Skip to main content
Download PDF
  • Research Note
  • Open access
  • Published:

In silico prediction of the action of bromelain on PI3K/Akt signalling pathway to arrest nasopharyngeal cancer oncogenesis by targeting phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha protein

BMC Research Notes volume 17, Article number: 346 (2024) Cite this article

Abstract

Objective

This research investigates the potential anti-tumour effects of bromelain, an aqueous extract from pineapple stems and fruits, on nasopharyngeal cancer (NPC). While bromelain is known for its medicinal properties in various cancers, its impact on NPC remains unexplored.

Results

Using in silico methods, we studied the predicted interactions between bromelain and key proteins involved in NPC oncogenesis, specifically β-catenin, PIK3CA, mTOR, EGFR, and BCL2. Molecular docking strategies were performed using a myriad of computational tools. A 3D model of bromelain was constructed using SWISS-MODEL, followed by molecular docking simulations performed with ClusPro. The binding affinities of the docked complexes were evaluated using HawkDock, and the interactions were analysed with LigPlot+. The docking scores indicated potential spontaneous interactions, with binding affinities based on being − 103.89 kcal/mol (PIK3CA), -73.16 kcal/mol (EGFR), -71.18 kcal/mol (mTOR), -65.22 kcal/mol (β-catenin), and − 57.48 kcal/mol (BCL2). LigPlot + analysis revealed the presence of hydrogen bonds, hydrophobic interactions, and salt bridges, indicating stable predicted interactions.

Conclusion

Our findings suggest that bromelain can target key proteins involved in NPC oncogenesis, with the strongest affinity towards PIK3CA. This suggests a hypothetical insight into bromelain’s anticancer effects on NPC through the modulation of the PI3K/Akt signaling pathway.

Peer Review reports

Introduction

Bromelain is a bioactive compound obtained from pineapple (Ananas comosus) aqueous extract that is widely studied as a drug candidate. It is known to have medicinal properties such as antimicrobial, antithrombotic and anti-inflammatory effects [1]. Previous in vitro and in vivo studies have revealed its anticancer effects on various types of cancer such as lung [2, 3], brain [4], colorectal [5, 6], skin [7], and breast [8,9,10] cancer. However, to date, literature evidence of this effect on Nasopharyngeal carcinoma (NPC) is lacking, including those from in silico findings.

NPC is a type of head and neck squamous cell cancer (HNSCC) that is preferentially common in Asia, particularly Southeast Asia [11, 12]. NPC pathogenesis involves several crucial signalling pathways including those that regulate cell proliferation, metastasis and apoptosis inhibition [13]. Several key proteins in these pathways can be targeted for in silico studies in order hypothetical insights into the anticancer potentials of bromelain. The essential NPC-associated signalling pathways include the EGFR, phosphatidylinositol 3‑kinase (PI3K)/protein kinase B (Akt), and Wnt/β-catenin pathways. Dysregulation of the EGFR pathway is linked to disease recurrence, tumour migration, as well as poor prognosis and lower survival rates in NPC patients [14,15,16]. Abnormal regulation of the PI3K/Akt/mammalian target of rapamycin mTOR signalling pathway is associated with proliferation, migration and invasion in NPC cells [17]. Radioresistance in NPC is associated with dysregulation of the Wnt/β-catenin pathway [18, 19] [18, 19]. In addition, the apoptosis pathway plays a crucial role in NPC tumorigenesis, during which the silencing of proapoptotic factors by antiapoptotic factors such as BCL2 can lead to tumour progression [20]. Taken together, these findings indicate that the target receptor proteins (key proteins crucial for the regulation of the aforementioned pathways) chosen for our study were EGFR (for the EGFR pathway), PIK3CA and mTOR (for the PI3K/Akt/mTOR pathway), β-catenin (for the Wnt/β-catenin pathway), and Bcl2 (for the apoptosis pathway).

The identification of interactions between drugs and targets is a critical prerequisite steps in drug development [21]. Drug-target interaction (DTI) prediction via a computational approach is a common contemporary strategy that is empirically reliable, time-saving, and cost effective [22]. One of the computational methods used to simulate DTI at the molecular level is the molecular docking approach. In this study, this in silico method was carried out to determine the feasibility and characteristics of simulated interactions between bromelain and the key proteins associated with NPC oncogenesis.

Methods

Preparation of the Bromelain structure

A 3D model of stem bromelain was generated using the SWISS-MODEL workspace server due to the significant heterogeneity observed in the available experimental crystal structure (PDB ID: 6YCE) and the need for a consistent and well-characterized sequence for our study. The model was generated based on homology modelling [23, 24], using the input sequence of 212 amino acids from the UniProt KB database entry P14518 (BROM2_ANACO). The template was chosen as it closely resembles target sequence. The model’s quality was assessed using QMEAN score, Ramachandran Plot, ERRAT, and VERIFY3D via the SAVES server. PyMOL software was used to generate the root mean square deviation (RMSD) through superimposition, and energy minimization was performed using Swiss-PdbViewer [25].

Preparation of target receptors

Five target receptor proteins of bromelain (β-catenin, PIK3CA, mTOR, EGFR, and BCL2) were selected. The 3D crystallographic structures of these proteins were obtained from the RCSB PDB website (PDB IDs: 7AFW, 5DXT, 4DRI, 3POZ, 4LVT). Preparation involved removing ligands, water molecules, and side chains using Discovery Studio 2021. Polar hydrogen and Kollman charges were added using AutoDock Tools [26].

Molecular docking and analysis

Molecular docking was performed using the ClusPro server, which involves three steps: rigid body docking with PIPER, clustering of the top 1000 structures using RMSD, and structural refinement via energy minimization [27,28,29,30,31]. The balanced category was chosen for the docked model, with scoring based on the formula:

$${\rm{E = 0}}{\rm{.40}}{{\rm{E}}_{{\rm{rep}}}}{\rm{ + - 0}}{\rm{.40}}{{\rm{E}}_{{\rm{att}}}}{\rm{ + 600}}{{\rm{E}}_{{\rm{elec}}}}{\rm{ + 1}}{\rm{.00}}{{\rm{E}}_{{\rm{DARS}}}}$$

The ligand and receptors used were bromelain and the target proteins, respectively. The best solution with the highest cluster size and lowest free energy was selected.

The binding affinities were predicted using the HawkDock server [32], which calculates the binding free energy (BFE) using the MM-GBSA approach [33]. BFEs were estimated based on Van der Waals forces, electrostatic bonds, Generalized Born model polar solvation free energies, and empirical model non-polar solvation free energies. LigPlot + software analysed interacting residues, assessing hydrogen bonds, hydrophobic residues, and salt bridges [34, 35]. The strength of the hydrogen bonds was evaluated by donor-acceptor distance, ranging from 2.2 Å to 4.0 Å.

Results

3D model structure of bromelain and quality assessment

The SWISS-MODEL homology-based modelling protocol required an initial target-template sequence comparison before constructing the computational structure. Sequence alignment between bromelain and the template protein (PDB ID: 6YCE) revealed a 95.73% sequence homology. Based on this template, a 3D structural model of bromelain was constructed and evaluated. The QMEAN score of -0.15 indicated the model’s acceptability, as scores around zero, not deviating more than 1 standard deviation from the mean, suggest high-quality models [25]. The Ramachandran plot showed 89.1% of residues in the favoured region with no outliers, affirming stereochemical quality. The low RMSD score of 0.079Å indicated high similarity with the template. High ERRAT (96.4) and VERIFY3D (100%) scores further confirmed the model’s quality. Collectively, these assessments validated the constructed model for use in molecular docking assays.

Molecular docking and assessment

PyMOL illustrations of the docked complexes for EGFR-bromelain, mTOR-bromelain, BCL2-bromelain, PIK3CA-bromelain, and β-catenin-bromelain are shown below. The MM-GBSA total binding free energy (BFE) from HawkDock showed that PIK3CA had the highest affinity for bromelain, followed by EGFR, mTOR, β-catenin, and BCL2 (Table 1). All docked complexes had negative values, indicating potential spontaneous reactions. The more negative the value, the greater the binding affinity. LigPlot + analysis revealed hydrogen bonds, hydrophobic residues, and salt bridges in all complexes (Table 2). The interacting residues within the docked complexes are shown for EGFR-bromelain, mTOR-bromelain, BCL2-bromelain, PIK3CA-bromelain, and β-catenin-bromelain. Additional figures viewed from PyMOL shows the illustration of 3D model structure of bromelain and the illustration of docked complex of each proteins with bromelain respectively; Ligplot + illustrations of docked complexes shows the interacting residues in more detail [see Supplementary Material 1].

Table 1 Values of docking scores, MM/GBSA, Van Der Waal potentials (VDW), electrostatic potentials (ELE), polar solvation free energies (from Generalised Born (GB) model prediction), and nonpolar contribution to the solvation (SA) free energies (from empirical model calculation) of the docked complexes
Full size table
Table 2 The hydrogen bonds, hydrophobic residues and salt bridges of the docked complexes obtained from dimplot results of LigPlot + analysis
Full size table

According to LigPlot + results, the bromelain-PIK3CA interaction involved the highest number of hydrogen bonds [25], followed by EGFR [15], mTOR and β-catenin (14 each), and BCL2 [8]. In the bromelain-PIK3CA complex, 15 and 5 interacting residues formed single and double hydrogen bonds, respectively. The shortest distance (2.48 Å) between two interacting residues in a hydrogen bond was found in the bromelain-PIK3CA complex involving Lys325 (PIK3CA) and Leu156 (bromelain). For hydrogen bonds exceeding 3.00 Å, the bromelain-mTOR complex had the most (35.7%), and the bromelain-PIK3CA complex had the least (4%). Comparable numbers of longer hydrogen bonds were found in bromelain-EGFR, bromelain-BCL2, and bromelain-β-catenin complexes, with 13.3%, 12.5%, and 14.3%, respectively. The hydrogen bond quantity and distances partly explain the higher binding affinity of bromelain with PIK3CA, as shown by the MM-GBSA total BFE results. Despite having the fewest hydrogen bonds, the bromelain-BCL2 complex had the highest number of hydrophobic interactions (21 residues), with nine from BCL2 and twelve from bromelain. The bromelain-PIK3CA interaction involved 17 hydrophobic residues, the second largest number after BCL2. Salt bridge interactions were comparable (two each) among all complexes except for the bromelain-BCL2 complex, which had one (Glu162-Lys64).

The BFE contribution by the top five residues for receptor proteins and bromelain based on HawkDock analysis (Table 3) was consistent in showing PIK3CA as the most preferred target receptor for bromelain. The bromelain-PIK3CA complex had the lowest average BFE for the top five receptor (-6.188 kcal/mol) and bromelain (-6.226 kcal/mol) residues compared to other complexes. Lower BFE values indicate higher binding affinity. For other complexes, the average BFE for the top five residues were: -4.362 kcal/mol for receptor and − 5.554 kcal/mol for bromelain in bromelain-EGFR; -6.096 kcal/mol for receptor and − 5.792 kcal/mol for bromelain in bromelain-mTOR; -4.134 kcal/mol for receptor and − 3.818 kcal/mol for bromelain in bromelain-BCL2; and − 5.526 kcal/mol for receptor and − 4.298 kcal/mol for bromelain in bromelain-β-catenin.

Table 3 Top 5 residues of receptor and ligand (bromelain) which contribute to the BFE of the docked complexes based on HawkDock analysis
Full size table

Discussion

Our in silico analysis suggests that bromelain interacts with key proteins (PIK3CA, EGFR, mTOR, β-catenin, and BCL2) from signalling pathways associated with NPC tumorigenesis. Notably, bromelain-PIK3CA interaction is the strongest, exhibiting the highest number of H-bonds, and strongest binding affinity.

The PI3K/Akt/mTOR pathway is involved in various biological functions including cell differentiation, proliferation, survival, as well as cell growth [36]. The dysregulation of this pathway has been strongly implicated in the development and progression of multiple cancers, including NPC. PIK3CA, also known as the p110α protein, is the catalytic subunit of phosphatidylinositol 3-kinase (PI3K), which plays a crucial role in this pathway. Mutation of PIK3CA usually occur in exons 9 (helical domain and 20 (kinase domain) and it has been reported in several types of cancer including head and neck cancer [37, 38]. PIK3CA mutations have also been shown to be oncogenic by promoting the growth of cancer cells as well as invasion [39, 40]. Evidence of PIK3CA gene mutations involving the previously mentioned exons 9 and 20 has been shown before in 9.6% of NPC cases (n = 73) [41]. Mutation of the PIK3CA gene reportedly is also associated with NPC where its elevated expression has been linked to advanced stages in NPC [42]. Other than that, PIK3CA amplification as well as overexpression of its gene product, p110α has also been reported [43]. This may lead to the activation of the downstream cascades of the PI3K pathway. In fact, increased in PIK3CA is associated with poor prognosis of NPC patients [44]. Given the critical role of PIK3CA in NPC, the interaction between bromelain and PIK3CA observed in our study could suggest a mechanism by which bromelain may exert its anticancer effects. Specifically, the strong binding affinity observed in our in silico analysis, characterized by multiple hydrogen bonds and favourable binding energies, hints at a possible inhibitory interaction that may reduce PIK3CA activity or expression in NPC.

The effects of bromelain on PI3K/Akt pathway has been studied before whereby through western blot analysis, it was found that bromelain significantly reduced the expression of PI3K in the carcinogenesis of colorectal cancer [6]. This aligns with our findings, suggesting that bromelain’s interaction with PIK3CA could similarly inhibit this pathway in NPC, potentially leading to decreased tumorigenesis. This information, together with the potential interaction between PIK3CA with bromelain from our result may suggest that bromelain could potentially inhibit the expression of PIK3CA in NPC.

Other proteins also merit attention. EGFR activation triggers signalling cascades, including the PI3K/Akt pathway [45], and its overexpression is common in many cancers including NPC, and is linked with tumour recurrence, migration, and poor prognosis in NPC [14,15,16, 46]. The interaction between bromelain and EGFR observed in our study could indicate that bromelain might interfere with EGFR-mediated activation of the PI3K/Akt pathway, thereby potentially reducing NPC progression. mTOR, part of the PI3K/Akt/mTOR pathway, is associated with poor prognosis in late-stage NPC [47, 48]. Bromelain’s interaction with mTOR may suggest a similar inhibitory effect, potentially disrupting downstream signaling necessary for NPC tumorigenesis. In addition, the overexpression of BCL2, a key player in the apoptosis pathway, in NPC cells has been established since the 90s and has been implicated in NPC’s early stages due to its abnormal expression inhibiting apoptotic activities [49, 50]. Bromelain’s potential interaction with BCL2 might restore apoptotic processes in NPC cells, thus reducing their viability. β-catenin, a crucial member of the Wnt/β-catenin pathway, is associated with poor prognosis in NPC due to its abnormal expression patterns [51, 52] and the interaction of bromelain with β-catenin could suggest that bromelain interferes with the Wnt/β-catenin pathway.

Our findings provide a preliminary mechanistic insight into how bromelain may interact with and potentially modulate the activity of key proteins involved in NPC tumorigenesis. Further studies, including molecular dynamic simulations and experimental assays, are needed to validate bromelain’s anticancer effects on NPC, particularly its interaction with PIK3CA.

Conclusion

In silico data indicate that bromelain interacts with key proteins; PIK3CA, EGFR, mTOR, β-catenin, and BCL2 involved in NPC tumorigenesis, with the strongest binding affinity observed with PIK3CA. These findings suggest a potential mechanism by which bromelain may exert anticancer effects on NPC, particularly through modulation of the PI3K/Akt pathway. However, it is important to note that these results are based on computational predictions and remain hypothetical. Further experimental validation is essential to confirm these interactions and their biological relevance in NPC.

Limitations

The limitation of this study is that it relies solely on in silico methods, which may not fully capture the complexities of in vivo environments. The predictions based on molecular docking and binding affinity calculations require experimental validation through in vitro and in vivo assays to confirm bromelain’s anticancer potential as previously mentioned.

Data availability

All data generated or analysed during this study are included in this published article and its additional files.

Abbreviations

Akt:

Protein kinase B

BCL2:

B-cell lymphoma 2

BFE:

Binding free energy

DTI:

Drug-target interaction

EGFR:

Epidermal growth factor receptor

ELE:

Electrostatic

FFT:

Fast Fourier transform

GB:

Generalised born model polar solvation free energies

H-bond:

Hydrogen bond

HNSCC:

Head and neck squamous cell cancer

mTOR:

Mammalian target of rapamycin

MM-GBSA:

Molecular mechanics-generalised born surface area

NPC:

Nasopharyngeal cancer

PDB:

Protein databank

PI3K:

Phosphatidylinositol 3‑kinase

PIK3CA:

Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha

QMEAN:

Qualitative model energy analysis

RCSB PDB:

Research Collaboratory for Structural Bioinformatics Protein Drug Bank

RMSD:

Root mean square deviation

SA:

Empirical model non-polar solvation free energies

VDW:

Van der Waal

References

  1. Dutta S, Bhattacharyya D. Enzymatic, antimicrobial and toxicity studies of the aqueous extract of Ananas comosus (pineapple) crown leaf. J Ethnopharmacol. 2013;150:451–7.

    Article  CAS  PubMed  Google Scholar 

  2. Batkin S, Taussig SJ, Szekerezes J. (1988) Antimetastatic effect of bromelain with or without its proteolytic and anticoagulant activity. Journal of Cancer Research and Clinical Oncology 1988 114:5 114, 507–508.

  3. Pillai K, Ehteda A, Akhter J, Chua TC, Morris DL. Anticancer effect of bromelain with and without cisplatin or 5-FU on malignant peritoneal mesothelioma cells. Anticancer Drugs. 2014;25:150–60.

    Article  CAS  PubMed  Google Scholar 

  4. Tysnes BB, Maurer HR, Porwol T, Probst B, Bjerkvig R, et al. Bromelain Reversibly inhibits Invasive properties of Glioma cells. Neoplasia. 2001;3:469–79.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Amini A, Ehteda A, Moghaddam SM, Akhter J, Pillai K, et al. Cytotoxic effects of bromelain in human gastrointestinal carcinoma cell lines (MKN45, KATO-III, HT29-5F12, and HT29-5M21). OncoTargets Therapy. 2013;6:403.

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Romano B, Fasolino I, Pagano E, Capasso R, Pace S, et al. The chemopreventive action of bromelain, from pineapple stem (Ananas comosus L.), on colon carcinogenesis is related to antiproliferative and proapoptotic effects. Mol Nutr Food Res. 2014;58:457–65.

    Article  CAS  PubMed  Google Scholar 

  7. Bhui K, Tyagi S, Srivastava AK, Singh M, Roy P, et al. Bromelain inhibits nuclear factor kappa-B translocation, driving human epidermoid carcinoma A431 and melanoma A375 cells through G2/M arrest to apoptosis. Mol Carcinog. 2012;51:231–43.

    Article  CAS  PubMed  Google Scholar 

  8. Bhui K, Tyagi S, Prakash B, Shukla Y. Pineapple bromelain induces autophagy, facilitating apoptotic response in mammary carcinoma cells. BioFactors. 2010;36:474–82.

    Article  CAS  PubMed  Google Scholar 

  9. Dhandayuthapani S, Perez HD, Paroulek A, Chinnakkannu P, Kandalam U et al. (2012) Bromelain-Induced apoptosis in GI-101A breast Cancer cells. https://home.liebertpub.com/jmf 15, 344–9.

  10. Fouz NAYZH-Y. Cytokinetic Study of MCF-7 Cells Treated with commercial and recombinant bromelain. Asian Pac J Cancer Prev. 2013;14:6709–14.

    Article  Google Scholar 

  11. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, et al. 394 CA: a Cancer Journal for clinicians Global Cancer statistics 2018: GLOBOCAN estimates of incidence and Mortality Worldwide for 36 cancers in 185 countries. CA CANCER J CLIN. 2018;68:394–424.

    Article  PubMed  Google Scholar 

  12. Yu MC, Yuan JM. Epidemiology of nasopharyngeal carcinoma. Sem Cancer Biol. 2002;12:421–9.

    Article  Google Scholar 

  13. Chou J, Lin YC, Kim J, You L, Xu Z, et al. Nasopharyngeal carcinoma—review of the molecular mechanisms of tumorigenesis. Head Neck. 2008;30:946–63.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Zhang P, Wu SK, Wang Y, Fan ZX, Li CR, et al. p53, MDM2, eIF4E and EGFR expression in nasopharyngeal carcinoma and their correlation with clinicopathological characteristics and prognosis: a retrospective study. Oncol Lett. 2015;9:113–8.

    Article  PubMed  Google Scholar 

  15. Pan J, Kong L, Lin S, Chen G, Chen Q, et al. The clinical significance of coexpression of cyclooxygenases-2, vascular endothelial growth factors, and epidermal growth factor receptor in nasopharyngeal carcinoma. Laryngoscope. 2008;118:1970–5.

    Article  CAS  PubMed  Google Scholar 

  16. Ma BBY, Poon TCW, To KF, Zee B, Mo FKF, et al. Prognostic significance of tumor angiogenesis, Ki 67, p53 oncoprotein, epidermal growth factor receptor and HER2 receptor protein expression in undifferentiated nasopharyngeal carcinoma–a prospective study. Head Neck. 2003;25:864–72.

    Article  PubMed  Google Scholar 

  17. Dai W, Dong P, Liu J, Gao Y, Hu Y, et al. Euscaphic acid inhibits proliferation and promotes apoptosis of nasopharyngeal carcinoma cells by silencing the PI3K/AKT/mTOR signaling pathway. Am J Translational Res. 2019;11:2090.

    CAS  Google Scholar 

  18. Li G, Wang Y, Liu Y, Su Z, Liu C, et al. Mir-185-3p regulates nasopharyngeal carcinoma radioresistance by targeting WNT2B in vitro. Cancer Sci. 2014;105:1560–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Zhang G, Wang W, Yao C, Zhang S, Liang L, et al. Radiation-resistant cancer stem-like cell properties are regulated by PTEN through the activity of nuclear β-catenin in nasopharyngeal carcinoma. Oncotarget. 2017;8:74661.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Lo KW, To KF, Huang DP. Focus on nasopharyngeal carcinoma. Cancer Cell. 2004;5:423–8.

    Article  CAS  PubMed  Google Scholar 

  21. Hopkins AL. Network pharmacology: the next paradigm in drug discovery. Nat Chem Biology 2008. 2008;4(11 4):682–90.

    Article  CAS  Google Scholar 

  22. Kitchen DB, Decornez H, Furr JR, Bajorath J. (2004) Docking and scoring in virtual screening for drug discovery: methods and applications. Nature Reviews Drug Discovery 2004 3:11 3, 935–949.

  23. Bienert S, Waterhouse A, De Beer TAP, Tauriello G, Studer G, et al. The SWISS-MODEL repository-new features and functionality. Nucleic Acids Research; 2017.

  24. Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Research; 2018.

  25. Benkert P, Biasini M, Schwede T. Toward the estimation of the absolute quality of individual protein structure models. Bioinformatics; 2011.

  26. Morris GM, Ruth H, Lindstrom W, Sanner MF, Belew RK, et al. AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem. 2009;30:2785–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Katchalski-Katzirtt E, Shariv I, Eisenstein M, Friesem AA, Ii CA et al. (1992) Molecular surface recognition: determination of geometric fit between proteins and their ligands by correlation techniques (protein-protein interaction/surface complementarity/macromolecular complex prediction/molecular docking). 89, 2195–9.

  28. Desta IT, Porter KA, Xia B, Kozakov D, Vajda S. Performance and its limits in rigid body protein-protein docking. Structure. 2020;28:1071–e10813.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Kozakov D, Beglov D, Bohnuud T, Mottarella SE, Xia B, et al. How good is automated protein docking? Proteins: Structure, Function and Bioinformatics; 2013.

    Book  Google Scholar 

  30. Kozakov D, Hall DR, Xia B, Porter KA, Padhorny D, et al. The ClusPro web server for protein-protein docking. Nature Protocols; 2017.

  31. Vajda S, Yueh C, Beglov D, Bohnuud T, Mottarella SE, et al. New additions to the ClusPro server motivated by CAPRI. Proteins: Structure, Function and Bioinformatics; 2017.

    Book  Google Scholar 

  32. Weng G, Wang E, Wang Z, Liu H, Zhu F, et al. HawkDock: a web server to predict and analyze the protein–protein complex based on computational docking and MM/GBSA. Nucleic Acids Res. 2019;47:W322–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Kollman PA, Massova I, Reyes C, Kuhn B, Huo S, et al. Calculating structures and free energies of Complex molecules: combining molecular mechanics and Continuum models. Acc Chem Res. 2000;33:889–97.

    Article  CAS  PubMed  Google Scholar 

  34. Wallace AC, Laskowski RA, Thornton JM. LIGPLOT: a program to generate schematic diagrams of protein-ligand interactions the LIGPLOT program automatically generates schematic 2-D representations of protein-ligand complexes from standard Protein Data Bank file input. Protein Eng. 1995;8:127–34.

    Article  CAS  PubMed  Google Scholar 

  35. Laskowski RA, Swindells MB. LigPlot+: multiple LigandÀProtein Interaction diagrams for Drug Discovery. J Chem Inf Model. 2011;51:2778–86.

    Article  CAS  PubMed  Google Scholar 

  36. Mendoza MC, Er EE, Blenis J. The Ras-ERK and PI3K-mTOR pathways: cross-talk and compensation. Trends Biochem Sci. 2011;36:320–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Samuels Y, Velculescu VE. (2004) Oncogenic Mutations of PIK3CA in Human Cancers. https://doiorg.publicaciones.saludcastillayleon.es/10.4161/cc.3.10.1164 3, 1221–1224.

  38. Thorpe LM, Yuzugullu H, Zhao JJ. PI3K in cancer: divergent roles of isoforms, modes of activation and therapeutic targeting. Nat Reviews Cancer 2015. 2014;15(1 15):7–24.

    Google Scholar 

  39. Kang S, Bader AG, Vogt PK. (2005) Phosphatidylinositol 3-kinase mutations identified in human cancer are oncogenic. Proceedings of the National Academy of Sciences 102, 802–807.

  40. Samuels Y, Diaz LA, Schmidt-Kittler O, Cummins JM, Delong L et al. (2005) Mutant PIK3CA promotes cell growth and invasion of human cancer cells.

  41. Chou CC, Chou MJ, Tzen CY. PIK3CA mutation occurs in nasopharyngeal carcinoma but does not significantly influence the disease-specific survival. Med Oncol. 2009;26:322–6.

    Article  CAS  PubMed  Google Scholar 

  42. Wang X, Huang Y, Guo R, Liu Y, Qian Y, et al. Clinicopathological significance of ROCK1 and PIK3CA expression in nasopharyngeal carcinoma. Experimental Therapeutic Med. 2017;13:1064–8.

    Article  CAS  Google Scholar 

  43. Yip WK, He PY, Abdullah MA, Yusoff S, Seow HF. Increased expression of phosphatidylinositol 3-Kinase p110α and gene amplification of PIK3CA in nasopharyngeal carcinoma. Pathol Oncol Res. 2016;22:413–9.

    Article  CAS  PubMed  Google Scholar 

  44. Fendri A, Khabir A, Mnejja W, Sellami-Boudawara T, Daoud J, et al. PIK3CA amplification is predictive of poor prognosis in Tunisian patients with nasopharyngeal carcinoma. Cancer Sci. 2009;100:2034–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Xu MJ, Johnson DE, Grandis JR. EGFR-Targeted therapies in the post-genomic era. Cancer Metastasis Rev. 2017;36:463.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Leong JL, Loh KS, Putti TC, Goh BC, Tan LKS. Epidermal growth factor receptor in undifferentiated carcinoma of the nasopharynx. Laryngoscope. 2004;114:153–7.

    Article  CAS  PubMed  Google Scholar 

  47. Wang Y, Sun J, Yao N. Correlation of the AKT/mTOR signaling pathway with the clinicopathological features and prognosis of nasopharyngeal carcinoma. Eur J Histochemistry: EJH. 2021;65:3304.

    Article  CAS  Google Scholar 

  48. Yu JH, Chen L, Yu JY, Luo HQ, Wang L. PI3K-PKB-mTOR hyperactivation in relation to nasopharyngeal carcinoma progression and prognosis. J Cell Biochem. 2019;120:10186–94.

    Article  CAS  PubMed  Google Scholar 

  49. Kouvidou CH, Kanavaros P, Papaioannou D, Stathopoulos E, Sotsiou F, et al. Expression of bcl-2 and p53 proteins in nasopharyngeal carcinoma. Absence of correlation with the presence of EBV encoded EBER1-2 transcripts and latent membrane protein-1. Clin Mol Pathol. 1995;48:M17.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Sheu LF, Chen A, Meng CL, Ho KC, Lin FG, et al. Analysis of bcl-2 expression in normal, inflamed, dysplastic nasopharyngeal epithelia, and nasopharyngeal carcinoma: association with p53 expression. Hum Pathol. 1997;28:556–62.

    Article  CAS  PubMed  Google Scholar 

  51. Jin PY, Zheng ZH, Lu HJ, Yan J, Zheng GH, et al. Roles of β-catenin, TCF-4, and survivin in nasopharyngeal carcinoma: correlation with clinicopathological features and prognostic significance. Cancer Cell Int. 2019;19:48.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Xu L, Jiang Y, Zheng J, Xie G, Li J, et al. Aberrant expression of β-catenin and E-cadherin is correlated with poor prognosis of nasopharyngeal cancer. Hum Pathol. 2013;44:1357–64.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors acknowledge the Universiti Malaysia Sarawak (UNIMAS) for funding this study via the Tun Ahmad Zaidi Chair Grant (Grant no. F07/TZC/2161/2021).

Funding

This research was supported by the Tun Ahmad Zaidi Chair Grant, funded by Universiti Malaysia Sarawak (UNIMAS), under the grant number F07/TZC/2161/2021.

Open Access funding provided by Universiti Malaysia Sarawak.

Author information

Authors and Affiliations

  1. Faculty of Resource Science and Technology, Universiti Malaysia Sarawak, Kota Samarahan, Sarawak, 94300, Malaysia

    Alyaa Syafiqah Shamsuri & Edmund Ui -Hang Sim

Authors
  1. Alyaa Syafiqah Shamsuri
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Edmund Ui -Hang Sim
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

Through a collaborative effort, both authors, A.S. and E.S. significantly shaped the research, from its initial concept and design to data collection, analysis, and interpretation. The main manuscript was written by A.S., but both authors jointly drafted and refined the manuscript to ensure its intellectual merit. Both authors agreed to submit the work to this journal, approved the final published version and share accountability for all aspects of the research.

Corresponding author

Correspondence to Edmund Ui -Hang Sim.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shamsuri, A.S., Sim, E.U.H. In silico prediction of the action of bromelain on PI3K/Akt signalling pathway to arrest nasopharyngeal cancer oncogenesis by targeting phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha protein. BMC Res Notes 17, 346 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13104-024-06995-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13104-024-06995-2

Keywords

BMC Research Notes

ISSN: 1756-0500

Contact us