Evaluation of Bacteriophage Φ11 host recognition protein and its host-binding peptides for diagnosing/targeting Staphylococcus aureus infections - Dokuz, Senanur; Tasdurmazli, Semra; Acar, Tayfun; Duran, Gizem Nur; Ozdemir, Cilem; Ozbey, Utku; Ozbil, Mehmet; Karadayi, Sukriye; Bayrak, Omer Faruk; Derman, Serap; Chen, John Yu -Shen; Ozbek, Tulin (ELSEVIER, 2024)
Background: Evaluating the potential of using both synthetic and biological products as targeting agents for the diagnosis, imaging, and treatment of infections due to particularly antibiotic-resistant pathogens is important for controlling infections. This study examined the interaction between Gp45, a receptor-binding protein of the phi 11 lysogenic phage, and its host Staphylococcus aureus (S. aureus), a common cause of nosocomial infections. Methods: Using molecular dynamics and docking simulations, this study identified the peptides that bind to S. aureus wall teichoic acids via Gp45. It compared the binding affinity of Gp45 and the two highest-scoring peptide sequences (P1 and P3) and their scrambled forms using microscopy, spectroscopy, and ELISA. Results: It was found that rGp45 (recombinant Gp45) and chemically synthesised P1 had a higher binding affinity for S. aureus compared with all other peptides, except for Escherichia coli. Furthermore, rGp45 had a capture efficiency of > 86%; P1 had a capture efficiency of > 64%. Conclusion: These findings suggest that receptor-binding proteins such as rGp45, which provide a critical initiation of the phage life cycle for host adsorption, might play an important role in the diagnosis, imaging, and targeting of bacterial infections. Studying such proteins could accordingly enable the development of effective strategies for controlling infections. (c) 2024 Elsevier Ltd and International Society of Antimicrobial Chemotherapy. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Keywords: Receptor binding protein; Targeting peptide; Phi 11 phage; Staphylococcus aureus; Antimicrobial resistance; CELL-SURFACE; BASEPLATE; ACID; PARAMETERIZATION; IDENTIFICATION; STRATEGIES; PREDICTION; ACCURACY; LIGANDS; MODELS; Infectious Diseases; Microbiology; Pharmacology & Pharmacy