Immunoinformatics Prediction of Epitope Based Peptide Vaccine Against Listeria Monocytogenes Fructose Bisphosphate Aldolase Protein

Elhag, Mustafa; Abubaker, Mustafa; Ahmad, Nagla Mohammad; Haroon, Esraa Musa; Alaagib, Ruaa Mohamed; Albagi, Sahar Obi Abd; Hassan, Mohammed A.

doi:10.1101/649111

Cited by 5 publications

(2 citation statements)

References 38 publications

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“…While other studies had focused only on specific proteins of C. perfringens ( 71 , 72 ), we consider that analyzing the whole proteome could reveal novel more immunogenic proteins. We followed three approaches to propose vaccine candidates: a whole-protein based vaccine, a protein-subunit based vaccine, and a multi-epitope protein vaccine.…”

Section: Discussionmentioning

confidence: 99%

Immunoinformatic analysis of the whole proteome for vaccine design: An application to Clostridium perfringens

et al. 2022

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Clostridium perfringens is a dangerous bacterium and known biological warfare weapon associated with several diseases, whose lethal toxins can produce necrosis in humans. However, there is no safe and fully effective vaccine against C. perfringens for humans yet. To address this problem, we computationally screened its whole proteome, identifying highly immunogenic proteins, domains, and epitopes. First, we identified that the proteins with the highest epitope density are Collagenase A, Exo-alpha-sialidase, alpha n-acetylglucosaminidase and hyaluronoglucosaminidase, representing potential recombinant vaccine candidates. Second, we further explored the toxins, finding that the non-toxic domain of Perfringolysin O is enriched in CTL and HTL epitopes. This domain could be used as a potential sub-unit vaccine to combat gas gangrene. And third, we designed a multi-epitope protein containing 24 HTL-epitopes and 34 CTL-epitopes from extracellular regions of transmembrane proteins. Also, we analyzed the structural properties of this novel protein using molecular dynamics. Altogether, we are presenting a thorough immunoinformatic exploration of the whole proteome of C. perfringens, as well as promising whole-protein, domain-based and multi-epitope vaccine candidates. These can be evaluated in preclinical trials to assess their immunogenicity and protection against C. perfringens infection.

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Section: Discussionmentioning

confidence: 99%

Immunoinformatic analysis of the whole proteome for vaccine design: An application to Clostridium perfringens

et al. 2022

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“…A previous study conducted by de Klerk et al [79] showed that the Fba1 protein has the ability to provoke immune responses in human against M. mycetomatis [79]. Also, several recent publications have used the Fba1 protein as a strong antigenic target for predicting Band T-cell epitopes in order to design promising vaccines against fungal and bacterial pathogens such as M. mycetomatis, P. aeruginosa, L. monocytogenes, and S. mansoni by using in silico tools [80][81][82][83]. Hence, there are more studies to explore the fructose bisphosphate aldolase protein immunogenic role and the possibility to find common conserved epitopes for different organisms.…”

Section: Discussionmentioning

confidence: 99%

Epitope-Based Peptide Vaccine Design against Fructose Bisphosphate Aldolase of Candida glabrata: An Immunoinformatics Approach

Elhasan

Hassan

Elhassan

et al. 2021

Journal of Immunology Research

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Background. Candida glabrata is a human opportunistic pathogen that can cause life-threatening systemic infections. Although there are multiple effective vaccines against fungal infections and some of these vaccines are engaged in different stages of clinical trials, none of them have yet been approved by the FDA. Aim. Using immunoinformatics approach to predict the most conserved and immunogenic B- and T-cell epitopes from the fructose bisphosphate aldolase (Fba1) protein of C. glabrata. Material and Method. 13 C. glabrata fructose bisphosphate aldolase protein sequences (361 amino acids) were retrieved from NCBI and presented in several tools on the IEDB server for prediction of the most promising epitopes. Homology modeling and molecular docking were performed. Result. The promising B-cell epitopes were AYFKEH, VDKESLYTK, and HVDKESLYTK, while the promising peptides which have high affinity to MHC I binding were AVHEALAPI, KYFKRMAAM, QTSNGGAAY, RMAAMNQWL, and YFKEHGEPL. Two peptides, LFSSHMLDL and YIRSIAPAY, were noted to have the highest affinity to MHC class II that interact with 9 alleles. The molecular docking revealed that the epitopes QTSNGGAAY and LFSSHMLDL have the lowest binding energy to MHC molecules. Conclusion. The epitope-based vaccines predicted by using immunoinformatics tools have remarkable advantages over the conventional vaccines in that they are more specific, less time consuming, safe, less allergic, and more antigenic. Further in vivo and in vitro experiments are needed to prove the effectiveness of the best candidate’s epitopes (QTSNGGAAY and LFSSHMLDL). To the best of our knowledge, this is the first study that has predicted B- and T-cell epitopes from the Fba1 protein by using in silico tools in order to design an effective epitope-based vaccine against C. glabrata.

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Epitope-Based Peptide Vaccine Design Against Fructose Bisphosphate Aldolase of Candida Glabrata: An Immunomics Approach

Elhasan

Hassan

Elhassan

et al. 2020

Preprint

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AbstractBackgroundCandida glabrata is a human opportunistic pathogen that can cause life-threatening systemic infections. Although, there are multiple effective vaccines against fungal infections, and some of these vaccines were engaged in different stages of clinical trials, none of them yet approved by (FDA).AimTo predict the most conserved and immunogenic B- and T-cell epitopes from the Fructose Bisphosphate aldolase (Fba1) protein of C. glabrata.Materials and Methods13 C. glabrata Fructose bisphosphate aldolase protein sequences (361amino acid) were retrieved from NCBI and several in silico tools presented in the IEDB server for predicting peptides were used and homology modeling and molecular docking were performed.ResultThe promising B-cell Epitopes were AYFKPH, VDKESLYTK, and HVDKESLYTK. While, promising peptides which have the high affinity to MHC I binding were: AVHEALAPI, KYFKRMAAM, QTSNGGAAY, RMAAMNQWL and YFKEHGEPL. Two peptides (LFSSHMLDL and YIRSIAPAY) were noted to have the highest affinity to MHC class II that interact with 9 MHC class II alleles. The molecular Docking revealed the epitopes QTSNGGAAY and LFSSHMLDL have the high binding energy to MHC moleculesConclusionThe epitope-based vaccines predicted by using immunoinformatics tools have remarkable advantages over the conventional vaccines that they are more specific, less time consuming, safe, less allergic and more antigenic. Further in vivo and in vitro experiments are needed to prove the effectiveness of the best candidates epitopes (QTSNGGAAY and LFSSHMLDL). To the best of our knowledge, this is the first study that has predicted B- and T-cells epitopes from Fba1 protein by using in silico tools in order to design an effective epitope-based vaccine against C. galabrata.

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Immunoinformatics Prediction of Epitope Based Peptide Vaccine Against Listeria Monocytogenes Fructose Bisphosphate Aldolase Protein

Cited by 5 publications

References 38 publications

Immunoinformatic analysis of the whole proteome for vaccine design: An application to Clostridium perfringens

Immunoinformatic analysis of the whole proteome for vaccine design: An application to Clostridium perfringens

Epitope-Based Peptide Vaccine Design against Fructose Bisphosphate Aldolase of Candida glabrata: An Immunoinformatics Approach

Epitope-Based Peptide Vaccine Design Against Fructose Bisphosphate Aldolase of Candida Glabrata: An Immunomics Approach

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