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2000
Volume 21, Issue 2
  • ISSN: 1570-1646
  • E-ISSN: 1875-6247

Abstract

Background

Parkinson's disease (PD) and its associated symptoms are closely associated with the self-assembly of α-Synuclein (α-Syn). Squalamine is a naturally occurring chemical substance with established antiviral and anticancer properties, and its profound impact on the α-Syn aggregation both and is well studied. Examining its interaction with lipid vesicles, which are known to encourage nucleation, can signify the mechanism of action of squalamine. The squalamine molecule is believed to displace α-Syn from the surfaces of the lipid vesicles, therefore preventing the initial steps in the process of aggregation. Additionally, the squalamine molecule reduces the harmful effects of α-Syn oligomers in human neuroblastoma cells by preventing them from interacting with lipid membranes.

Objective

The aim of this study was to perform computational investigation of the conformational changes of membrane-bound α-Syn in the presence of squalamine inhibitor molecule

Methods

Molecular Dynamics (MD) trajectory analysis was carried out to study the structural change of the α-Syn-squalamine conformers as a function of simulation time. The percentage of the secondary structural components of the α-Syn-squalamine complex was determined. Optimization of small molecule inhibitors was carried out using Density Functional Theory (DFT) analysis. Additionally, the values of electrophilicity (), nucleophilicity (N), Electron affinity (EA), and ionization potential (IP) were calculated.

Results

The docking of the α-Syn-squalamine complex revealed the binding site and the best structure was selected based on the highest docking vina score (-5.8), and the contact residues were listed. From the conformational snapshots of the α-Syn-squalamine complex, it was evident that the α-Syn remained stable, maintaining its integrity throughout the simulation. The α-helical content was found to be retained from the secondary structural content analysis. The and N of the squalamine molecule were calculated to be -0.84 and 3.25, respectively.

Conclusion

Our findings suggest that in the presence of a squalamine inhibitor molecule, α-Syn adopts a helical conformation that ensures stability and may indicate that the squalamine molecule causes gradual displacement of α-Syn across different regions within the lipid membrane.

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References

  1. BreydoL. WuJ.W. UverskyV.N. α-Synuclein misfolding and Parkinson’s disease.Biochim. Biophys. Acta Mol. Basis Dis.20121822226128510.1016/j.bbadis.2011.10.00222024360
    [Google Scholar]
  2. DettmerU. SelkoeD. BartelsT. New insights into cellular α-synuclein homeostasis in health and disease.Curr. Opin. Neurobiol.201636152210.1016/j.conb.2015.07.00726282834
    [Google Scholar]
  3. PerniM. GalvagnionC. MaltsevA. MeislG. MüllerM.B.D. ChallaP.K. KirkegaardJ.B. FlagmeierP. CohenS.I.A. CascellaR. ChenS.W. LimbockerR. SormanniP. HellerG.T. AprileF.A. CremadesN. CecchiC. ChitiF. NollenE.A.A. KnowlesT.P.J. VendruscoloM. BaxA. ZasloffM. DobsonC.M. A natural product inhibits the initiation of α-synuclein aggregation and suppresses its toxicity.Proc. Natl. Acad. Sci.20171146E1009E101710.1073/pnas.161058611428096355
    [Google Scholar]
  4. BuellA.K. GalvagnionC. GasparR. SparrE. VendruscoloM. KnowlesT.P.J. LinseS. DobsonC.M. Solution conditions determine the relative importance of nucleation and growth processes in α-synuclein aggregation.Proc. Natl. Acad. Sci.2014111217671767610.1073/pnas.131534611124817693
    [Google Scholar]
  5. FinkA.L. The aggregation and fibrillation of alpha-synuclein.Acc. Chem. Res.200639962863410.1021/ar050073t16981679
    [Google Scholar]
  6. GalvagnionC. BuellA.K. MeislG. MichaelsT.C.T. VendruscoloM. KnowlesT.P.J. DobsonC.M. Lipid vesicles trigger α-synuclein aggregation by stimulating primary nucleation.Nat. Chem. Biol.201511322923410.1038/nchembio.175025643172
    [Google Scholar]
  7. BryckiB. KoenigH. PospiesznyT. Quaternary alkylammonium conjugates of steroids: Synthesis, molecular structure, and biological studies.Molecules20152011208872090010.3390/molecules20111973526610455
    [Google Scholar]
  8. MooreK.S. WehrliS. RoderH. RogersM. ForrestJ.N.Jr McCrimmonD. ZasloffM. Squalamine: an aminosterol antibiotic from the shark.Proc. Natl. Acad. Sci.19939041354135810.1073/pnas.90.4.13548433993
    [Google Scholar]
  9. KhelaifiaS. DrancourtM. Susceptibility of archaea to antimicrobial agents: applications to clinical microbiology.Clin. Microbiol. Infect.201218984184810.1111/j.1469‑0691.2012.03913.x22748132
    [Google Scholar]
  10. CushnieT.P.T. CushnieB. LambA.J. Alkaloids: An overview of their antibacterial, antibiotic-enhancing and antivirulence activities.Int. J. Antimicrob. Agents201444537738610.1016/j.ijantimicag.2014.06.00125130096
    [Google Scholar]
  11. SchlottmannP.G. AlezzandriniA.A. ZasM. RodriguezF.J. LunaJ.D. WuL. New treatment modalities for neovascular age-related macular degeneration.Asia Pac. J. Ophthalmol.20176651451928933517
    [Google Scholar]
  12. YeungT. GilbertG.E. ShiJ. SilviusJ. KapusA. GrinsteinS. Membrane phosphatidylserine regulates surface charge and protein localization.Science2008319586021021310.1126/science.115206618187657
    [Google Scholar]
  13. SumiokaA. YanD. TomitaS. TARP phosphorylation regulates synaptic AMPA receptors through lipid bilayers.Neuron201066575576710.1016/j.neuron.2010.04.03520547132
    [Google Scholar]
  14. AlexanderR.T. JaumouilléV. YeungT. FuruyaW. PeltekovaI. BoucherA. ZasloffM. OrlowskiJ. GrinsteinS. Membrane surface charge dictates the structure and function of the epithelial Na + /H + exchanger.EMBO J.201130467969110.1038/emboj.2010.35621245831
    [Google Scholar]
  15. DouT. KurouskiD. Phosphatidylcholine and phosphatidylserine uniquely modify the secondary structure of α-synuclein oligomers formed in their presence at the early stages of protein aggregation.ACS Chem. Neurosci.202213162380238510.1021/acschemneuro.2c0035535904551
    [Google Scholar]
  16. LimbockerR. StaatsR. ChiaS. RuggeriF.S. ManniniB. XuC.K. PerniM. CascellaR. BigiA. SasserL.R. BlockN.R. WrightA.K. KreiserR.P. CustyE.T. MeislG. ErricoS. HabchiJ. FlagmeierP. KartanasT. HollowsJ.E. NguyenL.T. LeForteK. BarbutD. KumitaJ.R. CecchiC. ZasloffM. KnowlesT.P.J. DobsonC.M. ChitiF. VendruscoloM. Squalamine and its derivatives modulate the aggregation of amyloid-β and α-synuclein and suppress the toxicity of their oligomers.Front. Neurosci.20211568002610.3389/fnins.2021.68002634220435
    [Google Scholar]
  17. WestC.L. MaoY.K. DelungahawattaT. AminJ.Y. FarhinS. McQuadeR.M. DiwakarlaS. PustovitR. StaniszA.M. BienenstockJ. BarbutD. ZasloffM. FurnessJ.B. KunzeW.A. Squalamine restores the function of the enteric nervous system in mouse models of parkinson’s disease.J. Parkinsons Dis.20201041477149110.3233/JPD‑20207632925094
    [Google Scholar]
  18. Grosso JasutkarH. OhS.E. MouradianM.M. Therapeutics in the pipeline targeting α-synuclein for parkinson’s disease.Pharmacol. Rev.202274120723710.1124/pharmrev.120.00013335017177
    [Google Scholar]
  19. CamilleriM. SubramanianT. PaganF. IsaacsonS. GilR. HauserR.A. FeldmanM. GoldsteinM. KumarR. TruongD. ChhabriaN. WalterB.L. EskenaziJ. RiesenbergR. BurdickD. TseW. MolhoE. RobottomB. BhatiaP. KadimiS. KlosK. ShprecherD. Marquez-MendozaO. HidalgoG. GrillS. LiG. MandellH. HughesM. StephensonS. VandersluisJ. PfefferM. DukerA. ShivkumarV. KinneyW. MacDougallJ. ZasloffM. BarbutD. Oral ENT-01 targets enteric neurons to treat constipation in parkinson disease.Ann. Intern. Med.2022175121666167410.7326/M22‑143836343348
    [Google Scholar]
  20. BermanH.M. BattistuzT. BhatT.N. BluhmW.F. BourneP.E. BurkhardtK. The protein data bank.Acta Crystallogr. D Biol. Crystallogr.200258689990710.1107/S090744490200345112037327
    [Google Scholar]
  21. UlmerT.S. BaxA. ColeN.B. NussbaumR.L. Structure and dynamics of micelle-bound human alpha-synuclein.J. Biol. Chem.2005280109595960310.1074/jbc.M41180520015615727
    [Google Scholar]
  22. BeckeA.D. Density-functional thermochemistry. III. The role of exact exchange.J. Chem. Phys.19939875648565210.1063/1.464913
    [Google Scholar]
  23. WeigendF. AhlrichsR. Balanced basis sets of split valence, triple zeta valence and quadruple zeta valence quality for H to Rn: Design and assessment of accuracy.Phys. Chem. Chem. Phys.20057183297330510.1039/b508541a16240044
    [Google Scholar]
  24. WeigendF. Accurate coulomb-fitting basis sets for H to RN.Phys. Chem. Chem. Phys.2006891057106510.1039/b515623h16633586
    [Google Scholar]
  25. CossiM. RegaN. ScalmaniG. BaroneV. Energies, structures, and electronic properties of molecules in solution with the C-PCM solvation model.J. Comput. Chem.200324666968110.1002/jcc.1018912666158
    [Google Scholar]
  26. GrimmeS. AntonyJ. EhrlichS. KriegH. A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu.J. Chem. Phys.20101321515410410.1063/1.338234420423165
    [Google Scholar]
  27. FrischM.J. TrucksG.W. SchlegelH.B. ScuseriaG.E. RobbM.E. CheesemanJ.R. ScalmaniG. BaroneV. PeterssonG.A. NakatsujiH. LiX. CaricatoM. MarenichA.V. BloinoJ. JaneskoB.G. GompertsR. MennucciB. HratchianH.P. OrtizJ.V. IzmaylovA.F. SonnenbergJ.L. YoungD.W. DingF. LippariniF. EgidiF. GoingsJ. PengB. PetroneA. HendersonT. RanasingheD. ZakrzewskiV.G. GaoJ. RegaN. ZhengG. LiangW. HadaM. EharaM. ToyotaK. FukudaR. HasegawaJ. IshidaM. NakajimaT. HondaY. KitaoO. NakaiH. VrevenT. ThrossellK. MontgomeryJ.A. PeraltaJ.E. OgliaroF. BearparkM.J. HeydJ.J. BrothersE.N. KudinK.N. StaroverovV.N. KeithT.A. KobayashiR. NormandJ. RaghavachariK. RendellA.P. BurantJ.C. IyengarS.S. TomasiJ. CossiM. MillamJ.M. KleneM. AdamoC. CammiR. OchterskiJ.W. MartinR.L. MorokumaR. FarkasO. ForesmanJ.B. FoxD.J. Gaussian 16, Revision B.01.Wallingford, CTGaussian, Inc.2016
    [Google Scholar]
  28. GlendeningE.D. ReedA.E. CarpenterJ.E. WeinholdF. NBO Version 3.1.Gaussian Inc.Pittsburgh2003Available from: https://www.scienceopen.com/document?vid=6652d352-0292-499f-88d6-2221dae56281
    [Google Scholar]
  29. LiuY. YangX. GanJ. ChenS. XiaoZ.X. CaoY. CB- Dock2: improved protein–ligand blind docking by integrating cavity detection, docking and homologous template fitting.Nucleic Acids Res.202250W1W159W16410.1093/nar/gkac39435609983
    [Google Scholar]
  30. JoS. KimT. IyerV.G. ImW. CHARMM-GUI: A web-based graphical user interface for CHARMM.J. Comput. Chem.200829111859186510.1002/jcc.2094518351591
    [Google Scholar]
  31. FuscoG. PapeT. StephensA.D. MahouP. CostaA.R. KaminskiC.F. Kaminski SchierleG.S. VendruscoloM. VegliaG. DobsonC.M. De SimoneA. De SimoneA. Structural basis of synaptic vesicle assembly promoted by α-synuclein.Nat. Commun.2016711256310.1038/ncomms1256327640673
    [Google Scholar]
  32. DasD. MattaparthiV.S.K. Conformational dynamics of A30g α-synuclein that causes familial Parkinson’s disease.J. Biomol. Struct. Dyn.20232023113
    [Google Scholar]
  33. PettersenE.F. GoddardT.D. HuangC.C. CouchG.S. GreenblattD.M. MengE.C. FerrinT.E. UCSF Chimera : A visualization system for exploratory research and analysis.J. Comput. Chem.200425131605161210.1002/jcc.2008415264254
    [Google Scholar]
  34. CaseD.A. Ben-ShalomI.Y. BrozellS.R. CeruttiD.S. CheathamT.E.III CruzeiroV.W.D. DardenT.A. DukeR.E. GhoreishiD. GilsonM.K. GohlkeH. GoetzA.W. GreeneD. HarrisR. HomeyerN. HuangY. IzadiS. KovalenkoA. KurtzmanT. LeeT.S. LeGrandS. LiP. LinC. LiuJ. LuchkoT. LuoR. MermelsteinD.J. MerzK.M. MiaoY. MonardG. NguyenC. NguyenH. OmelyanI. OnufrievA. PanF. QiR. RoeD.R. RoitbergA. SaguiC. Schott-VerdugoS. ShenJ. SimmerlingC.L. SmithJ. Salomon FerrerR. SwailsJ. WalkerR.C. WangJ. WeiH. WolfR.M. WuX. XiaoL. YorkD.M. KollmanP.A. AMBER 2018University of CaliforniaSan Francisco2018Available from: https://ambermd.org/doc12/Amber18.pdf
    [Google Scholar]
  35. HenriquesJ. CragnellC. SkepöM. Molecular dynamics simulations of intrinsically disordered proteins: Force field evaluation and comparison with experiment.J. Chem. Theory Comput.20151173420343110.1021/ct501178z26575776
    [Google Scholar]
  36. DardenT. YorkD. PedersenL. Particle mesh Ewald: An N .log( N ) method for Ewald sums in large systems.J. Chem. Phys.19939812100891009210.1063/1.464397
    [Google Scholar]
  37. Salomon-FerrerR. GötzA.W. PooleD. Le GrandS. WalkerR.C. Routine microsecond molecular dynamics simulations with Amber on gpus. 2. Explicit solvent particle mesh ewald.J. Chem. Theory Comput.2013993878388810.1021/ct400314y26592383
    [Google Scholar]
  38. WangZ. PanH. SunH. KangY. LiuH. CaoD. HouT. fastDRH: A webserver to predict and analyze protein–ligand complexes based on molecular docking and MM/PB(GB)SA computation.Brief. Bioinform.2022235bbac20110.1093/bib/bbac20135580866
    [Google Scholar]
  39. LuJ. KobertzW.R. DeutschC. Mapping the electrostatic potential within the ribosomal exit tunnel.J. Mol. Biol.200737151378139110.1016/j.jmb.2007.06.03817631312
    [Google Scholar]
  40. DomingoL.R. ChamorroE. PérezP. Understanding the reactivity of captodative ethylenes in polar cycloaddition reactions. A theoretical study.J. Org. Chem.200873124615462410.1021/jo800572a18484771
    [Google Scholar]
  41. AksimentievA. SchultenK. Imaging α-hemolysin with molecular dynamics: Ionic conductance, osmotic permeability, and the electrostatic potential map.Biophys. J.20058863745376110.1529/biophysj.104.05872715764651
    [Google Scholar]
  42. ParrR.G. PearsonR.G. Absolute hardness: Companion parameter to absolute electronegativity.J. Am. Chem. Soc.1983105267512751610.1021/ja00364a005
    [Google Scholar]
  43. ParrR.G. SzentpályL. LiuS. Electrophilicity index.J. Am. Chem. Soc.199912191922192410.1021/ja983494x
    [Google Scholar]
  44. ParrR.G. WeitaoY. Density-functional theory of atoms and molecules.Oxford Science PublicationsNew York1995iiv10.1093/oso/9780195092769.001.0001
    [Google Scholar]
  45. WallaceA.C. LaskowskiR.A. ThorntonJ.M. LIGPLOT: A program to generate schematic diagrams of protein-ligand interactions.Protein Eng. Des. Sel.19958212713410.1093/protein/8.2.1277630882
    [Google Scholar]
  46. LandH. HumbleM.S. Yasara: A tool to obtain structural guidance in biocatalytic investigations.Methods Mol. Biol.20181685436710.1007/978‑1‑4939‑7366‑8_429086303
    [Google Scholar]
  47. DasD. BharadwazP. MattaparthiV.S.K. Computational investigation on the effect of the peptidomimetic inhibitors (NPT100-18A and NPT200-11) on the α-synuclein and lipid membrane interactions.J. Biomol. Struct. Dyn.202311210.1080/07391102.2023.226259937768058
    [Google Scholar]
  48. CostantiniS. ColonnaG. FacchianoA.M. ESBRI: A web server for evaluating salt bridges in proteins.Bioinformation20083313713810.6026/9732063000313719238252
    [Google Scholar]
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