Literature DB >> 32928063

Proteome-wide mapping and reverse vaccinology-based B and T cell multi-epitope subunit vaccine designing for immune response reinforcement against Porphyromonas gingivalis.

Shahzeb Khan1, Syed Shujait Ali1, Iqra Zaheer2, Shoaib Saleem3, Nasib Zaman1, Arshad Iqbal1, Muhammad Suleman1, Abdul Wadood4, Ashfaq Ur Rehman5, Asghar Khan6, Abbas Khan5, Dong-Qing Wei5,7,8.   

Abstract

Porphyromonas gingivalis, a prominent pathogen responsible for acute periodontal diseases, is widely studied by the scientific community for its successful evasion of the host immune system. P. gingivalis is associated with rheumatoid arthritis, dementia, and Alzheimer's. The pathogen successfully survives itself against the heavy load of conventional antibiotics because of its ability to evade the host immune system. Subtractive proteomics and reverse vaccinology approaches were employed in order to prioritize the best proteins for vaccine designing. Three vaccine candidates with Uniprot ID: Q7MWZ2 (histidine Kinase), Q7MVL1 (Fe (2+) transporter), and Q7MWZ2 (Capsular polysaccharide transport protein) were identified for vaccine designing. These proteins are antigenic and essential for pathogen survival. A wide range of immunoinformatics tools was applied for the prediction of epitopes, B, and T cells, for the vaccine candidate proteins. Molecular docking of the predicted epitopes against the MHC molecules were carried out. In-silico vaccine was constructed using carefully evaluated epitopes and consequently modeled for docking with human Toll-like receptor 2. Chain C of Pam3CSK4 (PDB ID; 2Z7X) was linked to the vaccine as an adjuvant to boost immune response towards the vaccine. For stability evaluation of the vaccine-TLR-2 docked complex, Molecular Dynamics simulations were performed. The reverse-translated nucleotide sequence cloned in Eschericia coli to attain the maximal expression of the vaccine protein. The maximal expression was ensured by CAI score of 0.96. The current vaccine requires future experimental validation to confirm its effectiveness. The vaccine developed will be helpful to protect against P. gingivalis associated infections.Communicated by Ramaswamy H. Sarma.

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Keywords:  B-cell epitopes; Subtractive proteomics; T-cell epitopes; in silico cloning; vaccine

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Year:  2020        PMID: 32928063     DOI: 10.1080/07391102.2020.1819423

Source DB:  PubMed          Journal:  J Biomol Struct Dyn        ISSN: 0739-1102


  5 in total

1.  Core-Proteomics-Based Annotation of Antigenic Targets and Reverse-Vaccinology-Assisted Design of Ensemble Immunogen against the Emerging Nosocomial Infection-Causing Bacterium Elizabethkingia meningoseptica.

Authors:  Muhammad Idrees; Muhammad Yasir Noorani; Kalim Ullah Altaf; Eid A Alatawi; Faris F Aba Alkhayl; Khaled S Allemailem; Ahmad Almatroudi; Murad Ali Khan; Muhammad Hamayun; Taimoor Khan; Syed Shujait Ali; Abbas Khan; Dong-Qing Wei
Journal:  Int J Environ Res Public Health       Date:  2021-12-24       Impact factor: 3.390

2.  Subtractive proteomics assisted therapeutic targets mining and designing ensemble vaccine against Candida auris for immune response induction.

Authors:  Taimoor Khan; Muhammad Suleman; Syed Shujait Ali; Muhammad Farhan Sarwar; Imtiaz Ali; Liaqat Ali; Abbas Khan; Bakht Rokhan; Yanjing Wang; Ruili Zhao; Dong-Qing Wei
Journal:  Comput Biol Med       Date:  2022-04-01       Impact factor: 6.698

3.  Reverse vaccinology approach to identify novel and immunogenic targets against Porphyromonas gingivalis: An in silico study.

Authors:  Omid Nasiri; Mahsa Hajihassani; Narjes Noori Goodarzi; Sepideh Fereshteh; Negin Bolourchi; Farzaneh Firoozeh; Omid Azizi; Farzad Badmasti
Journal:  PLoS One       Date:  2022-08-30       Impact factor: 3.752

4.  Immunoinformatics-Based Proteome Mining to Develop a Next-Generation Vaccine Design against Borrelia burgdorferi: The Cause of Lyme Borreliosis.

Authors:  Kashaf Khalid; Omar Ahsan; Tanwir Khaliq; Khalid Muhammad; Yasir Waheed
Journal:  Vaccines (Basel)       Date:  2022-08-02

5.  Subtractive Proteomics and Immuno-informatics Approaches for Multi-peptide Vaccine Prediction Against Klebsiella oxytoca and Validation Through In Silico Expression.

Authors:  Qudsia Yousafi; Humaira Amin; Shabana Bibi; Rafea Rafi; Muhammad S Khan; Hamza Ali; Ashir Masroor
Journal:  Int J Pept Res Ther       Date:  2021-09-20       Impact factor: 1.931

  5 in total

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