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In-Silico Vaccine Design Based on a Novel Vaccine Candidate Against Infections Caused by Acinetobacter baumannii.

ABSTRACT: Acinetobacter baumannii is notorious for causing serious infections of the skin, lungs, soft tissues, bloodstream, and urinary tract. Despite the overwhelming information available so far, there has still been no approved vaccine in the market to prevent these infections. Therefore, this study focuses on developing a rational vaccine design using the technique of epitope mapping to curb the infections caused by A. baumannii. An outer membrane protein with immunogenic potential as well as all the properties of a good vaccine candidate was selected and used to calculate epitopes for selection on the basis of a low percentile rank, high binding scores, good immunological properties, and non-allergenicity. Thus, a 240 amino-acid vaccine sequence was obtained by manually joining all the epitopes in sequence-wise manner with the appropriate linkers, namely AAY, GPGPG, and EAAAK. Additionally, a 50S ribosomal protein L7/L12, agonist to the human innate immune receptors was attached to the N-terminus to increase the overall immune response towards the vaccine. As a result, enhanced overall protein stability, expression, immunostimulatory capabilities, and solubility of the designed construct were observed. Molecular dynamic simulations revealed the compactness and stability of the polypeptide construct. Moreover, molecular docking exhibited strong binding of the designed vaccine with TLR-4 and TLR-9. In-silico immune simulations indicated an immense increment in T-cell and B-cell populations. Bioinformatic tools also significantly assisted with optimizing codons which allowed for successful cloning of constructs into desired host vectors. Using in-silico tools to design a vaccine against A. baumannii demonstrated that this construct could pave the way for successfully combating infections caused by multidrug-resistant bacteria.

Supplementary information

The online version contains supplementary material available at 10.1007/s10989-021-10316-7.

SUBMITTER: Khalid K

PROVIDER: S-EPMC8636788 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Objectives:To predict the novel vaccine peptide candidates against gacS protein involved with the citrate utilization in the two-component system of A. baumannii-associated virulence as an alternative strategy to combat the multi-drug resistant strains using an immuno-informatic approach. Methods:The study is designed as an observational in silico study design with the application of BepiPred, AlgPred, VaxiJen, AntigenPro, SolPro, Expasy ProtParam server, IEDB database, and MHC cluster analytical tools and servers to predict the immuno-dominant B-cell and T-cell epitopes from gacS FASTA sequences retrieved from UNIPROT database. Further peptide interactions with TLR-4 was assessed based on the number of hydrogen bonds. Results:Nine peptides (20aa) with the highest score of 1 were selected from the 137 epitopes, and five were predicted as antigenic epitopes (E1-E5). E3 was selected as the potent antigen (score: 0.939537) and E1 as the best vaccine candidate (score: 0.9803) under AntigenPro and Vaxijen server, respectively. SolPro predicted all epitopes as soluble peptides. ProtParam predictions showed E3 and E5 as stable proteins with a shelf life of 3.5 and 1.9 h and possessed negative GRAVY values. PsortB server predicted a final localization score of 7.88 for the gacS protein sequence as a cytoplasmic membrane protein. IEDB conservancy analysis showed 100% conserved sequences within the gacS sequence, and class I conservancy yielded positive values for all epitopes. Cluster analysis showed strong interactions, and the protein-peptide interactions with TLR-2 finally detected E5 as the best interacting peptide (H bonds = 14) followed by E3 (H bonds = 12). Conclusion:The study suggests five antigenic peptides as promiscuous vaccine candidates to target the gacS of A. baumannii using immuno-informatic approach toward the peptide synthesis and in vitro analysis. However, the study recommends further experimental validation for immunological response and memory through in vivo studies.

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In-Silico Vaccine Design Based on a Novel Vaccine Candidate Against Infections Caused by Acinetobacter baumannii.

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