Pan-Genome Analysis of Oral Bacterial Pathogens to Predict a Potential Novel Multi-Epitopes Vaccine Candidate
Abstract
:1. Introduction
2. Research Methodology
2.1. Subtractive Proteome and Reverse Vaccinology Phase
2.2. Pre-Screening Phase
2.3. Cluster Database at High Identity with Tolerance (CD-HIT) Analysis
2.4. Sub-Cellular Localization Phase
2.5. Vaccine Candidate’s Prioritization Phase
2.6. Physiochemical Properties Analysis
2.7. Analysis of Transmembrane Helices
2.8. Antigenicity, Allergenicity, and Adhesion Probability Prediction
2.9. Prediction of Immune Cell Epitopes
2.10. MHCPred Analysis
2.11. Multi-Epitopes Vaccine Design
2.12. Loop Modeling and Vaccine Refinement
2.13. Disulfide Engineering and Codon Optimization
2.14. Docking and Refinement
2.15. Molecular Dynamics Simulation
2.16. MM-GBSA Binding Free Energies
2.17. Immune Simulation
3. Results
3.1. Genomes Retrieval of P. gingivalis
3.2. Bacterial Pan-Genome Analysis
3.3. CD-HIT Analysis
3.4. Proteins Subcellular Localization
3.5. VFDB Analysis
3.6. Transmembrane Helices and Physiochemical Analysis
3.7. Similarity with Human Genome and Prediction of Antigenicity and Allergenicity
3.8. Homology Check of Normal Flora
3.9. B-Cell Epitopes Prediction
3.10. MHC-I and MHC-II Epitopes Prediction
3.11. Epitope Prioritization Phase
3.12. MHCPred, Allergenicity, Antigenicity, Solubility and Toxicity Analysis
3.13. Multi-Epitopes Vaccine Designing
3.14. Vaccine Structure Prediction, Loops Modeling and Refinement
3.15. Disulfide Engineering and Codon Optimization
3.16. Analysis of Molecular Docking
3.17. Docked Complexes Refinement
3.18. Docked Conformation of Vaccine with Immune Receptors
3.19. Interactions of Vaccine to Immune Receptors
3.20. Molecular Dynamics Simulation
3.21. Calculation of Binding Free Energies
3.22. Immune Stimulations
4. Discussion
5. Conclusions and Limitations
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Organism Name | Strain | Size (Mb) | GC% |
---|---|---|---|
P. gingivalis | ATCC 33277 | 2.35 | 48.4 |
P. gingivalis | TDC60 | 2.34 | 48.3 |
P. gingivalis | W83 | 2.34 | 48.3 |
Protein ID | Bit Score | Sequence Identity |
---|---|---|
Outer membrane | ||
>core/451/1/Org1_Gene734 | 117 | 35% |
>core/207/1/Org1_Gene488 | 1303 | 99% |
Extracellular membrane | ||
>core/12/1/Org1_Gene1814 | 208 | 39% |
Periplasmic membrane | ||
>core/1384/1/Org1_Gene274 | 213 | 53% |
>core/351/1/Org1_Gene1345 | 281 | 39% |
>core/1029/1/Org1_Gene254 | 112 | 36% |
Vaccine Target | T.M.H | Physiochemical Properties | Human Blast | Antigenicity | Allergenicity | |||
---|---|---|---|---|---|---|---|---|
Extracellular membrane | HMMTOP | TMHMM | M.W | T.PI | (I.I) | |||
>core/12/1/Org1_Gene1814 | 1 | 0 | 149.58 | 5.13 | 25.75 | Non-Similar | 0.42 | Non-allergen |
Outer membrane | ||||||||
>core/207/1/Org1_Gene488 | 5 | 0 | 73.12 | 8.9 | 8.9 | Non-similar | 0.54 | Non-allergen |
>core/451/1/Org1_Gene734 | 0 | 0 | 50.89 | 9.72 | 9.72 | Non-similar | 0.60 | |
Periplasmic membrane | ||||||||
>core/351/1/Org1_Gene1345 | 2 | 1 | 52.79 | 6.43 | 19.98 | −0.092 | 0.59 | Non-allergen |
>core/1029/1/Org1_Gene254 | 1 | 0 | 30.28 | 6.65 | 23.64 | Non-similar | 0.47 | Non-allergen |
>core/1384/1/Org1_Gene274 | 0 | 0 | 21.50 | 5.97 | 19.27 | Non-Similar | 0.50 | Non-allergen |
S.NO | Shortlisted Proteins | L. casei | L. johnsonii | L. rhamnosus | Bacteroides |
---|---|---|---|---|---|
1 | >core/451/1/Org1_Gene734 (Lytic transglycosylase domain-containing protein) | No Similarity Found | |||
2 | >core/1029/1/Org1_Gene254 (FKBP-type peptidyl-propyl cis-trans isomerase) | ||||
3 | >core/1384/1/Org1_Gene274 (Superoxide dismutase protein) |
Selected Epitopes | DRB*01 01 IC50 Score | Antigenicity | Allergenicity | Solubility | Toxin-Pred |
---|---|---|---|---|---|
KLYTEERRR | 12.11 | 0.1368 | Non-allergen | Good water soluble | Non-toxin |
TINSLVDER | 9.95 | 0.6485 | |||
EICAGETGV | 93.76 | 0.8637 | |||
EICAGETGV | 93.76 | 0.8637 | |||
IEHEICAGE | 52.48 | 0.6314 | |||
QLLNPQYKR | 10.26 | 0.574 | |||
ELQLLNPQY | 19.54 | 1.2269 | |||
GVSNDELQL | 27.35 | 1.3654 | |||
DLEASVSDF | 17.14 | 0.687 |
S. N | A. A | Sequence Number | A. A | Chi3 | Energy | Sum B-Factors |
---|---|---|---|---|---|---|
6 | Phe | 34 | His | 103.11 | 4.15 | 0 |
57 | Glu | 69 | Phe | 111.41 | 7.45 | 0 |
74 | Pro | 77 | Gln | 117.49 | 3.97 | 0 |
104 | Glu | 110 | Asn | 94.29 | 2.09 | 0 |
104 | Glu | 113 | Thr | 98.57 | 4.81 | 0 |
104 | Glu | 114 | Pro | 89.56 | 4.62 | 0 |
150 | Asp | 154 | Pro | 84.4 | 4.89 | 0 |
Rank | Solution Number | Global Energy | Attractive van der Waals | Repulsive van der Waals | Atomic Contact Energy | Hydrogen Bonds Energy |
---|---|---|---|---|---|---|
1 | 5 | −13.83 | −7.21 | 2.90 | −5.95 | −0.81 |
2 | 9 | −5.42 | −32.42 | 25.47 | 10.50 | −1.38 |
3 | 1 | 1.38 | −0.17 | 0.00 | 0.37 | 0.00 |
4 | 7 | 15.35 | −0.04 | 0.00 | 0.45 | 0.00 |
5 | 2 | 28.20 | −7.73 | 6.54 | 6.57 | −0.93 |
6 | 3 | 39.32 | −11.69 | 46.34 | 4.65 | −2.39 |
7 | 6 | 62.01 | −21.28 | 93.15 | 6.42 | −5.06 |
8 | 4 | 86.39 | −25.68 | 125.90 | 7.34 | −3.11 |
9 | 10 | 236.35 | −25.31 | 300.30 | 5.74 | −2.77 |
10 | 8 | 1229.01 | −57.59 | 1598.19 | 3.99 | −5.68 |
Rank | Solution Number | Global Energy | Attractive van der Waals | Repulsive van der Waals | Atomic Contact Energy | Hydrogen Bonds Energy |
---|---|---|---|---|---|---|
1 | 2 | 11.10 | −1.42 | 0.26 | −0.41 | 0.00 |
2 | 3 | 77.74 | −20.90 | 84.35 | 16.05 | −1.80 |
3 | 8 | 275.98 | −34.08 | 352.40 | 8.64 | −1.46 |
4 | 9 | 283.33 | −25.69 | 372.45 | 18.43 | −3.55 |
5 | 7 | 515.10 | −9.49 | 643.79 | 3.88 | −0.66 |
6 | 5 | 2625.03 | −43.38 | 3325.36 | 13.08 | −3.76 |
7 | 4 | 3591.01 | −54.69 | 4575.96 | 3.90 | −2.12 |
8 | 10 | 4292.57 | −74.36 | 5482.30 | 5.14 | −10.62 |
9 | 6 | 5698.37 | −73.32 | 7235.58 | 12.17 | −7.72 |
10 | 1 | 6855.32 | −82.75 | 8713.45 | 8.65 | −11.19 |
Rank | Solution Number | Global Energy | Attractive van der Waals | Repulsive van der Waals | Atomic Contact Energy | Hydrogen Bonds Energy |
---|---|---|---|---|---|---|
1 | 9 | −13.10 | −25.20 | 9.57 | 11.76 | −3.90 |
2 | 10 | 5.35 | −0.18 | 0.00 | 0.06 | 0.00 |
3 | 1 | 79.08 | −35.14 | 152.47 | 2.38 | −3.03 |
4 | 3 | 998.05 | −36.87 | 1285.61 | 20.01 | −3.89 |
5 | 5 | 1020.25 | −34.41 | 1304.89 | 21.14 | −9.75 |
6 | 2 | 3071.74 | −70.38 | 3963.53 | 11.31 | −10.56 |
7 | 7 | 3176.30 | −74.94 | 4102.83 | 14.27 | −10.73 |
8 | 8 | 4986.99 | −83.86 | 6372.21 | 10.54 | −11.68 |
9 | 6 | 5724.53 | −49.93 | 7242.80 | 0.76 | −12.72 |
10 | 4 | 11,424.45 | −116.65 | 14,451.06 | 29.22 | −14.28 |
Vaccine Complex | Interactive Residues |
---|---|
MHC-I | Ala128, Ala135, Arg157, Arg181, Arg51, Asn155, Asp76, Asp129, Asp 83, Asp238, Glu128, Glu148, Glu154, Gln120, Gly79, His151, Leu23, Lys64, Lys 104, Lys144, Lys197, Phe22, Phe152, Pro50, Ser207, Ser132, Thr240, Thr240, Val9, Val152, |
MHC-II | Arg44, Asn19, Asp66, Arg189, Cys174, Glu4, Glu10, Glu22, Glu187, Glu214, Gln10, Gln92, Gln174, Gly20, Leu8, Leu11, Leu45, Leu215, Lys197, Lys93, Pro183, Pro124, Pro142, Ser182, Ser126, Thr185,Thr100, Lys98, Thr21, Thr172, Tyr83,Thr181, Val99, Val91,Val86 |
TLR-4 | Asp428, Asn464, Asn464, Asn6, Asn86, Arg606, Cys542, Leu485, Gln588,Gln588, Gln484, Gln510, Glu136, Glu509, Glu605, Glu485, Gly183, His529, His555, His557, Len462, Lys 4, Lys244, Lys560, Leu87, Phe228, Phe 463, Phe487, Phe538, Pro88, Pro489, Ser569, Tyr79, Thr548, Thr584, Val461 |
Energy Parameter | TLR-4-Vaccine Complex | MHC-I-Vaccine Complex | MHC-II-Vaccine Complex |
---|---|---|---|
MM-GBSA | |||
VDWAALS | −90.14 | −80.96 | −70.46 |
EEL | −85.88 | −59.00 | −42.26 |
Delta G gas | −176.02 | −139.96 | −112.72 |
Delta G solv | 40.29 | 38.64 | 36.55 |
Delta Total | −135.73 | −101.32 | −76.17 |
MM-PBSA | |||
VDWAALS | −90.14 | −80.96 | −70.46 |
EEL | −85.88 | −59.00 | −42.26 |
Delta G gas | −176.02 | −139.96 | −112.72 |
Delta G solv | 43.16 | 39.87 | 42.59 |
Delta Total | −132.86 | −100.09 | −70.13 |
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Rida, T.; Ahmad, S.; Ullah, A.; Ismail, S.; Tahir ul Qamar, M.; Afsheen, Z.; Khurram, M.; Saqib Ishaq, M.; Alkhathami, A.G.; Alatawi, E.A.; et al. Pan-Genome Analysis of Oral Bacterial Pathogens to Predict a Potential Novel Multi-Epitopes Vaccine Candidate. Int. J. Environ. Res. Public Health 2022, 19, 8408. https://doi.org/10.3390/ijerph19148408
Rida T, Ahmad S, Ullah A, Ismail S, Tahir ul Qamar M, Afsheen Z, Khurram M, Saqib Ishaq M, Alkhathami AG, Alatawi EA, et al. Pan-Genome Analysis of Oral Bacterial Pathogens to Predict a Potential Novel Multi-Epitopes Vaccine Candidate. International Journal of Environmental Research and Public Health. 2022; 19(14):8408. https://doi.org/10.3390/ijerph19148408
Chicago/Turabian StyleRida, Tehniyat, Sajjad Ahmad, Asad Ullah, Saba Ismail, Muhammad Tahir ul Qamar, Zobia Afsheen, Muhammad Khurram, Muhammad Saqib Ishaq, Ali G. Alkhathami, Eid A. Alatawi, and et al. 2022. "Pan-Genome Analysis of Oral Bacterial Pathogens to Predict a Potential Novel Multi-Epitopes Vaccine Candidate" International Journal of Environmental Research and Public Health 19, no. 14: 8408. https://doi.org/10.3390/ijerph19148408