Computer-Aided Multi-Epitope Vaccine Design against Enterobacter xiangfangensis

Abdulrahman Alshammari, Metab Alharbi, Abdullah Alghamdi, Saif Ali Alharbi, Usman Ali Ashfaq, Muhammad Tahir ul Qamar, Asad Ullah, Muhammad Irfan, Amjad Khan and Sajjad Ahmad
Additional contact information
Abdulrahman Alshammari: Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
Metab Alharbi: Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
Abdullah Alghamdi: Department of Pathology and Laboratory Medicine, Riyadh Security Forces Hospital, Ministry of Interior, Riyadh 11432, Saudi Arabia
Saif Ali Alharbi: Ministry of Health, Riyadh 12613, Saudi Arabia
Usman Ali Ashfaq: Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad 38000, Pakistan
Muhammad Tahir ul Qamar: Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad 38000, Pakistan
Asad Ullah: Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan
Muhammad Irfan: Department of Oral Biology, College of Dentistry, University of Florida, Gainesville, FL 32611, USA
Amjad Khan: Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan
Sajjad Ahmad: Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan

IJERPH, 2022, vol. 19, issue 13, 1-21

Abstract: Antibiotic resistance is a global public health threat and is associated with high mortality due to antibiotics’ inability to treat bacterial infections. Enterobacter xiangfangensis is an emerging antibiotic-resistant bacterial pathogen from the Enterobacter genus and has the ability to acquire resistance to multiple antibiotic classes. Currently, there is no effective vaccine against Enterobacter species. In this study, a chimeric vaccine is designed comprising different epitopes screened from E. xiangfangensis proteomes using immunoinformatic and bioinformatic approaches. In the first phase, six fully sequenced proteomes were investigated by bacterial pan-genome analysis, which revealed that the pathogen consists of 21,996 core proteins, 3785 non-redundant proteins and 18,211 redundant proteins. The non-redundant proteins were considered for the vaccine target prioritization phase where different vaccine filters were applied. By doing so, two proteins; ferrichrome porin (FhuA) and peptidoglycan-associated lipoprotein (Pal) were shortlisted for epitope prediction. Based on properties of antigenicity, allergenicity, water solubility and DRB*0101 binding ability, three epitopes (GPAPTIAAKR, ATKTDTPIEK and RNNGTTAEI) were used in multi-epitope vaccine designing. The designed vaccine construct was analyzed in a docking study with immune cell receptors, which predicted the vaccine’s proper binding with said receptors. Molecular dynamics analysis revealed that the vaccine demonstrated stable binding dynamics, and binding free energy calculations further validated the docking results. In conclusion, these in silico results may help experimentalists in developing a vaccine against E. xiangfangensis in specific and Enterobacter in general.

Keywords: antibiotic resistance; Enterobacter xiangfangensis; multi-epitope vaccine; molecular docking; molecular dynamics simulation (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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