Volume 13 | Issue 6 |

 Abstract

Humans and other biological entities are at a great risk from microplastics, which are ubiquitous in both marine and terrestrial ecosystems. Their capacity to transport and absorb harmful substances is demonstrated by recent research, which suggests that they may be the source of a number of health problems. By offering insights into the fundamental molecular processes and aiding in the development of abatement techniques, computational biology has emerged as a critical method for identifying important genes impacted by microplastic exposure. This work uses databases and bioinformatics methods, such as MalaCard, GeneCard, and OMIM to find and examine the genes that are affected by exposure to microplastics. Additionally, utilizing 12 distinct cytohubba characteristics, the protein-protein interaction networks were examined in order to identify the hub gene. "TNF" protein was identified as the key regulator of the network. A list of phytochemicals was also carefully selected after a thorough review of the literature in order to determine which ones would be useful in protecting against the exposure to microplastics. Using ADMETLab 3.0, the drug-like properties of these phytochemicals were tested. The structure of the key hub gene, that is, TNF was modeled using Swiss-Model. Molecular docking studies were done to explore the potential of phytochemicals against TNF. Molecular docking studies revealed the potential role of "Ellagic Acid" that has the highest binding energy of "-9.36" in the management of microplastics exposure in human. This study underscores the pervasive threat of microplastics to both human health and the environment, highlighting their ability to transport harmful substances. Computational biology has played a pivotal role in identifying key genes affected by microplastic exposure, with TNF emerging as a critical regulator. Through molecular modeling and docking studies, Ellagic Acid shows promising potential as a therapeutic agent against microplastic-induced health risks.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Network biology, Computational biology, TNF, Mircoplastic, Molecular modeling, Exposure management, Gingerol, Binding energy.

  License

Creative Commons Attribution 4.0 and The Open Definition