and renal
activity (Fyhrquist et al. 1995). Consequently, hypertension
is commonly controlled by inhibiting the synthesis of this
peptide. Indeed, the first-line drugs for the control of
hypertension are ACEis and Ang II receptor blockers.
ACEis decrease BP by preventing smooth muscle con-
striction in the vasculature and by reducing the release of
aldosterone. Nevertheless, the recommendation has been
made to use a different pathway that can enhance the
activity of ACE/Ang (1–7)/MasR axis (Maia et al. 2004).
Based on the molecular docking results, the theoretical
assessment of the physicochemical properties, and the
determination of the ADME profile of the three molecules
synthesized, the one with the best properties (DD-01) was
selected. Thus, an in vivo evaluation of DD-01 and capto-
pril (as the reference drug) was carried out with the SHR
model. Compared with the normotensive control group
(WKY + VEH), the hypertensive control group (SHR +
VEH) exhibited higher SBP (Fig. 4), DBP (Fig. 5) and
MAP (Fig. 6). DD-01 (10 mg/kg) significantly diminished
all three parameters as of week 1 of treatment and for the
subsequent 3 weeks. Captopril (40 mg/kg) presented the
same pattern. The mol to mol comparison of both molecules
LD50 on mice
Acute toxicity of the three synthesized compounds was
assessed by the LD50 on CD1 male mice by following
Lorke’s method. The LD50 for all compounds was >1600
mg/kg, which represents >160 times the dose used for the
in vivo experiment. Hence, phthalic derivatives can be
proposed for continued research on their potential as drugs
with low toxicity and a potent antihypertensive effect.
In vivo evaluation
The SHR is the most common model for testing hyperten-
sion. Although the physiopathology of the increase in BP in
these rats is still undefined, some evidence suggests that
Ang II plays an essential role (Sueta et al. 2014). The RAS
comprises systemic and local activity in several tissues such
as the heart, lung, adrenal gland, kidney, blood vessels, and
brain. The complex mechanisms of RAS activate several
functions after ACE catalyzes Ang I to form Ang II. The
interaction of Ang II with the AT receptor triggers vaso-
1
constrictor, trophic, proliferative and pro-thrombotic

Medicinal Chemistry Research
Fig. 4 Effect of DD-01 on the systolic blood pressure of male spon-
taneously hypertensive rats (SHRs). *Significant difference versus the
SHR group treated with the vehicle (SHR + VEH). Data are expressed
as the mean ± SEM (n ≥ 4). Repeated-measures analysis of variance
Fig. 6 Effect of DD-01 on the mean arterial pressure of male spon-
taneously hypertensive rats (SHRs). *Significant difference versus the
SHR group treated with the vehicle (SHR + VEH). Data are expressed
as the mean ± SEM (n ≥ 4). Repeated-measures analysis of variance
(
RM-ANOVA) and the Bonferroni post-test were used for evaluating
(RM-ANOVA) and the Bonferroni post-test were used for evaluating
statistical significance (p < 0.05)
statistical significance (p < 0.05)
Conclusions
The design of new molecules with potential action on ACE
is a worthwhile strategy to find alternative treatments for
hypertension, especially if green chemistry is involved in
their synthesis. Three molecules were herein selected by in
silico analysis of their physicochemical properties, Gibbs
free energy, and ADME profile. Their structures were
confirmed by all spectrometry and spectroscopy methods.
After finding low toxicity for these selected molecules, one
was chosen for testing on the SHR model. It exhibited an
effect similar to that of captopril but is ∼7-fold more potent.
Therefore, we propose further studies to explore the inhi-
bitory activity of this and related phthalimide derivatives.
Fig. 5 Effect of DD-01 on the diastolic blood pressure of male
spontaneously hypertensive rats (SHRs). *Significant difference versus
the SHR group treated with the vehicle (SHR + VEH). Data are
expressed as the mean ± SEM (n ≥ 4). Repeated-measures analysis of
variance (RM-ANOVA) and the Bonferroni post-test were used for
evaluating statistical significance (p < 0.05)
Acknowledgements EA-J is a postdoctoral fellow from CONACYT.
This work was supported by PAPIIT IN223519 (to RV-M), PAPIIT
IN226819 (to IAGO) DGAPA from the UNAM, by SIP (m1930 and
20194934) from the Instituto Politécnico Nacional, and by CONACYT-
Mexico. We also thank MVZ L. Flores, MD. F. Barrón-Moreno, and
Biol. TE Villamar-Duque from FES Iztacala, UNAM, for their aid in
animal care and housing.
revealed that DD-01 is 6.85-fold more potent than captopril.
These two compounds produce an equivalent effect.
However, the normotensive values of the WKY + VEH
group were not reached by either captopril or DD-01. These
findings concur with those of other studies reporting a
decrease of 40–50% in BP after ACEi monotherapy. ACEis
administered in combination with diuretics or calcium
antagonists reduced BP by 80–90% (Cheung et al. 2009).
According to some researchers, the relatively low efficacy
of ACEis in diminishing BP implies that chymase is the
primary enzyme involved in forming Ang II from Ang I in
humans (Dell’Italia and Husain 2002). Although the inhi-
bition of chymase limits the synthesis of Ang II, it does not
control BP in the short term, possibly because chymase
inhibitors, unlike ACEis, only decrease Ang II locally and
not systemically (Roszkowska-Chojecka et al. 2015).
Compliance with ethical standards
Conflict of interest The authors declare that they have no conflict of
interest.
Publisher’s note: Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional affiliations.
References
Abdel-Rahman RF, Hessin AF, Abdelbaset M, Ogaly HA, Abd-
Elsalam RM, Hassan SM (2017) Antihypertensive effects of
Roselle-Olive combination in L-NAME-induced hypertensive
rats. Oxid Med Cell Longev 2017:1–24. https://doi.org/10.1155/
2
017/9460653

Medicinal Chemistry Research
Alanazi AM, El-Azab AS, Al-Suwaidan Ia, ElTahir KEH, Asiri Ya,
Abdel-Aziz NI, Abdel-Aziz Aa-M (2015) Structure-based design
of phthalimide derivatives as potential cyclooxygenase-2 (COX-
Herichova I, Szantoova K (2013) Renin-angiotensin system: upgrade
of recent knowledge and perspectives. Endocr Regul 47:39–52.
https://doi.org/10.4149/endo_2013_01_39
2
) inhibitors: anti-inflammatory and analgesic activities. Eur J
Med Chem 92:115–123. https://doi.org/10.1016/j.ejmech.2014.
2.039
Humphrey W, Dalke A, Schulten K (1996) VMD: visual molecular
dynamics. J Mol Graph 14:33–38. https://doi.org/10.1016/0263-
7855(96)00018-5
1
Aliabadi AR, Foroumadi AR, Mohammadi-Farani A, Garmsiri Mahvar
M (2013) Synthesis and evaluation of anti-acetylcholinesterase
activity of 2-(2-(4-(2-oxo-2-phenylethyl)piperazin-1-yl)ethyl)iso-
indoline-1,3-dione derivatives with potential anti-Alzheimer
effects. Iran J Basic Med Sci 16:1049–1054
Andrade-Jorge E, Sánchez-Labastida LA, Soriano-Ursúa MA,
Guevara-Salazar JA, Trujillo-Ferrara JG (2018) Isoindolines/iso-
indoline-1,3-diones as AChE inhibitors against Alzheimer’s dis-
ease, evaluated by an improved ultra-micro assay. Med Chem Res
Jan Danser AH, Batenburg WW, van Esch JHM (2007) Prorenin and
the (pro)renin receptor–an update. Nephrol Dial Transplant
22:1288–1292. https://doi.org/10.1093/ndt/gfl846
Jenis J, Kim JY, Uddin Z, Song YH, Lee H-H, Park KH (2017)
Phytochemical profile and angiotensin I converting enzyme
(ACE) inhibitory activity of Limonium michelsonii Lincz. J Nat
Med 71:650–658. https://doi.org/10.1007/s11418-017-1095-4
Li J, Li Q, Li J, Zhou B (2014) Peptides derived from Rhopilema
esculentum hydrolysate exhibit angiotensin converting enzyme
(ACE) inhibitory and antioxidant abilities. Molecules 19:13587–
13602. https://doi.org/10.3390/molecules190913587
Lin JH, Yamazaki M (2003) Role of P-glycoprotein in pharmacoki-
netics: clinical implications. Clin Pharmacokinet 42:59–98
Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (1997) Experi-
mental and computational approaches to estimate solubility and
permeability in drug discovery and development settings. Adv
Drug Deliv Rev 23:3–25. https://doi.org/10.1016/S0169-409X
(00)00129-0
Lloyd-Jones DM, Morris PB, Ballantyne CM, Birtcher KK, Daly DD,
DePalma SM, Minissian MB, Orringer CE, Smith SC (2017)
2017 Focused update of the 2016 ACC expert consensus decision
pathway on the role of non-statin therapies for LDL-cholesterol
lowering in the management of atherosclerotic cardiovascular
disease risk: a report of the American College of Cardiology Task
Fo. J Am Coll Cardiol 70:1785–1822. https://doi.org/10.1016/j.ja
cc.2017.07.745
Lorke D (1983) A new approach to practical acute toxicity testing.
Arch Toxicol 54:275–287. https://doi.org/10.1007/BF01234480
Luo J, Zhang C, Liu Q, Ou S, Zhang L, Peng X (2017) Combinative
effect of sardine peptides and quercetin alleviates hypertension
through inhibition of angiotensin I converting enzyme activity
and inflammation. Food Res Int 100:579–585. https://doi.org/10.
1016/j.foodres.2017.07.019
2
7:2187–2198. https://doi.org/10.1007/s00044-018-2226-5
Ben Salah B, Hamzaoui S, Krichen F, Saadaoui I, Ben Mansour R,
Miled N, Bougatef A, Kossentini M (2018) Design, synthesis of
novel triazolones and bis-triazolones derivatives under ultrasound
irradiation and evaluation as potent angiotensin converting
enzyme (ACE) inhibitors. Bioorg Chem 76:147–153. https://doi.
org/10.1016/j.bioorg.2017.11.004
Bloch MJ (2016) Worldwide prevalence of hypertension exceeds 1.3
billion. J Am Soc Hypertens 10:753–754. https://doi.org/10.1016/
j.jash.2016.08.006
Campos-nonato I, Hernández-barrera L (2018) Hipertensión arterial en
adultos mexicanos: prevalencia, diagnóstico y tipo de tratamiento.
Ensanut MC 2016 60:233–243
Cheung IWY, Nakayama S, Hsu MNK, Samaranayaka AGP, Li-Chan
ECY (2009) Angiotensin-I converting enzyme inhibitory activity
of hydrolysates from oat (Avena sativa) proteins by in silico and
in vitro analyses. J Agric Food Chem 57:9234–9242. https://doi.
org/10.1021/jf9018245
Chinedu E, Arome D, Ameh F (2013) A new method for determining
acute toxicity in animal models. Toxicol Int 20:224. https://doi.
org/10.4103/0971-6580.121674
Dell’Italia LJ, Husain A (2002) Dissecting the role of chymase in
angiotensin II formation and heart and blood vessel diseases. Curr
Opin Cardiol 17:374–379
Fienberg S, Cozier GE, Acharya KR, Chibale K, Sturrock ED (2018)
The design and development of a potent and selective novel
diprolyl derivative that binds to the N-domain of angiotensin-I
converting enzyme. J Med Chem 61:344–359. https://doi.org/10.
Lv Y, Li Y, Yi Y, Zhang L, Shi Q, Yang J, Lv Y, Li Y, Yi Y, Zhang L,
Shi Q, Yang J (2018) A genomic survey of angiotensin-
converting enzymes provides novel insights into their molecular
evolution in vertebrates. Molecules 23:2923. https://doi.org/10.
3390/molecules23112923
Magvanjav O, Cooper-DeHoff RM, McDonough CW, Gong Y, Segal
MS, Hogan WR, Johnson JA (2018) Antihypertensive therapy
prescribing patterns and correlates of blood pressure control
among hypertensive patients with chronic kidney disease. J Clin
Hypertens. https://doi.org/10.1111/jch.13429
Maia LG, Ramos MC, Fernandes L, de Carvalho MHC, Campagnole-
Santos MJ, Dos Santos RAS, Souza dos Santos RA (2004)
Angiotensin-(1-7) antagonist A-779 attenuates the potentiation of
bradykinin by captopril in rats. J Cardiovasc Pharmacol 43:685–
691. https://doi.org/10.1097/00005344-200405000-00011
Molinspiration Cheminformatics (2016) Calculation of molecular
properties and bioactivity score. Molinspiration.com
Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Belew RK,
Olson AJ (1998) Automated docking using a Lamarckian genetic
algorithm and an empirical binding free energy function J
Comput Chem 19:1639–1662. https://doi.org/10.1002/(SICI)
1096-987X(19981115)19:14<1639::AID-JCC10>3.0.CO;2-B
Morris GM, Ruth H, Lindstrom W, Sanner MF, Belew RK, Goodsell
DS, Olson AJ (2009) AutoDock4 and AutoDockTools4: auto-
mated docking with selective receptor flexibility. J Comput Chem
30:2785–2791. https://doi.org/10.1002/jcc.21256
1
021/acs.jmedchem.7b01478
Forli S, Huey R, Pique ME, Sanner MF, Goodsell DS, Olson AJ
2016) Computational protein-ligand docking and virtual drug
(
screening with the AutoDock suite. Nat Protoc 11:905–919
Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA,
Cheeseman JR, Scalmani G, Barone V, Mennucci B, Petersson
GA, Nakatsuji H, Caricato M, Li X, Hratchian HP, Izmaylov AF,
Bloino J, Zheng G, Sonnenberg JL, Hada M, Ehara M, Toyota K,
Fukuda R, Hasegawa J. et al. (2009) Gaussian 09, Revision E. 01;
Gaussian Inc., Wallingford CT (software)
Fu Y, Young JF, Rasmussen MK, Dalsgaard TK, Lametsch R, Aluko
RE, Therkildsen M (2016) Angiotensin I–converting enzyme–
inhibitory peptides from bovine collagen: insights into inhibitory
mechanism and transepithelial transport. Food Res Int 89:373–
3
81. https://doi.org/10.1016/j.foodres.2016.08.037
Fyhrquist F, Metsärinne K, Tikkanen I (1995) Role of angiotensin II in
blood pressure regulation and in the pathophysiology of cardio-
vascular disorders J Hum Hypertens 9(Suppl 5):S19–S24
Grootaert C, Matthijs B, Voorspoels S, Possemiers S, Smagghe G,
Van Camp J (2017) Egg-derived bioactive peptides with ACE-
inhibitory properties: a literature update. Food Funct 8:3847–
3
855

Medicinal Chemistry Research
Natesh R, Schwager SLU, Sturrock ED, Acharya KR (2003) Crystal
structure of the human angiotensin-converting enzyme–lisinopril
complex. Nature 421:551–554. https://doi.org/10.1038/nature01370
Nawaz KAAA, David SM, Murugesh E, Thandeeswaran M, Kiran KG,
Mahendran R, Palaniswamy M, Angayarkanni J (2017) Identification
and in silico characterization of a novel peptide inhibitor of angio-
tensin converting enzyme from pigeon pea (Cajanus cajan). Phyto-
medicine 36:1–7. https://doi.org/10.1016/j.phymed.2017.09.013
Paiva L, Lima E, Neto AI, Baptista J (2017) Angiotensin I-converting
enzyme (ACE) inhibitory activity, antioxidant properties, phe-
nolic content and amino acid profiles of fucus spiralis L. Protein
hydrolysate fractions. Mar Drugs 15:1DUMMY. https://doi.org/
function and vascular senescence in aged spontaneously hyperten-
sive rats are ameliorated by angiotensin blockade. Atherosclerosis
236:101–107. https://doi.org/10.1016/j.atherosclerosis.2014.06.016
Tai H-M, Li C-C, Hung C-Y, Yin L-J (2018) Production of functional
peptides with inhibition ability against angiotensin I-Converting
enzyme using P. pastoris expression system. J Food Drug Anal
26:1097–1104. https://doi.org/10.1016/j.jfda.2018.02.001
Te Riet L, Van Esch JHM, Roks AJM, Van Den Meiracker AH,
Danser AHHJ (2015) Hypertension: renin-angiotensin-
aldosterone system alterations. Circ Res 116:960–975
Van Booven D, Marsh S, McLeod H, Carrillo MW, Sangkuhl K, Klein
TE, Altman RB (2010) Cytochrome P450 2C9-CYP2C9. Pharm
Genom 20:1. https://doi.org/10.1097/FPC.0b013e3283349e84
Vildmyren I, Drotningsvik A, Oterhals Å, Ween O, Halstensen A,
Gudbrandsen OA, Vildmyren I, Drotningsvik A, Oterhals Å,
Ween O, Halstensen A, Gudbrandsen OA (2018) Cod residual
protein prevented blood pressure increase in Zucker fa/fa rats,
possibly by inhibiting activities of angiotensin-converting
enzyme and renin. Nutrients 10:1820. https://doi.org/10.3390/
nu10121820
Wang B, Yang L-P, Zhang X-Z, Huang S-Q, Bartlam M, Zhou S-F
(2009) New insights into the structural characteristics and functional
relevance of the human cytochrome P450 2D6 enzyme. Drug Metab
Rev 41:573–643. https://doi.org/10.1080/03602530903118729
WHO (2013) World Health Day 2013 - Hypertension. A Glob Br
Hypertens 9. https://doi.org/10.1136/bmj.1.4815.882-a
Xu F, Chen H, Xu J, Liang X, He X, Shao B, Sun X, Li B, Deng X,
Yuan M (2015) Synthesis, structure-activity relationship and
biological evaluation of novel arylpiperzines as α1A/1D-AR
subselective antagonists for BPH. Bioorganic. Med Chem
23:7735–7742. https://doi.org/10.1016/j.bmc.2015.11.020
Yu F, Zhang Z, Luo L, Zhu J, Huang F, Yang Z, Tang Y, Ding G, Yu
F, Zhang Z, Luo L, Zhu J, Huang F, Yang Z, Tang Y, Ding G
(2018) Identification and molecular docking study of a novel
angiotensin-I converting enzyme inhibitory peptide derived from
enzymatic hydrolysates of Cyclina sinensis. Mar Drugs 16:411.
https://doi.org/10.3390/md16110411
1
0.3390/md15100311
Parish RC, Miller LJ (1992) Adverse effects of angiotensin converting
enzyme (ACE) inhibitors. Drug Saf 7:14–31. https://doi.org/10.
2
165/00002018-199207010-00004
Roszkowska-Chojecka MM, Walkowska A, Gawryś O, Baranowska I,
Kalisz M, Litwiniuk A, Martyńska L, Kompanowska-Jezierska E
(
2015) Effects of chymostatin, a chymase inhibitor, on blood
pressure, plasma and tissue angiotensin II, renal haemodynamics
and renal excretion in two models of hypertension in the rat. Exp
Physiol 100:1093–1105. https://doi.org/10.1113/EP085325
Shen JI, Saxena AB, Montez-Rath ME, Leng L, Chang TI, Winkel-
mayer WC (2017) Comparative effectiveness of angiotensin
receptor blockers vs. angiotensin-converting enzyme inhibitors on
cardiovascular outcomes in patients initiating peritoneal dialysis. J
Nephrol 30:281–288. https://doi.org/10.1007/s40620-016-0340-3
Si W, Zhang T, Zhang L, Mei X, Dong M, Zhang K, Ning J (2016)
Design, synthesis and bioactivity of novel phthalimide derivatives
as acetylcholinesterase inhibitors. Bioorg Med Chem Lett
2
6:2380–2382. https://doi.org/10.1016/j.bmcl.2015.07.052
Sparks MA, Crowley SD, Gurley SB, Mirotsou M, Coffman TM,
Carolina N (2015) NIH public access. Compr Physiol 4:1201–
1
228. https://doi.org/10.1002/cphy.c130040.Classical
Sueta D, Koibuchi N, Hasegawa Y, Toyama K, Uekawa K, Katayama T,
Ma MJ, Nakagawa T, Waki H, Maeda M, Ogawa H, Kim-
Mitsuyama S (2014) Blood pressure variability, impaired autonomic