铁载体
化学空间
计算生物学
生物
细菌
生物信息学
遗传学
药物发现
作者
Ruolin He,Shaohua Gu,Jiazheng Xu,Xuejian Li,Haoran Chen,Zhengying Shao,Fanhao Wang,Jiqi Shao,Wen‐Bing Yin,Long Qian,Zhong Wei,Zhiyuan Li
出处
期刊:iMeta
[Wiley]
日期:2024-04-01
卷期号:3 (2): e192-e192
被引量:33
摘要
In this work, we introduced a siderophore information database (SIDERTE), a digitized siderophore information database containing 649 unique structures. Leveraging this digitalized data set, we gained a systematic overview of siderophores by their clustering patterns in the chemical space. Building upon this, we developed a functional group-based method for predicting new iron-binding molecules with experimental validation. Expanding our approach to the collection of open natural products (COCONUT) database, we predicted a staggering 3199 siderophore candidates, showcasing remarkable structure diversity that is largely unexplored. Our study provides a valuable resource for accelerating the discovery of novel iron-binding molecules and advancing our understanding of siderophores.
科研通智能强力驱动
Strongly Powered by AbleSci AI