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The removal of organic pollutants is a major challenge in wastewater treatment technologies. Coagulation by plant proteins is a promising technique for this purpose. The use of these proteins has been experimentally investigated and reported in the literature. However, the determination of the molecular interactions of these species is experimentally challenging and the computational approach offers a suitable alternative in gathering useful information for this system. The present study used a molecular dynamic simulation approach to predict the potentials of using Moringa oleifera (MO), Arachis hypogaea, Bertholletia excelsa, Brassica napus, and Helianthus annuus plant proteins for the coagulation of organic pollutants and the possible mechanisms of coagulation of these proteins. The results showed that the physicochemical and structural properties of the proteins are linked to their performance. Maximum coagulation of organic molecules to the proteins is between 50-100%. Among five proteins studied for coagulation, Brassica napus and Helianthus annuus performed better than the well-known MO protein. The amino acid residues interacting with the organic molecules play a significant role in the coagulation and this is peculiar with each plant protein. Hydrogen bond and π-interactions dominate throughout the protein-pollutants molecular interactions. The reusability of the proteins after coagulation derived from their structural quality analysis along with the complexes looks promising and most of them are better than that of the MO. The results showed that the seed proteins studied have good prediction potentials to be used for the coagulation of organic pollutants from the environment, as well as the insights into their molecular activities for bioremediation.


Victoria T Adeleke, Nkosinathi E Madlala, Adebayo A Adeniyi, David Lokhat. Molecular Interactions Associated with Coagulation of Organic Pollutants by 2S Albumin of Plant Proteins: A Computational Approach. Molecules (Basel, Switzerland). 2022 Mar 04;27(5)

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PMID: 35268786

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