Targeted Modification and Structure-Activity Study of GL-29, an Analogue of the Antimicrobial Peptide Palustrin-2ISb

Liu, Siyan; Lin, Yaxian; Liu, Jiachen; Chen, Xiaoling; Ma, Chengbang; Xi, Xinping; Chen, Tianbao; Burrows, James F.; Wang, Lei

doi:10.3390/antibiotics11081048

Cited by 4 publications

(3 citation statements)

References 63 publications

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“…This is consistent with the blue fluorescence of DAPI and the absence of PI in untreated cells, since PI cannot penetrate intact bacterial membranes. These findings are comparable with studies, such as [63] by Liu et al, where GL-22 and GL-29 peptides showed damage against S. aureus by a membranolytic mechanism suggested by fluorescence microscopy. On the other hand, it has been observed that bacteria exposed to peptides tend to cluster together, a characteristic event previously described due to instability caused by the reduced membrane potential [64].…”

Section: Discussionsupporting

confidence: 91%

Antibacterial and Antiviral Properties of Chenopodin-Derived Synthetic Peptides

Feijoo-Coronel,

Mendes,

Ramírez

et al. 2024

Antibiotics

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Antimicrobial peptides have been developed based on plant-derived molecular scaffolds for the treatment of infectious diseases. Chenopodin is an abundant seed storage protein in quinoa, an Andean plant with high nutritional and therapeutic properties. Here, we used computer- and physicochemical-based strategies and designed four peptides derived from the primary structure of Chenopodin. Two peptides reproduce natural fragments of 14 amino acids from Chenopodin, named Chen1 and Chen2, and two engineered peptides of the same length were designed based on the Chen1 sequence. The two amino acids of Chen1 containing amide side chains were replaced by arginine (ChenR) or tryptophan (ChenW) to generate engineered cationic and hydrophobic peptides. The evaluation of these 14-mer peptides on Staphylococcus aureus and Escherichia coli showed that Chen1 does not have antibacterial activity up to 512 µM against these strains, while other peptides exhibited antibacterial effects at lower concentrations. The chemical substitutions of glutamine and asparagine by amino acids with cationic or aromatic side chains significantly favoured their antibacterial effects. These peptides did not show significant hemolytic activity. The fluorescence microscopy analysis highlighted the membranolytic nature of Chenopodin-derived peptides. Using molecular dynamic simulations, we found that a pore is formed when multiple peptides are assembled in the membrane. Whereas, some of them form secondary structures when interacting with the membrane, allowing water translocations during the simulations. Finally, Chen2 and ChenR significantly reduced SARS-CoV-2 infection. These findings demonstrate that Chenopodin is a highly useful template for the design, engineering, and manufacturing of non-toxic, antibacterial, and antiviral peptides.

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Section: Discussionsupporting

confidence: 91%

Antibacterial and Antiviral Properties of Chenopodin-Derived Synthetic Peptides

Feijoo-Coronel,

Mendes,

Ramírez

et al. 2024

Antibiotics

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“…Such AMPs maximizes the role of targeted identification of infection sites and targeted killing of pathogenic bacteria while maintaining the homeostasis of the microflora and the health of tissue cells. [21] Targeted AMPs can be constructed in various ways and can be used to target lipopolysaccharides (LPS) to kill specific gram-negative bacteria. For example, Muhle et al constructed a cysteine 𝛽-fold framework to mimic the binding site of LPS and designed the resulting AMP sequence and its derivatives to have a significant bactericidal effect on gramnegative bacteria antimicrobial activity was 200-fold higher than that of gram-positive bacteria.…”

Section: Targeted Amp Designmentioning

confidence: 99%

Section: Abdominal Infectionmentioning

confidence: 99%

Advances of Antimicrobial Peptide‐Based Biomaterials for the Treatment of Bacterial Infections

Lai

Shan

2023

Advanced Science

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Owing to the increase in multidrug-resistant bacterial isolates in hospitals globally and the lack of truly effective antimicrobial agents, antibiotic resistant bacterial infections have increased substantially. There is thus an urgent need to develop new antimicrobial drugs and their related formulations. In recent years, natural antimicrobial peptides (AMPs), AMP optimization, self-assembled AMPs, AMP hydrogels, and biomaterial-assisted delivery of AMPs have shown great potential in the treatment of bacterial infections. In this review, it is focused on the development prospects and shortcomings of various AMP-based biomaterials for treating animal model infections, such as abdominal, skin, and eye infections. It is hoped that this review will inspire further innovations in the design of AMP-based biomaterials for the treatment of bacterial infections and accelerate their commercialization.

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Recent Progress in the Discovery and Design of Antimicrobial Peptides Using Traditional Machine Learning and Deep Learning

et al. 2022

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Antimicrobial resistance has become a critical global health problem due to the abuse of conventional antibiotics and the rise of multi-drug-resistant microbes. Antimicrobial peptides (AMPs) are a group of natural peptides that show promise as next-generation antibiotics due to their low toxicity to the host, broad spectrum of biological activity, including antibacterial, antifungal, antiviral, and anti-parasitic activities, and great therapeutic potential, such as anticancer, anti-inflammatory, etc. Most importantly, AMPs kill bacteria by damaging cell membranes using multiple mechanisms of action rather than targeting a single molecule or pathway, making it difficult for bacterial drug resistance to develop. However, experimental approaches used to discover and design new AMPs are very expensive and time-consuming. In recent years, there has been considerable interest in using in silico methods, including traditional machine learning (ML) and deep learning (DL) approaches, to drug discovery. While there are a few papers summarizing computational AMP prediction methods, none of them focused on DL methods. In this review, we aim to survey the latest AMP prediction methods achieved by DL approaches. First, the biology background of AMP is introduced, then various feature encoding methods used to represent the features of peptide sequences are presented. We explain the most popular DL techniques and highlight the recent works based on them to classify AMPs and design novel peptide sequences. Finally, we discuss the limitations and challenges of AMP prediction.

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Targeted Modification and Structure-Activity Study of GL-29, an Analogue of the Antimicrobial Peptide Palustrin-2ISb

Cited by 4 publications

References 63 publications

Antibacterial and Antiviral Properties of Chenopodin-Derived Synthetic Peptides

Antibacterial and Antiviral Properties of Chenopodin-Derived Synthetic Peptides

Advances of Antimicrobial Peptide‐Based Biomaterials for the Treatment of Bacterial Infections

Recent Progress in the Discovery and Design of Antimicrobial Peptides Using Traditional Machine Learning and Deep Learning

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