Molecular Dynamics Simulation Study of Chitosan−Zinc Chloride Complex Model
Source abstract
Abstract
We report molecular dynamics simulation study of chitosan-zinc chloride complex crystal model to predict a hydrated structure and to evaluate the potential of mean force (PMF), namely, the free energy difference, in migration of a guest zinc chloride molecule in the crystal model. The accelerated molecular dynamics method was adopted to predict the hydrate structure of the crystal model, which proposed the crystal model interior involving four to five water molecules per a unit cell. The water molecules were mostly located in the crystal void surrounded by the functional groups of D-glucosamine and zinc chloride molecules, where the water molecules were mostly coordinated to zinc atoms. The PMF profile, obtained by using adaptive steered molecular dynamics method, exhibited continuously increase in the base line accompanied with appreciable minima, each of which corresponded to formations of interactions between the zinc chloride molecule and the polar functional groups, suggesting that the zinc chloride molecule on migration was handed over the C6 hydroxyl and C2 amino groups, while C3 hydroxyl groups were irrelevant to such an interaction. It was suggested that a zinc chloride molecule was more readily accommodated in the void through coordination with a C6 hydroxyl group which was more spatially mobile through C5-C6 bond rotation.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Bacteriophages and microbial interactions · Surfactants and Colloidal Systems · Polymer Surface Interaction Studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Engineering, Graduate School of Engineering, University of Miyazaki
Department of Applied Chemistry, Faculty of Engineering, University of Miyazaki
References (49)
Show source-provided references
1. T. Yui, K. Ogawa, in Polysaccharides: Structural diversity and functional versatility, ed. S. Dumitriu, CRC Press, Boca Raton, 2nd ed., 2004, pp. 99-122.
2. T. Yui, K. Imada, K. Okuyama, Y. Obata, K. Suzuki, K. Ogawa, Macromolecules, 27, 7601 (1994).10.1021/ma00104a014 ↗
3. K. Okuyama, K. Noguchi, T. Miyazawa, T. Yui, K. Ogawa, Macromolecules, 30, 5849 (1997).10.1021/ma970509n ↗
4. R. A. A. Muzzarelli, Chitin, Pergamon press, U.K., 1977.
5. K. Ogawa, K. Oka, T. Yui, Chem. Mater., 5, 726 (1993).10.1021/cm00029a026 ↗
6. T. Yui, T. Uto, K. Ogawa, Nanomaterials, 11, 1407 (2021).10.3390/nano11061407 ↗
7. A. Lertworasirikul, S. Yokoyama, K. Noguchi, K. Ogawa, K. Okuyama, Carbohydr. Res., 339, 825 (2004).10.1016/j.carres.2004.01.001 ↗
8. J. J. Stewart, J. Mol. Model., 13, 1173 (2007).10.1007/s00894-007-0233-4 ↗
9. T. Yui, S. Nishimura, S. Akiba, S. Hayashi, Carbohydr. Res., 341, 2521 (2006).10.1016/j.carres.2006.04.051 ↗
10. T. Yui, S. Hayashi, Biomacromolecules, 8, 817 (2007).10.1021/bm060867a ↗
11. T. Yui, N. Okayama, S. Hayashi, Cellulose, 17, 679 (2010).10.1007/s10570-010-9422-x ↗
12. T. Uto, T. Hosoya, S. Hayashi, T. Yui, Cellulose, 20, 605 (2013).10.1007/s10570-013-9861-2 ↗
13. T. Uto, T. Yonekura, T. Yui, Cellulose Commun., 25, 20 (2018).
14. T. Uto, T. Yui, ACS Omega, 3, 8050 (2018).10.1021/acsomega.8b00834 ↗
15. T. Yui, T. Uto, Cellulose, 29, 2855 (2021).10.1007/s10570-021-04136-7 ↗
16. T. Yui, T. Uto, K. Noda, in preparation.
17. D. Hamelberg, J. Mongan, J. A. McCammon, J. Chem. Phys., 120, 11919 (2004).10.1063/1.1755656 ↗
18. D. Hamelberg, C. A. de Oliveira, J. A. McCammon, J. Chem. Phys., 127, 155102 (2007).10.1063/1.2789432 ↗
19. G. Ozer, E. F. Valeev, S. Quirk, R. Hernandez, J. Chem. Theory Comput., 6, 3026 (2010).10.1021/ct100320g ↗
20. G. Ozer, S. Quirk, R. Hernandez, J. Chem. Phys., 136, 215104 (2012).10.1063/1.4725183 ↗
21. W. L. Jorgensen, J. Am. Chem. Soc., 103, 335 (1981).10.1021/ja00392a016 ↗
22. W. L. Jorgensen, J. Chandrasekhar, J. D. Madura, R. W. Impey, M. L. Klein, J. Chem. Phys., 79, 926 (1983).10.1063/1.445869 ↗
23. L. C. T. Pierce, R. Salomon-Ferrer, C. A. F. de Oliveira, J. A. McCammon, R. C. Walker, J. Chem. Theory Comput., 8, 2997 (2012).10.1021/ct300284c ↗
24. R. Salomon-Ferrer, L. Pierce, R. Walker, Accelerated molecular dynamics in AMBER example analysis of all-atom enhanced sampling method accelerated molecular dynamics (aMD) to investigate conformational changes in proteins that typically occur on the millisecond time scale., https://ambermd.org/tutorials/advanced/tutorial22, (accessed June 1, 2021).
25. Y. Miao, W. Sinko, L. Pierce, D. Bucher, R. C. Walker, J. A. McCammon, J. Chem. Theory Comput., 10, 2677 (2014).10.1021/ct500090q ↗
26. S. Park, F. Khalili-Araghi, E. Tajkhorshid, K. Schulten, J. Chem. Phys., 119, 3559 (2003).10.1063/1.1590311 ↗
27. S. Park, K. Schulten, J. Chem. Phys., 120, 5946 (2004).10.1063/1.1651473 ↗
28. C. Jarzynski, Phys. Rev. Lett., 78, 2690 (1997).10.1103/PhysRevLett.78.2690 ↗
29. K. N. Kirschner, A. B. Yongye, S. M. Tschampel, J. Gonzalez-Outeirino, C. R. Daniels, B. L. Foley, R. J. Woods, J. Comput. Chem., 29, 622 (2008).10.1002/jcc.20820 ↗
30. A. Singh, M. B. Tessier, K. Pederson, X. Wang, A. P. Venot, G. J. Boons, J. H. Prestegard, R. J. Woods, Can. J. Chem., 94, 927 (2016).10.1139/cjc-2015-0606 ↗
31. P. Li, B. P. Roberts, D. K. Chakravorty, K. M. Merz, Jr., J. Chem. Theory Comput., 9, 2733 (2013).10.1021/ct400146w ↗
32. J. Wang, R. M. Wolf, J. W. Caldwell, P. A. Kollman, D. A. Case, J. Comput. Chem., 25, 1157 (2004).10.1002/jcc.20035 ↗
33. L. Martinez, R. Andrade, E. G. Birgin, J. M. Martinez, J. Comput. Chem., 30, 2157 (2009).10.1002/jcc.21224 ↗
34. D. A. Case, I. Y. Ben-Shalom and S. R. Brozell, et al., Amber 18, https://ambermd.org: University of California, San Francisco, CA (2018).
35. S. Le Grand, A. W. Götz, R. C. Walker, Comput. Phys. Commun., 184, 374 (2013).10.1016/j.cpc.2012.09.022 ↗
36. R. Salomon-Ferrer, A. W. Gotz, D. Poole, S. Le Grand, R. C. Walker, J. Chem. Theory Comput., 9, 3878 (2013).10.1021/ct400314y ↗
37. D. R. Roe, T. E. Cheatham, III, J. Chem. Theory Comput., 9, 3084 (2013).10.1021/ct400341p ↗
38. M. J. Frisch, G. W. Trucks and H. B. Schlegel, et al., Gaussian 09, Revision C. 01, Gaussian Inc.: Wallingford, CT (2009).
39. Schrödinger LLC., The PyMOL molecular graphics system, ver. 2.5.0, https://pymol.org: New York, NY (2021).
40. W. Humphrey, A. Dalke, K. Schulten, J. Mol. Graph., 14, 33 (1996).10.1016/0263-7855(96)00018-5 ↗
41. M. B. Peters, Y. Yang, B. Wang, L. Fusti-Molnar, M. N. Weaver, K. M. Merz, Jr., J. Chem. Theory Comput., 6, 2935 (2010).10.1021/ct1002626 ↗
42. A. C. van Duin, V. S. Bryantsev, M. S. Diallo, W. A. Goddard, O. Rahaman, D. J. Doren, D. Raymand, K. Hermansson, J. Phys. Chem. A, 114, 9507 (2010).10.1021/jp102272z ↗
43. C. F. Schwenk, H. H. Loeffler, B. M. Rode, J. Am. Chem. Soc., 125, 1618 (2003).10.1021/ja0286831 ↗
44. X. Lu, M. Gaus, M. Elstner, Q. Cui, J. Phys. Chem. B, 119, 1062 (2015).10.1021/jp506557r ↗
45. M. Wu, X. Zhang, Y. Zhao, C. Yang, S. Jing, Q. Wu, A. Brozena, J. T. Miller, N. J. Libretto, T. Wu, S. Bhattacharyya, M. N. Garaga, Y. Zhang, Y. Qi, S. G. Greenbaum, R. M. Briber, Y. Yan, L. Hu, Nat. Nanotechnol., 17, 629 (2022).10.1038/s41565-022-01112-5 ↗
46. B. Medronho, B. Lindman, Adv. Colloid Interface Sci., 222, 502 (2015).10.1016/j.cis.2014.05.004 ↗
47. S. Wang, A. Lu, L. Zhang, Prog. Polym. Sci., 53, 169 (2016).10.1016/j.progpolymsci.2015.07.003 ↗
48. T. Uto, K. Yamamoto, J. Kadokawa, J. Phys. Chem. B, 122, 258 (2018).10.1021/acs.jpcb.7b09525 ↗
49. T. Komori, H. Satria, K. Miyamura, A. Ito, M. Kamiya, A. Sumino, T. Onishi, K. Ninomiya, K. Takahashi, J. L. Anderson, T. Uto, K. Kuroda, ACS Sustainable Chem. Eng., 9, 11825 (2021).10.1021/acssuschemeng.1c03438 ↗