Cytotoxic Activities, Determining Toxin, and Molecular Docking of Ovary Pufferfish (Tetraodon leiurus) in Singkarak Lake as Cancer Chemoprevention Candidate
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Published:2023-12-05
Issue:6(Suppl.)
Volume:20
Page:2373
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ISSN:2411-7986
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Container-title:Baghdad Science Journal
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language:
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Short-container-title:Baghdad Sci.J
Author:
Roesma Dewi Imelda,
Tjong Djong Hon,
Hanif Monica MulniaORCID
Abstract
The primary toxin class discovered in freshwater pufferfish is a category of neurotoxins called PSTs (Paralytic shellfish toxins) and pufferfish toxin has been observed to have biological, biochemical, and cytotoxic effects on cancer cell lines. Therefore, it is crucial to determine the cytotoxic activity, toxins present in the ovary of T. leiurus, and interaction between ligand (toxin compound) and receptors test. This study used the MTT method in the T47D cell lines, liquid chromatograph-tandem mass spectrometry (LC-MS/MS), and analysis of the molecular interaction using molecular docking. The ovary of T. leiurus had cytotoxicity on the T47D cell, having an IC50 value of 229.535 μg/ml, and generated a chromatogram with a retention duration of 1.25 min that was similar to the Decarbamoylneosaxitoxin (dcNEO) standard solution. In molecular interactions between the dcNEO ligand to receptors, the lowest ΔG value was -9.29 kcal/mol at the Nav 1.7 receptor, and the lowest KI value was 1.23 µM at the Mcl-1 receptor. These findings indicate that the ovary of T. leiurus is cytotoxic to the T47D cell line and contains dcNEO toxin. It is more stable for the dcNEO ligand to engage with the Nav 1.7 receptor than with other receptors, and it inhibits the Mcl-1 receptor more potently than with other receptors. These findings indicate that the ovary of T. leiurus may be chemotherapy for the prevention of cancer strategy.
Publisher
College of Science for Women
Subject
General Physics and Astronomy,Agricultural and Biological Sciences (miscellaneous),General Biochemistry, Genetics and Molecular Biology,General Mathematics,General Chemistry,General Computer Science