ORIGINAL RESEARCH article

Front. Pharmacol., 23 February 2024

Sec. Ethnopharmacology

Volume 15 - 2024 | https://doi.org/10.3389/fphar.2024.1322865

Prediction of anticancer peptides derived from the true lectins of Phoenix dactylifera and their synergetic effect with mitotane

  • 1. Department of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia

  • 2. Center of Artificial Intelligence in Precision Medicines, King Abdulaziz University, Jeddah, Saudi

  • 3. Division of Biochemistry, Chemistry Department, Faculty of Science Tanta University, Tanta, Egypt

  • 4. Laboratory of Proteomics and Glycoproteins, Biotechnology Park, Africa City of Technology, Khartoum, Sudan

  • 5. Pharmaceutical Research and Development Centre, Faculty of Pharmacy, Karary University, Omdurman, Sudan

  • 6. Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia

Abstract

Background and aims: Cancer continues to be a significant source of both illness and death on a global scale, traditional medicinal plants continue to serve as a fundamental resource of natural bioactive compounds as an alternative source of remedies. Although there have been numerous studies on the therapeutic role of Phoenix dactylifera, the study of the role of peptides has not been thoroughly investigated. This study aimed to investigate the anticancer activity of lectin peptides from P. dactylifera using in silico and in vivo analysis.

Methods: Different computational tools were used to extract and predict anticancer peptides from the true lectins of P. dactylifera. Nine peptides that are bioactive substances have been investigated for their anticancer activity against MCF-7 and T47D (two forms of breast cancer). To counteract the unfavorable effects of mitotane, the most potent peptides (U3 and U7) were combined with it and assessed for anticancer activity against MCF-7 and HepG2.

Results:In silico analysis revealed that nine peptides were predicted with anticancer activity. In cell lines, the lowest IC50 values were measured in U3 and U7 against MCF-7 and T47D cells. U3 or U7 in combination with mitotane demonstrated the lowest IC50 against MCF-7 and HepG2. The maximum level of cell proliferation inhibition was 22% when U3 (500 µg/mL) and 25 µg/mL mitotane were combined, compared to 41% when 25 µg/mL mitotane was used alone. When mitotane and U3 or U7 were combined, it was shown that these bioactive substances worked synergistically with mitotane to lessen its negative effects. The combination of peptides and mitotane could be regarded as an efficient chemotherapeutic medication having these bioactive properties for treating a variety of tumors while enhancing the reduction of side effects.

Introduction

Over the past 2 decades, there has been a lot of interest in investigating natural materials for bioactive compounds as an alternative source of remedy (Alvin et al., 2014). Traditional medicine is a form of healthcare that draws upon the accumulated wisdom, techniques, and abilities rooted in the theories, customs, and historical insights specific to diverse societies. It is employed to maintain wellness and to address, diagnose, enhance, or remedy both physical and mental health conditions (Wangkheirakpam, 2018). Globally, traditional medicinal plants continue to serve as a fundamental resource for primary healthcare, a fact particularly evident in rural areas where people heavily depend on them (Wangkheirakpam, 2018). An approximate figure of 50,000–70,000 medicinal plants are utilized globally (Wachtel-Galor and Benzie, 2011). The World Health Organization (WHO) has formulated a strategy for traditional medicine aimed at integrating it into the official policies of national healthcare systems (Organization, 2001). This strategy highlights the significance of guaranteeing the safety, efficacy, and quality of medicinal plants. It also emphasizes the need to improve their availability and affordability while promoting their responsible and rational use in therapy (Hassan et al., 2020). In Saudi Arabia (KSA), the traditional utilization of ethnomedicinal plants reflects a deep connection between customary remedies, health, dietary habits, and traditional healing traditions that are unique to particular cultures (Aati et al., 2019).

Lifestyle diseases are of growing concern. Many prevalent diseases including type-2 diabetes, cardiovascular diseases, obesity, and cancer are reducing life span (Li et al., 2020). Plant-based natural compounds have a long history of providing preventative therapeutic benefits against these diseases (Najmi et al., 2022). Nowadays most of the research become oriented toward finding new alternative natural source products, a derivative of natural origin, or even semi-synthetic drugs based on natural product models from plants and animals to replace pure synthetic pharmaceutical drugs and hence, reduce their negative side effects (Pan et al., 2013).

The plant natural products fall into two categories: primary metabolites such as proteins and carbohydrates and secondary metabolites such as alkaloids, flavonoids, steroids, saponin, glycosides, tannin, carotenoid, and phenolic components (Silva et al., 1998). The primary metabolites such as some proteins and peptides provide an arsenal of defense molecules, including lectins, ribosome-inactivating proteins, protease inhibitors, antimicrobial proteins and peptides (AMP-ACPs), ureases, etc (Kocyigit et al., 2023).

The AMP are highly abundant in higher plants especially Caryophyllaceae and Rhamnaceae families (Abdoullahi et al., 2022). Such peptides were reported to have potent antitumor activities which are cherimolacyclopeptide C, cycloheptapeptide, dianthins E, etc. The other type of AMPs is the antimicrobial proteins which consist of around 12 families of which three members are reported to have antitumor activities (Abdoullahi et al., 2022). Because of the antitumor activities of these proteins and peptides, they can be also named ACPs (anticancer proteins/peptides).

Phoenix dactylifera L (the date palm tree) holds the distinction of being among the most ancient and fundamental crops in the Middle East, Southwest Asia, and North Africa (Al-Alawi et al., 2017). The scientific name of the plant is P. dactylifera L. cv. Hillaw and the scientific classification is Kingdom: Plantae. Phylum: Magnoliophyta. Class: Liliopsida. Subclass: Arecidae. Order: Arecales. Family: Arecaceae. Genus: Phoenix. Species: dactylifera (Al Sawafi and Al Maliki, 2020).

Lectins are a varied category of proteins from different families that possess the ability to recognize carbohydrates (Osman et al., 2023). Lectins are proteins that can bind to mono- or oligosaccharides in a specific and reversible manner, and they are characterized by having at least one non-catalytic domain for this purpose (Mishra et al., 2019). These proteins are found in all organisms from all kingdoms and play several roles including immunological and defense functions. It has been proven that some lectins trigger apoptosis and/or death of tested cancer cells (Rabelo et al., 2012). Thousands of lectins have indeed been isolated from all kinds of organisms, yet the search for new ones especially from plant sources is still a frontier area of study (Srikanth and Chen, 2016). Figuring out the way to solve their immunogenicity, increase their stability, identify their mode of action as defense proteins and engineer lectins for drug use and/or drug delivery systems are persistent issues scientists are trying to tackle (Dhuna et al., 2005).

Breast cancer stands as the most prevalent form of cancer across the globe and is the primary cause of cancer-related mortality among women (Organization, 2023). According to a recent WHO report, around the globe there are more than 2.3 million cases of breast cancer in both genders are reported annually (Organization, 2023).

In this study, we aim to study the anticancer activity (targeting breast cancer and liver cancer cells) of peptides derived from the true lectin of P. dactylifera, using in silico and in vivo analysis.

Methodology

Lectins putative genes from Phoenix dactylifera with ACPs motifs

A genome-wide search of P. dactylifera for lectin families and putative domains was done using NCBI nucleotide and protein databases, more details are found in our previous publication (Osman et al., 2023).

Screening of putative true lectins peptides

Eight true lectins were identified in P. dactylifera and they were legume (XP_038973335.1, XP_008793992.2), Malectin (XP_008795773.2, XP_008812544.3, XP_038974428.1, XP_008792302.2 and XP_026655880.2) and M-Type (XP_038985107.1). The above-mentioned sequences were screened for the presence of putative peptides using the PeptideCutter server, and three proteolytic gastric enzymes (Pepsin (pH1.3), Trypsin and Chymotrypsin) were used with the default setting.

In silico prediction of anticancer activity and toxicity of identified peptides

Different tools were used to screen the identified peptides for possible anticancer activity. AntiCP2.0 web tool (Agrawal et al., 2021) and Peptide Calculator were used to predict peptides with anticancer activity, hydrophobicity, Hydrophilicity, Hydropathicity, and charge. The CellPPD (Gautam et al., 2013) was used to predict cell penetration activity and other physical properties. CancerPPD database (Tyagi et al., 2015) was used for aligning peptide sequences with anticancer peptides. ToxinPred was used to screen toxic/non-toxic peptides (Gupta et al., 2013).

Peptide synthesis and in vitro anticancer activity

According to in silico analysis 9 peptides (U1, U2, U3, U4, U5, U6, U7, U8, and U9) (Peptide lable) were selected due their predicted anticancer activity and lower toxicity. These peptides were synthetized commercially by GenScript Biotech Corporation (GenScript, Piscataway, NJ) and they were dissolved in ultrapure water in different concentrations ranged from 10 µM −250 µM.

MCF-7, T47D (breast cancer), and HepG2 (liver cancer) were donated by the Tissue Culture Unit, Department of Biochemistry, Faculty of Science, King Abdulaziz University. Selected human cell lines were cultured in DMEM media with 10% fetal bovine serum (FBS) at 37°C in a CO2 incubator. After 70%–90% confluence, 5 mL of 0.25% trypsin is injected to separate the cells. The cells were counted using trypan blue, and the cell concentration was set at 105/mL. A 96-well plate was filled with 100 mL in each well, and the plate was then incubated for 24 h.

Mitotane, marketed as Lysodren, functions as a steroidogenesis inhibitor and cytostatic antineoplastic drug. It is employed for treating adrenocortical carcinoma and Cushing’s syndrome (Lo Iacono et al., 2021). In this study the media in each well was replaced to contain media containing peptides in varying concentrations (U1, U2, U3, U4, U5, U6, U7, U8, and U9). U3 and U7, which have the lowest IC50 values, were chosen to be combined with mitotane. Mitotane concentrations ranged from 20 to 600 µM. U3 and U7 were combined with mitotane using two different preparation techniques. Various concentrations of U3 or U7 (40–1500 µM) and mitotane (20–600 µM) were serially diluted. serial dilution of mitotane concentration with 500 µg/mL of U3 or U7 at a fixed concentration Each concentration was repeated four times.

After 48 h of incubation at 37°C, 100 µL of the 0.5 mg/mL MTT was changed with media containing the medication. At 37°C in the dark, the 96-well plate was incubated for 4 h. After removing the MTT and replacing it with 100 µL of DMSO, the plate was allowed to rest for 15 min. The absorbance of each well in 96 well plate was read at wave length 595 nm by ELISA reader (Bio-RAD microplate reader, Japan).

2.7 Statistical analysis

The treated cells viability and IC50 were expressed as the mean ± standard deviation (SD). The percentage viability was calculated by multiplying the absorbance of treated cells by 100 and dividing the absorbance of untreated cells. The software GraphPad Prism (version 9.0, San Diego, CA, United States) was conducted to calculate the IC50 of peptides, mitotane and their combination.

Results and discussion

In silico analysis

The genome-wide search of P. dactylifera yielded 11 lectin families, of which five families had sequences with ACP motifs (28 seq. total). Only eight sequences are reported to be true lectins (containing all amino acids required for sugar-binding) (Supplementary Table S1). Usually, ACPs are short sequence peptides their length ranging from of 10–50 aa (Chen et al., 2021). Accordingly, the digestion of true lectins by proteolytic gastric enzymes (Pepsin (pH1.3), Trypsin and Chymotrypsin) revealed the presence 96 putative peptides ranging in length from 9 to 20 aa as shown in Table 1, most of these peptides were non-toxic (Supplementary Table S2). AntiCP2.0 web tool revealed that 9 of these peptides were predicted with anticancer probabilities that are all scored more than 0.60 (Supplementary Table S3), suggesting their ACPs probability (Liu et al., 2022). The charge of four peptide (U1, U3, U6 and U8) was positive or zero, which increase their chance to interact with negatively charged cancer cells (Liu et al., 2022). Additionally, the Grand Average of Hydropathy Value for protein sequences (GRAVY) was recorded using by using Peptide Calculator tool. The GRAVY value represents the sum of hydropathy values of peptide residues divided by the protein length, where positive values indicate hydrophobic and negative values indicate hydrophilic (Avraamides et al., 2021). Two peptides (U3 and U6) scored 0.29 and 0.81 kcal/mol and were hydrophobic while the rest were hydrophilic. Previous studies have uncovered that ACPs possess a significant degree of hydrophobicity and a positive overall charge (Table 2). This enables them to selectively target and destroy cancer cells by interacting with the negatively charged components of cancer cell membranes (Huang et al., 2021).

TABLE 1

Sequence IDLectin familiesPeptide sequencePeptide mass [Da]Peptide length [aa]
XP_038973335.1LegumeMVYPEPVTIYDEASVIN1940.19517
SSYPSAIPDL1049.14510
TLPSTVVAVE1015.17210
DISANHIGIDVHTIYSVVQ2081.31319
SSQGYGSSPSPTPR1407.45914
EYISEVTIISR1309.48211
HEGWEQCVIHR1393.54311
AGTMGYIAPEYAITGK1642.88716
DTPLPALPPNMPIPMF1751.13216
NVPAPPPNSESCSIV1510.68215
XP_008793992.2LegumeNQADSSPSS891.8479
LSPYPSEIPENSYGGT1710.81416
NVEYNDSSSNHVGIDVHTIF2247.36220
DACVGYDGGAK1055.12711
HWSTSYVVD1093.1619
ASVVGAGVVA828.96410
EQVEMAVAIDS1191.31911
EYISEVTIISR1309.48211
HEEWEQCVVHR1451.57911
VDHDCDPATTV1172.23211
DAPLPILSPNMPLPVF1721.08816
LRPPPVDISN1107.27510
XP_008795773.2MalectinNGSIPATWASL1116.23911
IDGNPISGK899.9999
IDMQGTSMEGPFPPTF1754.99016
LAPSSCQEGN1005.06710
NMVSSYSSTESNSIAR1732.84016
DDHEYEDDPSQMGPSR1877.87016
IFDVSIQGQK1134.29710
EANGTGRPIIK1155.31911
LISAISVTPNF1161.36311
TDSKPDIQESK1247.32411
FINEIGMISA1094.29110
YGCCIEGSQ959.0569
IYEYMENNS1162.2369
NEEENTHISTR1329.34611
IAGTMGYMAPEYA1374.58913
VNTSVNIDQSSK1291.38112
NSSSSNISHQAV1230.25612
XP_008795773.2MalectinSVDPCSGNAGW109211
IDGNPISGK9009
LAPSSCQEGN100510
SSTESNSIAR105110
EDDPSQMGPSR121811
EANGTGRPIIK115511
LISAISVTPNF116111
TDSKPDIQESK124711
INEIGMISA947.19
NEEENTHISTR132911
EVISGMSNTNY121411
VNTSVNIDQSSK129112
XP_038974428.1MalectinSVDPCSGNAGW109211
IDGNPISGK9009
LAPSSCQEGN100510
SSTESNSIAR105110
EDDPSQMGPSR121811
EANGTGRPIIK115511
LISAISVTPNF116111
TDSKPDIQESK124711
INEIGMISA947.19
NEEENTHISTR132911
EVISGMSNTNY121411
TSVNIDQSSK107810
NSSSSNISHQAV123012
XP_008792302.2MalectinSVDPCSGDAAW110711
IDGNPITGK9149
DMQGTSMEGPFPSI149714
TESPPANCW10049
SSTNINSIASC109611
INCGGSHVTVDGNEY156515
EDDTSPQGASR116211
LISAISVTPNF116111
GIVAASCVVIM106211
PDGSEIAVK9159
INEIGMISA947.19
DEEENTHISTR133011
XP_026655880.2MalectinAVGSASPTL801.99
GVDPCSGEGNW112011
LESDVVCDCS106910
EGPIPSGISN97010
NCSIHGDIPAY118911
TVGSSGITQC95210
EGSVNTVECY110010
TFPCSASNK954.19
HINCGGEETIIK131312
MDDDVNADNY117110
NIEDAAGGPGKPVIK146615
LISAISVTPNF116111
DVGSPSSNR917.99
TIIVVVVMA944.29
XP_038985107.1M-TypeHDNTAHPAPDS116111
GGSDGGPGGGNK958.912
VNDIIIKPNDR129611
HNLLCPETVES124111
DDVTAMVPR10039
NTEAHSFPV10019

True lectins peptide sequences.

TABLE 2

Peptide IDPeptide sequenceChargeHydrophobicityGRAVYHydrophilicity
U1SSQGYGSSPSPTPR10.14−1.4−0.27
U2NQADSSPSS−10.46−1.5−0.32
U3NGSIPATWASL0.0−0.690.290.08
U4NEEENTHISTR−1.50.87−2.08−0.47
U5DEEENTHISTR−2.51.13−2.08−0.48
U6AVGSASPTL0−0.460.810.11
U7NCSIHGDIPAY−0.5−0.4−0.09−0.01
U8TFPCSASNK1−0.07−0.47−0.18
U9HDNTAHPAPDS−10.37−1.64−0.27

Peptide properties.

Experimental procedure

The percentage of viability of both human breast cancer cell lines (MCF-7 and T47D) treated with 9 bioactive peptides is shown in Figure 1. Nine bioactive peptides with varying quantities were found in P. dactylifera true lectins after being exposed to MCF-7 and T47D for 48 h. These nine bioactive peptides’ IC50 values were calculated in two different types of breast cancer cells (Table 3). The lowest IC50 values measured in U3 and U7 against MCF-7 were 480 and 348 µM, respectively, whereas 517 and 584 µM were recorded against T47D. The table below shows the greatest IC50 values for U1, U5, and U6 against MCF-7 and T47D, demonstrating reduced efficacy on both breast cell types. U2, U4, U8, and U9 each had an IC50 of 681, 297, 640, and 417 µM against MCF-7, whereas their IC50s against T47D ranged from 871 to 5462 µM, indicating that their effects on T47D were attenuated (Table 3). Interestingly, Wang et al. (Wang et al., 2019) identified an alternatively-activated pathway for both metastatic breast and liver cancers involving the enrichment of cytokine-cytokine receptor in both cases. This finding could support our results, where peptides exhibited activity against both cancer types, suggesting the potential for targeting common pathways associated with these cancers.

FIGURE 1

TABLE 3

Group (A)U1U2U3U4
MCF-71007–2258451.2–1030373.4–617.4260.6–338.5
Range1507 ± 71.70681.8 ± 32.03480.1 ± 55.04297 ± 19.72
Value
T47D457.6–784.51141–1988434.7–616.5722.7–1051
Range value599.1 ± 20.371506 ± 78.03517.6 ± 34.86871.5 ± 23.37
Group (B)U5U6U7U8U9
MCF-7548.7–10891359–2075265.9–457.8518.2–792.5351.3–496.3
Range773.1 ± 44.461680 ± 74.31348.9 ± 25.32640.8 ± 43.82417.5 ± 15.69
Value
T47D866.1–18292522–13781485.3–702.81993 to 11,1432615–11410
Range value1259 ± 62.475896 ± 118.59584 ± 29.994713 ± 83.595462 ± 99.29

IC50 of peptides (µM (U1, U2, U3, U4 U5, U6, U7, U8,U9) against MCF-7 and T47D.

Synergetic effect mitotane

Mitotane accumulates cholesterol lipoproteins in the adrenal cortex and adipose tissues that is used for the biosynthesis of corticosteroid hormones. Mitotane causes the cytochrome P450 enzymes to be out of control and the mitochondrial membranes to become depolarized, so mitotane damages the adrenal cortex. Mitotane is used for the treatment of advanced adrenocortical cancer as well as postoperative adjuvant therapy. Zona fasciculate and reticularis of the adrenal cortex are particularly affected by the high dose of mitotane-caused neuro-cellular toxicity (Lo Iacono et al., 2021).

Mitotane is used in combination with the peptides U3 and U7 to increase its therapeutic effects while lowering its side effects. Higher doses of mitotane have more commonly been linked to central neurological damage (Kasperlik-Zaluska, 2000; Fassnacht et al., 2018).

In this investigation, the percentage of viability of MCF-7 and HepG2 treated with various concentrations ranging from 40–1500 µM U3 and U7 was evaluated to determine the IC50 of U3 and U7 against both cells (Figure 2). The IC50 values of U3 and U7 ranged from 523 to 561 µM against MCF-7 and HepG2 and were both high and almost identical (Figure 2; Table 4).

FIGURE 2

TABLE 4

U3U7MitotaneMitotane + U3*Mitotane + U7*
MCF-7486.6–634.2480.9–639.562.41–93.3345.60–59.6344.00–55.04
Range555.5 ± 43.46554.5 ± 44.3576.32 ± 5.0452.14 ± 5.5149.21 ± 1.99
Value
HepG2454.4–692.5427.0–642.532.44–49.6920.85–26.7829.66–43.68
Range value561 ± 39.27523.8 ± 35.8240.15 ± 4.6923.63 ± 1.8736 ± 1.61
Mitotane + U3Mitotane + U7
500#500#
MCF-727.37–35.7140.31–51.72
Range31.27 ± 2.8545.66 ± 5.48
Value
HepG243.56–75.3633.77–53.40
Range value57.29 ± 1.6542.46 ± 1.46

IC50 (µM) of combined U3 and U7 peptides with mitotane against MCF-7 and HepG2.

*The serial dilution of concentration of mitotane ranging from 10, to 250 µM) and various concentrations of U3 or U7 (40–1500 µM/mL).

#Serial dilution of mitotane concentration with a fixed concentration of U3 or U7 (500 µg/mL).

The IC50 values for mitotane against HepG2 and MCF-7 cells were 31.27 and 57.29 µM HepG2 has shown greater anticancer activity efficacy than MCF-7. The HepG2 IC50 is 2-fold lower than MCF-7 (Table 4). The combination of U3 and U7 with mitotane with different concentrations of mitotane and peptides (U3 or U7) of HepG2 has nearly the same anticancer activity as cells treated alone with mitotane, although this combination is only marginally effective against MCF-7.

It is more effective to combine various mitotane doses with a constant amount of U3 or U7 (500 µg/mL), which is effective against both MCF-7 and HepG2. In contrast, the combination of mitotane with U3 (500 µg/mL) was more effective against MCF-7 and HepG2, with an IC50 that was 2.4 and 1.7 times lower than cells treated with mitotane alone. The combination of mitotane and U3 (500 µg/mL) is more effective than the combination of mitotane and U7 Table 4 and Figures 3, 4.

FIGURE 3

FIGURE 4

HepG2 cells were treated with mitotane (25 µg/mL) alone, in combination with U3 or U7 (200 µg/mL), and the viability percentages were 41.86 ± 4.54, 55 ± 4.64, and 43 ± 3.78, respectively. The anticancer activity of mitotane (25 µg/mL (80 µM) alone and in combination with U3 (22.62 ± 2.63) or U7 (35.68 ± 6.92) with concentration (500 µg/mL) was more strongly influenced by the percentage of inhibition HepG2 treated with these drugs. The viability percentages of MCF-7 treated with mitotane (25 µg/mL) alone, mixed with U3 or U7 with concentration (200 µg/mL were, respectively, 59.05 ± 1.83, 46.53 ± 4.94, and 44.04 ± 4.77. The percentage of MCF-7 cells that were treated with mitotane (25 µg/mL) alone or in combination with U3 (35.76 ± 3.74) or U7 (41.19 ± 3.16) with concentration (500 µg/mL) had a greater impact on the effectiveness of the anticancer treatment (Figure 5).

FIGURE 5

Conclusion

The most bioactive compounds in the current study were U3 and U7, which were successful in treating liver cancer (HepG2) and breast cancer (MCF-7 and T47D). U3 and U7 have high IC50, hence mitotane is utilized in combination with these. Compared to cells treated with mitotane alone, the IC50 of mitotane and U3 against MCF-7 and HepG2 were reduced to 2.4 and 1.7 times, respectively. Negative mitotane effects may be less likely due to the synergistic effects of mitotane with U3 and U7. It is advised to understand the mechanism by which U3 or U7 combined with mitotane inhibits cell proliferation. Consideration should be given to chemotherapeutic medications that have been combined with these bioactive molecules as a novel way to improve therapy effectiveness and lessen side effects.

Statements

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Materials, further inquiries can be directed to the corresponding authors.

Ethics statement

Ethical approval was not required for the studies on humans in accordance with the local legislation and institutional requirements because only commercially available established cell lines were used.

Author contributions

OB: Conceptualization, Writing–original draft, Writing–review and editing, Funding acquisition, Project administration, Supervision, Validation. EA: Writing–original draft, Writing–review and editing, Data curation, Methodology, Resources. SH: Methodology, Writing–review and editing, Software. EH: Methodology, Writing–review and editing, Conceptualization, Data curation. IA: Methodology, Writing–review and editing, Formal Analysis, Investigation. AA: Investigation, Methodology, Writing–review and editing. HA: Methodology, Writing–review and editing, Conceptualization, Software, Writing–original draft.

Funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The authors extend their appreciation to the Deputyship for Research and Innovation, Ministry of Education in Saudi Arabia, for funding this research work through the project number IFPRC-165-130-2020 and King Abdulaziz University DSR, Jeddah, Saudi Arabia.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fphar.2024.1322865/full#supplementary-material

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Summary

Keywords

date palm, MCF-7 breast cancer cells, HepG2, liver cancer, in silico analysis

Citation

Baothman O, Ali EMM, Hosawi S, Hassan E. Konozy E, Abu Zeid IM, Ahmad A and Altayb HN (2024) Prediction of anticancer peptides derived from the true lectins of Phoenix dactylifera and their synergetic effect with mitotane. Front. Pharmacol. 15:1322865. doi: 10.3389/fphar.2024.1322865

Received

18 October 2023

Accepted

18 January 2024

Published

23 February 2024

Volume

15 - 2024

Edited by

Sadiq Umar, University of Illinois Chicago, United States

Reviewed by

Imran Jamal, University of Pittsburgh Medical Center, United States

Sevgi Gezici, University of Gaziantep, Türkiye

Updates

Copyright

*Correspondence: Othman Baothman, ; Hisham N. Altayb,

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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