- Short Communications
- Open Access
Computational identification of significant immunogenic epitopes of the putative outer membrane proteins from Mycobacterium tuberculosis
Journal of Genetic Engineering and Biotechnology volume 19, Article number: 48 (2021)
Novel vaccines are required to effectively combat the epidemic spread of tuberculosis. Using in silico approaches, this study focuses on prediction of potential B cell and T cell binding immunogenic epitopes for 30 putative outer membrane proteins of Mtb. Among these, certain immunodominant epitopes of Rv0172, Rv0295c, Rv1006, Rv2264c, and Rv2525c were found, which are capable of binding B-cell and a maximum number of MHC alleles. The selected immunodominant epitopes were screened for their allergenic and antigenic properties, their percentage identity against the human proteome and their structural properties. Further, the binding efficacy of the immunodominant epitopes of Rv0295c and Rv1006 with HLA-DRB1*04:01 was analyzed using molecular docking and molecular dynamics studies. Hence, the in silico-derived immunogenic peptides (epitopes) could potentially be used for the design of subunit vaccines against tuberculosis.
Tuberculosis (TB) is caused by pathogenic bacillus Mycobacterium tuberculosis (Mtb) and is a deadly disease that affects millions of people worldwide. In accordance with the WHO Global tuberculosis report 2018, TB is one of the top ten causes for human deaths and estimated around 1.3 million deaths in HIV-negative people. Moreover, 10.0 million people developed TB disease in 2017. The emergence of multi-drug and extensively drug-resistant strains of Mtb increases the burden of the drug treatment regimen for TB. Currently, Bacille-Calmette-Guerin (BCG) is the only available vaccine for treating TB. In infants, it is shown to have a protective effect against tuberculous meningitis and miliary tuberculosis . However, in adults, it is shown to have only limited protection against pulmonary TB. Moreover, it causes more severe complications such as suppurative lymphadenitis, osteomyelitis/osteitis, and disseminated BCG infection. Disseminated BCG infection is a severe adverse reaction that arises in people with impaired immunity. Therefore, the BCG vaccine is not being given for HIV positive patients and for infants born to HIV-positive mothers. Due to the limitations of the BCG vaccine, we need novel and effective vaccines against all forms of TB.
Immunoinformatics involves the use of computational tools to predict the immunogenic epitopes or peptides which could be used to design ideal subunit vaccine candidates. These tools simply use the organism’s genetic information, and it reduces the cost and time taken for the development of vaccines . Subunit vaccines usually consist of certain immunoactive biomolecules such as polypeptides and glycolipids and usually, they need the help of an adjuvant for inducing immune protection. These can be easily prepared at low cost and highly specific and efficient with minimal side effects . Many new and promising subunit TB vaccine candidates are in various stages of clinical trials [10, 12].
Outer membrane proteins (OMPs) play an important role in the host-pathogen interactions and in maintaining the integrity and permeability of the cell membranes. Due to their localization on the mycobacterial surfaces, they can be easily targeted by the host immune system and hence they are ideal candidates for vaccine design . Recently, Baliga et al., in , have predicted immunogenic epitopes of the OMPs of the pathogen Vibrio anguillarum. Similarly, Rauta et al., in , have predicted immunogenic epitopes of the OMP's of the pathogen Vibrio cholerae. Song et al., in , have identified 144 putative OMPs of Mtb which could play some crucial role in mycobacterial pathogenesis. In this study, using computational approaches we intend to identify the potential immunogenic epitopes of 30 putative OMPs of Mtb. We believe that this study will provide suitable leads for the design of peptide-based subunit vaccines using OMP’s of Mtb.
The overall methodology adopted in this study to determine potential vaccine candidates of the putative OMPs of Mtb is depicted in Fig. 1.
FASTA Sequences of 143 putative OMPs of Mtb were retrieved from UniProtKB protein database and subjected for epitope prediction. UniprotKB Ids of the retrieved sequence is given in Table S1. The protein sequence of Rv1784 (one of the putative OMP) was not found in UniprotKB database.
Sequence-based B cell prediction
B cell epitope prediction for the retrieved FASTA sequences of the OMP’s of Mtb was performed using IEDB tools. BepiPred Linear Epitope prediction method  was employed which uses a propensity scale of amino acids and Hidden Markov models for the prediction of potential immunogenic B cell epitopes. Default parameters were employed for the prediction.
Evaluation of antigenic and allergenic properties of the predicted epitopes
Antigenic and allergenic values of the predicted B cell epitopes were calculated using VaxiJen (antigenic proteins should possess a score above 0.4)  and AlgPred servers (non-allergenic protein sequences should possess a score lesser than − 0.4)  using default parameters.
Homology of the epitopes with the human proteome
The B cell binding epitopes were further screened for their similarity against humans, in order to avoid cross-reactivity. BLASTp program  was used to check the similarity of the epitopes against humans. The default non redundant protein sequences (nr) database was employed for similarity searching. All the other parameters were set to default values. The epitopes having lesser than 80% similar to the human proteome were further analyzed for its structural properties.
T cell epitope prediction
The predicted B cell epitopes were further subjected for T cell binding prediction. The MHC-I binding predictions were made using the IEDB analysis resource Consensus tool  which combines predictions from ANN aka NetMHC (4.0) [3, 17, 20], SMM  and Comblib . The reference set of 27 MHC-I alleles was used for the prediction . The peptide length was set to 10. The high affinity binding epitopes were selected based on their percentile rank, which is set to 20.
The MHCII binding predictions were made using the IEDB analysis resource Consensus tool [30, 31]. The reference set of 27 MHC-II alleles was used for the prediction . The peptide length was set to 15. The high affinity binding epitopes were selected based on their percentile rank, which is set to 20.
Selection of immunodominant epitopes (IDEs) of the putative OMPs of Mtb
Immunodominant epitopes (IDEs) are regions which can bind B cell as well as maximum number of MHC-I and MHC-II alleles. The identification of IDEs has immense potential as it can lead to strong immune response and it can be effectively used to design peptide based vaccines. This method of finding IDEs was successfully employed by Verma et al. in  for the design of DnaK peptide vaccine against S. typhi.
Prediction of transmembrane topology and the solubility of the epitopes
Structural properties of the IDEs such as solvent accessibility, transmembrane topology, and solubility upon overexpression were predicted using ACCpro, ABTMpro, and SOLpro tools respectively, found in the SCRATCH protein prediction server . Solvent accessibility of the epitopes is an important criterion as the epitopes should be exposed for the interaction of the immune cells. Prediction of transmembrane topology for the epitopes is important because proteins spanning the membrane are difficult to clone and express; therefore, epitopes which are non-transmembrane proteins could be ideal vaccine candidates. The predicted epitopes should also be soluble on over-expression, so the solubility check was also performed.
Molecular docking and molecular dynamics studies of the IDEs with HLA-DRB1*04:01
The selected IDEs of Rv0295c and Rv1006 were modeled using PEPFOLD 3 server  and were made to dock with HLA-DRB1*04:01(PDB ID: 5JLZ) using Cluspro server . The higher ranked epitope-HLA complex was further subjected to molecular dynamics studies using GROMACS 2019  software for 20ns. For the MD setup, GROMOS 43a1 force field was used and the epitope-HLA complex was placed in a cubic box filled with spc water molecules. The complex was neutralized by adding corresponding ions and energy was minimized using steepest-descent algorithm. Further, the complex was subjected to NVT and NPT equilibration steps for 100 ps, each. The temperature and the pressure were fixed at 300 K and 1 bar, respectively. Finally, the all atom MD run was performed for 20ns. The coordinates was written for every 10 ps. RMSD and RMSF of the epitope-HLA complex was computed using the GROMACS in-built tool namely, rms. Xmgrace was used to plot the graph.
Song et al., in , have identified 144 putative OMPs of Mtb and we have used this list of OMPs for the prediction of potentially immunogenic epitopes. B cell epitopes have been predicted for all the 144 OMP’s of Mtb and its antigenic and allergenic properties have been calculated. The B cell epitopes which are allergenic, non-antigenic are not considered for further analysis. Moreover, in order to avoid cross-reactivity, the predicted B cell epitopes whose similarity is greater than 80% against the human proteome were further excluded from our analysis. By applying all the above criteria’s, we have predicted B cell binding epitopes for 30 putative OMPs of Mtb. Additionally, to predict IDEs for the putative OMP’s of Mtb, the B cell binding epitopes were further subjected to T cell binding prediction.
The list of B cell epitopes predicted from the 30 putative OMPs of Mtb, along with their Vaxijen and AlgPred scores and the number of MHC alleles capable of binding these epitopes is given in Table 1. Further, we selected certain IDEs (given in Table 1) which are predicted to bind B-cell and the maximum number of MHC alleles (at least capable of binding > 25 alleles each from Class I as well as Class II). Further, the selected IDEs were checked for solvent accessibility, transmembrane topology, and solubility upon overexpression.
Five selected IDEs are discussed below:
382ASTASTLPKE IAYSEPRLQPPNGYKDTTV PGIWVPDTPLSHRNTQPGWVVA432 of Rv0172 is predicted to be a B cell binding epitope and is predicted to bind all the 27 reference alleles of MHC Class I and Class II, respectively. Moreover, it is predicted to be antigenic and non-allergenic, cannot find significant similarity against the human proteome. This IE is a non-transmembrane protein; solvent exposed and is predicted to be soluble when over-expressed. Additionally, Rv0172 belongs to Mce (Mammalian cell entry) family of proteins which are crucial for the virulence of Mtb .
Similarly, we found a potential IE. 228AIGQDPKLAPA PMLERQANQRSDEW VDRYRAEAPRLG264B-cell binding epitope of Rv0295c is non-allergenic and antigenic and binds 26 alleles of MHC Class I and 27 alleles of MHC Class II. It has no sequence similarity with the human proteome, solvent-exposed, non-transmembrane protein and is predicted to be soluble when over-expressed. In fact, Rv0295c is a Trehalose 2-sulfotransferaseand it involves in catalyzing the transfer of a sulfuryl group from 3′-phosphoadenosine-5′-phosphosulfate (PAPS) to trehalose, which leads to the synthesis of trehalose-2-sulfate (T2S) .
The next IDE is “24LNGCSSSASHRG PLNAMGSPAI PSTAQEIPNPLRGQ59” from Rv1006 is predicted to be a B-cell binding epitope which also binds 26 and 27 alleles of MHC Class I and Class II alleles, respectively. It is antigenic, non-allergenic and has least similarity to the human host. Additionally, it is solvent exposed, non-transmembrane and soluble upon overexpression. Rv1006 is believed to be a conserved hypothetical protein.
“383AWSEADEDSHI GPAPGYTAARPSL SFDHDAHAEPEPKSPPIPW425” is predicted to be a B cell binding epitope from Rv2264c, it also binds all of the 27 reference alleles of Class I and Class II, respectively. It is also predicted to be antigenic, non-allergenic and has least similarity to the human proteome. It is solvent exposed non-transmembrane and soluble upon overexpression. Rv2264c is a conserved hypothetical protein.
“102YGKGSTADWLGGA SAGVQHARRGSELHA AAGGPTSAPIYA SIDDNPSYEQYK153” is predicted to be a B cell binding epitope from Rv2525c, it also binds all of the 27 reference alleles of Class I and Class II, respectively. It is also predicted to be antigenic, non-allergenic and has least similarity to the human proteome. It is solvent exposed non-transmembrane and soluble upon overexpression. Rv2525c is a tat secreted protein and it functions as a putative peptidoglycan hydrolase .
Molecular docking and molecular dynamics studies
The epitopes of Rv0295c and Rv1006 was modeled using PEPFOLD 3 server and was subjected to molecular docking studies with the 3D structure of HLA-DRB1*04:01 using Cluspro server. The other epitopes could not be modeled by the PEPFOLD 3 server as the length of the epitope was greater than 50 amino acids. The epitope of Rv2264c was having 52.17% similarity (Table 1) with the human proteome was also excluded for molecular docking and dynamics studies. The top-ranked epitope-HLA-DRB1*04:01 complex was retrieved. The binding energies for the top ranked epitope-HLA-DRB1*04:01 complex is given in Table 2.
The epitopes of Rv0295c and Rv1006 had strong affinity (Fig. 2a, b) with HLA-DRB1*04:01 and were further subjected to MD analysis. Each docked complex was subjected to a MD run for 20ns using GROMACS software. RMSD of HLA-DRB1*04:01 in Rv0295c-HLA-DRB1*04:01 complex (Fig. 3a) reached 10 Å around 10ns and remained the same until 20ns. Similarly, RMSD of HLA-DRB1*04:01 in the Rv1006-HLA-DRB1*04:01 complex reached 5 Å around 1ns and remained the same until 20 ns. The mobile regions (> 0.3 nm) of HLA-DRB1*04:01 depicted in Fig. 3b, mostly found to have interactions with the predicted epitope.
Vaccination is the best efficient method to treat TB. BCG is the currently available vaccine against TB. It expresses an Mtb immunodominant protein Antigen 85B (Ag85B) . The antigen85 (Ag85) proteins comprise of Ag85A, Ag85B, and Ag85C. They are well-known mycolyltransferases or Diacylglycerolacyltransferases of Mtb which involves the transfer of mycolic acids to the cell wall arabinogalactan and they possess a high binding affinity for fibronectin . BCG has been very effective against severe forms of TB in infants but it has protective efficacy against adults. Due to the adverse effects of BCG, a more effective and protective vaccine against all forms of TB is currently needed. In recent years, many new adjuvantedAg85B protein and vectored subunit vaccine candidates of Ag85A are in different phases of clinical trials. ESAT-6 and certain other proteins of Mtb have also been tested for their immunogenic competence .
Generally, bacterial OMPs serve as potential vaccine candidates, as their exposed epitopes on the bacterial cell surface could be easily recognized by the host immune system [5, 22]. In , Zvi et al. predicted 45 top-hits antigens covering the entire genome of Mtb as potential vaccine candidates which can be incorporated in the design of subunit vaccines against Mtb. Rv1813c, one of the 45 top-hits antigens predicted and is also predicted to be an OMP . In 2015, Scientists at Infectious Disease Research Institute (IDRI) at Seattle, created a vaccine candidate ID93 which is a recombinant fusion of the four Mtb proteins. Notably, Rv1813c, a predicted OMP, is one of the four proteins of the ID93 vaccine candidate which has advanced to phase II clinical trials .
Therefore, from our in silico study of the OMP’s of Mtb, we have retrieved five IDEs (Table 1) which can bind both B cell and maximum number of T cells, antigenic, and non-allergenic, having lesser or no sequence similarity with the human proteome, non-transmembrane proteins and are predicted to be soluble when over-expressed. These five IDEs of the putative OMP’s (Rv0172, Rv0295c, Rv1006, Rv2264c, and Rv2525c) of Mtb could serve as ideal candidates for the design of subunit vaccines against tuberculosis.
In this study, through immunoinformatics approach, potentially immunogenic epitopes for 30 putative OMPs of Mtb have been identified. Immuno dominant epitopes designed for Rv0172, Rv0295c, Rv1006, Rv2264c, and Rv2525c were predicted to be non-allergenic, antigenic and capable of binding B cells and a maximum number of MHC alleles. These epitopes also show lesser or no sequence similarity with the human proteome, solvent-exposed, non-transmembrane and soluble upon overexpression. Molecular docking and molecular dynamics analysis of Rv0295c and Rv1006 epitopes-HLA-DRB1*04:01 complex further enhance our study. Thus, we suggest that these in silico-derived epitopes could be useful in developing peptide-based subunit vaccines against tuberculosis.
Availability of data and materials
Human leukocyte antigen
Major histocompatibility complex
World Health Organization
Human immunodeficiency virus
Outer membrane protein
Abraham MJ, Murtola T, Schulz R et al (2015) GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 1:19–25
Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. J Mol Biol 215(3):403–410. https://doi.org/10.1016/S0022-2836(05)80360-2
Andreatta M, Nielsen M (2016) Gapped sequence alignment using artificial neural networks: application to the MHC class I system. Bioinformatics 32(4):511–517. https://doi.org/10.1093/bioinformatics/btv639
Baldwin SL, Reese VA, Po-wei DH et al (2016) Protection and long-lived immunity induced by the ID93/GLA-SE vaccine candidate against clinical Mycobacterium tuberculosis isolate. ClinVacc Immuno 23(2):137–147. https://doi.org/10.1128/CVI.00458-15
Baliga P, Shekar M, Venugopal MN (2018) Potential outer membrane protein candidates for vaccine development against the pathogen Vibrio anguillarum: a reverse vaccinology based identification. Curr Microbiol 75(3):368–377. https://doi.org/10.1007/s00284-017-1390-z
Bellinzoni M, Haouz A, Miras I, Magnet S, André-Leroux G, Mukherjee R, Shepard W, Cole ST, Alzari PM (2014) Structural studies suggest a peptidoglycan hydrolase function for the Mycobacterium tuberculosis Tat-secreted protein Rv2525c. J Struct Biol 188(2):156–164. https://doi.org/10.1016/j.jsb.2014.09.003
Cheng J, Randall AZ, Sweredoski MJ, Baldi P (2005) SCRATCH: a protein structure and structural feature prediction server. Nucleic Acids Res 33(suppl_2):W72–W76
De Groot AS, Sbai H, Aubin CS et al (2002) Immuno-informatics: mining genomes for vaccine components. Immunol Cell Biol 80(3):255–269. https://doi.org/10.1046/j.1440-1711.2002.01092.x
Doytchinova IA, Flower DR (2007) VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinformatics 8(1):4. https://doi.org/10.1186/1471-2105-8-4
Gong W, Liang Y, Wu X (2018) The current status, challenges, and future developments of new tuberculosis vaccines. Hum Vaccin Immunother 14(7):1697–1716. https://doi.org/10.1080/21645515.2018.1458806
Greenbaum J, Sidney J, Chung J, Brander C, Peters B, Sette A (2011) Functional classification of class II human leukocyte antigen (HLA) molecules reveals seven different supertypes and a surprising degree of repertoire sharing across supertypes. Immunogenetics 63(6):325–335. https://doi.org/10.1007/s00251-011-0513-0
Khoshnood S, Heidary M, Haeili M, Drancourt M, Darban-Sarokhalil D, Nasiri MJ, Lohrasbi V (2018) Novel vaccine candidates against Mycobacterium tuberculosis. Int J Biol Macromol 120(Pt A):180–188. https://doi.org/10.1016/j.ijbiomac.2018.08.037
Kim Y, Ponomarenko J, Zhu Z, Tamang D, Wang P, Greenbaum J, Lundegaard C, Sette A, Lund O, Bourne PE, Nielsen M, Peters B (2012) Immune epitope database analysis resource.Nucleic. Acids Res 40(W1):W525–W530. https://doi.org/10.1093/nar/gks438
Koebnik R, Locher KP, Van Gelder P (2000) Structure and function of bacterial outer membrane proteins: barrels in a nutshell. Mol Micro bio 37(2):239–253. https://doi.org/10.1046/j.1365-2958.2000.01983.x
Kozakov D, Hall DR, Xia B, Porter KA, Padhorny D, Yueh C, Beglov D, Vajda S (2017) The ClusPro web server for protein–protein docking. Nat Protoc 12(2):255–278. https://doi.org/10.1038/nprot.2016.169
Larsen JEP, Lund O, Nielsen M (2006) Improved method for predicting linear B-cell epitopes. Immunome Res 2(1):1–7
Lundegaard C, Lamberth K, Harndahl M et al (2008) NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8–11. Nucleic Acids Res 36(suppl_2):W509–W512
Malonis RJ, Lai JR, Vergnolle O (2019) Peptide-based vaccines: current progress and future challenges. Chem Rev 120(6):3210–3229
Mougous JD, Petzold CJ, Senaratne RH, Lee DH, Akey DL, Lin FL, Munchel SE, Pratt MR, Riley LW, Leary JA, Berger JM, Bertozzi CR (2004) Identification, function and structure of the mycobacterial sulfotransferase that initiates sulfolipid-1 biosynthesis. Nat Struct Mol Biol 11(8):721–729. https://doi.org/10.1038/nsmb802
Nielsen M, Lundegaard C, Worning P, Lauemøller SL, Lamberth K, Buus S, Brunak S, Lund O (2003) Reliable prediction of T-cell epitopes using neural networks with novel sequence representations. Protein Sci 12(5):1007–1017. https://doi.org/10.1110/ps.0239403
Peters B, Sette A (2005) Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method. BMC Bioinfo 6(1):132
Rauta PR, Ashe S, Nayak D, Nayak B (2016) In silico identification of outer membrane protein (Omp) and subunit vaccine design against pathogenic Vibrio cholerae. Comput Biol Chem 65:61–68. https://doi.org/10.1016/j.compbiolchem.2016.10.004
Rizzi C, Peiter AC, Oliveira TL, Seixas Neto ACP, Leal KS, Hartwig DD, Seixas FK, Borsuk S, Dellagostin OA, Universidade Federal de Pelotas, Brasil, Universidade Federal de Pelotas, Brasil (2017) Stable expression of Mycobacterium bovis antigen 85B in auxotrophic M. bovis bacillus Calmette-Guérin. Mem Inst Oswaldo Cruz 112(2):123–130. https://doi.org/10.1590/0074-02760160360
Saha S, Raghava GPS (2006) AlgPred: prediction of allergenic proteins and mapping of IgE epitopes. Nucleic Acids Res 34(suppl_2):W202–W209
Shen Y, Maupetit J, Derreumaux P, Tufféry P (2014) Improved PEP-FOLD approach for peptide and mini protein structure prediction. J Chem Comp 10(10):4745–4758
Sidney J, Assarsson E, Moore C, Ngo S, Pinilla C, Sette A, Peters B (2008) Quantitative peptide binding motifs for 19 human and mouse MHC class I molecules derived using positional scanning combinatorial peptide libraries. Immunome Res 4(1):2. https://doi.org/10.1186/1745-7580-4-2
Song H, Sandie R, Wang Y, Andrade-Navarro MA, Niederweis M (2008) Identification of outer membrane proteins of Mycobacterium tuberculosis. Tuberculosis 88(6):526–544. https://doi.org/10.1016/j.tube.2008.02.004
Trunz BB, Fine PEM, Dye C (2006) Effect of BCG vaccination on childhood tuberculous meningitis and miliary tuberculosis worldwide: a meta-analysis and assessment of cost-effectiveness. Lancet 367(9517):1173–1180. https://doi.org/10.1016/S0140-6736(06)68507-3
Verma S, Sugadev R, Kumar A, Chandna S, Ganju L, Bansal A (2018) Multi-epitope DnaK peptide vaccine against S. Typhi: an in silico approach. Vaccine 36(28):4014–4022. https://doi.org/10.1016/j.vaccine.2018.05.106
Wang P, Sidney J, Dow C, Mothé B, Sette A, Peters B (2008) A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach. PLoS Comput Biol 4(4):e1000048. https://doi.org/10.1371/journal.pcbi.1000048
Wang P, Sidney J, Kim Y, Sette A, Lund O, Nielsen M, Peters B (2010) Peptide binding predictions for HLA DR, DP and DQ molecules. BMC Bioinfo 11(1):568. https://doi.org/10.1186/1471-2105-11-568
Weiskopf D, Angelo MA, de Azeredo EL, Sidney J, Greenbaum JA, Fernando AN, Broadwater A, Kolla RV, de Silva AD, de Silva AM, Mattia KA, Doranz BJ, Grey HM, Shresta S, Peters B, Sette A (2013) Comprehensive analysis of dengue virus-specific responses supports an HLA-linked protective role for CD8+ T cells. Proc Natl Acad Sci 110(22):E2046–E2053. https://doi.org/10.1073/pnas.1305227110
Wiker HG, Harboe M (1992) The antigen 85 complex: a major secretion product of Mycobacterium tuberculosis. Microbiol Mol Biol Rev 56(4):648–661
Zhang F, Xie JP (2011) Mammalian cell entry gene family of Mycobacterium tuberculosis. Mol Cell Biochem 352(1-2):1–10. https://doi.org/10.1007/s11010-011-0733-5
Zvi A, Ariel N, Fulkerson J, Sadoff JC, Shafferman A (2008) Whole genome identification of Mycobacterium tuberculosis vaccine candidates by comprehensive data mining and bioinformaticanalyses. BMC Med Genomics 1(1):18. https://doi.org/10.1186/1755-8794-1-18
The authors thank the DBT-Bioinformatics Center at the Department of Bioinformatics, Bharathiar University, for the computational facilities.
Shobana Sundar thanks the financial support received through the award of ICMR-Research Associate (Award Letter No.: ISRM/11(13)/2019).
Ethics approval and consent to participate
Consent for publication
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
UniprotKB IDs of the putative OMPs of Mtb. Table S2. List of MHC-I and MHC-II alleles employed in the study. Figure S3. Ramachandran plot of IDE of Rv0295c. Figure 4. Ramachandran plot of IDE of Rv1006. Figure S5. Ramachandran plot of IDE of Rv2265.
About this article
Cite this article
Sundar, S., Thangamani, L. & Piramanayagam, S. Computational identification of significant immunogenic epitopes of the putative outer membrane proteins from Mycobacterium tuberculosis. J Genet Eng Biotechnol 19, 48 (2021). https://doi.org/10.1186/s43141-021-00148-9
- Outer membrane proteins
- Mycobacterium tuberculosis