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马齿苋转录组中计算机检测到的抗菌肽的肽-膜对接及分子动力学模拟

Peptide-Membrane Docking and Molecular Dynamic Simulation of In Silico Detected Antimicrobial Peptides from Portulaca oleracea's Transcriptome.

作者信息

Hasannejad-Asl Behnam, Heydari Salimeh, Azod Fahime, Pooresmaeil Farkhondeh, Esmaeili Ali, Bolhassani Azam

机构信息

Department of Hepatitis and AIDS, Pasteur Institute of Iran, Tehran, Iran.

Department of Biotechnology, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

出版信息

Probiotics Antimicrob Proteins. 2024 Oct;16(5):1501-1515. doi: 10.1007/s12602-024-10261-z. Epub 2024 May 4.

Abstract

The main issue with clinical infections is multidrug resistance to traditional antibiotics. As they are essential to innate immunity, shielding hosts from pathogenic microbes, traditional herbal remedies are an excellent supplier of antimicrobial peptides (AMPs), vital parts of defensive systems. Nevertheless, little is known about the bioactive peptide components of most ethnobotanical species. Our goal in this study was to find new, likely AMPs from Portulaca oleracea (P. oleracea) using in silico studies. The P. oleracea transcriptome was gained from Sequence Read Archive (SRA) and quality controlled, then adapters and other low-quality reads were trimmed. Afterward, de novo assembled and translated open reading frames (ORFs) were determined. Next, the ORFs were filtered based on AMP physiochemical criteria and deep learning methods. Finally, the five selected putative AMPs docked with E. coli and S. aureus membranes that showed penetration in bilayers. In this step, PO2 was chosen as a candidate AMP to analyze with molecular dynamics (MD) simulations. Our data demonstrated that PO2 is more stable in E. coli than in S. aureus. Moreover, these predicted AMPs can be good candidates for in vitro and in vivo analysis.

摘要

临床感染的主要问题是对传统抗生素的多重耐药性。由于传统草药疗法对先天免疫至关重要,能保护宿主免受致病微生物侵害,所以它们是抗菌肽(AMPs)的优质来源,而抗菌肽是防御系统的重要组成部分。然而,对于大多数民族植物种类的生物活性肽成分,我们了解得还很少。本研究的目的是通过计算机模拟研究,从马齿苋中寻找新的、可能的抗菌肽。马齿苋转录组取自序列读取存档库(SRA)并进行了质量控制,然后去除了接头和其他低质量 reads。之后,进行了从头组装并确定了翻译的开放阅读框(ORF)。接下来,根据抗菌肽的理化标准和深度学习方法对开放阅读框进行筛选。最后,将五个选定的假定抗菌肽与大肠杆菌和金黄色葡萄球菌的膜进行对接,结果显示它们能穿透双层膜。在这一步骤中,选择PO2作为候选抗菌肽进行分子动力学(MD)模拟分析。我们的数据表明,PO2在大肠杆菌中比在金黄色葡萄球菌中更稳定。此外,这些预测的抗菌肽可能是体外和体内分析的良好候选物。

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