Immunoinformatics-Based Proteome Mining to Develop a Next-Generation Vaccine Design against Borrelia burgdorferi: The Cause of Lyme Borreliosis
Abstract
:1. Introduction
2. Materials and Methods
2.1. Subtractive Proteomics
2.2. Epitope Mining
2.3. Prediction of IFN-γ Epitopes
2.4. Epitope Screening
2.5. Epitope Assemblage
2.6. Conformational B Cell Epitope Analysis
2.7. Antigenicity and Safety Profiling of the MEV
2.8. Physicochemical Profiling, Structure Projections, Model Refinement, and Quality-Check
2.9. MD Analysis
2.10. Molecular Docking with TLR-1 and TLR-2
2.11. In-Silico Cloning Experiment
2.12. Immune Simulations
3. Results
3.1. Data Assemblage and Proteome Subtraction
3.2. Immunogenicity and Protein Size Analysis
3.3. Epitope Mining
3.4. Designing of the MEV
3.5. Antigenicity, Allergenicity, and Safety Profiling of the MEV
3.6. Physicochemical Analysis
3.7. Projection of Secondary Structure
3.8. Projection, Refinement, and Evaluation of 3D Structure
3.9. Discontinuous BCEs
3.10. Analysis of MD Simulations Using GROMACS
3.11. Molecular Docking Analysis
3.12. Restriction Cloning In-Silico Experiment
3.13. Immune Simulations Experiment
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Protein Name | Protein ID | Antigenicity (>0.4) | Virulence | Allergenicity | Homology to Humans | Size (kDa) |
---|---|---|---|---|---|---|
TsaE | WP_002556784.1 | 0.68 | ✓ | ✗ | Not found | 15.4 |
FliP | WP_002556874.1 | 0.71 | ✓ | ✗ | Not found | 29.0 |
ABC transporter permease | WP_002557338.1 | 0.53 | ✓ | ✗ | Not found | 27.6 |
MreD | WP_002656052.1 | 0.71 | ✓ | ✗ | Not found | 20.9 |
YggT family protein | WP_002656831.1 | 0.63 | ✓ | ✗ | Not found | 22.2 |
MurJ | WP_002657239.1 | 0.64 | ✓ | ✗ | Not found | 58 |
CTL Epitope (9-mer) | Protein ID | Combined Score | VaxiJen | Toxin | Conservancy in B. burgdorfei sp. | Solubility |
---|---|---|---|---|---|---|
KSEKKMINF | WP_002556784 | 0.9186 | 0.5478 | No | 100% | Good |
TTNGLNFPF | WP_002556874 | 0.8427 | 1.3018 | No | 100% | Good |
DLGIILLQY | WP_002557338 | 0.8397 | 0.8354 | No | 100% | Good |
IIFAKPIMY | WP_002657239 | 0.8012 | 0.5076 | No | 100% | Good |
Epitope (9-mer) | Protein ID | Percentile Rank | Antigenicity | Toxin | IFN Epitope | Conservancy | Solubility |
---|---|---|---|---|---|---|---|
IILLQYLGI | WP_002557338 | 0.01 | 0.6290 | No | Positive | 100% | Good |
FQWDVGFSF | WP_002657239 | 0.01 | 1.82 | No | positive | 100% | Good |
ILILIRILL | WP_002656831 | 0.01 | 1.2411 | No | positive | 100% | Good |
Linear B Cell Epitope (15-mer) | Protein | Probability Score | Antigenicity | Toxin | Conservancy (%) | Solubility |
---|---|---|---|---|---|---|
IALSIVPKDRLFSLTF | WP_002556784.1 | 0.85 | 0.7432 | No | 100 | Good |
MGMIMLPPVMISLPFK | WP_002556874.1 | 0.92 | 1.2510 | No | 100 | Good |
YFTGLPLGFFVFGYTI | WP_002656052.1 | 0.75 | 0.9086 | No | 100 | Good |
Docking Analysis | TLR-1 | TLR-2 |
---|---|---|
HADDOCK Parameters | ||
HADDOCK score | −79.2 ± 14.1 | −103.0 ± 2.5 |
Z-Score | −1.3 | −0.8 |
RMSD | 1.2 ± 1.5 | 0.3 ± 0.1 |
Van der Waals energy | −81.4 ± 2.4 | −82.7 ± 4.1 |
Electrostatic energy | −332.3 ± 50.7 | −335.2 ± 49.5 |
Desolvation energy | −14.0 ± 10.2 | −51.2 ± 10.6 |
Buried Surface Area | 2567.8 ± 210.5 | 1938.2 ± 63.0 |
Binding affinity and kD prediction | ||
ΔG (kcal mol−1) | −12.1 | −12.0 |
Kd (M) at 25.0 °C | 1.3 × 10−9 | 1.5 × 10−9 |
Number of Interfacial Contacts (ICs) per property | ||
Charged-charged | 22 | 14 |
Charged-polar | 42 | 15 |
Charged-apolar | 23 | 36 |
Polar-polar | 3 | 2 |
Polar-apolar | 9 | 8 |
Apolar-apolar | 3 | 5 |
Protein-protein interface interaction statistics | ||
Salt bridges | 3 | 4 |
Hydrogen bonds | 14 | 13 |
No. of non-bonded contacts | 149 | 204 |
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Khalid, K.; Ahsan, O.; Khaliq, T.; Muhammad, K.; Waheed, Y. Immunoinformatics-Based Proteome Mining to Develop a Next-Generation Vaccine Design against Borrelia burgdorferi: The Cause of Lyme Borreliosis. Vaccines 2022, 10, 1239. https://doi.org/10.3390/vaccines10081239
Khalid K, Ahsan O, Khaliq T, Muhammad K, Waheed Y. Immunoinformatics-Based Proteome Mining to Develop a Next-Generation Vaccine Design against Borrelia burgdorferi: The Cause of Lyme Borreliosis. Vaccines. 2022; 10(8):1239. https://doi.org/10.3390/vaccines10081239
Chicago/Turabian StyleKhalid, Kashaf, Omar Ahsan, Tanwir Khaliq, Khalid Muhammad, and Yasir Waheed. 2022. "Immunoinformatics-Based Proteome Mining to Develop a Next-Generation Vaccine Design against Borrelia burgdorferi: The Cause of Lyme Borreliosis" Vaccines 10, no. 8: 1239. https://doi.org/10.3390/vaccines10081239
APA StyleKhalid, K., Ahsan, O., Khaliq, T., Muhammad, K., & Waheed, Y. (2022). Immunoinformatics-Based Proteome Mining to Develop a Next-Generation Vaccine Design against Borrelia burgdorferi: The Cause of Lyme Borreliosis. Vaccines, 10(8), 1239. https://doi.org/10.3390/vaccines10081239