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基于计算机辅助从中药中筛选针对耐抑制剂TEMβ-内酰胺酶突变体的强效抑制剂化合物

Computer aided screening of potent inhibitor compounds against inhibitor resistant TEM β-lactamase mutants from traditional Chinese medicine.

作者信息

Zhu Qifeng, Yin Yanxia, Liu Hanjie, Tian Jinhong

机构信息

College of Pharmaceutical Sciences, Southwest University, Chongqing, China.

出版信息

Bioinformation. 2014 Dec 31;10(12):750-6. doi: 10.6026/97320630010750. eCollection 2014.

Abstract

Inhibitor-resistant TEM (IRT) type β-lactamase mutation is largely known. Therefore, it is of interest to identify new yet improved leads against IRT from traditional Chinese medicine. Hence, we screened more than 10,000 compounds from Chinese medicine (tcm@taiwan database) with mutant molecular IRT models through docking techniques. This exercise identified compounds affeic acid, curcumin, salvianolic acid E, ferulic acid and p-coumaric acid with high binding score with the mutants. This was further validated in vitro where salvianolic acid E combined with cefoperazone and sulbactam effectively inhibit the R244S mutant.

摘要

耐抑制剂的TEM(IRT)型β-内酰胺酶突变广为人知。因此,从传统中药中鉴定出新的、更有效的抗IRT先导物具有重要意义。为此,我们通过对接技术,利用突变分子IRT模型从中药(台湾中医药数据库)中筛选了一万多种化合物。这项研究确定了阿魏酸、姜黄素、丹酚酸E、阿魏酸和对香豆酸与突变体具有高结合分数。这在体外进一步得到验证,其中丹酚酸E与头孢哌酮和舒巴坦联合使用可有效抑制R244S突变体。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17a7/4312368/7bc3662a8009/97320630010750F1.jpg

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