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Current Computer-Aided Drug Design

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ISSN (Print): 1573-4099
ISSN (Online): 1875-6697

Research Article

In silico Analysis of Sulpiride, Synthesis, Characterization and In vitro Studies of its Nanoparticle for the Treatment of Schizophrenia

Author(s): Serda Kecel-Gunduz*, Yasemin Budama-Kilinc, Rabia Cakir-Koc, Tolga Zorlu, Bilge Bicak, Yagmur Kokcu, Zeynep Kaya, Aysen E. Ozel and Sevim Akyuz

Volume 16, Issue 2, 2020

Page: [104 - 121] Pages: 18

DOI: 10.2174/1573409915666190627125643

Price: $65

Abstract

Background: Sulpiride, which has selective dopaminergic blocking activity, is a substituted benzamide antipsychotic drug playing a prominent role in the treatment of schizophrenia, which more selective and primarily blocks dopamine D2 and D3 receptor.

Objective: This study has two main objectives, firstly; the molecular modeling studies (MD and Docking, ADME) were conducted to define the molecular profile of sulpiride and sulpiridereceptor interactions, another to synthesize polymeric nanoparticles with chitosan, having the advantage of slow/controlled drug release, to improve drug solubility and stability, to enhance utility and reduce toxicity.

Methods: Molecular dynamic simulation was carried out to determine the conformational change and stability (in water) of the drug and the binding profile of D3 dopamine receptor was determined by molecular docking calculations. The pharmacological properties of the drug were revealed by ADME analysis. The ionic gelation method was used to prepare sulpiride loaded chitosan nanoparticles (CS NPs). The Dynamic Light Scattering (DLS), UV-vis absorption (UV), Scanning Electron Microscopy (SEM), Fourier transform infrared (FT-IR) spectroscopy techniques were carried out to characterize the nanoparticles. In vitro cell cytotoxicity experiments examined with MTT assay on mouse fibroblast (L929), human neuroblastoma (SH-SY5Y) and glioblastoma cells (U-87). The statistical evaluations were produced by ANOVA.

Results: The residues (ASP-119, PHE-417) of D3 receptor provided a stable docking with the drug, and the important pharmacological values (blood brain barrier, Caco-2 permeability and human oral absorption) were also determined. The average particle size, PdI and zeta potential value of sulpiride- loaded chitosan NPs having a spherical morphology were calculated as 96.93 nm, 0.202 and +7.91 mV. The NPs with 92.8% encapsulation and 28% loading efficiency were found as a slow release profile with 38.49% at the end of the 10th day. Due to the formation of encapsulation, the prominent shifted wave numbers for C-O, S-O, S-N stretching, S-N-H bending of Sulpiride were also identified. Mitochondrial activity of U87, SHSY-5Y and L929 cell line were assayed and evaluated using the SPSS program.

Conclusion: To provide more efficient use of Sulpiride having a low bioavailability of the gastrointestinal tract, the nanoparticle formulation with high solubility and bioavailability was designed and synthesized for the first time in this study for the treatment of schizophrenia. In addition to all pharmacological properties of drug, the dopamine blocking activity was also revealed. The toxic effect on different cell lines have also been interpreted.

Keywords: Sulpiride, MD, docking, ADME, chitosan nanoparticles, controlled release system.

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[1]
Vallone, D.; Picetti, R.; Borrelli, E. Structure and function of dopamine receptors. Neurosci. Biobehav. Rev., 2000, 24(1), 125-132.
[http://dx.doi.org/10.1016/S0149-7634(99)00063-9] [PMID: 10654668 ]
[2]
Caley, C.F.; Weber, S.S. Sulpiride: an antipsychotic with selective dopaminergic antagonist properties. Ann. Pharmacother., 1995, 29(2), 152-160.
[http://dx.doi.org/10.1177/106002809502900210] [PMID: 7756714 ]
[3]
Zanatta, G.; Della Flora Nunes, G.; Bezerra, E.M.; da Costa, R.F.; Martins, A.; Caetano, E.W.S.; Freire, V.N.; Gottfried, C. Two binding geometries for risperidone in dopamine d3 receptors: insights on the fast-off mechanism through docking, quantum biochemistry, and molecular dynamics simulations. ACS Chem. Neurosci., 2016, 7(10), 1331-1347.
[http://dx.doi.org/10.1021/acschemneuro.6b00074] [PMID: 27434874 ]
[4]
a)Bhargava, K.; Nath, R.; Seth, P.K.; Pant, K.K. Molecular docking studies of d2 dopamine receptor with risperidone derivatives. Bioinformation, 2014, 10(1), 8-12.
[http://dx.doi.org/10.6026/97320630010008] [PMID: 24516319 ]
b)Gershanik, O.S.; Gomez Arevalo, G.J. Typical and atypical neuroleptics. Handb. Clin. Neurol., 2011, 100, 579-599.
[http://dx.doi.org/10.1016/B978-0-444-52014-2.00042-2] [PMID: 21496609 ]
c)Nasrallah, H.A. Atypical antipsychotic-induced metabolic side effects: in-sights from receptor-binding profiles. Mol. Psychiatry, 2008, 13(1), 27-35.
[http://dx.doi.org/10.1038/sj.mp.4002066] [PMID: 17848919 ]
d)Sumiyoshi, T.; Higuchi, Y.; Uehara, T. Neural basis for the ability of atypical antipsychotic drugs to improve cognition in schizophrenia. Front. Behav. Neurosci., 2013, 7, 140.
[http://dx.doi.org/10.3389/fnbeh.2013.00140] [PMID: 24137114 ]
[5]
Semba, J. Functional role of dopamine D3 receptor in schizophrenia. Nihon Shinkei Seishin Yakurigaku Zasshi=. Yakubutsu Seishin Kodo, 2004, 24(1), 3-11.
[PMID: 15027325 ]
[6]
a)Joyce, J.N. Dopamine D(3) receptor as a therapeutic target for antipsy-chotic and antiparkinsonian drugs. Pharmacol. Ther., 2001, 90, 29.
[http://dx.doi.org/10.1016/S0163-7258(01)00139-5]
b)Micheli, F.; Heidbreder, C. Dopamine D3 receptor antagonists: a patent review (2007 - 2012). Expert opinion on therapeutic patents., 2013, 23(3), 363-381.
c)Nakajima, S.; Gerretsen, P.; Takeuchi, H.; Caravaggio, F. The potential role of dopamine D(3) receptor neurotransmission in cognition. European neuropsychopharmacology: the journal of the European College of Neuropsychopharmacology, 2013, 23(8), 799- 813.
d)Prasad, S.S.; Kojic, L.Z.; Li, P.; Mitchell, D.E. Gene expression patterns during enhanced periods of visual cortex plasticity. Neuroscience, 2002, 111(1), 35-45.
[http://dx.doi.org/10.1016/S0306-4522(01)00570-X] [PMID: 11955710 ]
e)Shimohama, S.; Sawada, H.; Kitamura, Y.; Taniguchi, T. Disease model: parkinson’s disease. Trends Mol. Med., 2003, 9(8), 360-365.
[http://dx.doi.org/10.1016/S1471-4914(03)00117-5] [PMID: 12928038 ]
f)Zarate, C.A., Jr; Payne, J.L.; Singh, J.; Quiroz, J.A. Pramipexole for bipolar II depression: a placebo-controlled proof of concept study. Biol. Psychiatry, 2004, 56(1), 54-60.
[http://dx.doi.org/10.1016/j.biopsych.2004.03.013] [PMID: 15219473 ]
g)Griffon, N; Sokoloff, P.; Diaz, J.; Lévesque, D. The dopamine D3 receptor and schizophrenia: pharmacological, anatomical and genetic approaches. Eur. Neuropsychopharmacol, 1995, 5, Suppl, 3-9.
[http://dx.doi.org/10.1016/0924-977X(95)00030-S] [PMID: 8775753 ]
[7]
Chien, E.Y.T.; Liu, W.; Zhao, Q.; Katritch, V.; Han, G.W.; Hanson, M.A.; Shi, L.; Newman, A.H.; Javitch, J.A.; Cherezov, V.; Stevens, R.C. Structure of the human dopamine D3 receptor in complex with a D2/D3 selective antagonist. Science, 2010, 330(6007), 1091-1095.
[http://dx.doi.org/10.1126/science.1197410] [PMID: 21097933 ]
[8]
a)Robinson, D.H.; Mauger, J. W Drug delivery systems. Am. J. Hosp. Pharm., 1991, 48(10)(Suppl. 1), S14-S23.
[PMID: 1772110 ]
b)Mohammed, M.A.; Syeda, J.T.M.; Wasan, K.M.; Wasan, E.K. An overview of chitosan nanoparticles and its application in non-parenteral drug delivery. Pharmaceutics, 2017, 9(4), 53.
[http://dx.doi.org/10.3390/pharmaceutics9040053] [PMID: 29156634 ]
c)Saraiva, C.; Praça, C.; Ferreira, R.; Santos, T. Nanoparticle-mediated brain drug delivery: Overcoming blood-brain barrier to treat neurodegenerative diseases. J. Control. Release, 2016, 235, 34-47.
[http://dx.doi.org/10.1016/j.jconrel.2016.05.044] [PMID: 27208862 ]
[9]
a)Wang, J.J.; Zeng, Z.W.; Xiao, R.Z.; Xie, T. Recent advances of chitosan nanoparticles as drug carriers. Int. J. Nanomedicine, 2011, 6, 765-774.
[PMID: 21589644 ]
b)Sahin, A.; Yoyen-Ermis, D.; Caban-Toktas, S.; Horzum, U. Evaluation of brain-targeted chitosan nanoparticles through blood-brain barrier cerebral microvessel endothelial cells. J. Microencapsul., 2017, 34(7), 659-666.
[http://dx.doi.org/10.1080/02652048.2017.1375039] [PMID: 28862080 ]
[10]
Van Der Spoel, D.; Lindahl, E.; Hess, B.; Groenhof, G.; Mark, A.E.; Berendsen, H.J.C. GROMACS: fast, flexible, and free. J. Comput. Chem., 2005, 26(16), 1701-1718.
[http://dx.doi.org/10.1002/jcc.20291] [PMID: 16211538 ]
[11]
Frisch, M.J.E.A.; Trucks, G.W.; Schlegel, H.B.; Scuseria, G.E.; Robb, M.A.; Cheeseman, J.R.; Nakatsuji, H. Gaussian 09, revision a. 02, gaussian; IncWallingford: CT, 2009, p. 200.
[12]
van Aalten, D.M.; Bywater, R.; Findlay, J.B.; Hendlich, M.; Hooft, R.W.; Vriend, G. PRODRG, a program for generating molecular topologies and unique molecular descriptors from coordinates of small molecules. J. Comput. Aided Mol. Des., 1996, 10(3), 255-262.
[http://dx.doi.org/10.1007/BF00355047] [PMID: 8808741 ]
[13]
Fletcher, R. Practical Methods of Optimization. Numerical Algorithms, 2nd ed; Wiley, Chichester: Columbia, MO. 2001, 26, p. (2), 198.
[http://dx.doi.org/10.1002/9781118723203]
[14]
Smith, P.E.; van Gunsteren, W.F. The viscosity of SPC and SPC/E water at 277 and 300 K. Chem. Phys. Lett., 1993, 215(4), 315-318.
[http://dx.doi.org/10.1016/0009-2614(93)85720-9]
[15]
Bussi, G.; Donadio, D.; Parrinello, M. Canonical sampling through velocity rescaling. J. Chem. Phys., 2007, 126(1)014101
[http://dx.doi.org/10.1063/1.2408420] [PMID: 17212484 ]
[16]
Parrinello, M.; Rahman, A. Polymorphic Transitions in Single-Crystals - a New Molecular-Dynamics Method. J. Appl. Phys., 1981, 52(12), 7182.
[http://dx.doi.org/10.1063/1.328693]
[17]
Hess, B.; Bekker, H.; Berendsen, H.J.C.; Fraaije, J.G.E.M. LINCS: A linear constraint solver for molecular simulations. J. Comput. Chem., 1997, 18(12), 1463-1472.
[http://dx.doi.org/10.1002/(SICI)1096-987X(199709)18:12<1463:AID-JCC4>3.0.CO;2-H]
[18]
Verlet, L. Computer “Experiments” on Classical Fluids. I. Thermodynamical Properties of Lennard-Jones Molecules. Phys. Rev., 1967, 159(1), 98-103.
[http://dx.doi.org/10.1103/PhysRev.159.98]
[19]
Darden, T.; York, D.; Pedersen, L. Particle mesh ewald - an N.Log(N) method for ewald sums in large systems. J. Chem. Phys., 1993, 98(12), 10089-10092.
[http://dx.doi.org/10.1063/1.464397]
[20]
Humphrey, W.; Dalke, A.; Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph., 1996, 14(1) 33-38-27-28
[http://dx.doi.org/10.1016/0263-7855(96)00018-5] [PMID: 8744570 ]
[21]
a)Friesner, R.A.; Banks, J.L.; Murphy, R.B.; Halgren, T.A. Glide: a new approach for rapid, accurate docking and scor-ing. 1. Method and assessment of docking accuracy. J. Med. Chem., 2004, 47(7), 1739-174.
[http://dx.doi.org/10.1021/jm0306430] [PMID: 15027865 ]
b)Friesner, R.A.; Murphy, R.B.; Repasky, M.P.; Frye, L. L Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complex-es. J. Med. Chem., 2006, 49(21), 6177-6196.
[http://dx.doi.org/10.1021/jm051256o] [PMID: 17034125 ]
c)Halgren, T.A.; Murphy, R.B.; Friesner, R.A.; Beard, H.S. Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. J. Med. Chem., 2004, 47(7), 1750-1759.
[http://dx.doi.org/10.1021/jm030644s] [PMID: 15027866 ]
[22]
Bienert, S.; Waterhouse, A.; de Beer, T.A.; Tauriello, G.; Studer, G.; Bordoli, L.; Schwede, T. The SWISS-MODEL Repository-new features and functionality. Nucleic Acids Res., 2017, 45(D1), D313-D319.
[http://dx.doi.org/10.1093/nar/gkw1132] [PMID: 27899672 ]
[23]
Søndergaard, C.R.; Olsson, M.H.M.; Rostkowski, M.; Jensen, J.H. Improved Treatment of Ligands and Coupling Effects in Empirical Calculation and Rationalization of pKa Values. J. Chem. Theory Comput., 2011, 7(7), 2284-2295.
[http://dx.doi.org/10.1021/ct200133y] [PMID: 26606496 ]
[24]
Sastry, G.M.; Adzhigirey, M.; Day, T.; Annabhimoju, R.; Sherman, W. Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments. J. Comput. Aided Mol. Des., 2013, 27(3), 221-234.
[http://dx.doi.org/10.1007/s10822-013-9644-8] [PMID: 23579614 ]
[25]
Harder, E.; Damm, W.; Maple, J.; Wu, C.; Reboul, M.; Xiang, J.Y.; Wang, L.; Lupyan, D.; Dahlgren, M.K.; Knight, J.L.; Kaus, J.W.; Cerutti, D.S.; Krilov, G.; Jorgensen, W.L.; Abel, R.; Friesner, R.A. OPLS3: A force field providing broad coverage of drug-like small molecules and proteins. J. Chem. Theory Comput., 2016, 12(1), 281-296.
[http://dx.doi.org/10.1021/acs.jctc.5b00864] [PMID: 26584231 ]
[26]
Lipinski, C.; Lombardo, F.; Dominy, B.; Feeney, P. Toward minimalistic modeling of oral drug absorption. Adv. Drug Deliv. Rev., 1997, 23, 3-25.
[http://dx.doi.org/10.1016/S0169-409X(96)00423-1]
[27]
a)Anicuta, S. G.; Dobre, L.; Stroescu, M.; Jipa, I. FOURIER TRANSFORM INFRARED (FTIR) SPECTROSCO-PY FOR CHARACTERIZATION OF ANTIMICROBIAL FILMS CONTAINING CHITOSAN. Analele Universită Ńii din Oradea Fascicula: Ecotoxicologie, Zootehnie şi Tehnologii de Industrie Alimentară, 2010.
b)Dounighi, N.M.; Eskandari, R.; Avadi, M.R.; Zolfagharian, H. Preparation and in vitro characterization of chitosan nanopar-ticles containing Mesobuthus eupeus scorpion venom as an antigen delivery system. J. Venom. Anim. Toxins, 2012, 18(1), 44-52.
c)Liu, C.G.; Desai, K.G.H.; Chen, X.G.; Park, H.J. Preparation and characterization of nanoparticles containing trypsin based on hydrophobically modified chitosan. J. Agric. Food Chem., 2005, 53(5), 1728-1733.
[http://dx.doi.org/10.1021/jf040304v] [PMID: 15740066 ]
d)Mazancová, P.; Némethová, V.; Treľová, D.; Kleščíková, L. Dissociation of chitosan/tripolyphosphate complexes into separate components upon pH elevation. Carbohydr. Polym., 2018, 192, 104-110.
[http://dx.doi.org/10.1016/j.carbpol.2018.03.030] [PMID: 29691001 ]
e)Negrea, P.; Caunii, A.; Sarac, I.; Butnariu, M. Dig. J. Nanomater. Biostruct., 2015, 10(4), 1129-1138.
f)Silva, S.M.; Braga, C.R.; Fook, M.V.; Raposo, C.M. Application of Infrared Spectroscopy to Analysis of Chi-tosan/Clay Nanocomposites; Infrared Spectroscopy-Materials Science, Engineering and Technology. In Tech, 2012.
[http://dx.doi.org/10.5772/35522]
g)Sullivan, D.J.; Cruz-Romero, M.; Collins, T.; Cummins, E. Synthesis of monodisperse chitosan nanoparticles. Food Hydrocoll., 2018, 83, 355-364.
[http://dx.doi.org/10.1016/j.foodhyd.2018.05.010]
[28]
Kecel-Gunduz, S.; Celik, S.; Ozel, A.E.; Akyuz, S. Structural and vibrational spectroscopic elucidation of sulpiride in solid state. J. Biomol. Struct. Dyn., 2015, 33(2), 322-343.
[http://dx.doi.org/10.1080/07391102.2013.874957] [PMID: 24428444 ]
[29]
Sun, L.; Chen, Y.; Zhou, Y.; Guo, D.; Fan, Y.; Guo, F. Asian J. Pharm. Sci., 2017, 12(5), 418-423.
[http://dx.doi.org/10.1016/j.ajps.2017.04.002]
[30]
Van Meerloo, J.; Kaspers, G.J.; Cloos, J. Cell sensitivity assays: the MTT assay.Cancer cell culture; Springer, 2011, pp. 237-245.
[http://dx.doi.org/10.1007/978-1-61779-080-5_20]
[31]
Scheideler, L.; Füger, C.; Schille, C.; Rupp, F.; Wendel, H-P.; Hort, N.; Reichel, H.P.; Geis-Gerstorfer, J. Comparison of different in vitro tests for biocompatibility screening of Mg alloys. Acta Biomater., 2013, 9(10), 8740-8745.
[http://dx.doi.org/10.1016/j.actbio.2013.02.020] [PMID: 23429234 ]

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