In silico Acute Toxicity Prediction of Dimethyl Phthalate on Fish as Per Simulated Molecular Descriptors
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

In silico Acute Toxicity Prediction of Dimethyl Phthalate on Fish as Per Simulated Molecular Descriptors

Rituparna Banerjee, Pranab Kanti Roy, Soumendra Nath Talapatra

Abstract: An organic compound, dimethyl phthalate (DMP) is a category of plasticizer that is commonly utilized in plastic materials. The prediction of acute toxicity in fish through an in silico approach is an active assessment because fish is an edible diet of human beings. The objective of the present study was to predict an in silico acute toxicity (median lethal concentration or LC50 at 96hrs exposure) of DMP on fish as per simulated molecular descriptors by using toxicity estimation software tool (T.E.S.T.). The LC50 value of fish was predicted of about 15.97 mg/L or 4.09 -Log10(mol/L) as per similarity coefficient ≥0.5 of mean absolute error (MAE) of 0.03. Different molecular descriptors such as chi connectivity indices, topological descriptor, molecular properties, molecular distance-edge vector, burden eigenvalue descriptors, 2D autocorrelation descriptors, electrotopological state indices, information indices, molecular fragments, etc. were obtained. The average value was predicted for LC50 value as per all of these descriptors. It is concluded that the acute toxicity of fish for DMP was easily predicted after simulation of different molecular descriptors within T.E.S.T tool. It is suggested to evaluate fish toxicity with other phthalate compounds.

Keywords: Acute toxicity prediction, Dimethyl phthalate, Fish toxicity prediction, In silico study, Plasticizer

How to Cite?: Rituparna Banerjee, Pranab Kanti Roy, Soumendra Nath Talapatra, "In silico Acute Toxicity Prediction of Dimethyl Phthalate on Fish as Per Simulated Molecular Descriptors", Volume 15 Issue 11, November 2026, International Journal of Science and Research (IJSR), Pages: 275-278, https://www.ijsr.net/getabstract.php?paperid=SR261107134834, DOI: https://dx.doi.org/10.21275/SR261107134834

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