2022
DOI: 10.1007/s12010-022-04116-y
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Genome-Wide Subtraction Analysis and Reverse Vaccinology to Detect Novel Drug Targets and Potential Vaccine Candidates Against Ehrlichia chaffeensis

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Cited by 11 publications
(6 citation statements)
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References 66 publications
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“…Reverse vaccinology has been used to identify such antigens as those used in the MenB vaccine against Neisseria meningitidis which represents a milestone in new vaccinology approaches ( Masignani et al., 2019 ). Reverse vaccinology has been used extensively to identify antigens from obligate intracellular bacteria and has identified components of secretion systems and their secreted effector proteins as novel antigens ( Khan et al., 2023 ; Sabzi et al., 2023 ). We are now in the era of rational vaccine design, which builds on reverse vaccinology with the addition of machine learning algorithms to identify antibody and T cell epitopes.…”
Section: Antigen Selectionmentioning
confidence: 99%
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“…Reverse vaccinology has been used to identify such antigens as those used in the MenB vaccine against Neisseria meningitidis which represents a milestone in new vaccinology approaches ( Masignani et al., 2019 ). Reverse vaccinology has been used extensively to identify antigens from obligate intracellular bacteria and has identified components of secretion systems and their secreted effector proteins as novel antigens ( Khan et al., 2023 ; Sabzi et al., 2023 ). We are now in the era of rational vaccine design, which builds on reverse vaccinology with the addition of machine learning algorithms to identify antibody and T cell epitopes.…”
Section: Antigen Selectionmentioning
confidence: 99%
“…Another recent study used subtractive genomics and reverse vaccinology to identify surface exposed proteins with linear B cell epitopes ( Sabzi et al., 2023 ). A multi-epitope vaccine was designed and used in a C-ImmSim immunoreactivity simulation to demonstrate a strong Th1 response, however, this would also have to be demonstrated in animal models ( Sabzi et al., 2023 ).…”
Section: Ehrlichia Spp Vaccinesmentioning
confidence: 99%
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“…In contrast to previous studies limited to one (Mandal and Sinha, 2021; Dineshkumar and Antony, 2022), or two computational methods (Subramanian et al, 2022), the present study employs a consensus approach from eight distinct computational tools, including Arti cial Intelligence (AI) and deep learning, to enhance the precision of protein location prediction. Recognizing the signi cance of cytoplasmic proteins as suitable targets for pathogens (Almeida et al, 2023;Sabzi et al, 2023), only proteins predicted to reside in the cytoplasm, as indicated by the consensus, were considered for subsequent analysis.…”
Section: Target Prioritization Protein Localization Predictionmentioning
confidence: 99%
“…There has been a significant amount of research dedicated to the advancement of potent antimicrobial agents that can effectively combat the challenge of drug resistance in biofilms. These efforts involve various strategies, such as insilico drug design, the use of herbal compounds, the application of antimicrobial peptides, and the utilization of nanomaterial-based methods [10][11][12][13]. There are new treatments being developed for drug-resistant bacteria, and some of them involve using metallic and metal oxide nanoparticles (NPs), silver NPs (Ag NPs), gold NPs (Au NPs), and zinc oxide NPs (ZnO NPs) are among the most promising options [14,15].…”
Section: Introductionmentioning
confidence: 99%