Skip to main content
Log in

Quantum chemical analysis of isomerization and protonation of amino group in D-glucosamine

  • Research Letter
  • Published:
MRS Communications Aims and scope Submit manuscript

Abstract

D-glucosamine (GluN) is a vital amino monosaccharide present in bio-polymers like chitin and chitosan. Using density functional theory (DFT), we examined its molecular and structural properties in different conformations and protonation states. Results revealed the β-form as more stable than the α-form when neutral. Protonation led to shorter hydrogen bond distances with improved interactions. Frontier molecular orbital analysis showed the amino group's significant role in influencing HOMO and LUMO orbitals based on protonation. The calculated energy gap (ΔE) indicated protonated D-glucosamine’s higher stability and lower reactivity compared to neutral isomers. These findings enhance our comprehension of D-glucosamine’s in bio-polymers applications.

Graphical abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3
Figure 4

Similar content being viewed by others

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. J.W. Anderson, R.J. Nicolosi, J.F. Borzelleca, Glucosamine effects in humans: a review of effects on glucose metabolism, side effects, safety considerations and efficacy. Food Chem. Toxicol. 43(2), 187–201 (2005). https://doi.org/10.1016/j.fct.2004.11.006

    Article  CAS  Google Scholar 

  2. D.L. Bertuzzi et al., General protocol to obtain D-glucosamine from biomass residues: shrimp shells, cicada sloughs and cockroaches. Global Chall. 2(11), 1800046 (2018). https://doi.org/10.1002/gch2.201800046

    Article  Google Scholar 

  3. C. Virués et al., Formulation of anomerization and protonation in d-glucosamine, based on 1H NMR. Carbohydr. Res. 490, 107952 (2020). https://doi.org/10.1016/j.carres.2020.107952

    Article  CAS  Google Scholar 

  4. H. Amiri et al., Chitin and chitosan derived from crustacean waste valorization streams can support food systems and the UN sustainable development goals. Nat Food 3(10), 822–828 (2022). https://doi.org/10.1038/s43016-022-00591-y

    Article  Google Scholar 

  5. K. Piekarska, M. Sikora, M. Owczarek, J. Jóźwik-Pruska, M. Wiśniewska-Wrona, Chitin and chitosan as polymers of the future—obtaining, modification, life cycle assessment and main directions of application. Polymers (Basel) 15(4), 793 (2023). https://doi.org/10.3390/polym15040793

    Article  CAS  Google Scholar 

  6. K. Ogawa, T. Yui, K. Okuyama, Three D structures of chitosan. Int. J. Biol. Macromol. 34(1–2), 1–8 (2004). https://doi.org/10.1016/j.ijbiomac.2003.11.002

    Article  CAS  Google Scholar 

  7. R.A. Muzzarelli, M. Mattioli-Belmonte, A. Pugnaloni, G. Biagini, Biochemistry, histology and clinical uses of chitins and chitosans in wound healing. EXS 87, 251–264 (1999). https://doi.org/10.1007/978-3-0348-8757-1_18

    Article  CAS  Google Scholar 

  8. I.M. van der Lubben, J.C. Verhoef, G. Borchard, H.E. Junginger, Chitosan and its derivatives in mucosal drug and vaccine delivery. Eur. J. Pharm. Sci. 14(3), 201–207 (2001). https://doi.org/10.1016/S0928-0987(01)00172-5

    Article  Google Scholar 

  9. R. Hejazi, M. Amiji, Chitosan-based gastrointestinal delivery systems. J. Control. Release 89(2), 151–165 (2003). https://doi.org/10.1016/S0168-3659(03)00126-3

    Article  CAS  Google Scholar 

  10. M. Prabaharan, J.F. Mano, Chitosan-based particles as controlled drug delivery systems. Drug Deliv. 12(1), 41–57 (2004). https://doi.org/10.1080/10717540590889781

    Article  CAS  Google Scholar 

  11. V.R. Sinha et al., Chitosan microspheres as a potential carrier for drugs. Int. J. Pharm. 274(1–2), 1–33 (2004). https://doi.org/10.1016/j.ijpharm.2003.12.026

    Article  CAS  Google Scholar 

  12. J.-K. Francis Suh, H.W.T. Matthew, Application of chitosan-based polysaccharide biomaterials in cartilage tissue engineering: a review. Biomaterials 21(24), 2589–2598 (2000). https://doi.org/10.1016/S0142-9612(00)00126-5

    Article  CAS  Google Scholar 

  13. M.G. Cascone, N. Barbani, C.C.P. Giusti, G. Ciardelli, L. Lazzeri, Bioartificial polymeric materials based on polysaccharides. J. Biomater. Sci. Polym. Ed. 12(3), 267–281 (2001). https://doi.org/10.1163/156856201750180807

    Article  CAS  Google Scholar 

  14. M.C. Neuffer, J. McDivitt, D. Rose, K. King, C.C. Cloonan, J.S. Vayer, Hemostatic dressings for the first responder: a review. Mil. Med. 169(9), 716–720 (2004). https://doi.org/10.7205/MILMED.169.9.716

    Article  Google Scholar 

  15. T.H. Fischer, A.P. Bode, M. Demcheva, J.N. Vournakis, Hemostatic properties of glucosamine-based materials. J. Biomed. Mater. Res. A 80A(1), 167–174 (2007). https://doi.org/10.1002/jbm.a.30877

    Article  CAS  Google Scholar 

  16. J.N. Vournakis, M. Demcheva, A. Whitson, R. Guirca, E.R. Pariser, Isolation, purification, and characterization of Poly-N-Acetyl glucosamine use as a hemostatic agent. J. Trauma: Injury, Infection Critical Care 57(1), S2–S6 (2004). https://doi.org/10.1097/01.TA.0000136741.66698.9D

    Article  CAS  Google Scholar 

  17. D. Bálint, L. Jäntschi, Comparison of molecular geometry optimization methods based on molecular descriptors. Mathematics 9(22), 2855 (2021). https://doi.org/10.3390/math9222855

    Article  Google Scholar 

  18. M. Manathunga, A.W. Götz, K.M. Merz, Computer-aided drug design, quantum-mechanical methods for biological problems. Curr. Opin. Struct. Biol. 75, 102417 (2022). https://doi.org/10.1016/j.sbi.2022.102417

    Article  CAS  Google Scholar 

  19. M.J. Frisch et al., Gaussian 09, Revision A.02 (Gaussian Inc, Wallingford CT, 2016)

    Google Scholar 

  20. A.D. Becke, Density-functional thermochemistry. V. Systematic optimization of exchange-correlation functionals. J Chem Phys 107(20), 8554–8560 (1997). https://doi.org/10.1063/1.475007

    Article  CAS  Google Scholar 

  21. P. Singla, M. Riyaz, S. Singhal, N. Goel, Theoretical study of adsorption of amino acids on graphene and BN sheet in gas and aqueous phase with empirical DFT dispersion correction. Phys. Chem. Chem. Phys. 18(7), 5597–5604 (2016). https://doi.org/10.1039/C5CP07078C

    Article  CAS  Google Scholar 

  22. H.T. Larijani, M. Jahanshahi, M.D. Ganji, M.H. Kiani, Computational studies on the interactions of glycine amino acid with graphene, h-BN and h-SiC monolayers. Phys. Chem. Chem. Phys. 19(3), 1896–1908 (2017). https://doi.org/10.1039/C6CP06672K

    Article  CAS  Google Scholar 

  23. A. Shokuhi Rad, M. Esfahanian, S. Maleki, G. Gharati, Application of carbon nanostructures toward SO2 and SO3 adsorption: a comparison between pristine graphene and N-doped graphene by DFT calculations”. J. Sulfur Chem. 37(2), 176–188 (2016). https://doi.org/10.1080/17415993.2015.1116536

    Article  CAS  Google Scholar 

  24. A.S. Rad, Al-doped graphene as a new nanostructure adsorbent for some halomethane compounds: DFT calculations. Surf Sci 645, 6–12 (2016). https://doi.org/10.1016/j.susc.2015.10.036

    Article  CAS  Google Scholar 

  25. A.R. Katritzky, N.G. Akhmedov, J. Doskocz, P.P. Mohapatra, C.D. Hall, A. Güven, NMR spectra, GIAO and charge density calculations of five-membered aromatic heterocycles. Magn. Reson. Chem. 45(7), 532–543 (2007). https://doi.org/10.1002/mrc.1967

    Article  CAS  Google Scholar 

  26. K. Momma, F. Izumi, VESTA 3 for three-dimensional visualization of crystal, volumetric and morphology data. J. Appl. Crystallogr. 44(6), 1272–1276 (2011). https://doi.org/10.1107/S0021889811038970

    Article  CAS  Google Scholar 

  27. G. Schaftenaar, E. Vlieg, G. Vriend, Molden 2.0: quantum chemistry meets proteins. J. Comput. Aided Mol. Des. 31(9), 789–800 (2017). https://doi.org/10.1007/s10822-017-0042-5

    Article  CAS  Google Scholar 

  28. C.H. Suresh, G.S. Remya, P.K. Anjalikrishna, Molecular electrostatic potential analysis: a powerful tool to interpret and predict chemical reactivity. WIREs Comput. Mol. Sci. (2022). https://doi.org/10.1002/wcms.1601

    Article  Google Scholar 

  29. A. Suvitha, S. Periandy, P. Gayathri, NBO, HOMO–LUMO, UV, NLO, NMR and vibrational analysis of veratrole using FT-IR, FT-Raman, FT-NMR spectra and HF–DFT computational methods. Spectrochim Acta A Mol. Biomol. Spectrosc. 138, 357–369 (2015). https://doi.org/10.1016/j.saa.2014.11.011

    Article  CAS  Google Scholar 

  30. M. Uzzaman, M. JabedulHoque, Physiochemical, molecular docking, and pharmacokinetic studies of Naproxen and its modified derivatives based on DFT. Int. J. Sci. Res. Manag. (2018). https://doi.org/10.18535/ijsrm/v6i9.c01

    Article  Google Scholar 

  31. J. Aihara, Reduced HOMO−LUMO gap as an index of kinetic stability for polycyclic aromatic hydrocarbons. J. Phys. Chem. A 103(37), 7487–7495 (1999). https://doi.org/10.1021/jp990092i

    Article  CAS  Google Scholar 

Download references

Acknowledgments

To Roberto López Rendón†, your legacy will live on through the years. The author is gratefully for the computing time granted by the Supercomputer Hybrid Cluster “Xiuhcoatl” at General Coordination of Information and Communications Technologies (CGSTIC) of Cinvestav-IPN. This research/thesis was partially supported by the NLHPC supercomputing infrastructure (ECM-02).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rodolfo Daniel Ávila-Avilés.

Ethics declarations

Conflict of interest

The author declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ávila-Avilés, R.D. Quantum chemical analysis of isomerization and protonation of amino group in D-glucosamine. MRS Communications 13, 1303–1308 (2023). https://doi.org/10.1557/s43579-023-00455-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1557/s43579-023-00455-x

Keywords

Navigation