{"title":"Investigation of Chlorophylls a and b Interaction with Inner and Outer Surfaces of Single-Walled Carbon Nanotube Using Molecular Dynamics Simulation","authors":"M. Dehestani, M. Ghasemi-Kooch","volume":135,"journal":"International Journal of Chemical and Molecular Engineering","pagesStart":107,"pagesEnd":111,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10008637","abstract":"<p>In this work, adsorption of chlorophylls a and b pigments in aqueous solution on the inner and outer surfaces of single-walled carbon nanotube (SWCNT) has been studied using molecular dynamics simulation. The linear interaction energy algorithm has been used to calculate the binding free energy. The results show that the adsorption of two pigments is fine on the both positions. Although there is the close similarity between these two pigments, their interaction with the nanotube is different. This result is useful to separate these pigments from one another. According to interaction energy between the pigments and carbon nanotube, interaction between these pigments-SWCNT on the inner surface is stronger than the outer surface. The interaction of SWCNT with chlorophylls phytol tail is stronger than the interaction of SWCNT with porphyrin ring of chlorophylls.<\/p>\r\n","references":"[1]\tB. I. Yakobson, P. Avouris, Mechanical properties of carbon nanotubes. In: Carbon nanotubes. 287-327. Springer, 2001.\r\n[2]\tH. Kataura, Y. Kumazawa, Y. Maniwa, I. Umezu, S. Suzuki, Y. Ohtsuka, Y. Achiba: Optical properties of single-wall carbon nanotubes. Synthetic. Metals 103(1-3), 1999, pp. 2555-2558.\r\n[3]\tJ. E. Fischer, A. T. Johnson, Electronic properties of carbon nanotubes. Curr. Opin. Solid State Mater. Sci. vol. 4(1), 1999, pp. 28-33.\r\n[4]\tJ. Che, T. Cagin, W.A. Goddard III, Thermal conductivity of carbon nanotubes. Nanotechnology 11(2), 2000, pp. 65.\r\n[5]\tM. Levitt, M. F. Perutz, Aromatic rings act as hydrogen bond acceptors. J. Mol. Biol. 201(4), 1988, pp. 751-754.\r\n[6]\tS. Az'hari, Y. Ghayeb, Effect of chirality, length and diameter of carbon nanotubes on the adsorption of 20 amino acids: a molecular dynamics simulation study. Mol. Simul. Vol. 40(5), 2014, pp. 392-398.\r\n[7]\tR. P. Weso\u0142owski, S. Furmaniak, A. P. Terzyk, P. A. Gauden, Simulating the effect of carbon nanotube curvature on adsorption of polycyclic aromatic hydrocarbons. Adsorption vol. 17(1), 2011, pp. 1-4.\r\n[8]\tM. Zheng, A. Jagota, E. D. Semke, B. A. Diner, R. S. McLean, S. R., Lustig, R. E. Richardson, N. G. Tassi, DNA-assisted dispersion and separation of carbon nanotubes. Nat. Mater. Vol. 2(5), 2003, pp. 338-342.\r\n[9]\tB. S. Wong, S. L., Yoong, A. Jagusiak, T. Panczyk, H. K. Ho, W. H Ang, G. Pastorin, Carbon nanotubes for delivery of small molecule drugs. Adv. Drug Deliv. Rev. vol. 65(15), 2013, pp. 1964-2015.\r\n[10]\tZ. Xu, X. Yang, Z. Yang, A molecular simulation probing of structure and interaction for supramolecular sodium dodecyl sulfate\/single-wall carbon nanotube assemblies. Nano Lett. Vol. 10(3), 2010, pp. 985-991.\r\n[11]\tM. Ghasemi-Kooch, M. Dehestani, M. R. Housaindokht, M. R. Bozorgmehr, Oleuropein interactions with inner and outer surface of different types of carbon nanotubes: Insights from molecular dynamic simulation. J. Mol. Liq. vol. 241, 2017, pp. 367-373.\r\n[12]\tM. Frisch, G. Trucks, H. Schlegel, G. Scuseria, M. Robb, J. Cheeseman, G. Scalmani, V. Barone, B. Mennucci, G. Petersson, Gaussian 03, Revision B. 03. In. Gaussian, Inc., Wallingford CT, 2004.\r\n[13]\tY. Duan, C. Wu, S. Chowdhury, M. C. Lee, G. Xiong, W. Zhang, R. Yang, P. Cieplak, R. Luo, T. Lee, A point\u2010charge force field for molecular mechanics simulations of proteins based on condensed\u2010phase quantum mechanical calculations. J. Comput. Chem. vol. 24(16), 2003, pp.1999-2012.\r\n[14]\tB. Hess, H. Bekker, H. J. C. Berendsen, J. G. E. M. Fraaije, LINCS: A linear constraint solver for molecular simulations, J. Comput. Chem. vol. 18(12), 1997, 1463-1472.\r\n[15]\tM. J. Abraham, T. Murtola, R. Schulz, S. P\u00e1ll, J. C. Smith, B. Hess, E. Lindahl: GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. Software X 1, 2015, pp. 19-25.\r\n[16]\tG. Bussi, D. Donadio, M. Parrinello, Canonical sampling through velocity rescaling. J. Chem. Phys. vol. 126(1), 2007, pp. 014101.\r\n[17]\tJ. \u00c5qvist, C. Medina, J.-E. Samuelsson, A new method for predicting binding affinity in computer-aided drug design. Protein Eng. vol. 7(3), 1994, pp. 385-391.\r\n[18]\tW. Wang, J. Wang, P.A. Kollman, What determines the van der waals coefficient \u03b2 in the LIE (linear interaction energy) method to estimate binding free energies using molecular dynamics simulations? Proteins: Struct. Funct. Bioinf. vol. 34 (3), 1999, pp. 395-402.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 135, 2018"}