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内分泌干扰化学物质雄激素受体结合亲和力的定量构效关系研究,包括相关性理想指数、分子对接、分子动力学和药物代谢及药物动力学研究。

Quantitative structure activity relationship studies of androgen receptor binding affinity of endocrine disruptor chemicals with index of ideality of correlation, their molecular docking, molecular dynamics and ADME studies.

作者信息

Goyal Surbhi, Rani Payal, Chahar Monika, Hussain Khalid, Kumar Parvin, Sindhu Jayant

机构信息

Department of Chemistry, Baba Mastnath University, Rohtak, India.

Department of Chemistry, COBS&H, CCS Haryana Agricultural University, Hisar, India.

出版信息

J Biomol Struct Dyn. 2023;41(23):13616-13631. doi: 10.1080/07391102.2023.2193991. Epub 2023 Apr 3.

Abstract

Endocrine disrupter chemicals (EDCs) are both natural and man-made chemicals that mimic, block or interfere with human hormonal system. In the present manuscript, QSAR modeling was performed for the androgen disruptors that interfere with biosynthesis, metabolism or action of androgens that causes adverse effects on male reproductive system. A set of 96 EDCs that exhibited affinity towards androgen receptors (Log RBA) in rats were employed for carrying out QSAR studies using Hybrid descriptors (combination of HFG and SMILES) through Monte Carlo Optimization. Using index of ideality of correlation (TF2), five splits were formed and predictability of five models resulting from these splits was assessed by various validation parameters. Models resulted from first split was the top most one with R = 0.7878. Structural attributes responsible for change in endpoint were studied by employing correlation weights of structural attributes. In order to further validate the model, new EDCs were designed using these attributes. molecular modelling studies were performed to assess the detailed interactions with the receptor. The binding energies of all the designed compounds were observed to be better than lead and are in the range of -10.46 to -14.80. Molecular dynamics simulation of 100 ns was performed for and . The results revealed that the protein-ligand complex bearing was more stable than lead exhibiting better interactions with the receptor. Further, in an attempt to assess their metabolism, ADME studies were evaluated using SwissADME. The developed model enables to predict the characteristics of designed compounds in an authentic way.Communicated by Ramaswamy H. Sarma.

摘要

内分泌干扰化学物质(EDCs)是天然和人造的化学物质,它们模拟、阻断或干扰人体激素系统。在本手稿中,对干扰雄激素生物合成、代谢或作用并对男性生殖系统产生不利影响的雄激素干扰物进行了定量构效关系(QSAR)建模。使用混合描述符(HFG和SMILES的组合)通过蒙特卡罗优化,对一组96种在大鼠中对雄激素受体表现出亲和力(Log RBA)的EDCs进行QSAR研究。使用相关性理想指数(TF2)形成五个分割,并通过各种验证参数评估由这些分割产生的五个模型的可预测性。第一次分割产生的模型是最优模型,R = 0.7878。通过使用结构属性的相关权重研究了导致终点变化的结构属性。为了进一步验证模型,利用这些属性设计了新的EDCs。进行了分子建模研究以评估与受体的详细相互作用。观察到所有设计化合物的结合能均优于先导化合物,范围在-10.46至-14.80之间。对[具体化合物1]和[具体化合物2]进行了100 ns的分子动力学模拟。结果表明,含有[具体化合物1]的蛋白质-配体复合物比先导化合物更稳定,与受体表现出更好的相互作用。此外,为了评估它们的代谢,使用SwissADME进行了药物代谢动力学(ADME)研究。所开发的模型能够以可靠的方式预测设计化合物的特性。由Ramaswamy H. Sarma传达。

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