| Literature DB >> 34340127 |
Saba Ismail1, Farah Shahid2, Abbas Khan3, Sadia Bhatti4, Sajjad Ahmad5, Anam Naz6, Ahmad Almatroudi7, Muhammad Tahir Ul Qamar8.
Abstract
Antimicrobial resistance (AMR) in bacterial pathogens is a major global distress. Due to the slow progress of antibiotics development and the fast pace of resistance acquisition, there is an urgent need for effective vaccines against such bacterial pathogens. In-silico approaches including pan-genomics, subtractive proteomics, reverse vaccinology, immunoinformatics, molecular docking, and dynamics simulation studies were applied in the current study to identify a universal potential vaccine candidate against the 18 multi-drug resistance (MDRs) bacterial pathogenic species from a WHO priority list. Ten non-redundant, non-homologous, virulent, and antigenic vaccine candidates were filtered against all targeted species. Nine B-cell-derived T-cell antigen epitopes which show a great affinity to the dominant HLA allele (DRB1*0101) in the human population were screened from selected vaccine candidates using immunoinformatics approaches. Screened epitopes were then used to design a multi-epitope peptide vaccine construct (MEPVC) along with β-defensin adjuvant to improve the immunogenic properties of the proposed vaccine construct. Molecular docking and MD simulation were carried out to study the binding affinity and molecular interaction of MEPVC with human immune receptors (TLR2, TLR3, TLR4, and TLR6). The final MEPVC construct was reverse translated and in-silico cloned in the pET28a(+) vector to ensure its effectiveness. This in silico construct is expected to be helpful for vaccinologists to assess its immune protection effectiveness in vivo and in vitro to counter rising antibiotic resistance worldwide.Entities:
Keywords: Computational vaccinology; Multi-drug resistance; Pan-vaccinomics; WHO priority List; β-defensin
Year: 2021 PMID: 34340127 DOI: 10.1016/j.compbiomed.2021.104705
Source DB: PubMed Journal: Comput Biol Med ISSN: 0010-4825 Impact factor: 4.589