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Predictive analysis of chitosan-based nanocomposite biopolymers elastic properties at nano- and microscale

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Abstract

Chitosan nanocomposites mechanical properties play a major role in usage of such materials for specific areas of application, mostly in medicine and development of ecologically-friendly production. Computer-based predictive modelling of such composites will reduce costs of their development. In this paper, a multiscale approach for structural characterization and evaluation of mechanical properties is proposed based on hybrid coarse-grained/all atom molecular dynamics. Chitosan films and fibers are constructed and studied in silico as well as chitosan composites with different types of randomly distributed reinforcing fillers (graphene nanoparticles, graphene oxide nanoparticles, carbon nanotubes, chitin nanoparticles). Young’s moduli are found for such composites, degrees of improvement of mechanical properties and size effects within the framework of proposed methodology are discussed.

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References

  1. Ramakrishna S, Mayer J, Wintermantel E, Leong KW (2001) Biomedical applications of polymer-composite materials: a review. Compos Sci Technol 61:1189–1224. doi:10.1016/S0266-3538(00)00241-4

    Article  CAS  Google Scholar 

  2. Goosen MFA (1996) Applications of Chitin and Chitosan. CRC Press

  3. Kossovich LY, Salkovskiy YE, Kirillova IV (2010) Electrospun Chitosan nanofiber materials as burn dressing. IFMBE Proc 31:1212–1214. doi:10.1007/978-3-642-14515-5-307

    Article  Google Scholar 

  4. Baldrick P (2009) The safety of chitosan as a pharmaceutical excipient. Regul Toxicol Pharmacol 56(3):290–299. doi:10.1016/j.yrtph.2009.09.015

    Article  Google Scholar 

  5. Agnihotri SA, Mallikarjuna NN, Aminabhavi TM (2004) Recent advances on chitosan-based micro- and nanoparticles in drug delivery. J Control Release 100(1):5–28. doi:10.1016/j.jconrel.2004.08.010

    Article  CAS  Google Scholar 

  6. Croisier F, Jérôme C (2013) Chitosan-based biomaterials for tissue engineering. Eur Polym J 49 (4):780–792. doi:10.1016/j.eurpolymj.2012.12.009

    Article  CAS  Google Scholar 

  7. Liang D, Hsiao BS, Chu B (2007) Functional electrospun nanofibrous scaffolds for biomedical applications. Adv Drug Deliver 59:1392–1412. doi:10.1016/j.addr.2007.04.021

    Article  CAS  Google Scholar 

  8. Chuang Y-J, Chen M-J, Chen P-R (2014) Fabrication and permeability characteristics of microdialysis probe using chitosan nanoporous membrane. J Nanomater 2014:968098. doi:10.1155/2014/968098

    Google Scholar 

  9. Razmimanesh F, Amjad-Iranagh S, Modarress H (2015) Molecular dynamics simulation study of chitosan and gemcitabine as a drug delivery system. J Mol Mod 21(7). doi:10.1007/s00894-015-2705-2

  10. Cunha RA, Franca EF, Soares TA, Rusu VH, Pontes FJS, Lins RD (2012) The molecular structure and conformational dynamics of chitosan polymers: an integrated perspective from experiments and computational simulations. In: Karunaratne DN (ed) The Complex World of Polysaccharide. InTech. doi:10.5772/51803

  11. Ahmad S, Johnson BF, Mackay SP et al (2010) In silico modeling of drug-polymer interactions for pharmaceutical formulations. J R Soc Interface 7(4):423–433. doi:10.1098/rsif.2010.0190.focus

    Article  Google Scholar 

  12. Subashini M, Devarajan PV, Sonavane GS, Doble M (2011) Molecular dynamics simulation of drug uptake by polymer. J Mol Mod 17(5). doi:10.1007/s00894-010-0811-8

  13. Marrink SJ, de Vries AH, Mark AE (2004) Coarse grained model for semiquantitative lipid simulations. J Phys Chem B 108:750–760. doi:10.1021/jp036508g

  14. Tozzini V (2005) Coarse-grained models for proteins. Curr Opin Chem Biol 15:144–150. doi:10.1016/j.sbi.2005.02.005

    CAS  Google Scholar 

  15. Nielsen SO, Lopez CF, Srinivas G, Klein ML (2004) Coarse grain models and the computer simulation of soft materials. J Phys Condens Matter 16:481–512. doi:10.1088/0953-8984/16/15/R03

    Article  Google Scholar 

  16. Rudnicki WR, Bakalarski G, Lesyng B (2000) A mezoscopic model of nucleic acids. Part 1: Lagrangian and quaternion molecular dynamics. J Biomol Struct Dyn 17:1097–1108. doi:10.1080/07391102.2000.10506595

    Article  CAS  Google Scholar 

  17. Voth GA (2008) Coarse-graining of condensed phase and biomolecular systems. CRC Press

  18. Izvekov S, Voth GA (2005) A multiscale coarse-graining method for biomolecular systems. J Phys Chem B 109:2469–2473. doi:10.1021/jp044629q

    Article  CAS  Google Scholar 

  19. Liwo A, Czaplewski C, Pillardy J, Scheraga HA (2001) Cumulant-based expressions for the multibody terms for the correlation between local and electrostatic interactions in the united-residue force field. J Chem Phys 115:2323–2347. doi:10.1063/1.1383989

    Article  CAS  Google Scholar 

  20. Izvekov S, Parrinello M, Burnham CJ, Voth GA (2004) Effective force fields for condensed phase systems from ab initio molecular dynamics simulation: a new method for force-matching. J Chem Phys 120:10896–10913. doi:10.1063/1.1739396

    Article  CAS  Google Scholar 

  21. Rzepiela A, Louhivuori M, Peter C, Marrink S (2011) Hybrid simulations: combining atomistic and coarse-grained force fields using virtual sites. Phys Chem Chem Phys 13:10437–10448. doi:10.1039/c0cp02981e

    Article  CAS  Google Scholar 

  22. Predeus AV, Gul S, Gopal SM, Feig M (2012) Conformational sampling of peptides in the presence of protein crowders from AA/CG-multiscale simulations. J Phys Chem B 116(29):8610–8620. doi:10.1021/jp300129u

    Article  CAS  Google Scholar 

  23. Theodoru D (2005) Multiscale modeling of polymers. In: Yip S (ed) Handbook of materials modeling. Springer, Netherlands, pp 2757–2761

    Chapter  Google Scholar 

  24. Li Q, Zhou J, Zhang L (2009) Structure and properties of the nanocomposite films of chitosan reinforced with cellulose whiskers. J Polym Sci Part B Polym Phys 47:1069–1077. doi:10.1002/polb.21711

    Article  CAS  Google Scholar 

  25. Thostenson ET, Li C, Chou T-W (2005) Nanocomposites in context. Compos Sci Technol 65:491–516. doi:10.1016/j.compscitech.2004.11.003

    Article  CAS  Google Scholar 

  26. Fan H, Wang L, Zhao K, Li N, Shi Z, Ge Z, Jin Z (2010) Fabrication, mechanical properties, and biocompatibility of graphene-reinforced chitosan composites. Biomacromolecules 11:2345–2351. doi:10.1021/bm100470q

    Article  CAS  Google Scholar 

  27. Manchado MAL, Valentini L, Biagiotti J, Kenny JM (2005) Thermal and mechanical properties of single-walled carbon nanotubes-polypropylene composites prepared by melt processing. Carbon 43:1499–1505. doi:10.1016/j.carbon.2005.01.031

    Article  CAS  Google Scholar 

  28. Ebrahimi S, Ghafoori-Tabrizi K, Rafii-Tabar H (2012) Multi-scale computational modelling of the mechanical behaviour of the chitosan biological polymer embedded with graphene and carbon nanotube. Comp Mater Sci 53 (1):347–353. doi:10.1016/j.commatsci.2011.08.034

    Article  CAS  Google Scholar 

  29. Kossovich EL, Kirillova IV, Kossovich LYu, Safonov RA, Ukrainskiy DV, Apshtein SA (2014) Hybrid coarse-grained/atomistic model of chitosan + carbon nanostructures? composites. J Mol Mod 20(10):2452. doi:10.1007/s00894-014-2452-9

    Article  Google Scholar 

  30. Plimpton S (1995) Fast parallel algorithms for short-range molecular dynamics. J Comp Phys 117:1–19. doi:10.1006/jcph.1995.1039

    Article  CAS  Google Scholar 

  31. Dennington R, Keith T, Millam J (2009) GaussView, Version 5. Semichem Inc., Shawnee Mission, KS

    Google Scholar 

  32. Thompson MA (2004) Molecular docking using ArgusLab, an efficient shape-based search algorithm and the AScore scoring function. ACS meeting, Philadelphia, 172, CINF 42, PA

  33. Cornell WD, Cieplak P, Bayly CI, Gould IR, Merz K M Jr, Ferguson DM, Spellmeyer DC, Fox T, Caldwell JW, Kollman PA (1995) A second generation force field for the simulation of proteins, nucleic acids, and organic molecules. J Am Chem Soc 117:5179–5197. doi:10.1021/ja00124a002

    Article  CAS  Google Scholar 

  34. Berendsen HJC, Postma JPM, van Gunsteren WF, DiNol A, Haak JR (1984) Molecular-dynamics with coupling to an external bath. J Chem Phys 81(8):3684–3690. doi:10.1063/1.448118.

    Article  CAS  Google Scholar 

  35. Humphrey W, Dalke A, Schulten K (1996) VMD - visual molecular dynamics. J Molec Graphics 14:33–38

    Article  CAS  Google Scholar 

  36. Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE et al (2009) Gaussian 09, Revision A.02. Gaussian Inc., Wallingford CT

    Google Scholar 

  37. Glukhova OE (2009) Study of mechanical properties of peapod-like carbon nanotubes based on molecular-mechanics model. Physika volnovih processov i radiotehnicheskie systemi 12(1):69–75. (in Russian)

    Google Scholar 

  38. Glukhova OE, Kirillova IV, Kolesnikova AS, Kossovich EL, Ten GN (2012) Strain-hardening effect of graphene on a chain of the chitosan for the tissue engineering. Proc SPIE 82331E:8233. doi:10.1117/12.907032

    Google Scholar 

  39. Glukhova OE, Kirillova IV, Kossovich EL, Fadeev AA (2012) Mechanical properties study for graphene sheets of various size. Izv Saratov Univ (NS) Ser Math Mech Inform 12(4):63–66. (in Russian)

    Google Scholar 

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Acknowledgments

The authors gratefully acknowledge the financial support of the Ministry of Education and Science of the Russian Federation in the framework of Increase Competitiveness Program of NUST “MISiS” (N K4-2014-085).

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Correspondence to Elena L. Kossovich.

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Kossovich, E.L., Safonov, R.A. Predictive analysis of chitosan-based nanocomposite biopolymers elastic properties at nano- and microscale. J Mol Model 22, 75 (2016). https://doi.org/10.1007/s00894-016-2942-z

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