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PMID: 42542631 已发表 · epublish 英语

In silico DFT study, molecular docking interactions, molecular dynamics and toxicological assessment of selected organochlorine-based pesticides.

In silico pharmacology ·第 14 卷 ·第 2 期

Uddin MJ, Evan MSH, Tulin WS, Khan MS, Nayeem J, Kawsar SMA

摘要

Organochlorine pesticides (OCPs) initially garnered significant attention because of their high efficacy in pest control. However, these compounds have been banned worldwide because they impair environmental biodiversity and adversely affect human health through in vivo exposure. In this study, we employed density functional theory (DFT) with the B3LYP/6-31G (d, p) basis set to evaluate the physicochemical, thermodynamic, and spectral properties of five well-known OCPs, namely, dichlorodiphenyltrichloroethane (DDT), endrin (END), endrin ketone (EDK), aldrin (ALD), and heptachlor epoxide (HCE), through in silico methods. Additionally, molecular docking and non-bonding interactions were calculated to investigate the binding properties and mode(s) of action against serine/threonine-protein kinase PIM-2 (PDB ID: 2IWI) and human estrogen receptor (PDB ID: 6PYF) proteins. Thermodynamic and molecular orbital evaluations revealed that DDT and HCE were highly stable and had the highest binding affinities against 2IWI and 6PYF, respectively. Molecular dynamics (MD) simulations conducted utilizing YASARA dynamics with the AMBER14 force field revealed that EDK and HCE exhibit greater conformational flexibility and stability. ADMET and PASS analyses were performed to determine the biological and toxicological effects of the OCPs. All the OCPs studied exhibited carcinogenic, neurotoxic, endocrine-disrupting, and hepatotoxic effects and can easily pass through the intestinal barrier and blood‒brain barrier, indicating their adverse effects on animals. These evaluations provide awareness of OCP use and a deeper understanding of its biochemical and toxicological effects on the environment and biological systems. The online version contains supplementary material available at 10.1007/s40203-026-00712-6.

关键词
ADMET Carcinogenic Molecular dynamics study Organochlorine pesticides PASS prediction
文献信息
期刊
In silico pharmacology
期刊简称
In Silico Pharmacol
ISSN
2193-9616
语言
英语
国家/地区
Germany
NLM ID
101623954
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