Prediction of Binding Free Energies for Dyes Removal Using Computational Chemistry
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32918
Prediction of Binding Free Energies for Dyes Removal Using Computational Chemistry

Authors: R. Chanajaree, D. Luanwiset, K. Pongpratea


Dye removal is an environmental concern because the textile industries have been increasing by world population and industrialization. Adsorption is the technique to find adsorbents to remove dyes from wastewater. This method is low-cost and effective for dye removal. This work tries to develop effective adsorbents using the computational approach because it will be able to predict the possibility of the adsorbents for specific dyes in terms of binding free energies. The computational approach is faster and cheaper than the experimental approach in case of finding the best adsorbents. All starting structures of dyes and adsorbents are optimized by quantum calculation. The complexes between dyes and adsorbents are generated by the docking method. The obtained binding free energies from docking are compared to binding free energies from the experimental data. The calculated energies can be ranked as same as the experimental results. In addition, this work also shows the possible orientation of the complexes. This work used two experimental groups of the complexes of the dyes and adsorbents. In the first group, there are chitosan (adsorbent) and two dyes (reactive red (RR) and direct sun yellow (DY)). In the second group, there are poly(1,2-epoxy-3-phenoxy) propane (PEPP), which is the adsorbent, and 2 dyes of bromocresol green (BCG) and alizarin yellow (AY).

Keywords: Dye removal, binding free energies, quantum calculation, docking.

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 684


[1] C. S. D. Rodrigues, L. M. Madeira, and R. A. R. Boaventura, “Synthetic Textile Dyeing Wastewater Treatment by Integration of Advanced Oxidation and Biological Processes โ€“ Performance Analysis with Costs Reduction,” Journal of Environmental Chemical Engineering, vol. 2(2), pp. 1027-39, 2014.
[2] G. Crini and P.-M. Badot, “Application of Chitosan, a Natural Aminopolysaccharide, for Dye Removal from Aqueous Solutions by Adsorption Processes Using Batch Studies: A Review of Recent Literature,” Progress in Polymer Science. vol. 33(4), pp. 399-447, 2008.
[3] V. Rizzi et al., “Applicative Study (Part I): The Excellent Conditions to Remove in Batch Direct Textile Dyes (Direct Red, Direct Blue and Direct Yellow) from Aqueous Solutions by Adsorption Processes on Low-Cost Chitosan Films under Different Conditions,” Advances in Chemical Engineering and Science. vol. 4, pp. 454-69, 2014.
[4] S. Chowdhury et al., “Adsorption Thermodynamics, Kinetics and Isosteric Heat of Adsorption of Malachite Green onto Chemically Modified Rice Husk,” Desalination. vol. 265,1, pp. 159-68, 2011.
[5] S. A. Odoemelam, U. N. Emeh, and N. O. Eddy, “Experimental and Computational Chemistry Studies on the Removal of Methylene Blue and Malachite Green Dyes from Aqueous Solution by Neem (Azadirachta Indica) Leaves,” Journal of Taibah University for Science. vol. 12(3), pp. 255-65, 2018.
[6] S. E. Subramani and N. Thinakaran, “Isotherm, Kinetic and Thermodynamic Studies on the Adsorption Behaviour of Textile Dyes onto Chitosan,” Process Safety and Environmental Protection. vol. 106, pp. 1-10, 2017.
[7] M. Sriuttha et al., “A Combined Experimental/Computational Study on Adsorption of Fe2+ by Cigarette Filter Added with Chitosan,” Asian Journal of Chemistry. vol. 26, pp. S189-S94, 2014.
[8] G. Tor˘gut and K. Demirelli, “Comparative Adsorption of Different Dyes from Aqueous Solutions onto Polymer Prepared by Rop: Kinetic, Equilibrium and Thermodynamic Studies,” Arab. J. Sci. Eng. vol. 43, pp. 3503-14, 2018.
[9] M. D. Hanwell et al., “Avogadro: An Advanced Semantic Chemical Editor, Visualization, and Analysis Platform,” Journal of Cheminformatics. vol. 4, pp. 17, 2012.
[10] G. M. Morris et al., “Autodock4 and Autodocktools4: Automated Docking with Selective Receptor Flexiblity,” J. Computational Chemistry vol. 16, pp. 2785-91, 2009.
[11] Y. Fu, J. Zhao, and Z. Chen, “Insights into the Molecular Mechanisms of Protein-Ligand Interactions by Molecular Docking and Molecular Dynamics Simulation: A Case of Oligopeptide Binding Protein,” Computational and mathematical methods in medicine. vol. 2018, pp. 3502514-, 2018.
[12] P. Mignon et al., “Influence of the P–P Interaction on the Hydrogen Bonding Capacity of Stacked DNA/Rna Bases,” Nucleic Acids Research. vol. 33(6), pp. 1779-89, 2005.