Rejuvenation of Meropenem by Conjugation with Tilapia Piscidin-4 Peptide Targeting NDM-1 Escherichia coli.

Sanjay Prasad Selvaraj, Kuan-Hung Lin,Wen-Chun Lin,Ming-Feng You,Tsung-Lin Li,Jyh-Yih Chen

ACS omega(2024)

Cited 0|Views0
No score
Abstract
Gram-negative pathogens that produce β-lactamases pose a serious public health threat as they can render β-lactam antibiotics inactive via hydrolysis. This action contributes to the waning effectiveness of clinical antibiotics and creates an urgent need for new antimicrobials. Antimicrobial peptides (AMPs) exhibiting multimodal functions serve as a potential source in spite of a few limitations. Thus, the conjugation of conventional antibiotics with AMPs may be an effective strategy to leverage the advantages of each component. In this study, we conjugated meropenem to the AMP Tilapia piscidin 4 (TP4) using a typical coupling reaction. The conjugate was characterized by using HPLC-MS, HR-MS, and MS-MS fragmentation analysis. It was then evaluated in terms of antibacterial potency, hemolysis, and cytotoxicity toward RAW264.7 and CCD-966SK cell lines. The conjugation of meropenem with TP4 significantly reduced the cytotoxicity compared to TP4. Conjugation of unprotected TP4 with meropenem resulted in cross-linking at the N-terminal and lysine sites. The structural activity relationship of the two isomers of the TP4-meropenem conjugate was investigated. Both the isomers showed notable antibacterial activities against NDM-1 Escherichia coli and reduced red blood cell hemolysis as compared to TP4. Lysine conjugate (TP4-K-Mero) showed lesser hemolysis than the N-terminal conjugate (TP4-N-Mero). Molecular modeling further revealed that the conjugates can bind to lipopolysaccharides and inhibit NDM-1 β-lactamase. Together, these data show that conjugation of antibiotics with AMP can be a feasible approach to increase the therapeutic profile and effectively target multidrug-resistant pathogens. Furthermore, antibiotic conjugation at different AMP sites tends to show unique biological properties.
More
Translated text
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined