Suppr超能文献

应用化学生信学方法鉴定与软珊瑚共生的链霉菌 HC14 产生的强效抗假丝酵母菌代谢产物。

Identification of potent anti-Candida metabolites produced by the soft coral associated Streptomyces sp. HC14 using chemoinformatics.

机构信息

Faculty of Aquatic and Fisheries Sciences, Kafrelsheikh University, Kafrelsheikh, 33516, Egypt.

Botany and Microbiology Department, Faculty of Science, Alexandria University, Alexandria, 21511, Egypt.

出版信息

Sci Rep. 2023 Aug 2;13(1):12564. doi: 10.1038/s41598-023-39568-7.

Abstract

Candida albicans is the most common pathogen responsible for both spontaneous and recurrent candidiasis. The available treatment of Candida infections has several adverse effects, and the development of new drugs is critical. The current study looked at the synthesis of anti-Candida metabolites by Streptomyces sp. HC14 recovered from a soft coral. Using the Plackett Burman design, the medium composition was formulated to maximize production. Using GC-MS, the compounds have been identified, and a cheminformatics approach has been used to identify the potential source of activity. The compounds that showed high potential for activity were identified as pyrrolo[1,2-a]pyrazine-1,4-dione, hexahydro-3-(phenylmethyl)-3 and di-n-octyl based on their docking score against the cytochrome monooxygenase (CYP51) enzyme in Candida albicans. As a result of their discovery, fewer molecules need to be chemically synthesized, and fermentation optimization maximizes their synthesis, providing a strong foundation for the development of novel anti-Candida albicans agents.

摘要

白色念珠菌是引起自发性和复发性念珠菌病的最常见病原体。现有的念珠菌感染治疗方法有多种不良反应,因此开发新药物至关重要。本研究着眼于从软珊瑚中回收的链霉菌 sp. HC14 合成抗念珠菌代谢物。使用 Plackett Burman 设计,制定了培养基组成以实现最大产量。使用 GC-MS 鉴定了化合物,并使用化学信息学方法确定了潜在的活性来源。根据它们对白色念珠菌细胞色素单加氧酶 (CYP51) 酶的对接评分,显示出高活性潜力的化合物被鉴定为吡咯并[1,2-a]吡嗪-1,4-二酮、六氢-3-(苯甲基)-3 和二正辛基。由于它们的发现,需要化学合成的分子更少,发酵优化最大限度地提高了它们的合成,为开发新型抗白色念珠菌药物提供了坚实的基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dceb/10397342/236d9afd93d4/41598_2023_39568_Fig1_HTML.jpg

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