| Autor: |
Heqian Zhang, Yihan Wang, Pengtao Huang, Yanran Zhu, Xiaojie Li, Zhaoying Chen, Yu Liu, Jiakun Jiang, Yuan Gao, Jiaquan Huang, Zhiwei Qin |
| Rok vydání: |
2022 |
| Popis: |
Antimicrobial peptides (AMPs) are valuable alternatives to traditional antibiotics that possess a variety of potent biological activities by exerting immunomodulatory effects to clear difficult-to-treat infections. Understanding the structure-activity relationships (SARs) of AMPs can direct the synthesis of desirable therapeutics. In this study, we use machine learning-guided directed evolution to develop the lipopolysaccharide-binding domain (LBD), which acts as a functional domain of anti-lipopolysaccharide factor (ALF), a family of AMPs, identified fromMarsupenaeus japonicus. We report the identification of LBDA-Das an output of this algorithm with the input of the original LBDMjsequence and show the NMR solution structure of LBDB, which possesses a circular extended structure with a disulfide crosslink in each terminus and two 310-helices and exhibits a broad antimicrobial spectrum. Scanning electron microscopy and transmission electron microscopy showed LBDBinduced the formation of a cluster of bacteria wrapped in a flexible coating that ruptured and consequently killed the bacteria. The co-injection of LBDBandVibrio alginolyticus, Staphylococcus aureusand another major pathogen in shrimp aquaculture white spot syndrome virusin vivoimproved the survival ofM. japonicus, indicating a promising therapeutic role of LBDBfor infectious disease. The findings of this study pave the way for the rational drug design of activity-enhanced peptide antibiotics. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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