摘要
酪氨酸酶是细胞内催化合成黑素的关键酶。理解酪氨酸酶抑制剂结构与活性之间的关系对于设计新药和化妆品具有重要意义。然而,酪氨酸酶抑制剂的定量构效关系仍不清楚。本文利用配体和结构描述符构建了隐式和显式模型,阐明了酪氨酸酶抑制剂定量构效关系。隐式模型的相关系数R高达0.961,显式模型的相关系数为0.775。两个模型很好地预测了3个茶多酚的酪氨酸酶抑制活性,表儿茶素没食子酸酯(ECG)>表没食子儿茶素没食子酸酯(EGCG)>没食子酸(G)。相关性分析发现,抑制剂与酪氨酸酶结合引起的构象熵损失与抑制剂的活性密切相关。具有较少构象熵损失的ECG在4种茶多酚中具有较高酪氨酸酶抑制活性。结合自由能计算也证实ECG与酪氨酸酶的结合能力最强。此外,通过分解结合自由能发现,酪氨酸酶活性中心的氨基酸残基(His57、His201、Asn202、His205、Glu192和Val215)与抑制剂形成了较强的范德华和静电相互作用,进而稳定了复合物结构。
The use of variant inhibitors to regulate the bioactivities of tyrosinase, which is the key enzyme in charge of the production of melanin and pigments, is a long-standing approach to design cosmetic and pharmaceutical products. The quantitative description of the structure-activity relationship of tyrosinase inhibitors is still unclear. In this study, we constructed descriptive models by integrating ligand- and structure-based approaches for such purpose. They provide correlation coefficients of 0.961 for implicit models and 0.775 for explicit model, respectively, to descript the activities of three tea polyphenols with the tyrosinase inhibitory activity order of ( - )-Epicatechin gallate(ECG)〉( - )-Epigallocatechin gallate(EGCG)〉Gallic acid(G). As revealing from the descriptive models, entropy loss is more important than other features for determining inhibitory activity and thus the tyrosinase-ECG complex with the fewer conformational entropy loss has the strongest inhibitory activity in vitro among the four tea polyphenols. Moreover, residues including His57, His201, Asn202, His205 Glu192 and Val215 are the core of active sites in tyrosinase, and stabilize the tyrosinase-inhibitor complex by van der Waals and hydrogen bonding interactions.
作者
汤海峰
崔凤超
刘伦洋
李云琦
TANG Haifeng;CUI Fengchao;LIU Lunyang;LI Yunqi(a Key Laboratory of Synthetic Rubber,Changchun Institute of Applied Chemistry,Chinese Academy of Sciences,Changchun 130022,China;b School of Life Science,Jilin University,Changchun 130012,China;c University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《应用化学》
CAS
CSCD
北大核心
2018年第7期788-794,共7页
Chinese Journal of Applied Chemistry
基金
国家自然科学基金(21374117,21504092)
中国科学院百人计划和国家博士后科学基金(2014M561310)资助