ESKtides: a comprehensive database and mining method for ESKAPE phage-derived antimicrobial peptides.

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-03-26 DOI:10.1093/database/baae022
Hongfang Wu, Rongxian Chen, Xuejian Li, Yue Zhang, Jianwei Zhang, Yanbo Yang, Jun Wan, Yang Zhou, Huanchun Chen, Jinquan Li, Runze Li, Geng Zou
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Abstract

'Superbugs' have received increasing attention from researchers, such as ESKAPE bacteria (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter spp.), which directly led to about 1 270 000 death cases in 2019. Recently, phage peptidoglycan hydrolases (PGHs)-derived antimicrobial peptides were proposed as new antibacterial agents against multidrug-resistant bacteria. However, there is still a lack of methods for mining antimicrobial peptides based on phages or phage PGHs. Here, by using a collection of 6809 genomes of ESKAPE isolates and corresponding phages in public databases, based on a unified annotation process of all the genomes, PGHs were systematically identified, from which peptides were mined. As a result, a total of 12 067 248 peptides with high antibacterial activities were respectively determined. A user-friendly tool was developed to predict the phage PGHs-derived antimicrobial peptides from customized genomes, which also allows the calculation of peptide phylogeny, physicochemical properties, and secondary structure. Finally, a user-friendly and intuitive database, ESKtides (http://www.phageonehealth.cn:9000/ESKtides), was designed for data browsing, searching and downloading, which provides a rich peptide library based on ESKAPE prophages and phages. Database URL:  10.1093/database/baae022.

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ESKtides:ESKAPE噬菌体衍生抗菌肽的综合数据库和挖掘方法。
超级细菌 "越来越受到研究人员的关注,例如 ESKAPE 细菌(粪肠球菌、金黄色葡萄球菌、肺炎克雷伯菌、鲍曼不动杆菌、铜绿假单胞菌和肠杆菌属),它们直接导致 2019 年约 1 270 000 例死亡病例。最近,有人提出将噬菌体肽聚糖水解酶(PGHs)衍生的抗菌肽作为对抗多重耐药菌的新型抗菌剂。然而,目前仍缺乏挖掘基于噬菌体或噬菌体肽聚糖水解酶的抗菌肽的方法。本文利用公共数据库中收集的 6809 个 ESKAPE 分离物基因组和相应的噬菌体,在对所有基因组进行统一注释的基础上,系统地鉴定了 PGHs,并从中挖掘出肽。结果,共分别确定了 12 067 248 个具有高抗菌活性的多肽。研究人员开发了一种用户友好型工具,用于预测从定制基因组中提取的噬菌体 PGHs 抗菌肽,该工具还可以计算肽的系统发育、理化性质和二级结构。最后,还设计了一个用户友好型直观数据库 ESKtides (http://www.phageonehealth.cn:9000/ESKtides),用于数据浏览、搜索和下载,该数据库提供了基于 ESKAPE 原噬菌体和噬菌体的丰富肽库。数据库 URL: 10.1093/database/baae022.
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CiteScore
7.20
自引率
4.30%
发文量
567
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