Identification and evaluation of immunogenic MHC-I and MHC-II binding peptides from Mycobacterium tuberculosis

Jagadeb, Manaswini; Pattanaik, Kali Prasad; Rath, Surya Narayan; Sonawane, Avinash

doi:10.1016/j.compbiomed.2020.104203

Cited by 8 publications

(10 citation statements)

References 47 publications

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“…Non-allergenicity and non-toxicity assessments are crucial to ensure safety when the vaccine is processed within hosts. Moreover, all epitopes demonstrated antigenicity that surpassed the score of 1.0, the threshold set for highly antigenic epitopes 46 . Therefore, these epitopes are expected to have a substantial ability to be recognized as foreign materials that can potentially trigger an immune response.…”

Section: Discussionmentioning

confidence: 96%

Immunoinformatics-guided approach for designing a pan-proteome multi-epitope subunit vaccine against African swine fever virus

Simbulan,

Banico,

Sira

et al. 2024

Sci Rep

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Despite being identified over a hundred years ago, there is still no commercially available vaccine for the highly contagious and deadly African swine fever virus (ASFV). This study used immunoinformatics for the rapid and inexpensive designing of a safe and effective multi-epitope subunit vaccine for ASFV. A total of 18,858 proteins from 100 well-annotated ASFV proteomes were screened using various computational tools to identify potential epitopes, or peptides capable of triggering an immune response in swine. Proteins from genotypes I and II were prioritized for their involvement in the recent global ASFV outbreaks. The screened epitopes exhibited promising qualities that positioned them as effective components of the ASFV vaccine. They demonstrated antigenicity, immunogenicity, and cytokine-inducing properties indicating their ability to induce potent immune responses. They have strong binding affinities to multiple swine allele receptors suggesting a high likelihood of yielding more amplified responses. Moreover, they were non-allergenic and non-toxic, a crucial prerequisite for ensuring safety and minimizing any potential adverse effects when the vaccine is processed within the host. Integrated with an immunogenic 50S ribosomal protein adjuvant and linkers, the epitopes formed a 364-amino acid multi-epitope subunit vaccine. The ASFV vaccine construct exhibited notable immunogenicity in immune simulation and molecular docking analyses, and stable profiles in secondary and tertiary structure assessments. Moreover, this study designed an optimized codon for efficient translation of the ASFV vaccine construct into the Escherichia coli K-12 expression system using the pET28a(+) vector. Overall, both sequence and structural evaluations suggested the potential of the ASFV vaccine construct as a candidate for controlling and eradicating outbreaks caused by the pathogen.

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Section: Discussionmentioning

confidence: 96%

Immunoinformatics-guided approach for designing a pan-proteome multi-epitope subunit vaccine against African swine fever virus

Simbulan,

Banico,

Sira

et al. 2024

Sci Rep

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Section: Preliminary Application Of Msm Vector Vaccinementioning

confidence: 98%

“…Two peptides, Pep-9 and Pep-15, were next discovered through the calculation of antigenicity scores and molecular dynamics simulations in conjunction with MHC-I and MHC-II structures. The results indicated that both peptides were non-cytotoxic and could induce the secretion of pro-inflammatory cytokines in stimulated macrophages [ 67 ]. This new avenue for rational design has streamlined the identification of powerful antigen subunits which, if successfully expressed in M.sm using recombinant techniques, would produce a potent vaccine construct.…”

Section: Why Is Msm An Effective Vaccine Vector Fo...mentioning

confidence: 99%

Mycobacterium smegmatis, a Promising Vaccine Vector for Preventing TB and Other Diseases: Vaccinomics Insights and Applications

Xie,

Wang,

Luo

et al. 2023

Vaccines

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Mycobacterium smegmatis (M.sm) is frequently used as an alternative model organism in Mycobacterium tuberculosis (M.tb) studies. While containing high sequence homology with M.tb, it is considered non-pathogenic in humans. As such it has been used to study M.tb and other infections in vivo and more recently been explored for potential therapeutic applications. A body of previous research has highlighted the potential of using genetically modified M.sm displaying rapid growth and unique immunostimulatory characteristics as an effective vaccine vector. Novel systems biology techniques can further serve to optimize these delivery constructs. In this article, we review recent advancements in vaccinomics tools that support the efficacy of a M.sm-based vaccine vector. Moreover, the integration of systems biology and molecular omics techniques in these pioneering studies heralds a potential accelerated pipeline for the development of next-generation recombinant vaccines against rapidly developing diseases.

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“…To evaluate the training effect and prediction ability of the model, we mainly used the Area Under the Receiver Operating Characteristic curve value (AUROC), supplemented by Sensitivity (Sn), Specificity (Sp), Matthew's correlation coefficient (MCC), accuracy (ACC) (55)(56)(57)(58)(59)(60)(61)(62)(63)(64)(65)(66)(67)(68)(69)(70)(71)(72). These indexes can be formulated as follows:…”

Section: Model Evaluation Metricsmentioning

confidence: 99%

Bitter-RF: A random forest machine model for recognizing bitter peptides

Zhang

Wang

et al. 2023

Front. Med.

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IntroductionBitter peptides are short peptides with potential medical applications. The huge potential behind its bitter taste remains to be tapped. To better explore the value of bitter peptides in practice, we need a more effective classification method for identifying bitter peptides.MethodsIn this study, we developed a Random forest (RF)-based model, called Bitter-RF, using sequence information of the bitter peptide. Bitter-RF covers more comprehensive and extensive information by integrating 10 features extracted from the bitter peptides and achieves better results than the latest generation model on independent validation set.ResultsThe proposed model can improve the accurate classification of bitter peptides (AUROC = 0.98 on independent set test) and enrich the practical application of RF method in protein classification tasks which has not been used to build a prediction model for bitter peptides.DiscussionWe hope the Bitter-RF could provide more conveniences to scholars for bitter peptide research.

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Identification and evaluation of immunogenic MHC-I and MHC-II binding peptides from Mycobacterium tuberculosis

Cited by 8 publications

References 47 publications

Immunoinformatics-guided approach for designing a pan-proteome multi-epitope subunit vaccine against African swine fever virus

Immunoinformatics-guided approach for designing a pan-proteome multi-epitope subunit vaccine against African swine fever virus

Mycobacterium smegmatis, a Promising Vaccine Vector for Preventing TB and Other Diseases: Vaccinomics Insights and Applications

Bitter-RF: A random forest machine model for recognizing bitter peptides

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