石诚, 孙影, 肖斌, 郑珩. 利用基因组数据挖掘发现新抗生素的研究J. 药学学报, 2018,53(6): 845-851. doi: 10.16438/j.0513-4870.2018-0221
引用本文: 石诚, 孙影, 肖斌, 郑珩. 利用基因组数据挖掘发现新抗生素的研究J. 药学学报, 2018,53(6): 845-851. doi: 10.16438/j.0513-4870.2018-0221
SHI Cheng, SUN Ying, XIAO Bin, ZHENG Heng. Discovery of new antibiotics using genome data miningJ. Acta Pharmaceutica Sinica, 2018,53(6): 845-851. doi: 10.16438/j.0513-4870.2018-0221
Citation: SHI Cheng, SUN Ying, XIAO Bin, ZHENG Heng. Discovery of new antibiotics using genome data miningJ. Acta Pharmaceutica Sinica, 2018,53(6): 845-851. doi: 10.16438/j.0513-4870.2018-0221

利用基因组数据挖掘发现新抗生素的研究

Discovery of new antibiotics using genome data mining

  • 摘要: 随着多重耐药(MDR)细菌在全球范围内传播,细菌耐药性问题已成为影响人类健康的重大问题。虽然通过筛选细菌菌株获得抗生素的传统方法已经为研究者找到了目前可用的大多数抗生素,然而在过去的几十年中,这种方法产生的抗生素日益减少,且越来越难以发现具有新结构的化合物实体。目前,临床上甚至研发中能对抗超级耐药细菌的药物已寥寥无几,因此,开发和应用新的技术来应对细菌耐药性问题已经迫在眉睫。自20多年前对第一个细菌基因组进行测序以来,大量细菌基因组序列信息可以为新抗生素的发现提供线索。本文简要概述了现有的数据资源,并着重介绍了基因组挖掘和宏基因组挖掘在发现新抗生素中的应用。

     

    Abstract: With the worldwide spread of multi-drug resistant (MDR) bacteria, bacterial resistance has become a major issue affecting human health. Although traditional methods for obtaining antibiotics by screening bacterial strains have found the most available antibiotics for us, this method has resulted in fewer and fewer antibiotics in the past few decades and is increasingly difficult to find the new structure of the compound entity. At present, there are few drugs that can fight super-resistant bacteria in the clinic or even research. therefore, the development and application of new technologies to address the issue of bacterial resistance is imminent. Since the first bacterial genome was sequenced more than 20 years ago, a large number of bacterial genomic sequence information can provide clues for the discovery of new antibiotics. In this review, we briefly outline the available data sources and highlight the use of genomic mining and metagenomics in discovery of new antibiotics.

     

/

返回文章
返回