Sivashanmugam Muthukumaran, Muthu Kannan, Honguntikar D Sachin, Konda Mani Saravanan
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引用次数: 0
Abstract
Microplastic pollution has emerged as a pressing worldwide health concern, having recently been identified in human blood. Nonetheless, the molecular specifics of microplastic's interactions with human biology remain poorly understood. This paper presents a comprehensive computational analysis of the structural mimicry and potential metabolic disruption caused by common microplastics compounds. Six prevalent microplastics were selected, and their three-dimensional structures were evaluated against the Human Metabolome Database using FTrees similarity analysis. Certain microplastic compounds, such as dimethyl terephthalate and 1-decene, exhibited significant structural resemblance to crucial human metabolites involved in lipid metabolism, detoxification, and neurotransmission. The virtual screening conducted with LigTMap and SeeSAR identified potential protein targets, revealing that dimethyl terephthalate demonstrated moderate binding affinity to Carbonic Anhydrase II. The structural stability of this interaction was validated using molecular dynamics simulation over 500 ns, with RMSD and RMSF analysis indicating the stabilization of the conformations. Free energy landscape analysis also suggested the creation of a partially stable complex. These data indicate that microplastics are not physiologically inert and may disrupt endogenous metabolites, hence affecting protein function and metabolic pathways. This study highlights the urgent need for a more in-depth toxicological examination of microplastic exposure, which would establish a mechanistic framework to understand their potential contribution to human health risks at the molecular level.
期刊介绍:
The Journal of Biomolecular Structure and Dynamics welcomes manuscripts on biological structure, dynamics, interactions and expression. The Journal is one of the leading publications in high end computational science, atomic structural biology, bioinformatics, virtual drug design, genomics and biological networks.