Immunoinformatics and structural aided approach to develop multi-epitope based subunit vaccine against Mycobacterium tuberculosis – Nature.com

Kyu, H. H. et al. Global, regional, and national burden of tuberculosis, 19902016: results from the Global Burden of Diseases, Injuries, and Risk Factors 2016 study. Lancet. Infect. Dis 18, 13291349 (2018).

Article Google Scholar

Sandhu, G. K. Tuberculosis: Current situation, challenges and overview of its control programs in India. J. Glob. Infect. Dis. 3, 143150 (2011).

Article PubMed PubMed Central Google Scholar

Bagcchi, S. WHOs global tuberculosis report 2022. Lancet Microbe 4, e20 (2023).

Article PubMed Google Scholar

Annual Reports:: Central TB Division. https://tbcindia.gov.in/index1.php?lang=1&level=1&sublinkid=4160&lid=2807.

Jang, J. G. & Chung, J. H. Diagnosis and treatment of multidrug-resistant tuberculosis. Yeungnam Univ. J. Med. 37, 277285 (2020).

Article CAS PubMed PubMed Central Google Scholar

Sharma, R., Rajput, V. S., Jamal, S., Grover, A. & Grover, S. An immunoinformatics approach to design a multi-epitope vaccine against Mycobacterium tuberculosis exploiting secreted exosome proteins. Sci. Rep. 11, 13836 (2021).

Article CAS PubMed PubMed Central Google Scholar

Watt, J. & Liu, J. Preclinical progress of subunit and live attenuated Mycobacterium tuberculosis vaccines: A review following the first in human efficacy trial. Pharmaceutics 12, 848 (2020).

Article CAS PubMed PubMed Central Google Scholar

Kaufmann, S. H. Novel tuberculosis vaccination strategies based on understanding the immune response. J. Intern. Med. 267(4), 337. https://doi.org/10.1111/j.1365-2796.2010.02216.x (2010).

Article CAS PubMed Google Scholar

Nieuwenhuizen, N. E. & Kaufmann, S. H. E. Next-generation vaccines based on Bacille Calmette-Gurin. Front. Immunol. 9, 121 (2018).

Article PubMed PubMed Central Google Scholar

Evans, T. G., Schrager, L. & Thole, J. Status of vaccine research and development of vaccines for tuberculosis. Vaccine 34, 29112914 (2016).

Article CAS PubMed Google Scholar

Wilkie, M. E. M. & McShane, H. TB vaccine development: Where are we and why is it so difficult?. Thorax 70, 299301 (2015).

Article PubMed Google Scholar

Mndez-Samperio, P. Global efforts in the development of vaccines for tuberculosis: Requirements for improved vaccines against Mycobacterium tuberculosis. Scand. J. Immunol. 84, 204210 (2016).

Article PubMed Google Scholar

Bibi, S. et al. In silico analysis of epitope-based vaccine candidate against tuberculosis using reverse vaccinology. Sci. Rep. 11, 1249 (2021).

Article CAS PubMed PubMed Central Google Scholar

Gillard, P. et al. Safety and immunogenicity of the M72/AS01E candidate tuberculosis vaccine in adults with tuberculosis: A phase II randomised study. Tuberculosis 100, 118127 (2016).

Article CAS PubMed Google Scholar

Kagina, B. M. N. et al. The novel tuberculosis vaccine, AERAS-402, is safe in healthy infants previously vaccinated with BCG, and induces dose-dependent CD4 and CD8T cell responses. Vaccine 32, 59085917 (2014).

Article CAS PubMed Google Scholar

Suliman, S. et al. Dose optimization of H56:IC31 vaccine for tuberculosis-endemic populations. A double-blind, placebo-controlled, dose-selection trial. Am. J. Respir. Crit. Care Med 199, 220231 (2019).

Article CAS PubMed Google Scholar

Penn-Nicholson, A. et al. Safety and immunogenicity of the novel tuberculosis vaccine ID93 + GLA-SE in BCG-vaccinated healthy adults in South Africa: A randomised, double-blind, placebo-controlled phase 1 trial. Lancet Respir. Med. 6, 287298 (2018).

Article CAS PubMed Google Scholar

Chatterjee, N., Ojha, R., Khatoon, N. & Prajapati, V. K. Scrutinizing Mycobacterium tuberculosis membrane and secretory proteins to formulate multiepitope subunit vaccine against pulmonary tuberculosis by utilizing immunoinformatic approaches. Int. J. Biol. Macromol. 118, 180188 (2018).

Article CAS PubMed Google Scholar

Andongma, B. T. et al. In silico design of a promiscuous chimeric multi-epitope vaccine against Mycobacterium tuberculosis. Comput. Struct. Biotechnol. J. 21, 9911004 (2023).

Article CAS PubMed PubMed Central Google Scholar

Jiang, F. et al. Design and development of a multi-epitope vaccine for the prevention of latent tuberculosis infection. Med. Adv. 1, 361382 (2023).

Article Google Scholar

Kang, S., Kim, D., Jin, C., Ahn, H. & Lee, B. The crystal structure of AcrR from Mycobacterium tuberculosis reveals a one-component transcriptional regulation mechanism. FEBS Open Bio 9, 17131725 (2019).

Article CAS PubMed PubMed Central Google Scholar

Pal, R., Bisht, M. K. & Mukhopadhyay, S. Secretory proteins of Mycobacterium tuberculosis and their roles in modulation of host immune responses: Focus on therapeutic targets. FEBS J. 289, 41464171 (2022).

Article CAS PubMed Google Scholar

Choudhary, R. K. et al. PPE antigen Rv2430c of Mycobacterium tuberculosis induces a strong B-cell response. Infect. Immun. 71, 63386343 (2003).

Article CAS PubMed PubMed Central Google Scholar

Chen, W. et al. Mycobacterium tuberculosis PE25/PPE41 protein complex induces activation and maturation of dendritic cells and drives Th2-biased immune responses. Med. Microbiol. Immunol. 205, 119131 (2016).

Article CAS PubMed Google Scholar

Assis, P. A. et al. Mycobacterium tuberculosis expressing phospholipase C subverts PGE2 synthesis and induces necrosis in alveolar macrophages. BMC Microbiol. 14, 128 (2014).

Article PubMed PubMed Central Google Scholar

Bakala NGoma, J. C., Schu, M., Carrire, F., Geerlof, A. & Canaan, S. Evidence for the cytotoxic effects of Mycobacterium tuberculosis phospholipase C towards macrophages. Biochim. Biophys. Acta BBA Mol. Cell Biol. Lipids 1801, 13051313 (2010).

Google Scholar

Wang, X. et al. Identification and evaluation of the novel immunodominant antigen Rv2351c from Mycobacterium tuberculosis. Emerg. Microbes Infect. 6, e48 (2017).

Article CAS PubMed PubMed Central Google Scholar

Shahbaaz, M., Potemkin, V., Bisetty, K., Hassan, Md. I. & Hussien, M. A. Classification and functional analyses of putative virulence factors of Mycobacterium tuberculosis: A combined sequence and structure based study. Comput. Biol. Chem. 87, 107270 (2020).

Article CAS PubMed Google Scholar

Usmani, S. S., Kumar, R., Bhalla, S., Kumar, V. & Raghava, G. P. S. Chapter SevenIn Silico tools and databases for designing peptide-based vaccine and drugs. In Advances in Protein Chemistry and Structural Biology Vol. 112 (ed. Donev, R.) 221263 (Academic Press, 2018).

Google Scholar

The UniProt Consortium. UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Res. 49, D480D489 (2021).

Article Google Scholar

Kolaskar, A. S. & Tongaonkar, P. C. A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Lett. 276, 172174 (1990).

Article CAS PubMed Google Scholar

Dimitrov, I., Naneva, L., Doytchinova, I. & Bangov, I. AllergenFP: Allergenicity prediction by descriptor fingerprints. Bioinformatics 30, 846851 (2014).

Article CAS PubMed Google Scholar

Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403410 (1990).

Article CAS PubMed Google Scholar

Saha, S. & Raghava, G. P. S. Prediction of continuous B-cell epitopes in an antigen using recurrent neural network. Proteins Struct. Funct. Bioinform. 65, 4048 (2006).

Article CAS Google Scholar

Saha, S., Bhasin, M. & Raghava, G. P. Bcipep: A database of B-cell epitopes. BMC Genom. 6, 79 (2005).

Article Google Scholar

Wang, P. et al. A systematic assessment of MHC Class II peptide binding predictions and evaluation of a consensus approach. PLOS Comput. Biol. 4, e1000048 (2008).

Article PubMed PubMed Central Google Scholar

Wang, P. et al. Peptide binding predictions for HLA DR, DP and DQ molecules. BMC Bioinform. 11, 568 (2010).

Article Google Scholar

Larsen, M. V. et al. Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction. BMC Bioinform. 8, 424 (2007).

Article Google Scholar

Lim, W. C. & Khan, A. M. Mapping HLA-A2, -A3 and -B7 supertype-restricted T-cell epitopes in the ebolavirus proteome. BMC Genom. 19, 42 (2018).

Article Google Scholar

Sette, A. & Sidney, J. Nine major HLA class I supertypes account for the vast preponderance of HLA-A and -B polymorphism. Immunogenetics 50, 201212 (1999).

Article CAS PubMed Google Scholar

Dhanda, S. K., Vir, P. & Raghava, G. P. S. Designing of interferon-gamma inducing MHC class-II binders. Biol. Direct 8, 30 (2013).

Article PubMed PubMed Central Google Scholar

Gupta, S. et al. In silico approach for predicting toxicity of peptides and proteins. PLoS ONE 8, e73957 (2013).

Article CAS PubMed PubMed Central Google Scholar

Larijani, A., Kia-Karimi, A. & Roostaei, D. Design of a multi-epitopic vaccine against EpsteinBarr virus via computer-based methods. Front. Immunol. 14, 1115345 (2023).

Article CAS PubMed PubMed Central Google Scholar

Gasteiger, E. et al. ExPASy: The proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res. 31, 37843788 (2003).

Article CAS PubMed PubMed Central Google Scholar

Doytchinova, I. A. & Flower, D. R. VaxiJen: A server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinform. 8, 4 (2007).

Article Google Scholar

Magnan, C. N. et al. High-throughput prediction of protein antigenicity using protein microarray data. Bioinformatics 26, 29362943 (2010).

Article CAS PubMed PubMed Central Google Scholar

Magnan, C. N., Randall, A. & Baldi, P. SOLpro: Accurate sequence-based prediction of protein solubility. Bioinformatics 25, 22002207 (2009).

Article CAS PubMed Google Scholar

Dimitrov, I., Bangov, I., Flower, D. R. & Doytchinova, I. AllerTOP vol 2A server for in silico prediction of allergens. J. Mol. Model 20, 2278 (2014).

Article PubMed Google Scholar

Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583589 (2021).

Article CAS PubMed PubMed Central Google Scholar

McGuffin, L. J., Bryson, K. & Jones, D. T. The PSIPRED protein structure prediction server. Bioinformatics 16, 404405 (2000).

Article CAS PubMed Google Scholar

Kouza, M., Faraggi, E., Kolinski, A. & Kloczkowski, A. The GOR method of protein secondary structure prediction and its application as a protein aggregation prediction tool. In Prediction of Protein Secondary Structure (eds Zhou, Y. et al.) 724 (Springer, 2017). https://doi.org/10.1007/978-1-4939-6406-2_2.

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Immunoinformatics and structural aided approach to develop multi-epitope based subunit vaccine against Mycobacterium tuberculosis - Nature.com

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