Skip to content
2000
Volume 21, Issue 10
  • ISSN: 1573-4064
  • E-ISSN: 1875-6638

Abstract

Background

The rise in the frequency of liver cancer all over the world makes it a prominent area of research in the discovery of new drugs or repurposing of existing drugs.

Methods

This article describes the pharmacophore-based structure-activity relationship (3D-QSAR) on the secondary metabolites of to inhibit human liver cancer cell lines Hepatocellular carcinoma (HCC) and hepatoma G2 (HepG2) which represents the molecular level understanding for isolated phytochemicals of The definite features, such as hydrophobic regions, average shape, and active compounds’ electrostatic patterns, were mapped to screen phytochemicals. The 3D-QSAR model generates pharmacophore-based descriptors and alignment of active compounds. Further, docking studies were performed on the active compounds to check out their binding affinity with the active site of the target proteins. It was further validated by applying molecular simulations, and the results were found to be accurate. The geometrical optimization and energy gap of the hit compound were calculated by the density functional theory (DFT). Then, ADMET was performed on this hit compound for drug-like features and toxicity.

Results

Out of 59 compounds, eight ligands were found active after the 3D-QSAR study. After that, molecular docking was performed on the active compounds which were recognized as potential targets, and the docking results showed that compound (also an FDA-approved drug) was the best hit. was found to be the best hit against liver cancer cell lines HCC and HepG2.

Conclusion

This study would be helpful for early drug discovery optimization and lead identification.

© 2025 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/mc/10.2174/0115734064309469240806104435
2025-12-01
2025-11-30

  • From This Site

    /content/journals/mc/10.2174/0115734064309469240806104435
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. LiuC.Y. ChenK.F. ChenP.J. Treatment of liver cancer.Cold Spring Harb. Perspect. Med.201559a02153510.1101/cshperspect.a021535 26187874
     [Google Scholar]
  2. PaulB. LewinskaM. AndersenJ.B. Lipid alterations in chronic liver disease and liver cancer.JHEP Rep.20224610047910.1016/j.jhepr.2022.100479 35469167
     [Google Scholar]
  3. LlovetJ.M. CastetF. HeikenwalderM. MainiM.K. MazzaferroV. PinatoD.J. PikarskyE. ZhuA.X. FinnR.S. Immunotherapies for hepatocellular carcinoma.Nat. Rev. Clin. Oncol.202219315117210.1038/s41571‑021‑00573‑2 34764464
     [Google Scholar]
  4. KimH. Fibrolamellar hepatocellular carcinoma. Atlas of Hepatocellular Carcinoma Pathology.Springer202210.1007/978‑981‑16‑8500‑2_5
     [Google Scholar]
  5. SperandioR.C. PestanaR.C. MiyamuraB.V. KasebA.O. Hepatocellular carcinoma immunotherapy.Annu. Rev. Med.202273126727810.1146/annurev‑med‑042220‑021121 34606324
     [Google Scholar]
  6. LiX. TangJ. MaoY. Incidence and risk factors of drug‐induced liver injury.Liver Int.20224291999201410.1111/liv.15262 35353431
     [Google Scholar]
  7. TuliH.S. RathP. ChauhanA. RamniwasS. VashishthK. VarolM. JaswalV.S. HaqueS. SakK. Phloretin, as a potent anticancer compound: From chemistry to cellular interactions.Molecules20222724881910.3390/molecules27248819 36557950
     [Google Scholar]
  8. YuY. ZhouB. YangY. GuoC.X. ZhaoJ. WangH. Estrogen deficiency aggravates fluoride-induced liver damage and lipid metabolism disorder in rats.Biol. Trace Elem. Res.202220062767277610.1007/s12011‑021‑02857‑1 34392477
     [Google Scholar]
  9. MasubuchiY. IharaA. Protection of mice against carbon tetrachloride-induced acute liver injury by endogenous and exogenous estrogens.Drug Metab. Pharmacokinet.20224610046010.1016/j.dmpk.2022.100460 35820204
     [Google Scholar]
  10. WuY. MinL. XuY. LiuH. ZhouN. HuaZ. MeiC. JiangZ. LiW. Combination of molecular docking and liver transcription sequencing analysis for the evaluation of salt-processed psoraleae fructus-induced hepatotoxicity in ovariectomized mice.J. Ethnopharmacol.202228811495510.1016/j.jep.2021.114955 35032590
     [Google Scholar]
  11. LangE. State-of-the-art review: Sex hormone therapy in trauma-hemorrhage shock: Injury, inflammation, and sepsis.Lab. Clin. Approaches2022573317326
     [Google Scholar]
  12. KurosakiK. UesawaY. Development of in silico prediction models for drug-induced liver malignant tumors based on the activity of molecular initiating events: Biologically interpretable features.J. Toxicol. Sci.2022473899810.2131/jts.47.89 35236804
     [Google Scholar]
  13. RaissaR. RiawanW. SafitriA. MasruriM. BeltranM.A.G. AulanniamA. In vitro and in vivo study: Ethanolic extract leaves of Azadirachta indica Juss. variant of Indonesia and Philippines suppresses tumor growth of hepatocellular carcinoma by inhibiting IL-6/STAT3 signaling.F1000 Res.20221147747710.12688/f1000research.109557.1 37829248
     [Google Scholar]
  14. YeH. ChenT. ZengZ. HeB. YangQ. PanQ. ChenY. WangW. The m6A writers regulated by the IL-6/STAT3 inflammatory pathway facilitate cancer cell stemness in cholangiocarcinoma.Cancer Biol. Med.202118-010.20892/j.issn.2095‑3941.2020.066134347395
     [Google Scholar]
  15. YuanC. JiangB. XuX. WanY. WangL. ChenJ. Anti-human ovarian cancer and cytotoxicity effects of nickel nanoparticles green-synthesized by Alhagi maurorum leaf aqueous extract.J. Exp. Nanosci.202217111312510.1080/17458080.2021.2011860
     [Google Scholar]
  16. AmmarR.B. KhalifaA. AlamerS.A. HussainS.G. HafezA.M. RajendranP. Investigation of the potential anti-urolithiatic activity of Alhagi maurorum (Boiss.) grown wild in Al-Ahsa (Eastern Province), Saudi Arabia.Braz. J. Biol.202484e25910010.1590/1519‑6984.259100 35588519
     [Google Scholar]
  17. ZhaoW. WangL. ChenH. QiL. YangR. OuyangT. NingL. Green synthesis, characterization and determination of anti-prostate cancer, cytotoxicity and antioxidant effects of gold nanoparticles synthesized using Alhagi maurorum.Inorg. Chem. Commun.202214110952510.1016/j.inoche.2022.109525
     [Google Scholar]
  18. MohammedR.K. Abd-alkadhemandN.A.D. Determination of active phytochemical compounds of Alhagi maurorum using gas chromatography-mass spectroscopy.Iraqi J. Sci.2022631879710.24996/ijs.2022.63.1.10
     [Google Scholar]
  19. AwareC.B. PatilD.N. SuryawanshiS.S. MaliP.R. RaneM.R. GuravR.G. JadhavJ.P. Natural bioactive products as promising therapeutics: A review of natural product-based drug development.S. Afr. J. Bot.202215151252810.1016/j.sajb.2022.05.028
     [Google Scholar]
  20. LiuM. LiW. MaH. YangX. LiuA. JiC. Formulation of a novel anti-leukemia drug and evaluation of its therapeutic effects in comparison with Cytarabine.Arab. J. Chem.202215510369010.1016/j.arabjc.2022.103690
     [Google Scholar]
  21. McBee-BlackK. ZhaoL. Using fashion revolution’s who made my clothes campaign to introduce cotton supply chain transparency to upper-level apparel undergraduates.International Textile and Apparel Association Annual Conference Proceedings202210.31274/itaa.13286
     [Google Scholar]
  22. AmmarR.B. Investigation of the potential antiurolytic activity of Alhagi maurorum (Boiss.) grown wild in Al-Ahsa (Eastern Province), Saudi Arabia.Braz. J. Biol.202284259100
     [Google Scholar]
  23. KumbharP. KoleK. YadavT. BhavarA. WaghmareP. BhokareR. ManjappaA. JhaN.K. ChellappanD.K. ShindeS. SinghS.K. DuaK. SalawiA. DisouzaJ. PatravaleV. Drug repurposing: An emerging strategy in alleviating skin cancer.Eur. J. Pharmacol.202292617503110.1016/j.ejphar.2022.175031 35580707
     [Google Scholar]
  24. MostafaI. MohamedN.H. MohamedB. AlmeerR. AbulmeatyM.M.A. BungauS.G. El-ShazlyA.M. YahyaG. In-silico screening of naturally derived phytochemicals against SARS-CoV Main protease.Environ. Sci. Pollut. Res. Int.20222918267752679110.1007/s11356‑021‑17642‑9 34855180
     [Google Scholar]
  25. SinghP. ChauhanS.S. PanditS. SinhaM. GuptaS. GuptaA. ParthasarathiR. The dual role of phytochemicals on SARS-CoV-2 inhibition by targeting host and viral proteins.J. Tradit. Complement. Med.2022121909910.1016/j.jtcme.2021.09.001 34513611
     [Google Scholar]
  26. VelmuruganV. Review of bioinformatic tools used in Computer Aided Drug Design (CADD).World J. Adv. Res. Rev.202214245346510.30574/wjarr.2022.14.2.0394
     [Google Scholar]
  27. AhmadH.M. AbrarM. IzharO. ZafarI. RatherM.A. AlanaziA.M. MalikA. RaufA. BhatM.A. WaniT.A. KhanA.A. Characterization of fenugreek and its natural compounds targeting AKT-1 protein in cancer: Pharmacophore, virtual screening, and MD simulation techniques.J. King Saud Univ. Sci.202234610218610.1016/j.jksus.2022.102186
     [Google Scholar]
  28. VeríssimoG.C. dos Santos JúniorV.S. de AlmeidaI.A.R. RuasM.S.A.M. CoutinhoL.G. de OliveiraR.B. AlvesR.J. MaltarolloV.G. The Brazilian compound library (BraCoLi) database: a repository of chemical and biological information for drug design.Mol. Divers.20222663387339710.1007/s11030‑022‑10386‑9 35089481
     [Google Scholar]
  29. MagalhãesR.P. VieiraT.F. MeloA. SousaS.F. Identification of novel candidates for inhibition of LasR, a quorum-sensing receptor of multidrug resistant Pseudomonas aeruginosa, through a specialized multi-level in silico approach.Mol. Syst. Des. Eng.20227543444610.1039/D2ME00009A
     [Google Scholar]
  30. ChenS.H. BellD.R. LuanB. Understanding interactions between biomolecules and two-dimensional nanomaterials using in silico microscopes.Adv. Drug Deliv. Rev.202218611433610.1016/j.addr.2022.114336 35597306
     [Google Scholar]
  31. RoiC. GajeP.N. CeaușuR.A. RoiA. RusuL.C. BoiaE.R. BoiaS. LucaR.E. RivișM. Heterogeneity of blood vessels and assessment of microvessel Density-MVD in gingivitis.J. Clin. Med.20221110275810.3390/jcm11102758 35628885
     [Google Scholar]
  32. AlamS. KhanF. 3D-QSAR studies on maslinic acid analogs for anticancer activity against breast cancer cell line MCF-7.Sci. Rep.201771601910.1038/s41598‑017‑06131‑0 28729623
     [Google Scholar]
  33. PrakashO. KhanF. SangwanR. MisraL. ANN-QSAR model for virtual screening of androstenedione C-skeleton containing phytomolecules and analogues for cytotoxic activity against human breast cancer cell line MCF-7.Comb. Chem. High Throughput Screen.2013161577210.2174/1386207311316010008 23030276
     [Google Scholar]
  34. KusumaningrumS. The molecular docking of 1,4-naphthoquinone derivatives as inhibitors of polo-like kinase 1 using molegro virtual docker.J. Appl. Pharm. Res.201441104705310.7324/JAPS.2014.4119
     [Google Scholar]
  35. Bitencourt-FerreiraG. AzevedoW.F.d. Molegro virtual docker for docking.Methods Mol. Biol.2019205314916710.1007/978‑1‑4939‑9752‑7_10
     [Google Scholar]
  36. DawoodS. ZarinaS. BanoS. Docking studies of antidepressants against single crystal structure of tryptophan 2, 3-dioxygenase using Molegro Virtual Docker software.Pak. J. Pharm. Sci.2014275 Spec no1529153925176248
     [Google Scholar]
  37. Discovery studio, Accelrys.2008Available from: https://accelrys-discovery-studio-visualizer.software.informer.com/2.5/
  38. ShafiqN. ShakoorB. YaqoobN. ParveenS. BrogiS. Mohammad SalamatullahA. RashidM. BourhiaM. A virtual insight into mushroom secondary metabolites: 3D-QSAR, docking, pharmacophore-based analysis and molecular modeling to analyze their anti-breast cancer potential.J. Biomol. Struct. Dyn.202412210.1080/07391102.2024.2304137 38299565
     [Google Scholar]
  39. RaafatA. MowafyS. AbouseriS.M. FouadM.A. FaragN.A. Lead generation of cysteine based mesenchymal epithelial transition (c-Met) kinase inhibitors: Using structure-based scaffold hopping, 3D-QSAR pharmacophore modeling, virtual screening, molecular docking, and molecular dynamics simulation.Comput. Biol. Med.202214610552610.1016/j.compbiomed.2022.105526 35487125
     [Google Scholar]
  40. LinS-K. Pharmacophore perception, development and use in drug design edited by Osman F. Güner.Molecules20005798798910.3390/50700987
     [Google Scholar]
  41. ZhouD. WeiH. JiangZ. LiX. JiaoK. JiaX. HouY. LiN. Natural potential neuroinflammatory inhibitors from Alhagi sparsifolia Shap.Bioorg. Med. Chem. Lett.201727497397810.1016/j.bmcl.2016.12.075 28073678
     [Google Scholar]
  42. GuijieZ. Isolation and identification of chemical constituents of aerial parts of Alhagi pseudalhagi (MB).Mod Chinese Med201057
     [Google Scholar]
  43. Al-SnafiA.E. Alhagi maurorum as a potential medicinal herb: An Overview.Int. J. Pharm. Sci. Rev. Res.201552130136
     [Google Scholar]
  44. LaghariA.H. MemonS. NelofarA. KhanK.M. Isolation and identification of catechin by a new method from food efficiency stimulating plant Alhagi camelorum.Pak. J. Sci. Ind. Res. Ser. A Phys. Sci.2017602596610.52763/PJSIR.PHYS.SCI.60.2.2017.59.66
     [Google Scholar]
  45. ChakrabortyP. AhilS.B. JammaT. YogeeswariP. Combining structure-based and 3D QSAR pharmacophore models to discover diverse ligands against EGFR in oral cancer.Future Med. Chem.202214746347810.4155/fmc‑2021‑0205 35167330
     [Google Scholar]
  46. ParveenS. BatoolA. ShafiqN. RashidM. SultanA. WondmieG.F. BinJ.Y.A. BrogiS. BourhiaM. Developmental landscape of computational techniques to explore the potential phytochemicals from Punica granatum peels for their antioxidant activity in Alzheimer’s disease.Front. Mol. Biosci.202310125217810.3389/fmolb.2023.1252178 37886033
     [Google Scholar]
  47. RashidM. MaqboolA. ShafiqN. Bin JardanY.A. ParveenS. BourhiaM. NafidiH.A. KhanR.A. The combination of multi-approach studies to explore the potential therapeutic mechanisms of imidazole derivatives as an MCF-7 inhibitor in therapeutic strategies.Front Chem.202311119766510.3389/fchem.2023.1197665 37441272
     [Google Scholar]
  48. DaréJ.K. FreitasM.P. Is conformation relevant for QSAR purposes? 2D Chemical representation in a 3D‐QSAR perspective.J. Comput. Chem.2022431391792210.1002/jcc.26848 35315534
     [Google Scholar]
  49. SonakS.S. Design of anti-fungal agents by 3D-QSAR.Indian J. Chem.20226174475410.56042/ijc.v61i7.64637
     [Google Scholar]
  50. ZiaM. ParveenS. ShafiqN. RashidM. FarooqA. DauelbaitM. ShahabM. SalamatullahA.M. BrogiS. BourhiaM. Exploring Citrus sinensis phytochemicals as potential inhibitors for breast cancer genes BRCA1 and BRCA2 using pharmacophore modeling, molecular docking, MD Simulations, and DFT Analysis.ACS Omega2024922161218210.1021/acsomega.3c05098 38250382
     [Google Scholar]
  51. El MchichiL. TabtiK. KasmiR. El-MernissiR. El AissouqA. En-nahliF. BelhassanA. LakhlifiT. BouachrineM. 3D-QSAR study, docking molecular and simulation dynamic on series of benzimidazole derivatives as anti-cancer agents.J. Indian Chem. Soc.202299910058210.1016/j.jics.2022.100582
     [Google Scholar]
  52. ProiaE. RagnoA. AntoniniL. SabatinoM. MladenovičM. CapobiancoR. RagnoR. Ligand-based and structure-based studies to develop predictive models for SARS-CoV-2 main protease inhibitors through the 3D-Qsar.com portal.J. Comput. Aided Mol. Des.202236748350510.1007/s10822‑022‑00460‑7 35716228
     [Google Scholar]
  53. VermaH. NarendraG. RajuB. KumarM. JainS.K. TungG.K. SinghP.K. SilakariO. 3D‐QSAR and scaffold hopping based designing of benzo[d]ox‐azol‐2(3H)‐one and 2‐oxazolo[4,5‐ b]pyridin‐2(3H)‐one derivatives as selective aldehyde dehydrogenase 1A1 inhibitors: Synthesis and biological evaluation.Arch. Pharm.20223559220010810.1002/ardp.202200108 35618489
     [Google Scholar]
  54. RashidM. SajjadN. ShafiqN. ParveenS. KhanR.A. FarooqA. ShahabM. DawoudT.M. BrogiS. BourhiaM. Multi‐technique approach to identify potent antimicrobial agents from Calotropis procera: Insight into pharmacophore modeling, molecular docking, MD simulation, and DFT approaches.ChemistrySelect202493e20230364210.1002/slct.202303642
     [Google Scholar]
  55. GaoW. MaX. YangH. LuanY. AiH. Molecular engineering and activity improvement of acetylcholinesterase inhibitors: Insights from 3D-QSAR, docking, and molecular dynamics simulation studies.J. Mol. Graph. Model.202211610823910.1016/j.jmgm.2022.108239 35696774
     [Google Scholar]
  56. GünselA. YıldırımA. TaslimiP. ErdenY. Taskin-TokT. PişkinH. BilgiçliA.T. Gülçinİ. NilüferY.M. Cytotoxicity effects and biochemical investigation of novel tetrakis-phthalocyanines bearing 2-thiocytosine moieties with molecular docking studies.Inorg. Chem. Commun.202213810926310.1016/j.inoche.2022.109263
     [Google Scholar]
  57. PetersX.Q. AgoniC. SolimanM.E.S. Unravelling the structural mechanism of action of 5-methyl-5-[4-(4-oxo-3H-quinazolin-2-yl)phenyl]imidazolidine-2,4-dione in dual-targeting tankyrase 1 and 2: A novel avenue in cancer therapy.Cell Biochem. Biophys.202280350551810.1007/s12013‑022‑01076‑2 35637423
     [Google Scholar]
  58. AttiqN. ArshadU. BrogiS. ShafiqN. ImtiazF. ParveenS. RashidM. NoorN. Exploring the anti-SARS-CoV-2 main protease potential of FDA approved marine drugs using integrated machine learning templates as predictive tools.Int. J. Biol. Macromol.20222201415142810.1016/j.ijbiomac.2022.09.086 36122771
     [Google Scholar]
  59. ShafiqN. ZameerR. AttiqN. MoveedA. FarooqA. ImtiazF. ParveenS. RashidM. NoorN. Integration of virtual screening of phytoecdysteroids as androgen receptor inhibitors by 3D-QSAR Model, CoMFA, molecular docking and ADMET analysis: An extensive and interactive machine learning.J. Steroid Biochem. Mol. Biol.202423710642710.1016/j.jsbmb.2023.106427 38008365
     [Google Scholar]
  60. SayinI. RadtkeA.J. VellaL.A. JinW. WherryE.J. BuggertM. BettsM.R. HeratiR.S. GermainR.N. CanadayD.H. Spatial distribution and function of T follicular regulatory cells in human lymph nodes.J. Exp. Med.201821561531154210.1084/jem.20171940 29769249
     [Google Scholar]
  61. ÖzdemirB.C. Pentcheva-HoangT. CarstensJ.L. ZhengX. WuC.C. SimpsonT.R. LaklaiH. SugimotoH. KahlertC. NovitskiyS.V. De Jesus-AcostaA. SharmaP. HeidariP. MahmoodU. ChinL. MosesH.L. WeaverV.M. MaitraA. AllisonJ.P. LeBleuV.S. KalluriR. Depletion of carcinoma-associated fibroblasts and fibrosis induces immunosuppression and accelerates pancreas cancer with reduced survival.Cancer Cell201528683183310.1016/j.ccell.2015.11.002 28843279
     [Google Scholar]
  62. AhmedK. KurnitskiJ. OlesenB. Data for occupancy internal heat gain calculation in main building categories.Data Brief2017151030103410.1016/j.dib.2017.10.036 29167812
     [Google Scholar]
/content/journals/mc/10.2174/0115734064309469240806104435
Loading
Natural Compounds from Alhagi maurorum as Potential HCC and HepG2 Inhibitors: An Integrated Study using Pharmacophore Development, Molecular Docking, MD Simulation, and DFT Approaches
Med. Chem. 21, 1153 (2025); https://doi.org/10.2174/0115734064309469240806104435
/content/journals/mc/10.2174/0115734064309469240806104435
/content/journals/mc/10.2174/0115734064309469240806104435
Loading

Data & Media loading...

Supplements

Supplementary material is available on the publisher’s website along with the published article.

file format download Download

  • Article Type:     Research Article
Keyword(s): carcinoma; hepatoblastoma cell line; Hepatocellular; malignant tumor; molecular electrostatic potential; structure-activity relationship

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test