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

Kyu, H. H. et al. Global, regional, and national burden of tuberculosis, 1990–2016: results from the Global Burden of Diseases, Injuries, and Risk Factors 2016 study. Lancet. Infect. Dis 18, 1329–1349 (2018).Article 

Google Scholar 
Sandhu, G. K. Tuberculosis: Current situation, challenges and overview of its control programs in India. J. Glob. Infect. Dis. 3, 143–150 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Bagcchi, S. WHO’s 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, 277–285 (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-Guérin. 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, 2911–2914 (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, 299–301 (2015).Article 
PubMed 

Google Scholar 
Méndez-Samperio, P. Global efforts in the development of vaccines for tuberculosis: Requirements for improved vaccines against Mycobacterium tuberculosis. Scand. J. Immunol. 84, 204–210 (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, 118–127 (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, 5908–5917 (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, 220–231 (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, 287–298 (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, 180–188 (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, 991–1004 (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, 361–382 (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, 1713–1725 (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, 4146–4171 (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, 6338–6343 (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, 119–131 (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 N’Goma, J. C., Schué, M., Carrière, 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, 1305–1313 (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 Seven—In Silico tools and databases for designing peptide-based vaccine and drugs. In Advances in Protein Chemistry and Structural Biology Vol. 112 (ed. Donev, R.) 221–263 (Academic Press, 2018).
Google Scholar 
The UniProt Consortium. UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Res. 49, D480–D489 (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, 172–174 (1990).Article 
CAS 
PubMed 

Google Scholar 
Dimitrov, I., Naneva, L., Doytchinova, I. & Bangov, I. AllergenFP: Allergenicity prediction by descriptor fingerprints. Bioinformatics 30, 846–851 (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, 403–410 (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, 40–48 (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, 201–212 (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 Epstein–Barr 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, 3784–3788 (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, 2936–2943 (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, 2200–2207 (2009).Article 
CAS 
PubMed 

Google Scholar 
Dimitrov, I., Bangov, I., Flower, D. R. & Doytchinova, I. AllerTOP vol 2—A 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, 583–589 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
McGuffin, L. J., Bryson, K. & Jones, D. T. The PSIPRED protein structure prediction server. Bioinformatics 16, 404–405 (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.) 7–24 (Springer, 2017). https://doi.org/10.1007/978-1-4939-6406-2_2.Chapter 

Google Scholar 
Källberg, M. et al. Template-based protein structure modeling using the RaptorX web server. Nat. Protoc. 7, 1511–1522 (2012).Article 
PubMed 
PubMed Central 

Google Scholar 
Heo, L., Park, H. & Seok, C. GalaxyRefine: Protein structure refinement driven by side-chain repacking. Nucleic Acids Res. 41, W384–W388 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Lovell, S. C. et al. Structure validation by Cα geometry: ϕ, ψ and Cβ deviation. Proteins Struct. Funct. Bioinform. 50, 437–450 (2003).Article 
CAS 

Google Scholar 
Wiederstein, M. & Sippl, M. J. ProSA-web: Interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 35, W407–W410 (2007).Article 
PubMed 
PubMed Central 

Google Scholar 
Pettersen, E. F. et al. UCSF Chimera—A visualization system for exploratory research and analysis. J. Comput. Chem. 25, 1605–1612 (2004).Article 
CAS 
PubMed 

Google Scholar 
Huang, S.-Y. & Zou, X. Advances and challenges in protein-ligand docking. Int. J. Mol. Sci. 11, 3016–3034 (2010).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Kozakov, D. et al. The ClusPro web server for protein–protein docking. Nat. Protoc. 12, 255–278 (2017).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Pettersen, E. F. et al. UCSF Chimera—A visualization system for exploratory research and analysis. J. Comput. Chem. 25(13), 1605. https://doi.org/10.1002/jcc.20084 (2004).Article 
CAS 
PubMed 

Google Scholar 
Laskowski, R. A., Jabłońska, J., Pravda, L., Vařeková, R. S. & Thornton, J. M. PDBsum: Structural summaries of PDB entries. Protein Sci. 27, 129–134 (2018).Article 
CAS 
PubMed 

Google Scholar 
Abraham, M. J. et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1–2, 19–25 (2015).Article 

Google Scholar 
Berendsen, H. J. C., Postma, J. P. M., van Gunsteren, W. F., DiNola, A. & Haak, J. R. Molecular dynamics with coupling to an external bath. J. Chem. Phys. 81, 3684–3690 (1984).Article 
CAS 

Google Scholar 
Hess, B., Bekker, H., Berendsen, H. J. C. & Fraaije, J. G. E. M. LINCS: A linear constraint solver for molecular simulations. J. Comput. Chem. 18, 1463–1472 (1997).Article 
CAS 

Google Scholar 
Miyamoto, S. & Kollman, P. A. Settle: An analytical version of the SHAKE and RATTLE algorithm for rigid water models. J. Comput. Chem. 13, 952–962 (1992).Article 
CAS 

Google Scholar 
Parrinello, M. & Rahman, A. Polymorphic transitions in single crystals: A new molecular dynamics method. J. Appl. Phys. 52, 7182–7190 (1981).Article 
CAS 

Google Scholar 
Sahoo, S. et al. Impact of nsSNPs in human AIM2 and IFI16 gene: A comprehensive in silico analysis. J. Biomol. Struct. Dyn. https://doi.org/10.1080/07391102.2023.2206907 (2023).Article 
PubMed 

Google Scholar 
Sethi, G., Hwang, J. H. & Krishna, R. Structure based exploration of potential lead molecules against the extracellular cysteine protease (EcpA) of Staphylococcus epidermidis: A therapeutic halt. J. Biomol. Struct. Dyn. https://doi.org/10.1080/07391102.2023.2250455 (2023).Article 
PubMed 

Google Scholar 
Swain, S. S. et al. Molecular docking and simulation study for synthesis of alternative dapsone derivative as a newer antileprosy drug in multidrug therapy. J. Cell. Biochem. 119, 9838–9852 (2018).Article 
CAS 
PubMed 

Google Scholar 
Bui, H.-H. et al. Predicting population coverage of T-cell epitope-based diagnostics and vaccines. BMC Bioinform. 7, 153 (2006).Article 

Google Scholar 
Carbone, A., Zinovyev, A. & Képès, F. Codon adaptation index as a measure of dominating codon bias. Bioinformatics 19, 2005–2015 (2003).Article 
CAS 
PubMed 

Google Scholar 
Grote, A. et al. JCat: A novel tool to adapt codon usage of a target gene to its potential expression host. Nucleic Acids Res. 33, W526–W531 (2005).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Rapin, N., Lund, O., Bernaschi, M. & Castiglione, F. Computational immunology meets bioinformatics: The use of prediction tools for molecular binding in the simulation of the immune system. PLoS ONE 5, e9862 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
Cyster, J. G. & Allen, C. D. C. B cell responses—Cell interaction dynamics and decisions. Cell 177, 524–540 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Ojha, R., Pandey, R. K. & Prajapati, V. K. Vaccinomics strategy to concoct a promising subunit vaccine for visceral leishmaniasis targeting sandfly and leishmania antigens. Int. J. Biol. Macromol. 156, 548–557 (2020).Article 
CAS 
PubMed 

Google Scholar 
Pollard, A. J. & Bijker, E. M. A guide to vaccinology: From basic principles to new developments. Nat. Rev. Immunol. 21, 83–100 (2021).Article 
CAS 
PubMed 

Google Scholar 
Gong, W. et al. Peptide-based vaccines for tuberculosis. Front. Immunol. 13, 830497 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Wicherska-Pawłowska, K., Wróbel, T. & Rybka, J. Toll-like receptors (TLRs), NOD-like receptors (NLRs), and RIG-I-like receptors (RLRs) in innate immunity. TLRs, NLRs, and RLRs ligands as immunotherapeutic agents for hematopoietic diseases. Int. J. Mol. Sci. 22, 13397 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Gong, W., Liang, Y. & Wu, X. The current status, challenges, and future developments of new tuberculosis vaccines. Hum. Vaccins Immunother. 14, 1697–1716 (2018).Article 

Google Scholar 
Gong, W. et al. Peptides-based vaccine MP3RT induced protective immunity against Mycobacterium tuberculosis infection in a humanized mouse model. Front. Immunol. 12, 666290 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Al-Hawash, A. B., Zhang, X. & Ma, F. Strategies of codon optimization for high-level heterologous protein expression in microbial expression systems. Gene Rep. 9, 46–53 (2017).Article 

Google Scholar 
Ejalonibu, M. A. et al. Drug discovery for Mycobacterium tuberculosis using structure-based computer-aided drug design approach. Int. J. Mol. Sci. 22, 13259 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Trunz, B. B., Fine, P. & Dye, C. Effect of BCG vaccination on childhood tuberculous meningitis and miliary tuberculosis worldwide: A meta-analysis and assessment of cost-effectiveness. Lancet 367, 1173–1180 (2006).Article 
PubMed 

Google Scholar 
Mangtani, P. et al. Protection by BCG vaccine against tuberculosis: A systematic review of randomized controlled trials. Clin. Infect. Dis. 58, 470–480 (2014).Article 
PubMed 

Google Scholar 
Ansari, M. A. et al. RD antigen based nanovaccine imparts long term protection by inducing memory response against experimental murine tuberculosis. PLoS ONE 6, e22889 (2011).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Baldwin, S. L. et al. Prophylactic efficacy against Mycobacterium tuberculosis using ID93 and lipid-based adjuvant formulations in the mouse model. PLoS ONE 16, e0247990 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Harris, R. C. et al. Cost-effectiveness of routine adolescent vaccination with an M72/AS01E-like tuberculosis vaccine in South Africa and India. Nat. Commun. 13, 602 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Sanches, R. C. O. et al. Immunoinformatics design of multi-epitope peptide-based vaccine against Schistosoma mansoni using transmembrane proteins as a target. Front. Immunol. 12, 621706 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Vasina, D. V. et al. First-in-human trials of GamTBvac, a recombinant subunit tuberculosis vaccine candidate: Safety and immunogenicity assessment. Vaccines 7, 166 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Maharaj, L. et al. Immunoinformatics approach for multi-epitope vaccine design against P. falciparum malaria. Infect. Genet. Evol. 92, 104875 (2021).Article 
CAS 
PubMed 

Google Scholar 
Jafari Najaf Abadi, M. H. et al. In silico design and immunoinformatics analysis of a chimeric vaccine construct based on Salmonella pathogenesis factors. Microb. Pathog. 180, 106130 (2023).Article 
CAS 
PubMed 

Google Scholar 
Aslam, S. et al. Proteome based mapping and reverse vaccinology techniques to contrive multi-epitope based subunit vaccine (MEBSV) against Streptococcus pyogenes. Infect. Genet. Evol. 100, 105259 (2022).Article 
CAS 
PubMed 

Google Scholar 
Li, M. et al. Design of a multi-epitope vaccine candidate against Brucella melitensis. Sci. Rep. 12, 10146 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Akhtar, N., Singh, A., Upadhyay, A. K. & Mannan, M. A. Design of a multi-epitope vaccine against the pathogenic fungi Candida tropicalis using an in silico approach. J. Genet. Eng. Biotechnol. 20, 140 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Tahir ul Qamar, M. et al. Designing multi-epitope vaccine against Staphylococcus aureus by employing subtractive proteomics, reverse vaccinology and immuno-informatics approaches. Comput. Biol. Med. 132, 104389 (2021).Article 
CAS 
PubMed 

Google Scholar 
Shamakhi, A. & Kordbacheh, E. Immunoinformatic design of an epitope-based immunogen candidate against Bacillus anthracis. Inform. Med. Unlocked 24, 100574 (2021).Article 

Google Scholar 
Albutti, A. An integrated computational framework to design a multi-epitopes vaccine against Mycobacterium tuberculosis. Sci. Rep. 11, 21929 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Mubarak, A. S., Ameen, Z. S., Hassan, A. S. & Ozsahin, D. U. Enhancing tuberculosis vaccine development: A deconvolution neural network approach for multi-epitope prediction. Sci. Rep. 14, 10375 (2024).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Moradi, J., Tabrizi, M., Izad, M., Mosavari, N. & Feizabadi, M. M. Designing a novel multi-epitope DNA-based vaccine against tuberculosis: In Silico approach. Jundishapur J. Microbiol. 10, e67156 (2017).Article 

Google Scholar 
Al Tbeishat, H. Novel In Silico mRNA vaccine design exploiting proteins of M. tuberculosis that modulates host immune responses by inducing epigenetic modifications. Sci. Rep. 12, 4645 (2022).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Cheng, P., Wang, L. & Gong, W. In silico analysis of peptide-based biomarkers for the diagnosis and prevention of latent tuberculosis infection. Front. Microbiol. 13, 947852 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Jiang, F. et al. PP19128R, a multiepitope vaccine designed to prevent latent tuberculosis infection, induced immune responses in silico and in vitro assays. Vaccines 11, 856 (2023).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Shiraz, M., Lata, S., Kumar, P., Shankar, U. N. & Akif, M. Immunoinformatics analysis of antigenic epitopes and designing of a multi-epitope peptide vaccine from putative nitro-reductases of Mycobacterium tuberculosis DosR. Infect. Genet. Evol. 94, 105017 (2021).Article 
CAS 
PubMed 

Google Scholar 
Sakai, S. et al. CD4 T cell-derived IFN-γ plays a minimal role in control of pulmonary mycobacterium tuberculosis infection and must be actively repressed by PD-1 to prevent lethal disease. PLoS Pathog. 12, e1005667 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Rozot, V. et al. Mycobacterium tuberculosis-specific CD8+ T cells are functionally and phenotypically different between latent infection and active disease. Eur. J. Immunol. 43, 1568–1577 (2013).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Chen, X., Zaro, J. L. & Shen, W.-C. Fusion protein linkers: Property, design and functionality. Adv. Drug Deliv. Rev. 65, 1357–1369 (2013).Article 
CAS 
PubMed 

Google Scholar 
Arai, R., Ueda, H., Kitayama, A., Kamiya, N. & Nagamune, T. Design of the linkers which effectively separate domains of a bifunctional fusion protein. Protein Eng. Design Sel. 14, 529–532 (2001).Article 
CAS 

Google Scholar 
Livingston, B. et al. A rational strategy to design multiepitope immunogens based on multiple Th lymphocyte epitopes. J. Immunol. 168, 5499–5506 (2002).Article 
CAS 
PubMed 

Google Scholar 
Yang, Y. et al. In silico design of a DNA-based HIV-1 multi-epitope vaccine for Chinese populations. Hum. Vaccins Immunother. 11, 795–805 (2015).Article 

Google Scholar 
Yano, A. et al. An ingenious design for peptide vaccines. Vaccine 23, 2322–2326 (2005).Article 
CAS 
PubMed 

Google Scholar 
Maphasa, R. E., Meyer, M. & Dube, A. The macrophage response to Mycobacterium tuberculosis and opportunities for autophagy inducing nanomedicines for tuberculosis therapy. Front. Cell. Infect. Microbiol. 10, 618414 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Kleinnijenhuis, J., Oosting, M., Joosten, L. A. B., Netea, M. G. & Van Crevel, R. Innate immune recognition of Mycobacterium tuberculosis. Clin. Dev. Immunol. 2011, 405310 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Bai, W. et al. TLR3 regulates mycobacterial RNA-induced IL-10 production through the PI3K/AKT signaling pathway. Cell. Signal. 26, 942–950 (2014).Article 
CAS 
PubMed 

Google Scholar 
Nayak, S. S., Sethi, G. & Ramadas, K. Design of multi-epitope based vaccine against Mycobacterium tuberculosis: A subtractive proteomics and reverse vaccinology based immunoinformatics approach. J. Biomol. Struct. Dyn. https://doi.org/10.1080/07391102.2023.2178511 (2023).Article 
PubMed 

Google Scholar 
Kumari, R. S., Sethi, G. & Krishna, R. Development of multi-epitope based subunit vaccine against Mycobacterium tuberculosis using immunoinformatics approach. J. Biomol. Struct. Dyn. https://doi.org/10.1080/07391102.2023.2270065 (2023).Article 
PubMed 

Google Scholar 

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