Designing a Novel Multi-Epitope Peptide as a Potential Serodiagnosis Marker for the Diagnosis of Acinetobacter baumannii: An In silico Approach

Title:Designing a Novel Multi-Epitope Peptide as a Potential Serodiagnosis Marker for the Diagnosis of Acinetobacter baumannii: An In silico Approach

Volume: 21

Author(s): Maryam Rezaee, Mohsen Mohammadi, Amir Savardashtaki, Mohammad Reza Rahbar and Navid Nezafat*

Affiliation:

• Pharmaceutical Sciences Research Center, Shiraz University of Medical Science, Shiraz, Iran
• Department of Pharmaceutical Biotechnology, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran

Keywords: Acinetobacter baumannii, ELISA, recombinant protein, multi-epitope, rapid diagnosis.

Abstract: Background: Acinetobacter baumannii is an opportunistic pathogen that causes many infections, including nosocomial infections; this bacterium has a high mortality rate among other bacteria. A. baumannii has an elastic genome that changes rapidly when exposed to harsh environmental conditions, leading to widespread bacterial resistance to various disinfectants and antibiotics. The high ability of bacteria to bind to all surfaces and survive in different conditions has caused the spread of bacteria in various environments. Rapid detection is very important in preventing the spread and even treatment of the infection.

Methods: Currently, the Polymerase Chain Reaction (PCR) method is the only effective method used for diagnosis, which has some pros and cons.

Results and Conclusion: This study aimed to design a new recombinant multi-epitope protein from Acinetobacter baumannii that can be used in ELISA for rapid diagnosis. The unique feature of this study from others is the use of patient serum for antibody monitoring.

Cite this article as:

Rezaee Maryam, Mohammadi Mohsen, Savardashtaki Amir, Rahbar Mohammad Reza and Nezafat Navid*, Designing a Novel Multi-Epitope Peptide as a Potential Serodiagnosis Marker for the Diagnosis of Acinetobacter baumannii: An In silico Approach, Current Proteomics 2024; 21 () . https://dx.doi.org/10.2174/0115701646297689240325062145