复杂网络用于典型环境内分泌干扰物毒性通路的研究

发布时间：2018-05-14 20:34

本文选题：复杂网络 + 内分泌干扰物　；参考：《兰州大学》2017年硕士论文

【摘要】：取代苯类化合物以及全氟化合物同属于内分泌干扰物,由于其结构的特殊性,使得进入环境和人体后无法降解,并干扰机体的正常的信号通路,导致人体激素水平失衡。因此,该类化学物质的毒理学评价,成为了其管理的重要环节,近年来得到了世界范围内的广泛重视。现有的毒性评价方法,对化合物的研究多限于单一靶点、单一机制的研究,无法整体性的对其毒性机理进行系统的评价。因此,基于整体通路的评价方法是当今对取代苯类及全氟化合物毒性效应完整、全面、准确评价的必然要求。“复杂网络”技术由于其整体性、系统性的分析特点,为取代苯类及全氟化合物毒性机制评价提供了一种新的途径。首先通过“复杂网络”技术构建了20个取代苯类内分泌干扰物与71个有效靶标的相互作用网络,分析其网络的拓扑系数后获得6个基因作为网络的中心节点基因并带入KEGG信号通路数据库。通过复杂网络预测取代苯类化合物可通过与靶标基因ESR2和MMP9的作用影响雌激素信号通路;通过与靶标基因HIST3H3和MMP9的作用影响前列腺癌及多发性骨髓癌的误转录调节通路。其中,多发性骨髓癌误转录通路可能是取代苯类内分泌干扰物毒性作用的一条新的信号通路。同时,我们选择了中心节点蛋白NR1I2和MMP9与中心节点化合物C133作为研究案例,进行了分子动力学模拟,研究其相互作用的稳定性。通过分析动力学前后靶标蛋白氨基酸相互作用网络、配体受体之间形成氢键情况的变化,发现取代苯类化合物与NR1I2和MMP9靶标蛋白的结合更为牢靠,相互作用更为强烈。进一步说明内分泌干扰物一旦进入人体,则可能更为优先并稳定的与受体蛋白结合,严重的影响人类健康。其次,通过“复杂网络”技术构建了10个全氟化合物与82个有效靶标的相互作用网络,并通过网络拓扑性质分析获得其中心节点基因GLTP、HBG1、HSD17B1和SHBG,其中HSD17B1参与类固醇类激素的生物合成通路。推测全氟化合物影响雌激素相关的生理途径中,HSD17B1是其潜在的作用靶标。同时,对GLTP、HBG1、SHBG靶标基因参与的疾病进行分析,通过化合物-靶标相互作用网络将全氟化合物与疾病相互联系。在全氟化合物的作用靶点以及作用通路不清晰的情况下,为全氟化合物影响相关疾病的研究的提供一定的理论依据。在本论文中,通过计算手段建立化合物与生物体的多个基因之间的“复杂网络”,有利于从蛋白质/基因的整体活动的角度出发,将化合物和机体信号通路相互联系,揭示和阐明化学物质对机体通路的影响,进而从系统和整体层面上阐明化学物质的复杂作用机制并预测潜在的毒性效应,为环境污染物的机制研究提供了一种新的手段。
[Abstract]:Substituted benzenes and perfluorinated compounds are endocrine disruptors. Because of their special structure, they can not be degraded after entering the environment and human body, and interfere with the normal signal pathway of the body, leading to the imbalance of human hormone level. Therefore, toxicological evaluation of this kind of chemical substances has become an important part of its management, which has been paid more and more attention worldwide in recent years. The existing methods of toxicity evaluation are mostly limited to single target and single mechanism, so it is impossible to systematically evaluate the toxicity mechanism of compounds. Therefore, it is necessary to evaluate the toxicity of substituted benzene and perfluorocarbons based on holistic pathway. The "complex network" technology provides a new way to evaluate the toxicity mechanism of substituted benzene and perfluorocarbons because of its integrity and systematic analysis. Firstly, the interaction network of 20 substituted benzene endocrine disruptors and 71 effective targets was constructed by "complex network" technology. After analyzing the topological coefficients of the network, six genes were obtained as the central node genes of the network and brought into the KEGG signal pathway database. It is predicted by complex networks that substituted benzenes can affect estrogen signaling pathway through interaction with target gene ESR2 and MMP9, and affect mistranscription regulation pathway of prostate cancer and multiple bone marrow carcinoma by interaction with target genes HIST3H3 and MMP9. The mistranscription pathway of multiple bone marrow carcinoma may be a new signal pathway to replace the toxic effect of benzene endocrine disruptors. At the same time, we selected the central node proteins (NR1I2 and MMP9) and the central node compound C133 as a case study, and carried out molecular dynamics simulation to study the stability of the interaction. By analyzing the amino acid interaction network of target protein before and after kinetic analysis, it was found that the binding of substituted benzenes to NR1I2 and MMP9 target proteins was stronger and the interaction was stronger. It is further indicated that once endocrine disruptors enter the human body, they may be more preferentially and stably bound to receptor proteins, seriously affecting human health. Secondly, the interaction network of 10 perfluorocarbons with 82 effective targets was constructed by "complex network" technology. The central node genes, GLTPhHSD17B1 and SHBG1, were obtained by analyzing the topological properties of the network, in which HSD17B1 was involved in the biosynthesis pathway of steroid hormones. It is speculated that HSD17B1 is a potential target of perfluorinated compounds in estrogen related physiological pathways. At the same time, the disease involved in GLTPhHBG1SHBG target gene was analyzed, and the perfluorocarbon compounds were connected with the disease by the chemical-target interaction network. When the targets and pathways of perfluorocarbons are not clear, it provides a theoretical basis for the study of the effects of perfluorocarbons on related diseases. In this paper, the establishment of a "complex network" between multiple genes of a compound and an organism by means of calculation is beneficial to the interrelation between the compound and the signal pathway of the organism from the perspective of the overall activity of the protein / gene. To reveal and clarify the influence of chemical substances on the pathway of organism, and then to elucidate the complex action mechanism of chemical substances and predict the potential toxic effects from the system and the whole level, which provides a new method for the study of the mechanism of environmental pollutants.
【学位授予单位】：兰州大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R99

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