ArticlePDF Available

Russian Text © The Author(s), 2022, published in Vestnik Moskovskogo Universiteta

Authors:
  • the research center at Poursina Hakim Digestive Disease Research Center (PDDRC)

Abstract

It was the aim of this study to develop Cyclosaplin analogues and assess the anticancer effects of those peptide analogues on both MDA-MB-231 and K562 cell lines. The analogues of Cyclosaplin peptide (Cyclosaplin-2A and Cyclosaplin-7G) were designed and then investigated by online web server predictor AntiCP. The peptide analogues were applied to MDA-MB-231 and K562 cells in various concentrations and for various periods of time. The anticancer potential was confirmed by the MTT assay. Haemolytic activity also was assessed. In order to investigate the apoptotic effects of peptides on cancer cells, different tests such as morphological examination, Giemsa test, and DNA fragmentation were performed. Lactate dehydroge-nase leakage assay was used to reject peptide-induced necrosis. As a result of computational studies, we discovered that the analogues of peptides also have anticancer properties. However, we have found through our practical research that analogues had less anticancer properties than their parent peptides. The MTT assay and morphological study confirmed the anticancer effects. For MD-AMB-231 cells, an IC 50 of Cyclosaplin-2A was 70 μg/ml, and Cyclosaplin-7G was 90 μg/ml. In addition, for K562 cells, an IC 50 of Cyclosaplin-2A was 10 μg/ml, and Cyclosaplin-7G was 15 μg/ml. Other tests also confirmed the anticancer effect of the pep-tide analogues. According to haemolytic assays, none of the peptide analogues possessed any haemolytic activity against human erythrocytes, indicating that the compounds are non-toxic to normal cells. There was evidence that peptide analogues, particularly Cyclosaplin-2A, had anticancer properties against cells derived from breast (MDA-MB-231) and blood (K562) cancers.
264
ISSN 0096-3925, Moscow University Biological Sciences Bulletin, 2022, Vol. 77, No. 4, pp. 264–271. © Allerton Press, Inc., 2022.
Russian Text © The Author(s), 2022, published in Vestnik Moskovskogo Universiteta, Seriya 16: Biologiya, 2022, Vol. 77, No. 00000, pp. 00000–00000.
Research on the Effect of Amino Acid Substitution of Cyclosaplin
Peptide in Breast Cancer Cell Line (MDA-MB-231)
and in a Human Leukemia Cell Line (K562)
P. Kadkhodaei Elyaderania,* (ORCID: 0000-0002-8502-716X), A. M. Asgharianb,
and M. Salehi c (ORCID: 0000-0002-6565-0907)
a Medical Genetics Research Center of Genome, Isfahan University of Medical Sciences, Isfahan, Iran
b Department of Cell and Molecular Biology, Tonekabon Branch, Islamic Azad University, Tonekabon, Iran
c Cellular, Molecular and Genetics Research Center, Isfahan University of Medical Sciences, 8175954319, Isfahan, Iran
* e-mail: kadkhodai23@gmail.com
Received July 11, 2022; revised November 1, 2022; accepted November 28, 2022
Abstract—It was the aim of this study to develop Cyclosaplin analogues and assess the anticancer effects of
those peptide analogues on both MDA-MB-231 and K562 cell lines. The analogues of Cyclosaplin peptide
(Cyclosaplin-2A and Cyclosaplin-7G) were designed and then investigated by online web server predictor
AntiCP. The peptide analogues were applied to MDA-MB-231 and K562 cells in various concentrations and
for various periods of time. The anticancer potential was confirmed by the MTT assay. Haemolytic activity
also was assessed. In order to investigate the apoptotic effects of peptides on cancer cells, different tests such
as morphological examination, Giemsa test, and DNA fragmentation were performed. Lactate dehydroge-
nase leakage assay was used to reject peptide-induced necrosis. As a result of computational studies, we dis-
covered that the analogues of peptides also have anticancer properties. However, we have found through our
practical research that analogues had less anticancer properties than their parent peptides. The MTT assay
and morphological study confirmed the anticancer effects. For MD-AMB-231 cells, an IC50 of Cyclosaplin-
2A was 70 μg/ml, and Cyclosaplin-7G was 90 μg/ml. In addition, for K562 cells, an IC50 of Cyclosaplin-2A
was 10 μg/ml, and Cyclosaplin-7G was 15 μg/ml. Other tests also confirmed the anticancer effect of the pep-
tide analogues. According to haemolytic assays, none of the peptide analogues possessed any haemolytic
activity against human erythrocytes, indicating that the compounds are non-toxic to normal cells. There was
evidence that peptide analogues, particularly Cyclosaplin-2A, had anticancer properties against cells derived
from breast (MDA-MB-231) and blood (K562) cancers.
Keywords: anticancer peptide, peptide analogue, Cyclosaplin, MDA-MB-231, K562, AntiCP
Abbreviations: ACP—Anticancer peptide, 2A—Cyclosaplin-2A, 7G—Cyclosaplin-7G, AntiCP—Anticancer
peptides, SVM—Support vector machine, RP-HPLC—Reversed phase high-performance liquid chromatog-
raphy, MALDI-MS—Matrix-assisted laser desorption/ionization-time of flight, NTC—No Template Con-
trol, RBC—Red blood cell, PI—Propidium iodide, LDH—Lactate dehydrogenase
DOI: 10.3103/S00963925220 40101
One of the leading causes of death worldwide has
long been cancer, which is regarded as a severe health
problem [1–3]. Cancer is the result of a mutation that
disrupts the function of proteins encoded by somatic
genes, resulting in uncontrolled cell division and inva-
sion of surrounding tissue [1, 4]. So far, various kinds
of cancer have been identified, the most common of
which are bladder, breast, colon, rectal, leukemia,
lung, lymphoma, and prostate [3, 5, 6]. A number of
factors contribute to the formation of carcinogens,
including lifestyle, chemical exposure, heredity,
genetics, immune system disorders, and environmen-
tal circumstances [4, 7]. A number of treatment meth-
ods are proposed for cancer, such as surgery, chemo-
therapy, radiation therapy, hormonal therapy, and
immunotherapy [8–10]. Each of these methods is
limited in its application, depending on the organs
involved, the stage of the disease progression, and the
patient’s medical condition [11]. Aside from that, each
of them has its own complications and defects [8, 12].
For instance, the major problem with conventional
chemotherapy is the inability to separate cancer cells
from normal cells to deliver the cytotoxic agent and kill
not only cancer cells but also normal cells [2, 13, 14].
Several disadvantages of these conventional methods
include high costs, long treatment cycles, drug resis-
tance, altered biodistribution, biotransformation, and
difficulty in eliminating chemicals from the body [14–
RESEARCH ARTICLE
MOSCOW UNIVERSITY BIOLOGICAL SCIENCES BULLETIN Vol. 77 No. 4 2022
RESEARCH ON THE EFFECT OF AMINO ACID SUBSTITUTION 265
17]. The indeterminate effect of current cancer treat-
ment methods and their complications prompted sci-
entists to find another medicine and approach more
effectively to overcome cancer [18, 19].
The discovery of anticancer peptides (ACPs), a
type of short peptides, generally has led to the emer-
gence of a novel alternative treatment for cancer with
more target-specific and fewer side effects over con-
ventional drugs of cancer therapy [16, 18, 20]. A cat-
ionic quality of ACP, due to the negative charge on
cancer cell membranes, makes them unique for bind-
ing and killing the cancer cells compared to others.
Moreover, amphipathic and hydrophobic properties
of anticancer peptides are vital for specific penetration
into cancer cell membranes. These features contribute
destabilization of the membrane integrity. Thus,
according to the specific potentials of ACPs, they can
be considered as a highlighted option for cancer treat-
ment [5, 21, 24].
Our study focused on the amino acid substitution
of an anticancer peptide with a high level of anticancer
potential to study some of its properties and develop a
novel anticancer peptide. Consequently, Cyclosaplin,
a cyclic peptide with eight amino acids, was chosen as
the framework for this study. It is a cyclic peptide that
was purified from somatic seeds of Santalum album L.
(Sandalwood) and tested and confirmed to have cyto-
toxic activity against MDA-MB-231 in a dose- and
time-dependent manner [25]. Due to the high inhibi-
tory concentration (IC50), short length, positive net
charge, several hydrophobic amino acids, herbal ori-
gin, and cyclic form of Cyclosaplin, this peptide was
considered for substitution. The study was conducted
to replace amino acids in Cyclosaplin, and the peptide
analogues were analyzed in silico by AntiCP
(webs.iiitd.edu.in/raghava/anticp/submission.php)
[13]. In order to explore the anticancer properties of
the peptide analogues experimentally, we investigated
their influence on the MDA-MB123 (breast) and
K562 (blood) cancer cell lines. According to the
Mishra et al. study [25], MDA-MB-231 cells were
selected to compare the properties of peptide ana-
logues with the parent peptide. K562 cells were also
selected for screening due to differences in appearance
and structure with MDA-MB-231 cells.
MATERIALS AND METHODS
Bioinformatic Prediction of ACP
In this study, the in silico model, AntiCP server
(webs.iiitd.edu.in/raghava/anticp/submission.php)
was used to predict ACPs before synthesis and study
on certain cancer cells [13]. For this purpose, the
Cyclosaplin sequence (RLGDGCTR) was submitted
as a framework peptide on the AntiCP website. Several
physiochemical features including charge, hydropho-
bicity, hydrophilicity, amphipathicity and molecular
weight were considered for providing the analogues.
Before running the analysis, model 1 (ACP/AMP
Dataset) was selected and the SVM threshold was set
on “zero”. Following pushing the “Run analysis” bot-
tom, the server displayed the result as “ACP” or “non-
ACP” along with the prediction score and phys-
iochemical properties selected before submission.
Finally, based on the calculated results, users can
select different mutations and prediction scores to
change the activity.
Peptide Preparation
Cyclosaplin-2A and Cyclosaplin-7G (2A and 7G)
peptides were designed and then synthesized in linear
format by TAG Copenhagen company (Denmark).
HPLC (250 × 4.6 mm C18 column) was used to purify
over 95% of the synthesized peptides. The peptides
were eluted in acetonitrile/water mixed with 0.1% tri-
fluoroacetic acid from 5 to 95% at a flow rate of
1 mL/min. The peptides were further characterized by
mass spectrometry.
Cell Cultures
MDA-MB-231, human breast cancer cells, and
K562, human leukemia cells, were provided from the
Royan Institute, Iran, Tehran in February 2018. Cells
were cultured according to the cell culture protocol
[10]. Both cell cultures were seeded in 96-well micro-
titer plates at a density of 5 × 104 cells/well.
MTT Assay and IC50 Determination of 2A and 7G
against MDA-MB-231 and K562 Cells
Cell viability count and cytotoxicity of ACPs were
performed using an MTT assay [26]. Brief ly, cells were
treated to the five concentrations (10, 15, 50, 100,
150 μg/ml in 24, 48, and 72 h) of 2A and 7G in each
plate, followed by incubation for various periods.
Plates were read at 570 nm using an ELISA analyzer
(Elisys Uno, REF 17200, Germany). The results were
expressed as IC50, representing the concentration at
which cell viability was reduced by 50%.
Determination of Cell Morphology
with Light Microscopy
5 × 104 cells/well MDA-MB-231 and K562 cells
were cultured and incubated for 24 h. Then, both cell
cultures were treated with the IC50 concentration of 2A
and 7G for 48 h. After incubation, treated and control
MDA-MB-231 and K562 cells were collected to
observe morphological changes of cells related to the
apoptotic effects under inverted microscopy (Eclipse
Ts2 , Nikon, Japan) .
266
MOSCOW UNIVERSITY BIOLOGICAL SCIENCES BULLETIN Vol. 77 No. 4 2022
ELYADERANI et al.
Giemsa Staining
Giemsa staining was also performed cytologically
to assess the apoptotic morphology to evaluate the
apoptosis of cell death in MDA-MB-231 and K562
cells. Treated and control cells were collected and
washed according to the Giemsa staining method [10].
The morphological changes of apoptosis cells were
observed by light microscopy (SC Binocular, Nikon,
Japan).
Haemolytic Assay
The haemolytic examination was aimed to assess
whether 2A and 7G caused oxidative damages to the
erythrocyte membrane or not. Erythrocyte suspension
was prepared according to the protocol [2]. The first
well served as a negative control containing only sol-
vent and the last served as a positive control containing
20 μl of 0.1% Triton X-100 in 0.85% saline. Finally,
the absorbance of the supernatant was recorded by
spectrophotometry at 560 nm (M550, UV-Vis True
Double Beam, UK). The average value was calculated
from triplicate assays.
Lactate Dehydrogenase (LDH) Leakage Assay
The growth inhibitory effects of 2A and 7G were
further investigated through LDH into the culture
medium upon damage to the plasma membrane.
Treated cells with IC50 concentration of each peptide
and without peptides (negative control) were incu-
bated for 48 hrs according to the protocol [3]. The
absorption of each well at 490 nm was measured by an
ELISA analyzer (LT-4000, Visible EuroClone, Italy).
DNA Laddering Assay
Untreated and treated with 2A and 7G cells of both
lines were extracted using a DNA extraction kit (QIA-
wave DNA Blood and Tissue Kit, Netherlands)
according to the manufacturer’s protocol. Cells’
extracted DNA along with 100 bp DNA ladder was
loaded on to 1.5% agarose gel. The gel was visualized
under the Gel Doc system to determine DNA frag-
mentation.
Statistical Analysis
Each test in th e in vitro anticancer assay was carried
out in triplicate and the results were expressed as mean
± SEM (p < 0.005). Haemolytic test analysis was car-
ried out using one-way ANOVA.
RESULTS AND DISCUSSION
The detection and development of novel ACPs
effects are extremely time-consuming and often
expensive, so computational methods are absolutely
essential before applying them clinically. As a result,
due to the importance of ACPs, we improved the qual-
ity of identification in this study using a strong AntiCP
predictor. Based on amino acid composition and
binary profiles, AntiCP develops support vector
machine models (SVMs) to predict ACPs. The design
of ACPs was mainly done by modifying the physico-
chemical properties of natural peptides; therefore, it
was expected that the designed peptides would display
new properties.
In this study, as part of the process of designing the
analogues of Cyclosaplin, much attention was paid to
physicochemical properties of the peptides such as
hydrophobicity, hydrophilicity, amphipathicity,
charge, etc. Thus, amino acid changes were performed
to alter these properties. As a result, in one analogue of
the peptide, the amino acid leucine was substituted
with an alanine (the most hydrophobic amino acids)
at position 2 (RAGDGCTR) to increase hydropho-
bicity, whereas, in another analogue, the amino acid
threonine was substituted with the amino acid glycine
(non-hydrophobic change) at position 7 (RLGDG-
CGR). In replacement of amino acids of analogues,
we expected that the properties of peptides would be
altered, especially their anticancer properties. Fur-
thermore, linear peptides were developed instead of
cyclic ones to reduce synthesis costs. All the physico-
chemical properties of the Cyclosaplin and its ana-
logues were evaluated after changing their features
(Table 1). Despite the changes made to the parent
peptide, it was found that the major physicochemical
properties of the parent peptide and its analogues were
very similar based on the results of the AntiCP predic-
tor server. However, it was not possible to conduct a
computer comparison of the anticancer properties of
peptide analogues and their parent compounds due to
software limitations.
TAGC Company in Denmark synthesized the pep-
tide analogues based on the sequences provided. Syn-
thetic peptides were purified by RP-HPLC, and their
molecular weights were confirmed by MALDI-MS.
RP-HPLC was also been used frequently to measure
hydrophobic-hydrophilic balances of amphipathic
peptides. Due to the amphipathic nature of the pep-
tide, the company suggested a 1:1 solution of water
and acetonitrile to dissolve the peptide analogues.
An MTT assay was performed on MDA-MB-231
and K562 cells to measure the cytotoxicity of 2A and
7G peptides. The results first showed that the modifi-
cations had a different effect on the anticancer activity
of the peptide analogues. Based on the MTT assay,
both peptides decreased cell viability when concentra-
tion was increased in both cells lines (Supplementary
Fig. S1). In order to evaluate the anticancer activity of
the peptide analogues, we calculated the IC50 values of
two cancer cell lines after a certain period of incuba-
tion. On MDA-MB-231 cells with a concentration of
70 μg/ml of 2A and 90 μg/ml of 7G, and with a con-
centration of 10 μg/ml of 2A and 15 μg/ml of 7G on
MOSCOW UNIVERSITY BIOLOGICAL SCIENCES BULLETIN Vol. 77 No. 4 2022
RESEARCH ON THE EFFECT OF AMINO ACID SUBSTITUTION 267
K562 cells in 48 h, less than 50% of the cells were via-
ble (±SEM, p < 0.005) (Supplementary Fig. S2).
According to the above results, after IC50 determina-
tion (the value of less than 50% viable cells), other tests
were conducted based on this level of peptide ana-
logues concentration.
On the other hand, it was observed that the parent
peptide had a greater anticancer effect than peptide
analogues on MDA-MB-231 cells [25]. On MDA-
MB -231, t he IC50 values of the parent, 2A, and 7G
peptides were equivalent to 2.06, 70, and 90 μg/ml,
respectively. 2A and 7G had much lower IC50 values
on K562 cells (2A:10 μg/ml, 7G:15 μg/ml). As a
result, the role of amino acid sequences and peptide
structures were highlighted. In various studies, it was
determined that peptide drugs have different effects on
different cancer cells depending on their structure. For
example, in the study of the effect of Buforin IIb and
cyclic iso-DGR on MBA-MB-231 cancer cells, their
IC50 was calculated as 11.3 and 212 μg/ml, respectively
[23, 25]. In other studies, on other cell lines, the effect
of Longicalycinin A peptide on HepG2 immortal
cells, IC50 was calculated as 13.52 μg/ml [25, 29]. But
in the study of the effect of Brevinin-1Ema peptide on
A498 and A549 cell lines, IC50 was calculated as 0.071
and 1.256 μg/ml, respectively, and also the effect of
Ligatoxin B peptide on U-937-GTB cell line, IC50
equal to 1.8 μg/ml was obtained [17, 25].
The morphological study was conducted by an
inverted microscope which showed many distinct
morphological changes in both 2A and 7G treated cell
lines compared to untreated cells. Apoptotic cell sig-
naling manifested itself in terms of membrane wrin-
kling, cytoplasm condensation, cell degradation
(change from a spindle or round shape to a wrinkled
shape) and slow growth and progression of cells in the
vicinity of the peptide drug. The morphological
changes demonstrated that concentration and time
were likely to affect cell morphology. Phenotypic
changes were more noticeable as peptide concentra-
tions increase over time (Supplementary Figs. S4 and
S5).
Giemsa staining was also conducted in order to
assess apoptotic morphology. In terms of apoptotic
morphology, our results were similar to those of many
other authors who used this method. The results were
consistent with Chen et al. [8] and Srinivas et al. [9]
morphological analysis of apoptotic morphology
using Giemsa staining. In treated cells as compared to
control cells, apoptotic bodies were found to show
morphological changes and high differentiation. This
included nuclei with chromatin condensation. As seen
with Giemsa staining in our finding, in MDA-MB-
231 cells treated with 70 μg/ml 2A and 90 μg/ml 7G
for 48 h and also in K562 cells treated with 10 μg/ml
2A and 15 μg/ml 7G, nuclei with chromatin conden-
sation, cell size depletion, disruption of membrane
integrity, and formation of apoptotic bodies were
detected by a light microscope (Figs. 1 and 2).
In the evaluation of cellular toxicity and drug
safety, haemolysis is often employed as a rapid
method, as confirmed by Róka et al. and Greco et al.
[29, 30]. Thus, in the present survey, an RBC hemoly-
sis test was used to determine if peptide analogues were
capable of damaging membranes. It is well-known
that erythrocytes, the most abundant cells in the
human body [12], have been widely exploited in drug
delivery. Haemolysis, the destruction of red blood
cells, also occurs much more extensively in the pres-
ence of any toxicant like Triton X-100. In our finding,
it was evaluated whether 2A and 7G could cause oxi-
dative damage to erythrocyte membranes in this
experiment. 2A and 7G peptides, Triton X-100 (posi-
tive control) and solvent (negative control) demon-
strated differential anti-haemolytic activity. The
results of the analysis of the haemolytic activity of pep-
tide analogues at their highest IC50 concentrations are
presented in Table 2. Neither 2A nor 7G peptides
exhibited potent anti-haemolytic action in a dose-
dependent manner compared to the solvent. In con-
trast, Triton X-100 as a strong haemolytic substance
illustrated most haemolytic activity (one-way
ANOVA, p < 0.005). As a result, in parallel with deter-
mining the cytotoxic effect of analogues on cancer
Table 1. Characteristics of both analogue peptides as compared to the parent peptide
Peptide Parent Cyclosaplin-2A Cyclosaplin-7G
Sequenc RLGDGCTR RAGDGCTR RLGDGCGR
No of residues 888
Format Cyclo Linear Linear
AntiCP predictor Anticp Anticp Anticp
Hydrophobicity –0.44 –0.48 –0.40
Hydrophilicity 0.73 0.89 0.78
Amphipathicity 0.61 0.61 0.61
Charge +1 +1 +1
Mr(Da) 877.09 835.00 833.04
268
MOSCOW UNIVERSITY BIOLOGICAL SCIENCES BULLETIN Vol. 77 No. 4 2022
ELYADERANI et al.
cells, the haemolytic assay was performed to rule out
the possibility of analogues' damaging normal cells.
In order to measure the integrity of MDA-MB-231
and K562 cells, LDH activity was assessed. Due to the
fact that damaged cells fragment completely after pro-
longed incubation with drug substances, LDH has
been shown to act as an appropriate biomarker of
patient outcome and response to treatment in cancer
patients. When LDH leaks out of the cytoplasm into
the medium, it indicates a change in plasma mem-
brane permeability. A necrotic process could be
responsible for this event. In the present study, it was
demonstrated by the measurement of LDH in cancer
cell lines treated with various concentrations of pep-
Fig. 1. Giemsa staining in MDA-MB-231 cells observed by light microscope (100×). (a) Control cell line (untreated). (b) Treated
cells by IC50 concentration of Cyclosaplin-2A. (c) Treated cells by IC50 concentration of Cyclosaplin-7G. The treated cells exhib-
ited distinct differences, such as chromatin condensation, loss of cell size, disrupted membrane integrity, and apoptotic bodies,
compared to the controls.
(a) (b) (c)
Fig. 2. Giemsa staining in K562 cells observed by light microscope (100×). (a) Control cell line (untreated). (b) Treated cells by
IC50 concentration of Cyclosaplin-2A. (c) Treated cells by IC50 concentration of Cyclosaplin-7G. These cells also showed dis-
tinct differences, such as chromatin condensation, loss of cell size, disrupted membrane integrity, and apoptotic bodies, when
compared to controls.
(a) (b) (c)
Table 2. Hemolytic activity (absorbance) of Triton X-100 (one-way ANOVA, P < 0.005), solvent, Cyclosaplin-2A and
Cyclosaplin-7G on RBC. Three independent experiments were performed
RBC+Solvent RBC+Triton X-100 (20μL) RBC+2A (90 μg/mL) RBC+7G (15 μg/mL)
Absorbance (Mean) 0.454 0.771 0.466 0.463
MOSCOW UNIVERSITY BIOLOGICAL SCIENCES BULLETIN Vol. 77 No. 4 2022
RESEARCH ON THE EFFECT OF AMINO ACID SUBSTITUTION 269
tides that the percentage of LDH leakage from the
treated cells did not increase as a function of dose
compared to the control cells. After 48 hrs of treat-
ment, no increase in LDH levels was observed in both
MDA-MB-231 and K562 cells exposed to IC50 and
higher concentrations of 2A and 7G (Supplementary
Fig. S3). The amount of LDH produced by MDA-
MB-231 cells treated with 2A at IC50 concentration
was 25.9%, and 7G was 24.91%. While for K562 cells
treated with 2A at IC50 concentration was 23.32% and
7G was 25.81% (means ± SEM, p < 0.005). An
unchanged LDH level could be representative that
these cell lines did not experience a necrotic shock.
This technique was widely considered to be a more
reliable and accurate cytotoxicity indicator by
Gurunathan et al. and Asirvatham et al. in their
research [34, 35]. Based on studies of van Zoggel et al.
[15], increased LDH release, positive PI staining as
well as confocal microscopy indicate necrotic mecha-
nisms. Upon binding the Dermaseptin B2 peptide and
disruption of the plasma membrane, they claim these
necrotic mechanisms might be induced.
Further investigation into the apoptotic pathway
was carried out by determining the DNA fragmenta-
tion assay. This method was widely used by researchers
such as Mahassni et al., Mishra et al., and Fani et al. as
a characteristic of apoptosis [15, 25, 28]. The results of
our survey in our study revealed that MDA-MB-231
and K562 cells samples treated with 2A or 7G demon-
strated significant internucleosomal fragmentation. In
Fig. 3, it can be seen that the DNA smear (frag-
mented) was created following treatment with 2A and
7G at IC50 concentration over 48 h. In this study,
inducing apoptosis by analogue peptides was evaluated
and proved by Giemsa staining and DNA fragmenta-
tion. Apoptosis induced by the parent peptide used in
our study has been reported previously by Mishra et al.
They used scanning electron microscopy and DNA
fragmentation techniques in their study [25].
In summary, our present findings indicated that
analogue Cyclosaplin peptides could induce cytotox-
icity to MDA-MB-123 and K562 cells without any
toxicity to normal cells, as evidenced by haemolytic
assay. In MDA-MB-231 cells, IC50 was recorded at
70 µg/mL of 2A and 90 µg/ml of 7G, while in K562
cells, IC50 was recorded at 10 µg/ml of 2A and
15 µg/mL of 7G through the MTT test. It was demon-
strated that the 2A analogue had a greater cytotoxic
effect than 7G on both cancer cell lines. Additionally,
MDA-MB-123 and K562 cells treated by 2A and 7G
represented no changes in LDH leakage levels, and
this issue proves neither type of cell undergone a
necrotic shock. Further enhancement of analogues'
anticancer activity may be achieved by modifying pep-
tide properties such as their hydrophobicity, structure,
or net charge in a specific time and concentration.
ACKNOWLEDGMENTS
Not applicable.
FUNDING
This research received no specific grant from any fund-
ing agency.
COMPLIANCE WITH ETHICAL STANDARDS
Statement on the Welfare of Humans or Animals. This
article does not contain any studies involving humans or
animals performed by the author.
CONFLICT OF INTEREST
The authors declare that they have no conflicts of inter-
est.
REFERENCES
1. Marqus, S., Pirogova, E., and Piva, T.J., Evaluation of
the use of therapeutic peptides for cancer treatment, J.
Biomed. Sci., 2017, vol. 24, no. 1, p. 21.
2. Li, Q., Zhou, W., Wang, D., and Wang, S., Prediction
of anticancer peptides using a low-dimensional feature
model, Front. Bioeng. Biotechnol., 2020, vol. 8, p. 892.
3. Shoombuatong, W., Schaduangrat, N., and Nan-
tasenamat, C., Unraveling the bioactivity of anticancer
peptides as deduced from machine learning, EXCLI J.,
2018, vol. 17, pp. 734–752.
4. Vogelstein, B., Papadopoulos, N., Velculescu, V.E.,
Zhou, S., Diaz, L.A., and Kinzler, K.W., Cancer ge-
nome landscapes, Science, 2013, vol. 340, no. 6127,
pp. 1546–1558.
Fig. 3. A—MDA-MB-231 cells DNA (untreated cells); B,
G—NTC; C—treated MDA-MB-231 cells by IC50 con-
centration of Cyclosaplin-2A; D—treated MDA-MB-231
cells by IC50 concentration of Cyclosaplin-7G; F—treated
K562 cells by IC50 concentration of Cyclosaplin-2A; H—
treated MDA-MB-231 cells by IC50 concentration of
Cyclosaplin-7G; I—K562 cells DNA (untreated cells);
E—DNA laddering assay 100 bp ladder.
ABCDEFGHI
270
MOSCOW UNIVERSITY BIOLOGICAL SCIENCES BULLETIN Vol. 77 No. 4 2022
ELYADERANI et al.
5. Global Burden of Disease Cancer Collaboration, The
global burden of cancer 2013, JAMA Oncol., 2015,
vol. 1, no. 4, pp. 505–527.
6. Idikio, H.A., Human cancer classification: A systems
biology-based model integrating morphology, cancer
stem cells, proteomics, and genomics, J. Cancer, 2011,
vol. 2, pp. 107–115.
7. Wang, S.H. and Yu, J., Structure-based design for
binding peptides in anti-cancer therapy, Biomaterials,
2018, vol. 156, pp. 1–15.
8. Lu, C., Wang, W., Ma, N., Cui, Y., Li, X., and Zhou,
Y., Anticancer peptide from Chinese toad (Bufo Bufo
Gargarizans) skin enhanced sensitivity to 5-Fu in hepa-
tocarcinoma cells (HepG2), Clin. Oncol. Cancer Res.,
2011, vol. 8, no. 3, pp. 149–154.
9. Agrawal, P., Bhagat, D., Mahalwal, M., Sharma, N.,
and Raghava, G.P.S., AntiCP 2.0: an updated model
for predicting anticancer peptides, Brief Bioinform.,
2021, vol. 22, no. 3, p. bbaa153.
10. E-Kobon, T., Thongararm, P., Roytrakul, S., Meesuk,
L., and Chumnanpuen, P., Prediction of anticancer
peptides against MCF-7 breast cancer cells from the
peptidomes of Achatina fulica mucus fractions, Comput.
Struct. Biotechnol. J., 2016, vol. 14, pp. 49–57.
11. Boopathi, V., Subramaniyam, S., Malik, A., Lee, G.,
Manavalan, B., and Yang, D.C., MACppred: A support
vector machine-based meta-predictor for identification
of anticancer peptides, Int. J. Mol. Sci. 2019, vol. 20,
no. 8, p. 1964.
12. Huang, Y.B., Wang, X.F., Wang, H.Y., Liu, Y., and
Chen, Y., Studies on mechanism of action of anticancer
peptides by modulation of hydrophobicity within a de-
fined structural framework, Mol. Cancer Ther., 2011,
vol. 10, no. 3, pp. 416–426.
13. Tyagi, A., Kapoor, P., Kumar, R., Chaudhary, K.,
Gautam, A., and Raghava, G.P.S., In silico models for
designing and discovering novel anticancer peptides,
Sci. Rep., 2013, vol. 3, 2984.
14. Thundimadathil, J., Cancer treatment using peptides:
current therapies and future prospects, J. Amino Acids,
2012, vol. 2012, p. 967347.
15. Mahassni, S.H., Al-Reemi, R.M., Mahassni, S.H., and
Al-Reemi, R.M., Apoptosis and necrosis of human
breast cancer cells by an aqueous extract of garden cress
(Lepidium sativum) seeds, Saudi J. Biol. Sci., 2013,
vol. 20, no. 2, pp. 131–139.
16. Yi, H.C., You, Z.H., Zhou, X., Cheng, L., Li, X., Ji-
ang, T.H., and Chen, Z.H., A deep learning long short-
term memory model to predict anticancer peptides us-
ing high-efficiency feature representation, Mol. Ther.
Nucleic Acids, 2019, vol. 17, pp. 1–9.
17. Kang, S.J., Ji, H.Y., and Lee, B.J., Anticancer activity
of undecapeptide analogues derived from antimicrobial
peptide, Brevinin-1EMa, Arch. Pharm. Res., 2012,
vol. 35, no. 5, pp. 791–799.
18. Xie, M., Liu, D., Yang, Y., Xie, M., Liu, D., and Yang,
Y., Anti-cancer peptides: classification, mechanism of
action, reconstruction and modification: Anticancer
peptides, Open Biol., 2020, vol. 10, no. 7, p. 200004.
19. Prabhu, P.T., Panneerselvam, P., Selvakumari, S., and
Sivaraman, D., Invitro and Invivo anticancer activity of
Ethanolic extract of Canthium Parvif lorum Lam on
DLA and Hela cell lines, Int. J. Drug Dev. Res., 2011,
vol. 3, pp. 280–285.
20. Gaspar, D., Salomé Veiga, A., and Castanho,
M.A.R.B., From antimicrobial to anticancer peptides.
A review, Front. Microbiol., 2013, vol. 4, p. 249.
21. Ausbacher, D., Svineng, G., Hansen, T., and Strøm,
M.B., Anticancer mechanisms of action of two small
amphipathic β 2,2-amino acid derivatives derived from
antimicrobial peptides, Biochim. Biophys. Acta –
Biomembr., 2012, vol. 1818, no. 11, pp. 2917–2925.
22. Zhao, R.L., Han, J.Y., Han, W.Y., He, H.X., and Ma,
J.F., Effects of two novel peptides from skin of litho-
bates catesbeianus on tumor cell morphology and pro-
liferation, in Molecular Cloning – Selected Applications
in Medicine and Biology, Brown, G.G., Ed., Inte-
chOpen, 2011, pp. 73–80.
23. Hou, L., Zhao, X., Wang, P., Ning, Q., Meng, M., and
Liu, C., Antitumor activity of antimicrobial peptides
containing CisoDGRC in CD13 negative breast cancer
cells, PLoS One, 2013, vol. 8, no. 1, p. e53491.
24. Chiangjong, W., Chutipongtanate, S., and Hongeng,
S., Anticancer peptide: Physicochemical property,
functional aspect and trend in clinical application (Re-
view), Int. J. Oncol., 2020, vol. 57, no. 3, pp. 678–696.
25. Mishra, A., Gauri, S.S., Mukhopadhyay, S.K., Chat-
terjee, S., Das, S.S., Mandal, S.M., and Dey, S., Iden-
tification and structural characterization of a new pro-
apoptotic cyclic octapeptide cyclosaplin from somatic
seedlings of Santalum album L., Peptides, 2014, vol. 54.
pp. 148–158.
26. Srinivas, B.K., Shivamadhu, M.C., Devegowda, P.S.,
Mathew, G., Tamizhmani, T., Prabhakaran, S.G., and
Jayarama, S., Screening and evaluation of lectin and
anti-cancer activity from the phloem exudate/Sap of
the indian dietary ethnomedicinal plants, Pharmacogn.
J., 2019, vol. 11, no. 3, pp. 570–578.
27. Afsar, T., Razak, S., Khan, M.R., Mawash, S., Alma-
jwal, A., Shabir, M., and Haq, I.U., Evaluation of anti-
oxidant, anti-hemolytic and anticancer activity of vari-
ous solvent extracts of Acacia hydaspica R. Parker aerial
parts, BMC Complementary Altern. Med., 2016, vol. 16,
258.
28. Fani, S., Kamalidehghan, B., Lo, K.M., Hashim,
N.M., Chow, K.M., and Ahmadipour, F., Synthesis,
structural characterization, and anticancer activity of a
monobenzyltin compound against MCF-7 breast can-
cer cells, Drug Des. Dev. Ther., 2015, vol. 9, pp. 6191–
6201.
29. Kakde, D., Jain, D., Shrivastava, V., Kakde, R., and
Patil, A.T. Cancer therapeutics- opportunities, chal-
lenges and advances in drug delivery, J. Appl. Pharm.
Sci., 2011, vol. 1, no. 9, pp. 1–10.
30. Chen, J., Zhou, M., Zhang, Q., Xu, J., and Ouyang, J.
Anticancer effect and apoptosis induction of gambogic
acid in human leukemia cell line K562 in vitro, Med.
Sci. Monit., 2015, vol. 21, pp. 1604–1610.
MOSCOW UNIVERSITY BIOLOGICAL SCIENCES BULLETIN Vol. 77 No. 4 2022
RESEARCH ON THE EFFECT OF AMINO ACID SUBSTITUTION 271
31. Greco, I., Molchanova, N., Holmedal, E., Jenssen, H.,
Hummel, B.D., Watts, J.L., Håkansson, J., Hansen, P.R.,
and Svenson, J., Correlation between hemolytic activi-
ty, cytotoxicity and systemic in vivo toxicity of synthetic
antimicrobial peptides, Sci. Rep., 2020, vol. 10, no. 1,
p. 13206.
32. Róka, E., Ujhelyi, Z., Deli, M., Bocsik, A.,
Fenyvesi, É., Szente, L., Fenyvesi, F., Vecsernyés, M.,
Váradi, J., Fehér, P., Gesztelyi, R., Félix, C., Perret, F.,
and Bácskay, I.K. Evaluation of the cytotoxicity of α-cy-
clodextrin derivatives on the Caco-2 cell line and hu-
man erythrocytes, Molecules, 2015, vol. 20, no. 11,
pp. 20269–20285.
33. D’Alessandro, A., Editorial: Rising stars in red
blood cell physiology, Front Physiol., 2022, vol. 13,
p. 1020144.
34. Gurunathan, S., Han, J.W., Eppakayala, V., Jeyaraj,
M., and Kim, J.H., Cytotoxicity of biologically synthe-
sized silver nanoparticles in MDA-MB-231 human
breast cancer cells, Biomed. Res. Int., 2013, vol. 2013,
p. 535796.
35. Asirvatham, R., Christina, A.J.M., and Murali, A., In
vitro antioxidant and anticancer activity studies on Dro-
sera indica L. (Droseraceae), Adv. Pharm. Bull., 2013,
vol. 3, no. 1, pp. 115–120.
36. van Zoggel, H., Carpentier, G., Dos Santos, C., Ham-
ma-Kourbali, Y., Courty, J., Amiche, M., Delbé,
J.,van Zoggel, H., Carpentier, G., Dos Santos, C.,
Hamma-Kourbali, Y., Courty, J., Amiche, M., and
Delbé, J., Antitumor and angiostatic activities of the
antimicrobial peptide Dermaseptin B2, PLoS One,
2012, vol. 7, no. 9, p. e44351.
SPELL:OK
ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
Cancer is still a severe health problem globally. The therapy of cancer traditionally involves the use of radiotherapy or anticancer drugs to kill cancer cells, but these methods are quite expensive and have side effects, which will cause great harm to patients. With the find of anticancer peptides (ACPs), significant progress has been achieved in the therapy of tumors. Therefore, it is invaluable to accurately identify anticancer peptides. Although biochemical experiments can solve this work, this method is expensive and time-consuming. To promote the application of anticancer peptides in cancer therapy, machine learning can be used to recognize anticancer peptides by extracting the feature vectors of anticancer peptides. Nevertheless, poor performance usually be found in training the machine learning model to utilizing high-dimensional features in practice. In order to solve the above job, this paper put forward a 19-dimensional feature model based on anticancer peptide sequences, which has lower dimensionality and better performance than some existing methods. In addition, this paper also separated a model with a low number of dimensions and acceptable performance. The few features identified in this study may represent the important features of anticancer peptides.
Article
Full-text available
The use of non-standard toxicity models is a hurdle in the early development of antimicrobial peptides towards clinical applications. Herein we report an extensive in vitro and in vivo toxicity study of a library of 24 peptide-based antimicrobials with narrow spectrum activity towards veterinary pathogens. The haemolytic activity of the compounds was evaluated against four different species and the relative sensitivity against the compounds was highest for canine erythrocytes, intermediate for rat and human cells and lowest for bovine cells. Selected peptides were additionally evaluated against HeLa, HaCaT and HepG2 cells which showed increased stability towards the peptides. Therapeutic indexes of 50–500 suggest significant cellular selectivity in comparison to bacterial cells. Three peptides were administered to rats in intravenous acute dose toxicity studies up to 2–8 × MIC. None of the injected compounds induced any systemic toxic effects in vivo at the concentrations employed illustrating that the correlation between the different assays is not obvious. This work sheds light on the in vitro and in vivo toxicity of this class of promising compounds and provides insights into the relationship between the different toxicity models often employed in different manners to evaluate the toxicity of novel bioactive compounds in general.
Article
Full-text available
Cancer is currently ineffectively treated using therapeutic drugs, and is also able to resist drug action, resulting in increased side effects following drug treatment. A novel therapeutic strategy against cancer cells is the use of anticancer peptides (ACPs). The physicochemical properties, amino acid composition and the addition of chemical groups on the ACP sequence influences their conformation, net charge and orientation of the secondary structure, leading to an effect on targeting specificity and ACP‑cell interaction, as well as peptide penetrating capability, stability and efficacy. ACPs have been developed from both naturally occurring and modified peptides by substituting neutral or anionic amino acid residues with cationic amino acid residues, or by adding a chemical group. The modified peptides lead to an increase in the effectiveness of cancer therapy. Due to this effectiveness, ACPs have recently been improved to form drugs and vaccines, which have sequentially been evaluated in various phases of clinical trials. The development of the ACPs remains focused on generating newly modified ACPs for clinical application in order to decrease the incidence of new cancer cases and decrease the mortality rate. The present review could further facilitate the design of ACPs and increase efficacious ACP therapy in the near future.
Article
Full-text available
Cancer is a well-known killer of human beings, which has led to countless deaths and misery. Anticancer peptides open a promising perspective for cancer treatment, and they have various attractive advantages. Conventional wet experiments are expensive and inefficient for finding and identifying novel anticancer peptides. There is an urgent need to develop a novel computational method to predict novel anticancer peptides. In this study, we propose a deep learning long short-term memory (LSTM) neural network model, ACP-DL, to effectively predict novel anticancer peptides. More specifically, to fully exploit peptide sequence information, we developed an efficient feature representation approach by integrating binary profile feature and k-mer sparse matrix of the reduced amino acid alphabet. Then we implemented a deep LSTM model to automatically learn how to identify anticancer peptides and non-anticancer peptides. To our knowledge, this is the first time that the deep LSTM model has been applied to predict anticancer peptides. It was demonstrated by cross-validation experiments that the proposed ACP-DL remarkably outperformed other comparison methods with high accuracy and satisfied specificity on benchmark datasets. In addition, we also contributed two new anticancer peptides benchmark datasets, ACP740 and ACP240, in this work. The source code and datasets are available at https://github.com/haichengyi/ACP-DL. Keywords: anticancer peptides, long short-term memory, deep learning, binary profile feature, k-mer sparse matrix
Article
Full-text available
Anticancer peptides (ACPs) are promising therapeutic agents for targeting and killing cancer cells. The accurate prediction of ACPs from given peptide sequences remains as an open problem in the field of immunoinformatics. Recently, machine learning algorithms have emerged as a promising tool for helping experimental scientists predict ACPs. However, the performance of existing methods still needs to be improved. In this study, we present a novel approach for the accurate prediction of ACPs, which involves the following two steps: (i) We applied a two-step feature selection protocol on seven feature encodings that cover various aspects of sequence information (composition-based, physicochemical properties and profiles) and obtained their corresponding optimal feature-based models. The resultant predicted probabilities of ACPs were further utilized as feature vectors. (ii) The predicted probability feature vectors were in turn used as an input to support vector machine to develop the final prediction model called mACPpred. Cross-validation analysis showed that the proposed predictor performs significantly better than individual feature encodings. Furthermore, mACPpred significantly outperformed the existing methods compared in this study when objectively evaluated on an independent dataset.
Article
Full-text available
Cancer imposes a global health burden as it represents one of the leading causes of morbidity and mortality while also giving rise to significant economic burden owing to the associated expenditures for its monitoring and treatment. In spite of advancements in cancer therapy, the low success rate and recurrence of tumor has necessitated the ongoing search for new therapeutic agents. Aside from drugs based on small molecules and protein-based biopharmaceuticals, there has been an intense effort geared towards the development of peptide-based therapeutics owing to its favorable and intrinsic properties of being relatively small, highly selective, potent, safe and low in production costs. In spite of these advantages, there are several inherent weaknesses that are in need of attention in the design and development of therapeutic peptides. An abundance of data on bioactive and therapeutic peptides have been accumulated over the years and the burgeoning area of artificial intelligence has set the stage for the lucrative utilization of machine learning to make sense of these large and high-dimensional data. This review summarizes the current state-of-the-art on the application of machine learning for studying the bioactivity of anticancer peptides along with future outlook of the field. Data and R codes used in the analysis herein are available on GitHub at https://github.com/Shoombuatong2527/anticancer-peptides-review. © 2018, Leibniz Research Centre for Working Environment and Human Factors. All rights reserved.
Article
Increasing use of therapeutic peptides for treating cancer has received considerable attention of the scientific community in the recent years. The present study describes the in silico model developed for predicting and designing anticancer peptides (ACPs). ACPs residue composition analysis show the preference of A, F, K, L and W. Positional preference analysis revealed that residues A, F and K are favored at N-terminus and residues L and K are preferred at C-terminus. Motif analysis revealed the presence of motifs like LAKLA, AKLAK, FAKL and LAKL in ACPs. Machine learning models were developed using various input features and implementing different machine learning classifiers on two datasets main and alternate dataset. In the case of main dataset, dipeptide composition based ETree classifier model achieved maximum Matthews correlation coefficient (MCC) of 0.51 and 0.83 area under receiver operating characteristics (AUROC) on the training dataset. In the case of alternate dataset, amino acid composition based ETree classifier performed best and achieved the highest MCC of 0.80 and AUROC of 0.97 on the training dataset. Five-fold cross-validation technique was implemented for model training and testing, and their performance was also evaluated on the validation dataset. Best models were implemented in the webserver AntiCP 2.0, which is freely available at https://webs.iiitd.edu.in/raghava/anticp2/. The webserver is compatible with multiple screens such as iPhone, iPad, laptop and android phones. The standalone version of the software is available at GitHub; docker-based container also developed.
Article
The conventional anticancer therapeutics usually lack cancer specificity, leading to damage of normal tissues that patients find hard to tolerate. Ideally, anticancer therapeutics carrying payloads of drugs equipped with cancer targeting peptides can act like "guided missiles" with the capacity of targeted delivery toward many types of cancers. Peptides are amenable for conjugation to nano drugs for functionalization, thereby improving drug delivery and cellular uptake in cancer-targeting therapies. Peptide drugs are often more difficult to design through molecular docking and in silico analysis than small molecules, because peptide structures are more flexible, possess intricate molecular conformations, and undergo complex interactions. In this review, the development and application of strategies for structure-based design of cancer-targeting peptides against GRP78 are discussed. This Review also covers topics related to peptide pharmacokinetics and targeting delivery, including molecular docking studies, features that provide advantages for in vivo use, and properties that influence the cancer-targeting ability. Some advanced technologies and special peptides that can overcome the pharmacokinetic challenges have also been included.