請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/90153
標題: | 雌激素受體α與內分泌干擾物結合相互作用的QSAR和量子化學研究 QSAR and Quantum Chemical Studies on the Binding Interaction of Estrogen Receptor Alpha with Endocrine Disrupting Chemicals |
作者: | 紀淑君 Shu-Chun Chi |
指導教授: | 席行正 Hsing-Cheng Hsi |
關鍵字: | 雌激素受體α,內分泌干擾化學物質,遺傳算法多元線性回歸,分子對接,量子化學團簇模型,概念密度泛函理論, Estrogen receptor α,Endocrine disrupting chemicals,Genetic algorithm multiple linear regression,Molecular docking,Quantum chemical cluster model,Conceptual density functional theory, |
出版年 : | 2023 |
學位: | 碩士 |
摘要: | 近年來,內分泌干擾物質(EDC)所引起的環境污染是一個重要的議題,由於內分泌系統對激素濃度的微小變化極其敏感,因此人們越來越關注可能模仿激素活性的環境污染物。全球有80%未經處理的工業廢水直接排出造成水污染及土壤污染,幾乎在每個生態系統中都能檢測到EDC。由於大多數的內分泌干擾物質作用機制仍然未知,測試所有使用過的化學品的作用是一項重要但也是昂貴且困難的任務。而且生物測定的可用性有限,體外和體內測定法存在實驗週期長、經濟成本高的缺點,因此不適用於大量化學品的常規篩查,反之迫切需要更合理的方法來幫助快速識別潛在有害的化學物質。
本研究採用PaDEL描述符和量子化學遺傳算法多重線性回歸(GA-MLR)方法對雌激素受體α(ERα)與異種雌激素(PCB、苯酚和DDT)和植物性雌激素的相對結合親和力(log RBA)進行預測。 優化模型的結果表明,異種雌激素和植物性雌激素皆受疏水相互作用的影響,不同的是異種雌激素主要是電子流動影響log RBA大小,而影響植物性雌激素的log RBA的主要因素則是氫鍵相互作用和分子的結構。透過全局的分子對接與局部的量子化學簇模型方法結果表明,氫鍵相互作用和疏水相互作用證實了內分泌干擾物化學質和ERα結合結構的穩定性。基於概念密度泛函理論計算的化學反應性描述符也表明電荷控制相互作用的結合機制通常會優於前沿控制相互作用的結合機制。 Environmental pollution caused by endocrine-disrupting substances (EDC) has been an essential topic recently. Since the endocrine system is susceptible to small changes in hormone concentrations, there has been increasing concern about environmental pollutants that may mimic hormone activity. 80% of the world's untreated industrial wastewater is directly discharged to cause water and soil pollution, and EDC can be detected in almost every ecosystem. Since the mechanism of action of most endocrine-disrupting substances remains unknown, testing the effects of all chemicals used is a necessary but also expensive and challenging task. Moreover, the limited availability of bioassays, in vitro and in vivo assays have the disadvantages of long experimental cycle and high economic cost, making them unsuitable for routine screening of many chemicals. In contrast, more rational methods are urgently needed to help rapidly identify potentially harmful chemicals. In this study, PaDEL descriptors and quantum chemical genetic algorithm multiple linear regression (GA-MLR) methods were used to predict the relative binding affinities (log RBA) of estrogen receptor α (ERα) to xenoestrogens (PCB, phenol, and DDT) and phytoestrogens. The results of the optimized model show that both xenoestrogens and phytoestrogens are affected by hydrophobic interactions. The difference is that xenoestrogens mainly affect the size of log RBA by electron flow, while the main factors affecting log RBA of phytoestrogens are hydrogen bond interactions and molecular structures. Through the global molecular docking and local quantum chemical cluster modeling methods, the hydrogen bond interaction and hydrophobic interaction confirmed the stability of the endocrine disruptor chemical substance and the binding structure of ERα. Chemical reactivity descriptors based on conceptual density functional theory calculations suggest that binding mechanisms for charge-controlled interactions generally outperform those for front-controlled interactions. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/90153 |
DOI: | 10.6342/NTU202304011 |
全文授權: | 同意授權(全球公開) |
顯示於系所單位: | 環境工程學研究所 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-111-2.pdf 此日期後於網路公開 2028-08-10 | 6.43 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。