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Effect of chitosan/albendazole nanocarriers’ solvation by molecular dynamics

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Abstract

Molecular dynamics (MD) simulations of chitosan (CS) and albendazole (ABZ) were performed in the presence (BW1 BW2 and BW3) and absence (B1, B2 and B3) of water to evaluate CS/ABZ interactions in synthesis and solubility through solvation effect of nanoencapsulated ABZ. Molecular chemical reactivity was investigated through DFT-based reactivity descriptors, electrophilicity (ɷ), chemical potential (μ) and chemical hardness (η) as well as values of boundary molecular orbitals HOMO and LUMO that revealed interactions of the amino and hydroxyl groups of CS with groups of nitrogen, sulfur and ABZ ester bond. MD showed BW1 and BW2 with best Radial Distribution (RDF) profiles in aqueous medium as well as solvation energy indicating spontaneous formation of BW1 and BW2 nanoparticles. MD simulations demonstrate CS as a carrier capable of spontaneously encapsulating hydrophobic ABZ molecules in water-containing environments. Thus, a new perspective was presented for planning and design of controlled drug delivery systems with low solubility through MD.

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References

  1. Amidon GL, Lennernäs H, Shah VP, Crison JR (1995) A theoretical basis for a biopharmaceutic drug classification: the correlation of in vitro drug product dissolution and in vivo bioavailability. Pharm Res An Off J Am Assoc Pharm Sci 12:413–420. https://doi.org/10.1023/A:1016212804288

    Article  CAS  Google Scholar 

  2. Ibrahim MA, Shazly GA, El-Badry M (2014) Albendazole microparticles prepared by spray drying technique: improvement of drug dissolution. Trop J Pharm Res 13:1963–1970. https://doi.org/10.4314/tjpr.v13i12.2

    Article  CAS  Google Scholar 

  3. Jung H, Medina L, García L et al (1998) Absorption studies of albendazole and some physicochemical properties of the drug and its metabolite albendazole sulphoxide. J Pharm Pharmacol 50:43–48. https://doi.org/10.1111/j.2042-7158.1998.tb03303.x

    Article  CAS  PubMed  Google Scholar 

  4. Liu Y, Wang XQ, Ren WX et al (2013) Novel albendazole–chitosan nanoparticles for intestinal absorption enhancement and hepatic targeting improvement in rats. J Biomed Mater Res Part B Appl Biomater 101B:998–1005. https://doi.org/10.1002/jbm.b.32908

    Article  CAS  Google Scholar 

  5. Mansuri S, Kesharwani P, Tekade RK, Jain NK (2016) Lyophilized mucoadhesive-dendrimer enclosed matrix tablet for extended oral delivery of albendazole. Eur J Pharm Biopharm 102:202–213. https://doi.org/10.1016/j.ejpb.2015.10.015

    Article  CAS  PubMed  Google Scholar 

  6. Regti A, El Ayouchia HB, Laamari MR et al (2016) Experimental and theoretical study using DFT method for the competitive adsorption of two cationic dyes from wastewaters. Appl Surf Sci 390:311–319. https://doi.org/10.1016/j.apsusc.2016.08.059

    Article  CAS  Google Scholar 

  7. Gawad AEDA, Ibrahim M (2013) Computational studies of the interaction of chitosan nanoparticles and αB-crystallin. Bionanoscience 3:302–311. https://doi.org/10.1007/s12668-013-0096-3

    Article  Google Scholar 

  8. Razmimanesh F, Amjad-Iranagh S, Modarress H (2015) Molecular dynamics simulation study of chitosan and gemcitabine as a drug delivery system. J Mol Model 21:165. https://doi.org/10.1007/s00894-015-2705-2

    Article  CAS  PubMed  Google Scholar 

  9. Wei XH, Niu YP, Xu YY et al (2010) Salicylic acid-grafted chitosan oligosaccharide nanoparticle for paclitaxel delivery. J Bioact Compat Polym 25:319–335. https://doi.org/10.1177/0883911510363548

    Article  CAS  Google Scholar 

  10. Li J, Cai C, Li J et al (2018) Chitosan-based nanomaterials for drug delivery. Molecules 23:2661

    Article  PubMed Central  Google Scholar 

  11. Marpu SB, Benton EN (2018) Shining light on chitosan: A review on the usage of chitosan for photonics and nanomaterials research. Int J Mol Sci 19:1795

    Article  PubMed Central  Google Scholar 

  12. Farshbaf M, Davaran S, Zarebkohan A et al (2018) Significant role of cationic polymers in drug delivery systems. Artif Cells, Nanomedicine Biotechnol 46:1872–1891. https://doi.org/10.1080/21691401.2017.1395344

    Article  CAS  Google Scholar 

  13. de Souza TNV, de Carvalho SML, Vieira MGA et al (2018) Adsorption of basic dyes onto activated carbon: experimental and theoretical investigation of chemical reactivity of basic dyes using DFT-based descriptors. Appl Surf Sci 448:662–670. https://doi.org/10.1016/j.apsusc.2018.04.087

    Article  CAS  Google Scholar 

  14. Vale VV, Cruz JN, Viana GMR et al (2020) Naphthoquinones isolated from Eleutherine plicata herb: in vitro antimalarial activity and molecular modeling to investigate their binding modes. Med Chem Res 29:487–494. https://doi.org/10.1007/s00044-019-02498-z

    Article  CAS  Google Scholar 

  15. dos Santos KLB, Cruz JN, Silva LB et al (2020) Identification of novel chemical entities for adenosine receptor type 2a using molecular modeling approaches. Molecules 25:1245. https://doi.org/10.3390/molecules25051245

    Article  CAS  PubMed Central  Google Scholar 

  16. de Silva NF, da Silva RL, de Almeida KO et al (2017) Study of molecular interactions between Chitosan and Vi Antigen. J Mol Graph Model 72:148–155. https://doi.org/10.1016/j.jmgm.2016.12.015

    Article  CAS  PubMed  Google Scholar 

  17. Suknuntha K, Tantishaiyakul V, Vao-Soongnern V et al (2008) Molecular modeling simulation and experimental measurements to characterize chitosan and poly(vinyl pyrrolidone) blend interactions. J Polym Sci, Part B Polym Phys 46:1258–1264. https://doi.org/10.1002/polb.21460

    Article  CAS  Google Scholar 

  18. Sliwoski G, Kothiwale S, Meiler J, Lowe EW (2014) Computational methods in drug discovery. Pharmacol Rev 66:334–395. https://doi.org/10.1124/pr.112.007336

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Ramezanpour M, Leung SSW, Delgado-Magnero KH et al (2016) Computational and experimental approaches for investigating nanoparticle-based drug delivery systems. Biochim Biophys Acta Biomembr 1858:1688–1709. https://doi.org/10.1016/j.bbamem.2016.02.028

    Article  CAS  Google Scholar 

  20. de Oliveira MS, da Cruz JN, Gomes Silva S et al (2019) Phytochemical profile, antioxidant activity, inhibition of acetylcholinesterase and interaction mechanism of the major components of the Piper divaricatum essential oil obtained by supercritical CO2. J Supercrit Fluids 145:74–84. https://doi.org/10.1016/j.supflu.2018.12.003

    Article  CAS  Google Scholar 

  21. De Campos AM, Diebold Y, Carvalho ELS et al (2004) Chitosan nanoparticles as new ocular drug delivery systems: in vitro stability, in vivo fate, and cellular toxicity. Pharm Res 21:803–810. https://doi.org/10.1023/B:PHAM.0000026432.75781.cb

    Article  PubMed  Google Scholar 

  22. Shu XZ, Zhu KJ (2000) A novel approach to prepare tripolyphosphate/chitosan complex beads for controlled release drug delivery. Int J Pharm 201:51–58. https://doi.org/10.1016/S0378-5173(00)00403-8

    Article  CAS  PubMed  Google Scholar 

  23. Jain V, Bharatam PV (2014) Pharmacoinformatic approaches to understand complexation of dendrimeric nanoparticles with drugs. Nanoscale 6:2476–2501

    Article  CAS  PubMed  Google Scholar 

  24. Da Costa KS, Galúcio JM, Da Costa CHS et al (2019) Exploring the potentiality of natural products from essential oils as inhibitors of odorant-binding proteins: a structure- and ligand-based virtual screening approach to find novel mosquito repellents. ACS Omega 4:22475–22486. https://doi.org/10.1021/acsomega.9b03157

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Costa ACS, Brandão HM, da Silva SR et al (2016) Mucoadhesive nanoparticles: a new perspective for fish drug application. J Fish Dis 39:503–506. https://doi.org/10.1111/jfd.12373

    Article  PubMed  Google Scholar 

  26. Frisch MJ, Trucks GW, Schlegel HB et al (2004) Gaussian 03. Gaussian Inc, Wallingford

    Google Scholar 

  27. Becke AD (1993) Density-functional thermochemistry. III. The role of exact exchange. J Chem Phys 98:5648–5652. https://doi.org/10.1063/1.464913

    Article  CAS  Google Scholar 

  28. Silva SG, Da Costa RA, De Oliveira MS et al (2019) Chemical profile of lippia thymoides, evaluation of the acetylcholinesterase inhibitory activity of its essential oil, and molecular docking and molecular dynamics simulations. PLoS ONE 14:e0213393. https://doi.org/10.1371/journal.pone.0213393

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Neves Cruz J, Santana de Oliveira M, Gomes Silva S et al (2020) Insight into the interaction mechanism of nicotine, NNK, and NNN with cytochrome P450 2A13 based on molecular dynamics simulation. J Chem Inf Model 60:766–776. https://doi.org/10.1021/acs.jcim.9b00741

    Article  CAS  PubMed  Google Scholar 

  30. Ramos RS, Macêdo WJC, Costa JS et al (2019) Potential inhibitors of the enzyme acetylcholinesterase and juvenile hormone with insecticidal activity: study of the binding mode via docking and molecular dynamics simulations. J Biomol Struct Dyn. https://doi.org/10.1080/07391102.2019.1688192

    Article  PubMed  Google Scholar 

  31. Neves Cruz J, da Costa KS, de Carvalho TAA, de Alencar NAN (2020) Measuring the structural impact of mutations on cytochrome P450 21A2, the major steroid 21-hydroxylase related to congenital adrenal hyperplasia. J Biomol Struct Dyn 38:1425–1434. https://doi.org/10.1080/07391102.2019.1607560

    Article  CAS  PubMed  Google Scholar 

  32. de Pinto VS, Araújo JSC, Silva RC et al (2019) In silico study to identify new antituberculosis molecules from natural sources by hierarchical virtual screening and molecular dynamics simulations. Pharmaceuticals 12:36. https://doi.org/10.3390/ph12010036

    Article  CAS  PubMed Central  Google Scholar 

  33. Kutzelnigg W (1992) Atoms in molecules. A quantum theory (Reihe: International Series of Monographs on Chemistry, Vol. 22.) Von R.F.W. Bader. Clarendon Press, Oxford, 1990. XVIII, 438 S., geb. £ 50.00. ISBN 0-19-855168-1. Angew Chemie 104:1423. https://doi.org/10.1002/ange.19921041040

  34. Ruiz-Morales Y (2002) HOMO-LUMO gap as an index of molecular size and structure for polycyclic aromatic hydrocarbons (PAHs) and asphaltenes: a theoretical study. I. J Phys Chem A 106:11283–11308. https://doi.org/10.1021/jp021152e

    Article  CAS  Google Scholar 

  35. Huang Y, Rong C, Zhang R, Liu S (2017) Evaluating frontier orbital energy and HOMO/LUMO gap with descriptors from density functional reactivity theory. J Mol Model 23:3. https://doi.org/10.1007/s00894-016-3175-x

    Article  CAS  PubMed  Google Scholar 

  36. Froimowitz M (1993) HyperChem: a software package for computational chemistry and molecular modeling. Biotechniques 14:1010–1013

    CAS  PubMed  Google Scholar 

  37. Lee C, Yang W, Parr RG (1988) Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density. Phys Rev B 37:785–789. https://doi.org/10.1103/PhysRevB.37.785

    Article  CAS  Google Scholar 

  38. Kruse H, Goerigk L, Grimme S (2012) Why the standard B3LYP/6-31G* model chemistry should not be used in DFT calculations of molecular thermochemistry: understanding and correcting the problem. J Org Chem 77:10824–10834. https://doi.org/10.1021/jo302156p

    Article  CAS  PubMed  Google Scholar 

  39. Tirado-Rives J, Jorgensen WL (2008) Performance of B3LYP density functional methods for a large set of organic molecules. J Chem Theory Comput 4:297–306. https://doi.org/10.1021/ct700248k

    Article  CAS  PubMed  Google Scholar 

  40. Jorgensen WL, Chandrasekhar J, Madura JD et al (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79:926–935. https://doi.org/10.1063/1.445869

    Article  CAS  Google Scholar 

  41. Bredas JL (2014) Mind the gap! Mater Horizons 1:17–19. https://doi.org/10.1039/c3mh00098b

    Article  CAS  Google Scholar 

  42. Malde AK, Zuo L, Breeze M et al (2011) An automated force field topology builder (ATB) and repository: version 1.0. J Chem Theory Comput 7:4026–4037. https://doi.org/10.1021/ct200196m

    Article  CAS  PubMed  Google Scholar 

  43. Lindorff-Larsen K, Piana S, Palmo K et al (2010) Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins Struct Funct Bioinforma 78:1950–1958. https://doi.org/10.1002/prot.22711

    Article  CAS  Google Scholar 

  44. Abraham MJ, Murtola T, Schulz R et al (2015) Gromacs: high performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1–2:19–25. https://doi.org/10.1016/j.softx.2015.06.001

    Article  Google Scholar 

  45. Bussi G, Donadio D, Parrinello M (2007) Canonical sampling through velocity rescaling. J Chem Phys 126:014101. https://doi.org/10.1063/1.2408420

    Article  CAS  PubMed  Google Scholar 

  46. Westergren J, Lindfors L, Höglund T et al (2007) In silico prediction of drug solubility: 1. Free energy of hydration. J Phys Chem B 111:1872–1882. https://doi.org/10.1021/jp064220w

    Article  CAS  PubMed  Google Scholar 

  47. Nilsson F, Söderman O, Johansson I (1996) Physical-chemical properties of the n-octyl β-D-glucoside/water system. A phase diagram, self-diffusion NMR, and SAXS study. Langmuir 12:902–908. https://doi.org/10.1021/la950602+

    Article  CAS  Google Scholar 

  48. Lee KY, Kwon IC, Jo WH, Jeong SY (2005) Complex formation between plasmid DNA and self-aggregates of deoxycholic acid-modified chitosan. Polymer (Guildf) 46:8107–8112. https://doi.org/10.1016/j.polymer.2005.06.082

    Article  CAS  Google Scholar 

  49. Ibrahim M, Mahmoud AA, Osman O et al (2010) Molecular spectroscopic analysis of nano-chitosan blend as biosensor. Spectrochim Acta Part A Mol Biomol Spectrosc 77:802–806. https://doi.org/10.1016/j.saa.2010.08.007

    Article  CAS  Google Scholar 

  50. Shen JW, Li J, Zhao Z et al (2017) Molecular dynamics study on the mechanism of polynucleotide encapsulation by chitosan/639/638/298/54/152/639/638/563/981/639/301/1034/1035/119/118 article. Sci Rep 7:1–9. https://doi.org/10.1038/s41598-017-05197-0

    Article  CAS  Google Scholar 

  51. Deepa G, Sivakumar KC, Sajeevan TP (2018) Molecular simulation and in vitro evaluation of chitosan nanoparticles as drug delivery systems for the controlled release of anticancer drug cytarabine against solid tumours. 3 Biotech 8:493. https://doi.org/10.1007/s13205-018-1510-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Skovstrup S, Hansen SG, Skrydstrup T, Schiøtt B (2010) Conformational flexibility of chitosan: a molecular modeling study. Biomacromol 11:3196–3207. https://doi.org/10.1021/bm100736w

    Article  CAS  Google Scholar 

  53. Hess B, Kutzner C, Van Der Spoel D, Lindahl E (2008) GRGMACS 4: algorithms for highly efficient, load-balanced, and scalable molecular simulation. J Chem Theory Comput 4:435–447. https://doi.org/10.1021/ct700301q

    Article  CAS  PubMed  Google Scholar 

  54. Stephens PJ, Devlin FJ, Chabalowski CF, Frisch MJ (1994) Ab Initio calculation of vibrational absorption and circular dichroism spectra using density functional force fields. J Phys Chem 98:11623–11627. https://doi.org/10.1021/j100096a001

    Article  CAS  Google Scholar 

  55. Ziegler T (1991) Approximate density functional theory as a practical tool in molecular energetics and dynamics. Chem Rev 91:651–667. https://doi.org/10.1021/cr00005a001

    Article  CAS  Google Scholar 

  56. Fukui K (1982) Role of frontier orbitals in chemical reactions. Science (80-) 218:747–754. https://doi.org/10.1126/science.218.4574.747

    Article  CAS  Google Scholar 

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Acknowledgments

All the authors would like to thank the National Council for Scientific and Technological Development (CNPq), EMBRAPA, Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES) (001) and Dean of Graduate Studies and Research (PROPESP/UFPA).

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Correspondence to Roseane Maria Ribeiro-Costa.

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da Silva Costa, A.C., Carvalho, S.C., de Farias Silva, N. et al. Effect of chitosan/albendazole nanocarriers’ solvation by molecular dynamics. Theor Chem Acc 139, 105 (2020). https://doi.org/10.1007/s00214-020-02620-0

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