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2000
Volume 31, Issue 10
  • ISSN: 1381-6128
  • E-ISSN: 1873-4286

Abstract

Background

About 10-15% of all breast cancers comprise triple-negative breast cancer (TNBC), defined as cancer cells that lack ER, PR, and HER2 protein receptors. Due to the absence of these receptors, treating TNBC using conventional chemotherapy is challenging and, therefore, requires the discovery of novel chemotherapeutic agents derived from natural sources.

Objective

The current work was intended to study the potential phytochemicals of Ajwa dates ( L.) with the predicted potential targets (namely, Akt and PI3K) to determine possible TNBC inhibitors.

Methods

We harnessed network pharmacology, molecular docking, drug-likeness studies, Molecular Dynamics (MD) simulation, and binding free energy (MM-GBSA) calculation to get phytochemicals with potential effects against TNBC. Firstly, molecular docking was performed on 125 phytochemicals against the Akt and PI3K proteins utilizing PyRx. Then, the phytochemicals with the highest binding affinity (≤ -8.1 kcal/mol) were examined for drug-likeness and toxicity profiles. Finally, phytochemicals with optimal drug-likeness and toxicity profiles were studied by Molecular Dynamics (MD) simulation and binding free energy (MM-GBSA) to identify compounds that can form stable complexes.

Results

The results of the network pharmacology revealed that the Akt and PI3K proteins are potential targets of TNBC for the phytochemicals of L. used in this study. The outcomes of molecular docking displayed that among 125 phytochemicals, 42 of them (with a binding affinity ≤ -8.1 kcal/mol) have potentially inhibiting effects on both proteins PI3K and Akt expressed in TNBC. Then, the results of drug-likeness identified seven phytochemicals with optimal pharmacokinetic profiles. Furthermore, toxicity studies showed that three phytochemicals (namely, Chrysoeriol, Daidzein, and Glycitein) did not cause any toxicities. Finally, the Molecular Dynamics (MD) simulation studies and binding free energy (MM-GBSA) verified that Daidzein stayed within the binding cavities of both proteins (Akt and PI3K) by establishing a stable protein-ligand complex during simulation.

Conclusion

Taken together, the current work emphasizes the potential effects of Daidzein from L. against TNBC, and it can be further studied to establish it as a standard chemotherapy for TNBC.

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References

  1. ThunM.J. DeLanceyJ.O. CenterM.M. JemalA. WardE.M. The global burden of cancer: Priorities for prevention.Carcinogenesis201031110011010.1093/carcin/bgp26319934210
    [Google Scholar]
  2. SibuhB.Z. KhannaS. TanejaP. SarkarP. TanejaN.K. Molecular docking, synthesis and anticancer activity of thiosemicarbazone derivatives against MCF-7 human breast cancer cell line.Life Sci.202127311930511930510.1016/j.lfs.2021.11930533675898
    [Google Scholar]
  3. SungH. FerlayJ. SiegelR.L. LaversanneM. SoerjomataramI. JemalA. BrayF. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.CA Cancer J. Clin.202171320924910.3322/caac.2166033538338
    [Google Scholar]
  4. SiegelR.L. MillerK.D. JemalA. Cancer statistics, 2016.CA Cancer J. Clin.201666173010.3322/caac.2133226742998
    [Google Scholar]
  5. PivaR. SpandidosD.A. GambariR. From microRNA functions to microRNA therapeutics: Novel targets and novel drugs in breast cancer research and treatment.Int. J. Oncol.201343498599410.3892/ijo.2013.205923939688
    [Google Scholar]
  6. ChokshiM. PatilB. KhannaR. NeogiS.B. SharmaJ. PaulV.K. ZodpeyS. Health systems in India.J. Perinatol.201636S3S9S1210.1038/jp.2016.18427924110
    [Google Scholar]
  7. HassanpourS.H. DehghaniM. Review of cancer from perspective of molecular.J. Cancer Res. Pract.20174412712910.1016/j.jcrpr.2017.07.001
    [Google Scholar]
  8. DentR. TrudeauM. PritchardK.I. HannaW.M. KahnH.K. SawkaC.A. LickleyL.A. RawlinsonE. SunP. NarodS.A. Triple-negative breast cancer: Clinical features and patterns of recurrence.Clin. Cancer Res.200713154429443410.1158/1078‑0432.CCR‑06‑304517671126
    [Google Scholar]
  9. KurebayashiJ. Possible treatment strategies for triple-negative breast cancer on the basis of molecular characteristics.Breast Cancer200916427528010.1007/s12282‑009‑0111‑219408071
    [Google Scholar]
  10. PascualJ. TurnerN.C. Targeting the PI3-kinase pathway in triple-negative breast cancer.Ann. Oncol.20193071051106010.1093/annonc/mdz13331050709
    [Google Scholar]
  11. ZhangH. JiangR. ZhuJ. SunK. HuangY. ZhouH. ZhengY. WangX. PI3K/Akt/mTOR signaling pathway: An important driver and therapeutic target in triple-negative breast cancer.Breast Cancer202431453955110.1007/s12282‑024‑01567‑538630392
    [Google Scholar]
  12. PozoF.M. HunterT. ZhangY. The ‘New (Nu)-clear’ evidence of the tumor-driving role of PI3K.Acta Materia Med.20221219319610.15212/AMM‑2022‑001337200937
    [Google Scholar]
  13. VagiaE. MahalingamD. CristofanilliM. The landscape of targeted therapies in TNBC.Cancers (Basel)202012491610.3390/cancers1204091632276534
    [Google Scholar]
  14. PolleyM.Y.C. Leon-FerreR.A. LeungS. ChengA. GaoD. SinnwellJ. LiuH. HillmanD.W. Eyman-CaseyA. GilbertJ.A. NegronV. BougheyJ.C. LiuM.C. IngleJ.N. KalariK. CouchF. CarterJ.M. VisscherD.W. NielsenT.O. GoetzM.P. A clinical calculator to predict disease outcomes in women with triple-negative breast cancer.Breast Cancer Res. Treat.2021185355756610.1007/s10549‑020‑06030‑533389409
    [Google Scholar]
  15. CleatorS. HellerW. CoombesR.C. Triple-negative breast cancer: Therapeutic options.Lancet Oncol.20078323524410.1016/S1470‑2045(07)70074‑817329194
    [Google Scholar]
  16. MaqboolM. BekeleF. FekaduG. Treatment strategies against triple-negative breast cancer: An updated review.Breast Cancer (Dove Med. Press)202214152410.2147/BCTT.S34806035046722
    [Google Scholar]
  17. Keihan ShokoohM. EmamiF. JeongJ.H. YookS. Bio-inspired and smart nanoparticles for triple negative breast cancer microenvironment.Pharmaceutics202113228710.3390/pharmaceutics1302028733671698
    [Google Scholar]
  18. CatalanoA. IacopettaD. CeramellaJ. MaricondaA. RosanoC. ScumaciD. SaturninoC. LongoP. SinicropiM. New achievements for the treatment of triple-negative breast cancer.Appl. Sci. (Basel)20221211555410.3390/app12115554
    [Google Scholar]
  19. Al-MahmoodS. SapiezynskiJ. GarbuzenkoO.B. MinkoT. Metastatic and triple-negative breast cancer: Challenges and treatment options.Drug Deliv. Transl. Res.2018851483150710.1007/s13346‑018‑0551‑329978332
    [Google Scholar]
  20. GhoshS. Cisplatin: The first metal based anticancer drug.Bioorg. Chem.20198810292510.1016/j.bioorg.2019.10292531003078
    [Google Scholar]
  21. MallipeddiH. ThyagarajanA. SahuR.P. Implications of Withaferin-A for triple-negative breast cancer chemoprevention.Biomed. Pharmacother.202113411112410.1016/j.biopha.2020.11112433434782
    [Google Scholar]
  22. LiJ. GuA. NongX.M. ZhaiS. YueZ.Y. LiM.Y. LiuY. Six‐membered aromatic nitrogen heterocyclic anti‐tumor agents: Synthesis and applications.Chem. Rec.20232312e20230029310.1002/tcr.20230029338010365
    [Google Scholar]
  23. ShiX.Y. BaoX. LiY. YinC.L. Theanine combined with cisplatin inhibits the proliferation and metastasis of TNBC cells through Akt signaling pathway.Trad. Med. Res.2023852510.53388/TMR20221025001
    [Google Scholar]
  24. O’ReillyD. SendiM.A. KellyC.M. Overview of recent advances in metastatic triple negative breast cancer.World J. Clin. Oncol.202112316418210.5306/wjco.v12.i3.16433767972
    [Google Scholar]
  25. ShahA.N. GradisharW.J. Adjuvant anthracyclines in breast cancer: What is their role?Oncologist201823101153116110.1634/theoncologist.2017‑067230120159
    [Google Scholar]
  26. MoscaL. IlariA. FaziF. AssarafY.G. ColottiG. Taxanes in cancer treatment: Activity, chemoresistance and its overcoming.Drug Resist. Updat.20215410074210.1016/j.drup.2020.10074233429249
    [Google Scholar]
  27. MizrahiD. ParkS.B. LiT. TimminsH.C. TrinhT. AuK. BattagliniE. WyldD. HendersonR.D. GrimisonP. KeH. Geelan-SmallP. MarkerJ. WallB. GoldsteinD. Hemoglobin, body mass index, and age as risk factors for paclitaxel- and oxaliplatin-induced peripheral neuropathy.JAMA Netw. Open202142e203669510.1001/jamanetworkopen.2020.3669533587134
    [Google Scholar]
  28. YangR. ShiY.Y. HanX.H. LiuS. The impact of platinum-containing chemotherapies in advanced triple-negative breast cancer: Meta-analytical approach to evaluating its efficacy and safety.Oncol. Res. Treat.202144633334310.1159/00051535333975311
    [Google Scholar]
  29. EikesdalH.P. YndestadS. ElzawahryA. Llop-GuevaraA. GiljeB. BlixE.S. EspelidH. LundgrenS. GeislerJ. VagstadG. VenizelosA. MinsaasL. LeirvaagB. GudlaugssonE.G. VintermyrO.K. AaseH.S. AasT. BalmañaJ. SerraV. JanssenE.A.M. KnappskogS. LønningP.E. Olaparib monotherapy as primary treatment in unselected triple negative breast cancer.Ann. Oncol.202132224024910.1016/j.annonc.2020.11.00933242536
    [Google Scholar]
  30. HanY. YuX. LiS. TianY. LiuC. New perspectives for resistance to parp inhibitors in triple-negative breast cancer.Front. Oncol.20201057809510.3389/fonc.2020.57809533324554
    [Google Scholar]
  31. McRaeJ. YangQ. CrawfordR. PalomboE. Review of the methods used for isolating pharmaceutical lead compounds from traditional medicinal plants.Environmentalist200727116517410.1007/s10669‑007‑9024‑9
    [Google Scholar]
  32. FellowsL. ScofieldA. Intellectual property rights and biodiversity conservation—an interdisciplinary analysis of the values of medicinal plants.Cambridge, EnglandCambridge University Press19951944
    [Google Scholar]
  33. FarnsworthN.R. AkereleO. BingelA.S. SoejartoD.D. GuoZ. Medicinal plants in therapy.Bull. World Health Organ.19856369659813879679
    [Google Scholar]
  34. BalunasM.J. KinghornA.D. Drug discovery from medicinal plants.Life Sci.200578543144110.1016/j.lfs.2005.09.01216198377
    [Google Scholar]
  35. YadavB. BajajA. SaxenaM. SaxenaA.K. In vitro anticancer activity of the root, stem and leaves of Withania Somnifera against various human cancer cell lines.Indian J. Pharm. Sci.201072565966310.4103/0250‑474X.7854321695006
    [Google Scholar]
  36. PawarA.P. VinugalaD. BothirajaC. Nanocochleates derived from nanoliposomes for paclitaxel oral use: Preparation, characterization, in vitro anticancer testing, bioavailability and biodistribution study in rats.Biomed. Pharmacother.201435021910.1016/j.biopha.2014.11.014
    [Google Scholar]
  37. SonI.H. ChungI.M. LeeS.I. YangH.D. MoonH.I. Pomiferin, histone deacetylase inhibitor isolated from the fruits of Maclura pomifera.Bioorg. Med. Chem. Lett.200717174753475510.1016/j.bmcl.2007.06.06017662606
    [Google Scholar]
  38. BaligaM.S. BaligaB.R.V. KandathilS.M. BhatH.P. VayalilP.K. A review of the chemistry and pharmacology of the date fruits (Phoenix dactylifera L.).Food Res. Int.20114471812182210.1016/j.foodres.2010.07.004
    [Google Scholar]
  39. JassimS.A.A. NajiM.A. In vitro evaluation of the antiviral activity of an extract of date palm ( Phoenix dactylifera L.) pits on a Pseudomonas phage.Evid. Based Complement. Alternat. Med.201071576210.1093/ecam/nem16018955267
    [Google Scholar]
  40. AbdallahE. MusaK. QureshiK. SadeekA. Antimicrobial activity and antioxidant potential of the methanolic leaf extracts of three cultivars of date palm trees (Phoenix dactylifera) from Saudi Arabia.Med. Sci. (Turkey)20176110.5455/medscience.2017.06.8621
    [Google Scholar]
  41. KhanM.A. SinghR. SiddiquiS. AhmadI. AhmadR. UpadhyayS. BarkatM.A. AliA.M.A. ZiaQ. SrivastavaA. TrivediA. HusainI. SrivastavaA.N. MishraD.P. Anticancer potential of Phoenix dactylifera L. seed extract in human cancer cells and pro-apoptotic effects mediated through caspase-3 dependent pathway in human breast cancer MDA-MB-231 cells: An in vitro and in silico investigation.BMC Complement. Med. Ther.20222216810.1186/s12906‑022‑03533‑035291987
    [Google Scholar]
  42. HabibH.M. El-FakharanyE.M. El-GendiH. El-ZineyM.G. El-YazbiA.F. IbrahimW.H. Palm fruit (Phoenix dactylifera L.) Pollen extract inhibits cancer cell and enzyme activities and DNA and protein damage.Nutrients20231511261410.3390/nu1511261437299576
    [Google Scholar]
  43. KhanF. AhmedF. PushparajP.N. AbuzenadahA. KumosaniT. BarbourE. AlQahtaniM. GauthamanK. Ajwa date (Phoenix dactylifera L.) extract inhibits human breast adenocarcinoma (MCF7) cells in vitro by inducing apoptosis and cell cycle arrest.PLoS One2016117e015896310.1371/journal.pone.015896327441372
    [Google Scholar]
  44. KhanM.A. SiddiquiS. AhmadI. SinghR. MishraD.P. SrivastavaA.N. AhmadR. Phytochemicals from Ajwa dates pulp extract induce apoptosis in human triple-negative breast cancer by inhibiting AKT/mTOR pathway and modulating Bcl-2 family proteins.Sci. Rep.20211111032210.1038/s41598‑021‑89420‑z33990623
    [Google Scholar]
  45. MiaM.A.T. MosaibM.G. KhalilM.I. IslamM.A. GanS.H. Potentials and safety of date palm fruit against diabetes: A critical review.Foods2020911155710.3390/foods911155733126433
    [Google Scholar]
  46. MohanrajK. KarthikeyanB.S. Vivek-AnanthR.P. ChandR.P.B. AparnaS.R. MangalapandiP. SamalA. IMPPAT: A curated database of Indian medicinal plants, phytochemistry And Therapeutics.Sci. Rep.201881432910.1038/s41598‑018‑22631‑z29531263
    [Google Scholar]
  47. O’BoyleN.M. BanckM. JamesC.A. MorleyC. VandermeerschT. HutchisonG.R. Open babel: An open chemical toolbox.J. Cheminform.2011313310.1186/1758‑2946‑3‑3321982300
    [Google Scholar]
  48. DallakyanS. OlsonA.J. Small-molecule library screening by docking with PyRx.Chemical BiologyChamSpringer201510.1007/978‑1‑4939‑2269‑7_19
    [Google Scholar]
  49. GfellerD. GrosdidierA. WirthM. DainaA. MichielinO. ZoeteV. SwissTargetPrediction: A web server for target prediction of bioactive small molecules.Nucleic Acids Res.201442W1W32W3810.1093/nar/gku29324792161
    [Google Scholar]
  50. YaoZ.J. DongJ. CheY.J. ZhuM.F. WenM. WangN.N. WangS. LuA.P. CaoD.S. TargetNet: A web service for predicting potential drug–target interaction profiling via multi-target SAR models.J. Comput. Aided Mol. Des.201630541342410.1007/s10822‑016‑9915‑227167132
    [Google Scholar]
  51. SafranM. DalahI. AlexanderJ. RosenN. Iny SteinT. ShmoishM. NativN. BahirI. DonigerT. KrugH. Sirota-MadiA. OlenderT. GolanY. StelzerG. HarelA. LancetD. GeneCards Version 3: The human gene integrator.Database (Oxford)20102010baq02010.1093/database/baq02020689021
    [Google Scholar]
  52. YeungN. ClineM.S. KuchinskyA. SmootM.E. BaderG.D. Exploring biological networks with Cytoscape software.New York, United StatesWiley200810.1002/0471250953.bi0813s23
    [Google Scholar]
  53. ChinC.H. ChenS.H. WuH.H. HoC.W. KoM.T. LinC.Y. cytoHubba: Identifying hub objects and sub-networks from complex interactome.BMC Syst. Biol.20148S4Suppl. 4S1110.1186/1752‑0509‑8‑S4‑S1125521941
    [Google Scholar]
  54. HuangD.W. ShermanB.T. TanQ. KirJ. LiuD. BryantD. GuoY. StephensR. BaselerM.W. LaneH.C. LempickiR.A. DAVID bioinformatics resources: Expanded annotation database and novel algorithms to better extract biology from large gene lists.Nucleic Acids Res.200735Web Server issueSuppl. 2W169W17510.1093/nar/gkm41517576678
    [Google Scholar]
  55. GeS.X. JungD. YaoR. ShinyGO: A graphical gene-set enrichment tool for animals and plants.Bioinformatics20203682628262910.1093/bioinformatics/btz93131882993
    [Google Scholar]
  56. MeringC. HuynenM. JaeggiD. SchmidtS. BorkP. SnelB. STRING: A database of predicted functional associations between proteins.Nucleic Acids Res.200331125826110.1093/nar/gkg03412519996
    [Google Scholar]
  57. RoseY. DuarteJ.M. LoweR. SeguraJ. BiC. BhikadiyaC. ChenL. RoseA.S. BittrichS. BurleyS.K. WestbrookJ.D. RCSB Protein Data Bank: Architectural advances towards integrated searching and efficient access to macromolecular structure data from the PDB archive.J. Mol. Biol.20214331116670410.1016/j.jmb.2020.11.00333186584
    [Google Scholar]
  58. GuexN. PeitschM.C. SWISS‐MODEL and the Swiss‐Pdb Viewer: An environment for comparative protein modeling.Electrophoresis199718152714272310.1002/elps.11501815059504803
    [Google Scholar]
  59. ZhangB. LiH. YuK. JinZ. Molecular docking-based computational platform for high-throughput virtual screening.CCF Trans. High Perform. Comput.202241637410.1007/s42514‑021‑00086‑535039800
    [Google Scholar]
  60. AbdelsattarA.S. DawoudA. HelalM.A. Interaction of nanoparticles with biological macromolecules: A review of molecular docking studies.Nanotoxicology2021151669510.1080/17435390.2020.184253733283572
    [Google Scholar]
  61. GuptaM. SharmaR. KumarA. Docking techniques in pharmacology: How much promising?Comput. Biol. Chem.20187621021710.1016/j.compbiolchem.2018.06.00530067954
    [Google Scholar]
  62. PatilR. DasS. StanleyA. YadavL. SudhakarA. VarmaA.K. Optimized hydrophobic interactions and hydrogen bonding at the target-ligand interface leads the pathways of drug-designing.PLoS One201058e1202910.1371/journal.pone.001202920808434
    [Google Scholar]
  63. KumariR. RathiR. PathakS.R. DalalV. Structural-based virtual screening and identification of novel potent antimicrobial compounds against YsxC of Staphylococcus aureus.J. Mol. Struct.2022125513247610.1016/j.molstruc.2022.132476
    [Google Scholar]
  64. KumariR. DalalV. Identification of potential inhibitors for LLM of Staphylococcus aureus : Structure-based pharmacophore modeling, molecular dynamics, and binding free energy studies.J. Biomol. Struct. Dyn.202240209833984710.1080/07391102.2021.193617934096457
    [Google Scholar]
  65. DainaA. MichielinO. ZoeteV. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules.Sci. Rep.2017714271710.1038/srep4271728256516
    [Google Scholar]
  66. BanerjeeP. EckertA.O. SchreyA.K. PreissnerR. ProTox-II: A webserver for the prediction of toxicity of chemicals.Nucleic Acids Res.201846W1W257W26310.1093/nar/gky31829718510
    [Google Scholar]
  67. BowersK.J. ChowE. XuH. DrorR.O. EastwoodM.P. GregersenB.A. KlepeisJ.L. KolossvaryI. MoraesM.A. SacerdotiF.D. Scalable algorithms for molecular dynamics simulations on commodity clusters.Proceedings of the 2006 ACM/IEEE Conference on Supercomputing11-17 November 2006Tampa, FL, USA20068410.1145/1188455.1188544
    [Google Scholar]
  68. FerreiraL. Dos SantosR. OlivaG. AndricopuloA. Molecular docking and structure-based drug design strategies.Molecules2015207133841342110.3390/molecules20071338426205061
    [Google Scholar]
  69. HildebrandP.W. RoseA.S. TiemannJ.K.S. Bringing molecular dynamics simulation data into view.Trends Biochem. Sci.2019441190291310.1016/j.tibs.2019.06.00431301982
    [Google Scholar]
  70. RasheedM.A. IqbalM.N. SaddickS. AliI. KhanF.S. KanwalS. AhmedD. IbrahimM. AfzalU. AwaisM. Identification of lead compounds against Scm (fms10) in Enterococcus faecium using computer aided drug designing.Life (Basel)20211127710.3390/life1102007733494233
    [Google Scholar]
  71. ShivakumarD. WilliamsJ. WuY. DammW. ShelleyJ. ShermanW. Prediction of absolute solvation free energies using molecular dynamics free energy perturbation and the OPLS force field.J. Chem. Theory Comput.2010651509151910.1021/ct900587b26615687
    [Google Scholar]
  72. WangE. SunH. WangJ. WangZ. LiuH. ZhangJ.Z.H. HouT. End-point binding free energy calculation with MM/PBSA and MM/GBSA: Strategies and applications in drug design.Chem. Rev.2019119169478950810.1021/acs.chemrev.9b0005531244000
    [Google Scholar]
  73. AhammadF. AlamR. MahmudR. AkhterS. TalukderE.K. TonmoyA.M. FahimS. Al-GhamdiK. SamadA. QadriI. Pharmacoinformatics and molecular dynamics simulation-based phytochemical screening of neem plant (Azadiractha indica) against human cancer by targeting MCM7 protein.Brief. Bioinform.2021225bbab09810.1093/bib/bbab09833834183
    [Google Scholar]
  74. NewmanD.J. CraggG.M. Natural products as sources of new drugs from 1981 to 2014.J. Nat. Prod.201679362966110.1021/acs.jnatprod.5b0105526852623
    [Google Scholar]
  75. HamS.L. NasrollahiS. ShahK.N. SoltiszA. ParuchuriS. YunY.H. LukerG.D. BishayeeA. TavanaH. Phytochemicals potently inhibit migration of metastatic breast cancer cells.Integr. Biol.20157779280010.1039/C5IB00121H26120051
    [Google Scholar]
  76. OrtegaM.A. Fraile-MartínezO. AsúnsoloÁ. BujánJ. García-HonduvillaN. CocaS. Signal transduction pathways in breast cancer: The important role of PI3K/Akt/mTOR.J. Oncol.2020202011110.1155/2020/925839632211045
    [Google Scholar]
  77. MoranaO. WoodW. GregoryC.D. The apoptosis paradox in Cancer.Int. J. Mol. Sci.2022233132810.3390/ijms2303132835163253
    [Google Scholar]
  78. AzbazdarY. KarabiciciM. ErdalE. OzhanG. Regulation of Wnt signaling pathways at the plasma membrane and their misregulation in cancer.Front. Cell Dev. Biol.2021963162310.3389/fcell.2021.63162333585487
    [Google Scholar]
  79. ZhangZ. RichmondA. YanC. Immunomodulatory Properties of PI3K/AKT/mTOR and MAPK/MEK/ERK Inhibition Augment Response to Immune Checkpoint Blockade in Melanoma and Triple-Negative Breast Cancer.Int. J. Mol. Sci.20222313735310.3390/ijms2313735335806358
    [Google Scholar]
  80. Yi-LeiZ. Yi-LeiZ. Ruo-ChenW. KenC. Brian ZR. LiS. Ruo-ChenW. KenC. Brian ZR. LiS. Roles of Rap1 signaling in tumor cell migration and invasion.Cancer Biol. Med.2017141909910.20892/j.issn.2095‑3941.2016.008628443208
    [Google Scholar]
  81. KhanM.A. JainV.K. RizwanullahM. AhmadJ. JainK. PI3K/Akt/mTOR pathway inhibitors in triple-negative breast cancer: A review on drug discovery and future challenges.Drug Discov. Today201924112181219110.1016/j.drudis.2019.09.00131520748
    [Google Scholar]
  82. BrendanJM VladimirS MarvinE The performance of current methods in ligand–protein docking.Curr. Sci.2002837834
    [Google Scholar]
  83. JainA.N. NichollsA. Recommendations for evaluation of computational methods.J. Comput. Aided Mol. Des.2008223-413313910.1007/s10822‑008‑9196‑518338228
    [Google Scholar]
  84. PinziL. RastelliG. Molecular docking: Shifting paradigms in drug discovery.Int. J. Mol. Sci.201920184331433110.3390/ijms2018433131487867
    [Google Scholar]
  85. CummingJ.G. DavisA.M. MuresanS. HaeberleinM. ChenH. Chemical predictive modelling to improve compound quality.Nat. Rev. Drug Discov.2013121294896210.1038/nrd412824287782
    [Google Scholar]
  86. van de WaterbeemdH. GiffordE. ADMET in silico modelling: Towards prediction paradise?Nat. Rev. Drug Discov.20032319220410.1038/nrd103212612645
    [Google Scholar]
  87. HouT. WangJ. Structure – ADME relationship: Still a long way to go?Expert Opin. Drug Metab. Toxicol.20084675977010.1517/17425255.4.6.75918611116
    [Google Scholar]
  88. HodgsonJ. ADMET—turning chemicals into drugs.Nat. Biotechnol.200119872272610.1038/9076111479558
    [Google Scholar]
  89. CookD. BrownD. AlexanderR. MarchR. MorganP. SatterthwaiteG. PangalosM.N. Lessons learned from the fate of AstraZeneca’s drug pipeline: A five-dimensional framework.Nat. Rev. Drug Discov.201413641943110.1038/nrd430924833294
    [Google Scholar]
  90. WaringM.J. ArrowsmithJ. LeachA.R. LeesonP.D. MandrellS. OwenR.M. PairaudeauG. PennieW.D. PickettS.D. WangJ. WallaceO. WeirA. An analysis of the attrition of drug candidates from four major pharmaceutical companies.Nat. Rev. Drug Discov.201514747548610.1038/nrd460926091267
    [Google Scholar]
  91. MinD.Y. JungE. AhnS.S. LeeY.H. LimY. ShinS.Y. Chrysoeriol prevents TNFα-induced CYP19 gene expression via EGR-1 Downregulation in MCF7 breast cancer cells.Int. J. Mol. Sci.20202120752310.3390/ijms2120752333053908
    [Google Scholar]
  92. WeiW. HeJ. RuanH. WangY. In vitro and in vivo cytotoxic effects of chrysoeriol in human lung carcinoma are facilitated through activation of autophagy, sub-G1/G0 cell cycle arrest, cell migration and invasion inhibition and modulation of MAPK/ERK signalling pathway.JBUON201924393694231424645
    [Google Scholar]
  93. YangY. ZhouX. XiaoM. HongZ. GongQ. JiangL. ZhouJ. Discovery of chrysoeriol, a PI3K-AKT-mTOR pathway inhibitor with potent antitumor activity against human multiple myeloma cells in vitro.J. Huazhong Univ. Sci. Technolog. Med. Sci.201030673474010.1007/s11596‑010‑0649‑421181363
    [Google Scholar]
  94. WongkularbS. LimboonreungT. TuchindaP. ChongthammakunS. Suppression of PI3K/Akt/mTOR pathway in chrysoeriol-induced apoptosis of rat C6 glioma cells.In Vitro Cell. Dev. Biol. Anim.2022581293610.1007/s11626‑021‑00634‑x34907494
    [Google Scholar]
  95. KaushikS. ShyamH. SharmaR. BalapureA.K. Dietary isoflavone daidzein synergizes centchroman action via induction of apoptosis and inhibition of PI3K/Akt pathway in MCF-7/MDA MB-231 human breast cancer cells.Phytomedicine20184011612410.1016/j.phymed.2018.01.00729496164
    [Google Scholar]
  96. ChoiE.J. KimG.H. Daidzein causes cell cycle arrest at the G1 and G2/M phases in human breast cancer MCF-7 and MDA-MB-453 cells.Phytomedicine200815968369010.1016/j.phymed.2008.04.00618541420
    [Google Scholar]
  97. MontalesiE. CipollettiM. CraccoP. FiocchettiM. MarinoM. Divergent effects of daidzein and its metabolites on estrogen-induced survival of breast cancer cells.Cancers (Basel)202012116710.3390/cancers1201016731936631
    [Google Scholar]
  98. SakamotoT. HoriguchiH. OgumaE. KayamaF. Effects of diverse dietary phytoestrogens on cell growth, cell cycle and apoptosis in estrogen-receptor-positive breast cancer cells.J. Nutr. Biochem.201021985686410.1016/j.jnutbio.2009.06.01019800779
    [Google Scholar]
  99. ZhuY. YaoY. ShiZ. EveraertN. RenG. Synergistic effect of bioactive anticarcinogens from soybean on anti-proliferative activity in MDA-MB-231 and MCF-7 human breast cancer cells in vitro.Molecules2018237155710.3390/molecules2307155729954123
    [Google Scholar]
  100. AljahdaliM.O. MollaM.H.R. AhammadF. Compounds identified from marine mangrove plant (Avicennia alba) as potential antiviral drug candidates against WDSV, an in-silico approach.Mar. Drugs202119525310.3390/md1905025333925208
    [Google Scholar]
  101. BharadwajS. DubeyA. YadavaU. MishraS.K. KangS.G. DwivediV.D. Exploration of natural compounds with anti-SARS-CoV-2 activity via inhibition of SARS-CoV-2 Mpro.Brief. Bioinform.20212221361137710.1093/bib/bbaa38233406222
    [Google Scholar]
  102. BaildyaN. KhanA.A. GhoshN.N. DuttaT. ChattopadhyayA.P. Screening of potential drug from Azadirachta indica (Neem) extracts for SARS-CoV-2: An insight from molecular docking and MD-simulation studies.J. Mol. Struct.2021122712939010.1016/j.molstruc.2020.12939033041371
    [Google Scholar]
  103. ElebeedyD. ElkhatibW.F. KandeilA. GhanemA. KutkatO. AlnajjarR. SalehM.A. Abd El MaksoudA.I. BadawyI. Al-KarmalawyA.A. Anti-SARS-CoV-2 activities of tanshinone IIA, carnosic acid, rosmarinic acid, salvianolic acid, baicalein, and glycyrrhetinic acid between computational and in vitro insights.RSC Advances20211147292672928610.1039/D1RA05268C35492070
    [Google Scholar]
  104. PatelS. MackerellA.D.Jr BrooksC.L.III CHARMM fluctuating charge force field for proteins: II Protein/solvent properties from molecular dynamics simulations using a nonadditive electrostatic model.J. Comput. Chem.200425121504151410.1002/jcc.2007715224394
    [Google Scholar]
  105. MahmudS. RahmanE. NainZ. BillahM. KarmakarS. MohantoS.C. PaulG.K. AminA. AcharjeeU.K. SalehM.A. Computational discovery of plant-based inhibitors against human carbonic anhydrase IX and molecular dynamics simulation.J. Biomol. Struct. Dyn.20213982754277010.1080/07391102.2020.175357932266872
    [Google Scholar]
  106. MahmoudA. MostafaA. Al-KarmalawyA.A. ZidanA. AbulkhairH.S. MahmoudS.H. ShehataM. ElhefnawiM.M. AliM.A. Telaprevir is a potential drug for repurposing against SARS-CoV-2: Computational and in vitro studies.Heliyon202179e0796210.1016/j.heliyon.2021.e0796234518806
    [Google Scholar]
  107. AhmadA. BiersackB. LiY. KongD. BaoB. SchobertR. PadhyeS. SarkarF. Deregulation of PI3K/Akt/mTOR signaling pathways by isoflavones and its implication in cancer treatment.Anticancer. Agents Med. Chem.20131371014102410.2174/1871520611313999011723272911
    [Google Scholar]
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