| 紫外分光光度法-核磁共振法用于胆甾类人工受体对酚类的识别研究 |
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| 引用本文： | 叶英,索有瑞,杨永晶,杨芳,韩丽娟.紫外分光光度法-核磁共振法用于胆甾类人工受体对酚类的识别研究[J].分析测试技术与仪器,2015,21(1):1-6. |
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| 作者姓名： | 叶英 索有瑞 杨永晶 杨芳 韩丽娟 |
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| 作者单位： | 1. 中国科学院西北高原生物研究所,青海西宁810001;中国科学院大学研究生院,北京 100049
2. 中国科学院西北高原生物研究所,青海西宁810001;青海大学农林科学院,青海西宁810016 |
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| 基金项目： | 国家国际科技合作专项(S2014GR0058)资助. |
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| 摘 要： | 利用常规加热方法,以脱氧胆酸甲酯为主体、芳酰肼及氨基酸甲酯为手臂合成了分子钳a-d.利用紫外分光光度法及1H NMR研究考察了部分分子钳对苯酚、对甲氧基苯酚、间甲氧基苯酚的识别性能,并测定了主客体之间的结合常数(Ka)和自由能变化值(-△G0).研究结果表明,主体分子钳与所考察的酚类化合物可形成1∶1型超分子配合物.
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| 关 键 词： | 脱氧胆酸 分子钳 酚类化合物 紫外分光光度法 识别性能 |
| 收稿时间： | 3/8/2015 12:00:00 AM |
| 修稿时间： | 2015/3/24 0:00:00 |
Application of UV Spectrophotometry-NMR Methodology in Research on Recognition Properties of Receptors Based on Deoxycholic Acid for Phenolic Compounds |
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| YE Ying,SUO You-rui,YANG Yong-jing,YANG Fang and HAN Li-juan.Application of UV Spectrophotometry-NMR Methodology in Research on Recognition Properties of Receptors Based on Deoxycholic Acid for Phenolic Compounds[J].Analysis and Testing Technology and Instruments,2015,21(1):1-6. |
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| Authors: | YE Ying SUO You-rui YANG Yong-jing YANG Fang and HAN Li-juan |
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| Institution: | Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China;Graduate University of Chinese Academy of Sciences, Beijing 100049, China;Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China;Academy of Agriculture and Forestry Sciences, Qinghai University, Xining 810016, China;Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China;Graduate University of Chinese Academy of Sciences, Beijing 100049, China;Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China;Graduate University of Chinese Academy of Sciences, Beijing 100049, China;Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China;Graduate University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | |
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| Keywords: | deoxycholic acid molecular tweezers phenolic compounds UV spectrophotometry molecular recognition |
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