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2000
Volume 25, Issue 2
  • ISSN: 1871-5303
  • E-ISSN: 2212-3873

Abstract

Background

Small molecule phytocompounds can potentially ameliorate degenerative changes in cerebral tissues. Thus, the current study aimed to evaluate the neuroprotective efficacy of phytocompounds of methanolic shoots extract of L. (MSECP) in hypercholesterolemia-associated neurodegenerations.

Methods

Phytochemical screening of the extract was made by LCMS/MS and validated by a repository of the chemical library. The hypercholesterolemia was induced through the intraperitoneal administration of poloxamer-407 with a high-fat diet. The assessments were accomplished by following the molecular docking, ADME and molecular dynamics. MMPBSA and PCA (Principal Component Analysis) analyzed the molecular dynamics simulations. Consequently, studies were examined by lipid metabolism, free radical scavenging capabilities and histopathology of brain tissues (cortex and hippocampus).

Results

22 leading phytocompounds were exhibited in the test extract, as revealed by LC-MS/MS scrutiny. Molecular docking evaluated significant interactions of apigenin triacetate with target proteins (HMGCR (HMG-CoA reductase), (AChE-Acetylcholinesterase) and (BuChE- Butyrylcholinesterase). Molecular dynamics examined the interactions through assessments of the radius of gyration, RSMD, RSMF and SASA at 100 ns, which were further analyzed by MMPBSA (Molecular Mechanics Poisson-Boltzmann) and PCA (Principal Component Analysis). Accordingly, the treatment of test extract caused significant alterations in lipid profile, dyslipidemia indices, antioxidant levels and histopathology of brain tissues.

Conclusion

It can be concluded that apigenin triacetate is a potent phytoconstituent of MSEPC and can interact with HMGCR, AChE, and BuChE, which resulted in improved hypercholesterolemia along with neuroprotective ameliorations in the cortex and hippocampus.

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References

  1. RicciarelliR. CanepaE. MarengoB. MarinariU.M. PoliG. PronzatoM.A. DomenicottiC. Cholesterol and Alzheimer’s disease: A still poorly understood correlation.IUBMB Life2012641293193510.1002/iub.109123124820
    [Google Scholar]
  2. SchultzB.G. PattenD.K. BerlauD.J. The role of statins in both cognitive impairment and protection against dementia: A tale of two mechanisms.Transl. Neurodegener.201871510.1186/s40035‑018‑0110‑3
    [Google Scholar]
  3. RalhanI. ChangC.L. Lippincott-SchwartzJ. IoannouM.S. Lipid droplets in the nervous system.J. Cell Biol.20212207e20210213610.1083/jcb.20210213634152362
    [Google Scholar]
  4. WangY. HuH. LiuX. GuoX. Hypoglycemic medicines in the treatment of Alzheimer ’ s disease : Pathophysiological links between AD and glucose metabolism.Front. Pharmacol.202314125
    [Google Scholar]
  5. WuM. ZhaiY. LiangX. ChenW. LinR. MaL. HuangY. ZhaoD. LiangY. ZhaoW. FangJ. FangS. ChenY. WangQ. LiW. Connecting the dots between hypercholesterolemia and alzheimer’s disease: A potential mechanism based on 27-hydroxycholesterol.Front. Neurosci.20221684281410.3389/fnins.2022.84281435464321
    [Google Scholar]
  6. BjörkhemI. MeaneyS. FogelmanA.M. Brain cholesterol: Long secret life behind a barrier.Arterioscler. Thromb. Vasc. Biol.200424580681510.1161/01.ATV.0000120374.59826.1b14764421
    [Google Scholar]
  7. SamejoM.Q. MemonS. BhangerM.I. KhanK.M. Preliminary phytochemicals screening of calligonum polygonoides linn.J. Pharm. Res.2011444024403
    [Google Scholar]
  8. SwarnkarS.K. KhuntetaA. GuptaM.K. JainP. PaliwalS. Pharmacognostic, phytochemical and pharmacological review of “phog”- calligonum polygonoides L.J. Drug Deliv. Ther.201992469473[Internet].10.22270/jddt.v9i2.2384
    [Google Scholar]
  9. ChatrouL.W. TurnerI.M. KlitgaardB.B. MaasP.J.M. UtteridgeT.M.A. A linear sequence to facilitate curation of herbarium specimens of Annonaceae.Kew Bull.20187333910.1007/s12225‑018‑9764‑330956369
    [Google Scholar]
  10. AltemimiA. LakhssassiN. BaharloueiA. WatsonD. LightfootD. Phytochemicals: Extraction, isolation, and identification of bioactive compounds from plant extracts.Plants2017644210.3390/plants604004228937585
    [Google Scholar]
  11. Al-DalahmehY. Al-BatainehN. Al-BalawiS.S. LahhamJ.N. Al-MomaniI.F. Al-SheraidehM.S. MayyasA.S. Abu OrabiS.T. Al-QudahM.A. LC-MS/MS screening, total phenolic, flavonoid and antioxidant contents of crude extracts from three asclepiadaceae species growing in jordan.Molecules202227385910.3390/molecules2703085935164120
    [Google Scholar]
  12. LeeU. KwonM.H. KangH.E. Pharmacokinetic alterations in poloxamer 407-induced hyperlipidemic rats.Xenobiotica Taylor & Francis20194961162510.1080/00498254.2018.1466212
    [Google Scholar]
  13. Kumar NigamP. Calculated low density lipoprotein-cholesterol: Friedewald’s formula versus other modified formulas. Int. J. Life.Sci. Med. Res.20144253110.5963/LSMR0402002
    [Google Scholar]
  14. KamoruA.A. JaphetO.M. AdetunjiA.D. MusaM.A. HammedO.O. AkinlawonA.A. Castelli risk index, atherogenic index of plasma, and atherogenic coefficient: emerging risk predictors of cardiovascular disease in HIV-treated patients.Int. J. Clin. Trials Case Stud20172815
    [Google Scholar]
  15. AllainC.C. PoonL.S. ChanC.S.G. RichmondW. FuP.C. Enzymatic determination of total serum cholesterol.Clin. Chem.197420447047510.1093/clinchem/20.4.4704818200
    [Google Scholar]
  16. MoshidesJ.S. Kinetic enzymatic method for automated determination of HDL cholesterol in plasma.Clin. Chem. Lab. Med.198725958358710.1515/cclm.1987.25.9.5833681196
    [Google Scholar]
  17. GottfriedS.P. RosenbergB. Improved manual spectrophotometric procedure for determination of serum triglycerides.Clin. Chem.19731991077107810.1093/clinchem/19.9.10774744812
    [Google Scholar]
  18. Njie-MbyeY.F. Kulkarni-ChitnisM. OpereC.A. BarrettA. OhiaS.E. Lipid peroxidation: Pathophysiological and pharmacological implications in the eye.Front. Physiol.2013436610.3389/fphys.2013.0036624379787
    [Google Scholar]
  19. RagavendranP. SophiaD. RajC.A. StarlinT.G. Evaluation of enzymatic and non-enzymatic antioxidant properties of Aerva lanata (L)-An intro study.Int. J. Pharm. Pharm. Sci.20124522526
    [Google Scholar]
  20. BenzieI.F.F. StrainJ.J. The ferric reducing ability of plasma (FRAP) as a measure of “antioxidant power”: the FRAP assay.Anal. Biochem.19962391707610.1006/abio.1996.02928660627
    [Google Scholar]
  21. KumarS. ChowdhuryS. RazdanA. KumariD. PurtyR.S. RamH. KumarP. NayakP. ShuklaS.D. Downregulation of candidate gene expression and neuroprotection by piperine in streptozotocin-induced hyperglycemia and memory impairment in rats.Front. Pharmacol.20211159547110.3389/fphar.2020.59547133737876
    [Google Scholar]
  22. RiyadP. PurohitA. KarishmaS. RamH. Atherosclerotic plaque regression and HMG-CoA reductase inhibition potential of curcumin: An integrative omics and in vivo study.J. Appl. Biol. Biotechnol.202210129135
    [Google Scholar]
  23. MadanagopalP. RamprabhuN. JagadeesanR. In silico prediction and structure-based multitargeted molecular docking analysis of selected bioactive compounds against mucormycosis.Bull. Natl. Res. Cent.20224612410.1186/s42269‑022‑00704‑435125861
    [Google Scholar]
  24. RudnitskayaA. TörökB. TörökM. Molecular docking of enzyme inhibitors.Biochem. Mol. Biol. Educ.201038426126510.1002/bmb.2039221567838
    [Google Scholar]
  25. JaipalN. RamH. CharanJ. DixitA. SinghG. SinghB.P. KumarA. PanwarA. HMG‐CoA reductase inhibition medicated hypocholesterolemic and antiatherosclerotic potential of phytoconstituents of an aqueous pod extract of Prosopis cineraria (L.) Druce: In silico, in vitro, and in vivo studies.eFood202236e4210.1002/efd2.42
    [Google Scholar]
  26. Al-KarmalawyA.A. DahabM.A. MetwalyA.M. ElhadyS.S. ElkaeedE.B. EissaI.H. DarwishK.M. Molecular docking and dynamics simulation revealed the potential inhibitory activity of ACEIs against SARS-CoV-2 targeting the hACE2 receptor.Front Chem.2021966123010.3389/fchem.2021.66123034017819
    [Google Scholar]
  27. WangC. GreeneD.A. XiaoL. QiR. LuoR. Recent developments and applications of the MMPBSA method.Front. Mol. Biosci.201848710.3389/fmolb.2017.0008729367919
    [Google Scholar]
  28. PapaleoE. MereghettiP. FantucciP. GrandoriR. De GioiaL. Free-energy landscape, principal component analysis, and structural clustering to identify representative conformations from molecular dynamics simulations: The myoglobin case.J. Mol. Graph. Model.200927888989910.1016/j.jmgm.2009.01.00619264523
    [Google Scholar]
  29. de OliveiraJ. EngelD.F. de PaulaG.C. dos SantosD.B. LopesJ.B. FarinaM. MoreiraE.L.G. de BemA.F. High cholesterol diet exacerbates blood-brain barrier disruption in LDLr–/– Mice: Impact on cognitive function.J. Alzheimers Dis.20207819711510.3233/JAD‑20054132925052
    [Google Scholar]
  30. Álvarez-AlmazánS. Filisola-VillaseñorJ.G. Alemán-González-DuhartD. Tamay-CachF. Mendieta-WejebeJ.E. Current molecular aspects in the development and treatment of diabetes.J. Physiol. Biochem.2020761133510.1007/s13105‑019‑00717‑031925679
    [Google Scholar]
  31. Merino-SerraisP. Loera-ValenciaR. Rodriguez-RodriguezP. Parrado-FernandezC. IsmailM.A. MaioliS. MatuteE. Jimenez-MateosE.M. BjörkhemI. DeFelipeJ. Cedazo-MinguezA. 27-Hydroxycholesterol induces aberrant morphology and synaptic dysfunction in hippocampal neurons.Cereb. Cortex201929142944610.1093/cercor/bhy27430395175
    [Google Scholar]
  32. Loera-ValenciaR. IsmailM.A.M. GoikoleaJ. LodeiroM. MateosL. BjörkhemI. Hypercholesterolemia and 27-hydroxycholesterol increase S100A8 and RAGE expression in the brain: A link between cholesterol, alarmins, and neurodegeneration.Mol. Neurobiol.2021586063607610.1007/s12035‑021‑02521‑8
    [Google Scholar]
  33. KumarS. SinghU.N. DhakalS. Study of oxidative stress in hypercholesterolemia.Artic. Int. J. Contemp. Med. Res.2017424547379
    [Google Scholar]
  34. SinghR. SharadS. KapurS. Free radicals and oxidative stress in neurodegenerative diseases: relevance of dietary antioxidants.J Indian Acad Clin Med.20045218225
    [Google Scholar]
  35. MohammadaliS. HeshamiN. KomakiA. TayebiniaH. Abbasi OshaghiE. KarimiJ. HashemniaM. KhodadadiI. Dill tablet and Ocimum basilicum aqueous extract: Promising therapeutic agents for improving cognitive deficit in hypercholesterolemic rats.J. Food Biochem.20204412e1348510.1111/jfbc.1348533015851
    [Google Scholar]
  36. RamH. JaipalN. KumarP. DekaP. KumarS. KashyapP. KumarS. SinghB.P. AlqarawiA.A. HashemA. TabassumB. Abd-AllahE.F. Dual inhibition of DPP-4 and cholinesterase enzymes by the phytoconstituents of the ethanolic extract of prosopis cineraria pods: Therapeutic implications for the treatment of diabetes-associated neurological impairments.Curr. Alzheimer Res.202016131230124410.2174/156720501666619120316150931797759
    [Google Scholar]
  37. VenkatesanR. JiE. KimS.Y. Phytochemicals that regulate neurodegenerative disease by targeting neurotrophins: A comprehensive review.BioMed Res. Int.2015201512210.1155/2015/81406826075266
    [Google Scholar]
  38. UshaT. ShanmugarajanD. GoyalA.K. KumarC.S. MiddhaS.K. Recent updates on computer-aided drug discovery: Time for a paradigm shift.Curr. Top. Med. Chem.201817303296330710.2174/156802661866618010116365129295698
    [Google Scholar]
  39. KhanG.B. QasimM. RasulA. AshfaqU.A. AlnuqaydanA.M. Identification of lignan compounds as new 6-Phosphogluconate dehydrogenase inhibitors for lung cancer.Metabolites20221313410.3390/metabo1301003436676959
    [Google Scholar]
  40. GenhedenS. RydeU. The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities.Expert Opin. Drug Discov.201510544946110.1517/17460441.2015.103293625835573
    [Google Scholar]
  41. ChughA. SehgalI. KhuranaN. VermaK. RoltaR. VatsP. SalariaD. FadareO.A. AwofisayoO. VermaA. PhartyalR. VermaM. Comparative docking studies of drugs and phytocompounds for emerging variants of SARS-CoV-2.3 Biotech20231313610.1007/s13205‑022‑03450‑636619821
    [Google Scholar]
  42. SnehaP. DossC.G.P. Gliptins in managing diabetes: Reviewing computational strategy.Life Sci.201616610812010.1016/j.lfs.2016.10.00927744054
    [Google Scholar]
  43. SeeX.Y. WenX. WheelerT.A. KleinC.K. GoodpasterJ.D. ReinerB.R. TonksI.A. Iterative supervised principal component analysis driven ligand design for regioselective ti-catalyzed pyrrole synthesis.ACS Catal.20201022135041351710.1021/acscatal.0c0393934327040
    [Google Scholar]
  44. MaisuradzeG.G. LiwoA. ScheragaH.A. Principal component analysis for protein folding dynamics.J. Mol. Biol.2009385131232910.1016/j.jmb.2008.10.01818952103
    [Google Scholar]
  45. MathewB. HaridasA. UçarG. BaysalI. AdeniyiA.A. SolimanM.E.S. JoyM. MathewG.E. LakshmananB. JayaprakashV. Exploration of chlorinated thienyl chalcones: A new class of monoamine oxidase-B inhibitors.Int. J. Biol. Macromol.20169168069510.1016/j.ijbiomac.2016.05.11027262516
    [Google Scholar]
  46. EbenezerO. DamoyiN. ShapiM. Predicting new anti-norovirus inhibitor with the help of machine learning algorithms and molecular dynamics simulation–based model.Front Chem.2021975342710.3389/fchem.2021.75342734869204
    [Google Scholar]
  47. WaltersW.P. Going further than Lipinski’s rule in drug design.Expert Opin. Drug Discov.2012729910710.1517/17460441.2012.64861222468912
    [Google Scholar]
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