Department of Chemistry, Queen's University, Kingston, ON, K7L 3N6, Canada.
Department of Chemistry, Queen's University, Kingston, ON, K7L 3N6, Canada.
Curr Opin Chem Biol. 2023 Oct;76:102367. doi: 10.1016/j.cbpa.2023.102367. Epub 2023 Jul 17.
Historically, bacterial natural products have served as an excellent source of drug leads, however, in recent decades the rate of discovery has slowed due to multiple challenges. Rapid advances in genome sequencing science in recent years have revealed the vast untapped encoded potential of bacteria to make natural products. To access these molecules, researchers can employ the ever-growing array of bioinformatic tools at their disposal and leverage newly developed experimental approaches to validate these bioinformatic-driven hypotheses. When used together effectively, bioinformatic and experimental tools enable researchers to deeply examine the full diversity of bacterial natural products. This review briefly outlines recent bioinformatic tools that can facilitate natural product research in bacteria including the use of CRISPR, co-occurrence network analysis, and combinatorial generation of microbial natural products to test bioinformatic hypotheses in the lab.
从历史上看,细菌天然产物一直是药物先导的绝佳来源,但近几十年来,由于多种挑战,发现的速度已经放缓。近年来,基因组测序科学的快速发展揭示了细菌制造天然产物的巨大未开发的编码潜力。为了获取这些分子,研究人员可以利用他们手中不断增长的生物信息学工具,并利用新开发的实验方法来验证这些基于生物信息学的假设。当这些工具被有效地结合使用时,生物信息学和实验工具使研究人员能够深入研究细菌天然产物的全部多样性。本文简要概述了最近可用于细菌天然产物研究的生物信息学工具,包括 CRISPR 的使用、共现网络分析以及微生物天然产物的组合生成,以在实验室中检验生物信息学假设。