Suppr超能文献

生物信息学工具和方法的亮点,用于验证微生物天然产物研究中基于生物信息学的假设。

Highlights of bioinformatic tools and methods for validating bioinformatics derived hypotheses for microbial natural products research.

机构信息

Department of Chemistry, Queen's University, Kingston, ON, K7L 3N6, Canada.

Department of Chemistry, Queen's University, Kingston, ON, K7L 3N6, Canada.

出版信息

Curr Opin Chem Biol. 2023 Oct;76:102367. doi: 10.1016/j.cbpa.2023.102367. Epub 2023 Jul 17.

Abstract

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.

摘要

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。

相似文献

1
Highlights of bioinformatic tools and methods for validating bioinformatics derived hypotheses for microbial natural products research.
Curr Opin Chem Biol. 2023 Oct;76:102367. doi: 10.1016/j.cbpa.2023.102367. Epub 2023 Jul 17.
2
Leveraging a large microbial strain collection for natural product discovery.
J Biol Chem. 2019 Nov 8;294(45):16567-16576. doi: 10.1074/jbc.REV119.006514. Epub 2019 Sep 30.
3
Targeting Bacterial Genomes for Natural Product Discovery.
Trends Pharmacol Sci. 2020 Jan;41(1):13-26. doi: 10.1016/j.tips.2019.11.002. Epub 2019 Dec 7.
4
Machine Learning-Enabled Genome Mining and Bioactivity Prediction of Natural Products.
ACS Synth Biol. 2023 Sep 15;12(9):2650-2662. doi: 10.1021/acssynbio.3c00234. Epub 2023 Aug 22.
5
Recent advances in the culture-independent discovery of natural products using metagenomic approaches.
Chin J Nat Med. 2024 Feb;22(2):100-111. doi: 10.1016/S1875-5364(24)60585-6.
7
The re-emerging role of microbial natural products in antibiotic discovery.
Antonie Van Leeuwenhoek. 2014 Jul;106(1):173-88. doi: 10.1007/s10482-014-0204-6. Epub 2014 Jun 13.
8
Genomic charting of ribosomally synthesized natural product chemical space facilitates targeted mining.
Proc Natl Acad Sci U S A. 2016 Oct 18;113(42):E6343-E6351. doi: 10.1073/pnas.1609014113. Epub 2016 Oct 3.
9
Discovery of novel bioactive natural products driven by genome mining.
Drug Discov Ther. 2018;12(6):318-328. doi: 10.5582/ddt.2018.01066.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验