4.7 Article

Toxic Relationships: Prediction of TBT's Affinity to the Ecdysteroid Receptor of Triops longicaudatus

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TOXICS
卷 11, 期 11, 页码 -

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MDPI
DOI: 10.3390/toxics11110937

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comparative genomics; tributyltin; proteomics; phylogeny; crustacea

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Tributyltin (TBT) is a persistent biocide that causes significant harm to organisms despite being banned. This study compares the three-dimensional structure, phylogenetic distribution, and amino acid sequence alterations of TBT-sensitive species. The results show conservation of the protein and no specific distribution of sensitivity among different taxa.
Tributyltin (TBT) is a biocide introduced in the 1960s in antifouling paints. Despite legislation banning its use, its persistence in the environment still causes significant harm to organisms. Tributyltin is a ligand of retinoid X receptors (RXR) and ecdysteroid receptors (EcRs), which in arthropods act as homologs of RXR. Focusing on Metazoan species, this study used genomic and proteomic information from different sources to compare their three-dimensional structure, phylogenetic distribution, and amino acid sequence alterations. The objective was to identify possible patterns that relate organisms' sensitivity to TBT using the species Triops longicaudatus as the basis for the comparisons. The results showed great conservation of this protein across several species when comparing the interaction amino acids described to RXR (an EcR analog) in Homo sapiens. The three-dimensional comparison of RXR showed little conformational variation between different sequences by maintaining the interaction pocket. As for the Species Sensitivity Distribution (SSD) curve, an HC05 = 0.2649 [0.0789-0.7082] mu g/L was obtained with no specific distribution between the different taxa. Protein-ligand docking analysis was then used to confirm the SSD curve ranking of species. Still, the results showed an opposite trend that may be related, for example, to differences in the LC50 values used in the calculations. This study serves as the first step for applying bioinformatics techniques to produce information that can be used as an alternative to animal or cellular experimentation. These techniques could be adapted to various chemicals and proteins, allowing for observations in a shorter timeframe and providing information on a broader spectrum.

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