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Designing of a Recombinant Multi-Epitopes Based Vaccine against Enterococcus mundtii Using Bioinformatics and Immunoinformatics Approaches

Author

Listed:
  • Metab Alharbi

    (Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia)

  • Abdulrahman Alshammari

    (Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia)

  • Abdullah F. Alasmari

    (Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia)

  • Salman Mansour Alharbi

    (Ministry of Health, Kingdom of Saudi Arabia, Riyadh 11451, Saudi Arabia)

  • Muhammad Tahir ul Qamar

    (Department of Bioinformatics and Biotechnology, Government College University, Faisalabad 38000, Pakistan)

  • Asad Ullah

    (Department of Health and Biological Sciences, Abasyn University, Peshawar 25000, Pakistan)

  • Sajjad Ahmad

    (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)

  • Atif Ali Khan Khalil

    (Department of Biological Sciences, National University of Medical Sciences, Rawalpindi 46000, Pakistan)

Abstract

Enterococcus species are an emerging group of bacterial pathogens that have a significant role in hospital-associated infections and are associated with higher mortality and morbidity rates. Among these pathogens, Enterococcus mundtii is one of the causative agents of multiple hospital associated infections. Currently, no commercially available licensed vaccine is present, and multi-drug resistant strains of the pathogen are prominent. Due to several limitations of experimental vaccinology, computational vaccine designing proved to be helpful in vaccine designing against several bacterial pathogens. Herein, we designed a multi-epitope-based vaccine against E. mundtii using in silico approaches. After an in-depth analysis of the core genome, three probable antigenic proteins (lytic polysaccharide monooxygenase, siderophore ABC transporter substrate-binding protein, and lytic polysaccharide monooxygenase) were shortlisted for epitope prediction. Among predicted epitopes, ten epitopes—GPADGRIAS, TTINHGGAQA, SERTALSVTT, GDGGNGGGEV, GIKEPDLEK, KQADDRIEA, QAIGGDTSN, EPLDEQTASR, AQWEPQSIEA, QPLKFSDFEL—were selected for multi-epitope vaccine construct designing. The screened B- and T-cell epitopes were joined with each other via specific linkers and linked to the cholera toxin B subunit as an adjuvant to enhance vaccine immune protection efficacy. The designed vaccine construct induced cellular and humoral immune responses. Blind docking with immune cell receptors, followed by molecular dynamic simulation results confirms the good binding potency and stability of the vaccine in providing protection against the pathogen.

Suggested Citation

  • Metab Alharbi & Abdulrahman Alshammari & Abdullah F. Alasmari & Salman Mansour Alharbi & Muhammad Tahir ul Qamar & Asad Ullah & Sajjad Ahmad & Muhammad Irfan & Atif Ali Khan Khalil, 2022. "Designing of a Recombinant Multi-Epitopes Based Vaccine against Enterococcus mundtii Using Bioinformatics and Immunoinformatics Approaches," IJERPH, MDPI, vol. 19(6), pages 1-19, March.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:6:p:3729-:d:776050
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    References listed on IDEAS

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    1. Sudheer Gupta & Pallavi Kapoor & Kumardeep Chaudhary & Ankur Gautam & Rahul Kumar & Open Source Drug Discovery Consortium & Gajendra P S Raghava, 2013. "In Silico Approach for Predicting Toxicity of Peptides and Proteins," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-10, September.
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    Cited by:

    1. Abdulrahman Alshammari & Metab Alharbi & Abdullah Alghamdi & Saif Ali Alharbi & Usman Ali Ashfaq & Muhammad Tahir ul Qamar & Asad Ullah & Muhammad Irfan & Amjad Khan & Sajjad Ahmad, 2022. "Computer-Aided Multi-Epitope Vaccine Design against Enterobacter xiangfangensis," IJERPH, MDPI, vol. 19(13), pages 1-21, June.

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