Engineering of Cytolethal Distending Toxin B by Its Reducing Immunogenicity and Maintaining Stability as a New Drug Candidate for Tumor Therapy; an In Silico Study
Abstract
:1. Introduction
2. Results
2.1. Retrieving Native CdtB Sequence
2.2. Antigenic Properties of the CdtB Toxin
2.3. B-Cell Epitope Prediction
2.4. Conserved and Functional Residues Determination
2.5. Hotspot Regions Identification
2.6. Tertiary Structure Prediction, Refinement and Validation
2.7. Molecular Dynamics Simulation Results
3. Discussion
4. Conclusions
5. Materials and Methods
5.1. Sequence Analysis
5.2. Predicting Antigenicity
5.3. Predicting the Linear B-Cell Epitopes
5.4. Predicting the Conformational B-Cell Epitopes
5.5. Predicting the Conseverd and Functional Residues
5.6. Predicting the Mutability Residues
5.7. Dstructure Prediction and Energy Minimization
5.8. Validation of 3D Models
5.9. Computational Methods
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Pfeffer, C.M.; Singh, A.T. Apoptosis: A target for anticancer therapy. Int. J. Mol. Sci. 2018, 19, 448. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sohrabi, E.; Rezaie, E.; Heiat, M.; Sefidi-Heris, Y. An Integrated Data Analysis of mRNA, miRNA and Signaling Pathways in Pancreatic Cancer. Biochem. Genet. 2021, 59, 1326–1358. [Google Scholar] [CrossRef] [PubMed]
- Sohrabi, E.; Moslemi, M.; Rezaie, E.; Nafissi, N.; Khaledi, M.; Afkhami, H.; Fathi, J.; Zekri, A. The tissue expression of MCT3, MCT8, and MCT9 genes in women with breast cancer. Genes Genom. 2021, 43, 1065–1077. [Google Scholar] [CrossRef] [PubMed]
- Pucci, C.; Martinelli, C.; Ciofani, G. Innovative approaches for cancer treatment: Current perspectives and new challenges. Ecancermedicalscience 2019, 13, 961. [Google Scholar] [CrossRef]
- Keshtvarz, M.; Salimian, J.; Yaseri, M.; Bathaie, S.Z.; Rezaie, E.; Aliramezani, A.; Norouzbabaei, Z.; Amani, J.; Douraghi, M. Bioinformatic prediction and experimental validation of a PE38-based recombinant immunotoxin targeting the Fn14 receptor in cancer cells. Immunotherapy 2017, 9, 387–400. [Google Scholar] [CrossRef]
- Patyar, S.; Joshi, R.; Byrav, D.P.; Prakash, A.; Medhi, B.; Das, B. Bacteria in cancer therapy: A novel experimental strategy. J. Biomed. Sci. 2010, 17, 21. [Google Scholar] [CrossRef] [Green Version]
- Rezaie, E.; Amani, J.; Pour, A.B.; Hosseini, H.M. A new scfv-based recombinant immunotoxin against EPHA2-overexpressing breast cancer cells; High in vitro anti-cancer potency. Eur. J. Pharmacol. 2020, 870, 172912. [Google Scholar] [CrossRef]
- Keshtvarz, M.; Salimian, J.; Amani, J.; Douraghi, M.; Rezaie, E. In silico analysis of STX2a-PE15-P4A8 chimeric protein as a novel immunotoxin for cancer therapy. In Silico Pharmacol. 2021, 9, 19. [Google Scholar] [CrossRef]
- Hashemi Yeganeh, H.; Heiat, M.; Kieliszek, M.; Alavian, S.M.; Rezaie, E. DT389-YP7, a Recombinant Immunotoxin against Glypican-3 That Inhibits Hepatocellular Cancer Cells: An In Vitro Study. Toxins 2021, 13, 749. [Google Scholar] [CrossRef]
- Heiat, M.; Hashemi Yeganeh, H.; Alavian, S.M.; Rezaie, E. Immunotoxins Immunotherapy against Hepatocellular Carcinoma: A Promising Prospect. Toxins 2021, 13, 719. [Google Scholar] [CrossRef]
- Ohara, M.; Hayashi, T.; Kusunoki, Y.; Nakachi, K.; Fujiwara, T.; Komatsuzawa, H.; Sugai, M. Cytolethal distending toxin induces caspase-dependent and-independent cell death in MOLT-4 cells. Infect. Immun. 2008, 76, 4783–4791. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lin, H.-J.; Liu, H.-H.; Lin, C.-D.; Kao, M.-C.; Chen, Y.-A.; Chiang-Ni, C.; Jiang, Z.-P.; Huang, M.-Z.; Lin, C.-J.; Lo, U. Cytolethal distending toxin enhances radiosensitivity in prostate cancer cells by regulating autophagy. Front. Cell. Infect. Microbiol. 2017, 7, 223. [Google Scholar] [CrossRef]
- Bachran, C.; Hasikova, R.; Leysath, C.E.; Sastalla, I.; Zhang, Y.; Fattah, R.J.; Liu, S.; Leppla, S.H. Cytolethal distending toxin B as a cell-killing component of tumor-targeted anthrax toxin fusion proteins. Cell Death Dis. 2014, 5, e1003. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Asakura, M.; Samosornsuk, W.; Taguchi, M.; Kobayashi, K.; Misawa, N.; Kusumoto, M.; Nishimura, K.; Matsuhisa, A.; Yamasaki, S. Comparative analysis of cytolethal distending toxin (cdt) genes among Campylobacter jejuni, C. coli and C. fetus strains. Microb. Pathog. 2007, 42, 174–183. [Google Scholar] [CrossRef]
- Haghjoo, E.; Galán, J.E. Salmonella typhiencodes a functional cytolethal distending toxin that is delivered into host cells by a bacterial-internalization pathway. Proc. Natl. Acad. Sci. USA 2004, 101, 4614–4619. [Google Scholar] [CrossRef] [Green Version]
- Pons, B.J.; Vignard, J.; Mirey, G. Cytolethal Distending Toxin Subunit B: A Review of Structure-Function Relationship. Toxins 2019, 11, 595. [Google Scholar] [CrossRef] [Green Version]
- Lara-Tejero, M.A.; Galán, J.E. CdtA, CdtB, and CdtC form a tripartite complex that is required for cytolethal distending toxin activity. Infect. Immun. 2001, 69, 4358–4365. [Google Scholar]
- Pons, B.J.; Loiseau, N.; Hashim, S.; Tadrist, S.; Mirey, G.; Vignard, J. Functional Study of Haemophilus ducreyi Cytolethal Distending Toxin Subunit B. Toxins 2020, 12, 530. [Google Scholar]
- Bezine, E.; Malaisé, Y.; Loeuillet, A.; Chevalier, M.; Boutet-Robinet, E.; Salles, B.; Mirey, G.; Vignard, J. Cell resistance to the Cytolethal Distending Toxin involves an association of DNA repair mechanisms. Sci. Rep. 2016, 6, 36022. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Jinadasa, R.N.; Bloom, S.E.; Weiss, R.S.; Duhamel, G.E. Cytolethal distending toxin: A conserved bacterial genotoxin that blocks cell cycle progression, leading to apoptosis of a broad range of mammalian cell lineages. Microbiology 2011, 157, 1851. [Google Scholar] [CrossRef] [Green Version]
- Shenker, B.J.; Dlakić, M.; Walker, L.P.; Besack, D.; Jaffe, E.; LaBelle, E.; Boesze-Battaglia, K. A novel mode of action for a microbial-derived immunotoxin: The cytolethal distending toxin subunit B exhibits phosphatidylinositol 3,4,5-triphosphate phosphatase activity. J. Immunol. 2007, 178, 5099–5108. [Google Scholar] [PubMed]
- Liu, P.; Cheng, H.; Roberts, T.M.; Zhao, J.J. Targeting the phosphoinositide 3-kinase pathway in cancer. Nat. Rev. Drug Discov. 2009, 8, 627–644. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chen, Y.-A.; Lai, Y.-R.; Wu, H.-Y.; Lo, Y.-J.; Chang, Y.-F.; Hung, C.-L.; Lin, C.-J.; Lo, U.; Lin, H.; Hsieh, J.-T. Bacterial Genotoxin-Coated Nanoparticles for Radiotherapy Sensitization in Prostate Cancer. Biomedicines 2021, 9, 151. [Google Scholar] [CrossRef]
- Vafadar, A.; Taheri-Anganeh, M.; Movahedpour, A.; Jamali, Z.; Irajie, C.; Ghasemi, Y.; Savardashtaki, A. In Silico Design and Evaluation of scFv-CdtB as a Novel Immunotoxin for Breast Cancer Treatment. Int. J. Cancer Manag. 2020, 13, e96094. [Google Scholar] [CrossRef]
- Hassan, R.; Bera, T.; Pastan, I. Mesothelin: A new target for immunotherapy. Clin. Cancer Res. 2004, 10, 3937–3942. [Google Scholar] [CrossRef] [Green Version]
- Schönholzer, C.; Keusch, G.; Nigg, L.; Robert, D.; Wauters, J.-P. High prevalence in Switzerland of pure red-cell aplasia due to anti-erythropoietin antibodies in chronic dialysis patients: Report of five cases. Nephrol. Dial. Transplant. 2004, 19, 2121–2125. [Google Scholar] [CrossRef] [Green Version]
- Jawa, V.; Terry, F.; Gokemeijer, J.; Mitra-Kaushik, S.; Roberts, B.J.; Tourdot, S.; De Groot, A.S. T-cell dependent immunogenicity of protein therapeutics pre-clinical assessment and mitigation–updated consensus and review 2020. Front. Immunol. 2020, 11, 1301. [Google Scholar] [CrossRef]
- Galán, J.E. Bacterial toxins and the immune system: Show me the in vivo targets. J. Exp. Med. 2005, 201, 321. [Google Scholar]
- Shepherd, F.R.; McLaren, J.E. T Cell Immunity to Bacterial Pathogens: Mechanisms of Immune Control and Bacterial Evasion. Int. J. Mol. Sci. 2020, 21, 6144. [Google Scholar]
- Harding, F.A.; Stickler, M.M.; Razo, J.; DuBridge, R. The immunogenicity of humanized and fully human antibodies: Residual immunogenicity resides in the CDR regions. In MAbs; Taylor & Francis: Thames, UK, 2010; pp. 256–265. [Google Scholar]
- Bugelski, P.J.; Treacy, G. Predictive power of preclinical studies in animals for the immunogenicity of recombinant therapeutic proteins in humans. Curr. Opin. Mol. Ther. 2004, 6, 10–16. [Google Scholar]
- Wising, C.; Svensson, L.A.; Ahmed, H.J.; Sundaeus, V.; Ahlman, K.; Jonsson, M.; Mölne, L.; Lagergård, T. Toxicity and immunogenicity of purified Haemophilus ducreyi cytolethal distending toxin in a rabbit model. Microb. Pathog. 2002, 33, 49–62. [Google Scholar]
- Mazor, R.; King, E.M.; Pastan, I. Strategies to reduce the immunogenicity of recombinant immunotoxins. Am. J. Pathol. 2018, 188, 1736–1743. [Google Scholar] [CrossRef] [PubMed]
- Rezaie, E.; Bidmeshki Pour, A.; Amani, J.; Mahmoodzadeh Hosseini, H. Bioinformatics Predictions, Expression, Purification and Structural Analysis of the PE38KDEL-scfv Immunotoxin Against EPHA2 Receptor. Int. J. Pept. Res. Ther. 2020, 26, 979–996. [Google Scholar] [CrossRef]
- Kringelum, J.V.; Lundegaard, C.; Lund, O.; Nielsen, M. Reliable B cell epitope predictions: Impacts of method development and improved benchmarking. PLoS Comput. Biol. 2012, 8, e1002829. [Google Scholar] [CrossRef] [PubMed]
- Rezaie, E.; Nekoie, H.; Miri, A.; Oulad, G.; Ahmadi, A.; Saadati, M.; Bozorgmehr, M.; Ebrahimi, M.; Salimian, J. Different frequencies of memory B-cells induced by tetanus, botulinum, and heat-labile toxin binding domains. Microb. Pathog. 2019, 127, 225–232. [Google Scholar] [CrossRef]
- Doytchinova, I.A.; Flower, D.R. VaxiJen: A server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinform. 2007, 8, 4. [Google Scholar]
- Mbwana, J.; Ahmed, H.J.; Ahlman, K.; Sundaeus, V.; Dahlén, G.; Lyamuya, E.; Lagergård, T. Specificity of antibodies directed against the cytolethal distending toxin of Haemophilus ducreyi in patients with chancroid. Microb. Pathog. 2003, 35, 133–137. [Google Scholar] [CrossRef]
- Wang, H.-W.; Lin, Y.-C.; Pai, T.-W.; Chang, H.-T. Prediction of B-cell linear epitopes with a combination of support vector machine classification and amino acid propensity identification. J. Biomed. Biotechnol. 2011, 2011, 432830. [Google Scholar]
- Jahangiri, A.; Rasooli, I.; Owlia, P.; Fooladi, A.A.I.; Salimian, J. In silico design of an immunogen against Acinetobacter baumannii based on a novel model for native structure of outer membrane protein A. Microb. Pathog. 2017, 105, 201–210. [Google Scholar] [CrossRef]
- Saha, S.; Raghava, G.P.S. Prediction of continuous B-cell epitopes in an antigen using recurrent neural network. Proteins Struct. Funct. Bioinform. 2006, 65, 40–48. [Google Scholar]
- Yao, B.; Zhang, L.; Liang, S.; Zhang, C. SVMTriP: A method to predict antigenic epitopes using support vector machine to integrate tri-peptide similarity and propensity. PLoS ONE 2012, 7, e45152. [Google Scholar] [CrossRef] [Green Version]
- Lise, S.; Archambeau, C.; Pontil, M.; Jones, D.T. Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods. BMC Bioinform. 2009, 10, 365. [Google Scholar] [CrossRef] [Green Version]
- Peters, B.; Sidney, J.; Bourne, P.; Bui, H.-H.; Buus, S.; Doh, G.; Fleri, W.; Kronenberg, M.; Kubo, R.; Lund, O. The immune epitope database and analysis resource: From vision to blueprint. PLoS Biol. 2005, 3, e91. [Google Scholar] [CrossRef] [Green Version]
- Laskowski, R.A. PDBsum: Summaries and analyses of PDB structures. Nucleic Acids Res. 2001, 29, 221–222. [Google Scholar]
- Martínez, L. Automatic identification of mobile and rigid substructures in molecular dynamics simulations and fractional structural fluctuation analysis. PLoS ONE 2015, 10, e0119264. [Google Scholar]
- Lee, B.; Richards, F.M. The interpretation of protein structures: Estimation of static accessibility. J. Mol. Biol. 1971, 55, 379–400. [Google Scholar] [CrossRef]
- Yamada, T.; Komoto, J.; Saiki, K.; Konishi, K.; Takusagawa, F. Variation of loop sequence alters stability of cytolethal distending toxin (CDT): Crystal structure of CDT from Actinobacillus actinomycetemcomitans. Protein Sci. 2006, 15, 362–372. [Google Scholar] [PubMed] [Green Version]
- Brady, L.J. Antibody-mediated immunomodulation: A strategy to improve host responses against microbial antigens. Infect. Immun. 2005, 73, 671–678. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Haghighi, M.A.; Mobarez, A.M.; Salmanian, A.H.; Moazeni, M.; Zali, M.R.; Sadeghi, M.; Amani, J. In silico experiment with an-antigen-toll like receptor-5 agonist fusion construct for immunogenic application to Helicobacter pylori. Indian J. Hum. Genet. 2013, 19, 43. [Google Scholar]
- Lon, J.R.; Bai, Y.; Zhong, B.; Cai, F.; Du, H. Prediction and evolution of B cell epitopes of surface protein in SARS-CoV-2. Virol. J. 2020, 17, 165. [Google Scholar] [CrossRef]
- Jespersen, M.C.; Peters, B.; Nielsen, M.; Marcatili, P. BepiPred-2.0: Improving sequence-based B-cell epitope prediction using conformational epitopes. Nucleic Acids Res. 2017, 45, W24–W29. [Google Scholar] [CrossRef] [Green Version]
- EL-Manzalawy, Y.; Dobbs, D.; Honavar, V. Predicting linear B-cell epitopes using string kernels. J. Mol. Recognit. Interdiscip. J. 2008, 21, 243–255. [Google Scholar]
- Potocnakova, L.; Bhide, M.; Pulzova, L.B. An introduction to B-cell epitope mapping and in silico epitope prediction. J. Immunol. Res. 2016, 2016, 6760830. [Google Scholar] [CrossRef] [Green Version]
- Barlow, D.; Edwards, M.; Thornton, J. Continuous and discontinuous protein antigenic determinants. Nature 1986, 322, 747–748. [Google Scholar] [CrossRef]
- Van Regenmortel, M.H. What is a B-cell epitope? In Epitope Mapping Protocols; Springer: Berlin/Heidelberg, Germany, 2009; pp. 3–20. [Google Scholar]
- Abdolvahab, M.H.; Venselaar, H.; Fazeli, A.; Arab, S.S.; Behmanesh, M. Point Mutation Approach to Reduce Antigenicity of Interferon Beta. Int. J. Pept. Res. Ther. 2019, 26, 1353–1361. [Google Scholar] [CrossRef]
- Ponomarenko, J.; Bui, H.-H.; Li, W.; Fusseder, N.; Bourne, P.E.; Sette, A.; Peters, B. ElliPro: A new structure-based tool for the prediction of antibody epitopes. BMC Bioinform. 2008, 9, 514. [Google Scholar] [CrossRef] [Green Version]
- Elwell, C.A.; Dreyfus, L.A. DNase I homologous residues in CdtB are critical for cytolethal distending toxin-mediated cell cycle arrest. Mol. Microbiol. 2000, 37, 952–963. [Google Scholar] [CrossRef]
- Nešić, D.; Hsu, Y.; Stebbins, C.E. Assembly and function of a bacterial genotoxin. Nature 2004, 429, 429–433. [Google Scholar] [CrossRef] [PubMed]
- Hu, X.; Nesic, D.; Stebbins, C.E. Comparative structure–function analysis of cytolethal distending toxins. Proteins Struct. Funct. Bioinform. 2006, 62, 421–434. [Google Scholar] [CrossRef]
- Nagata, S.; Pastan, I. Removal of B cell epitopes as a practical approach for reducing the immunogenicity of foreign protein-based therapeutics. Adv. Drug Deliv. Rev. 2009, 61, 977–985. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hopp, T.P.; Woods, K.R. Prediction of protein antigenic determinants from amino acid sequences. Proc. Natl. Acad. Sci. USA 1981, 78, 3824–3828. [Google Scholar] [CrossRef] [Green Version]
- Liu, W.; Onda, M.; Lee, B.; Kreitman, R.J.; Hassan, R.; Xiang, L.; Pastan, I. Recombinant immunotoxin engineered for low immunogenicity and antigenicity by identifying and silencing human B-cell epitopes. Proc. Natl. Acad. Sci. USA 2012, 109, 11782–11787. [Google Scholar]
- Ramya, L.; Pulicherla, K.K. Studies on deimmunization of antileukaemic L-asparaginase to have reduced clinical immunogenicity-an in silico approach. Pathol. Oncol. Res. 2015, 21, 909–920. [Google Scholar] [PubMed]
- Tjoa, S.E.E.; Vianney, Y.M.; Putra, S.E.D. In silico mutagenesis: Decreasing the immunogenicity of botulinum toxin type A. J. Biomol. Struct. Dyn. 2019, 37, 4767–4778. [Google Scholar]
- Kamaraj, B.; Purohit, R. In silico screening and molecular dynamics simulation of disease-associated nsSNP in TYRP1 gene and its structural consequences in OCA3. BioMed Res. Int. 2013, 2013, 697051. [Google Scholar]
- Mohammadi, M.; Rezaie, E.; Sakhteman, A.; Zarei, N. A highly potential cleavable linker for tumor targeting antibody-chemokines. J. Biomol. Struct. Dyn. 2020, 1–11. [Google Scholar] [CrossRef]
- Rezaie, E.; Mohammadi, M.; Sakhteman, A.; Bemani, P.; Ahrari, S. Application of molecular dynamics simulations to design a dual-purpose oligopeptide linker sequence for fusion proteins. J. Mol. Model. 2018, 24, 313. [Google Scholar]
- Haste Andersen, P.; Nielsen, M.; Lund, O. Prediction of residues in discontinuous B-cell epitopes using protein 3D structures. Protein Sci. 2006, 15, 2558–2567. [Google Scholar] [PubMed]
- Abraham, M.J.; Murtola, T.; Schulz, R.; Páll, S.; Smith, J.C.; Hess, B.; Lindahl, E. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 2015, 1, 19–25. [Google Scholar] [CrossRef] [Green Version]
- Berendsen, H.J.; van der Spoel, D.; van Drunen, R. GROMACS: A message-passing parallel molecular dynamics implementation. Comput. Phys. Commun. 1995, 91, 43–56. [Google Scholar] [CrossRef]
- Jorgensen, W.L.; Chandrasekhar, J.; Madura, J.D.; Impey, R.W.; Klein, M.L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 1983, 79, 926–935. [Google Scholar] [CrossRef]
- Hess, B. P-LINCS: A Parallel Linear Constraint Solver for Molecular Simulation. J. Chem. Theory Comput. 2008, 4, 116–122. [Google Scholar] [CrossRef] [PubMed]
- Parrinello, M.; Rahman, A. Polymorphic transitions in single crystals: A new molecular dynamics method. J. Appl. Phys. 1981, 52, 7182. [Google Scholar] [CrossRef]
- Hoover, W.G. Canonical dynamics: Equilibrium phase-space distributions. Phys. Rev. A 1985, 31, 1695–1697. [Google Scholar] [CrossRef] [Green Version]
- Nosé, S. A unified formulation of the constant temperature molecular dynamics methods. J. Chem. Phys. 1984, 81, 511–519. [Google Scholar] [CrossRef] [Green Version]
Residue NO. | Residue | Hydrophilicity | Surface Accessibility | IEDB Score (before Mutation) | IEDB Score (after Mutation) | Vaxijen |
---|---|---|---|---|---|---|
16 | S | 4.3 | 0.5 | 0.77 | S:V = 0.28 S:L = 0.05 S:I = 0.12 S:M = 0.19 S:F = 0.10 S:W = 0.35 S:A = 0.62 S:T = 0.73 S:H = 0.50 S:R = 0.57 S:K = 0.63 S:Q = 0.75 S:E = 0.82 S:D = 0.91 | S:V = 0.49 S:L = 0.48 S:I = 0.48 S:M = 0.48 S:F = 0.47 S:W = 0.47 S:A = 0.49 S:T = 0.50 S:H = 0.49 S:R = 0.50 S:K = 0.50 S:Q = 0.50 S:E = 0.50 S:D = 0.50 |
17 | A | 4.5 | 0.8 | 1.17 | A:L = 0.59 A:R = 1.123 | A:L = 0.51 A:R = 0.54 |
19 | N | 4.5 | 1.3 | 0.83 | N:V = 0.34 N:L = 0.11 N:I = 0.18 N:M = 0.26 N:F = 0.16 N:W = 0.41 N:Y = 0.47 N:T = 0.8 N:C = 0.28 N:R = 0.64 N:E = 0.89 ND = 0.98 | N:V =0.51 N:L = 0.50 N:I = 0.51 N:M = 0.50 N:F = 0.50 N:W = 0.49 N:Y = 0.50 N:T = 0.50 N:C = 0.49 N:R = 0.51 N:E = 0.50 ND = 0.50 |
20 | E | 2.2 | 1.3 | 0.71 | E:V = 0.17 E:L = −0.06 E:I = 0.01 E:M = 0.08 E:F = −0.009 E:W = 0.24 E:T = 0.62 E:C = 0.1 E:R = 0.46 E:D = 0.80 | E:V = 0.50 E:L = 0.49 E:I = 0.49 E:M = 0.49 E:F = 0.49 E:W = 0.47 E:T = 0.51 E:C = 0.49 E:R = 0.49 E:D = 0.49 |
47 | S | 3.0 | 0.5 | 1.23 | S:V = 0.74 S:L = 0.51 S:I = 0.58 | S:V = 0.53 S:L = 0.52 S:I = 0.52 |
52 | L | 3.2 | 0.8 | 0.62 | A:V = 0.2 A:L = 0.05 A:I = 0.1 A:F = 0.1 A:W = 0.35 E A:P = 1.13 E A:S = 0.77 E A:C = 0.21 A:R = 0.58 E | A:V = 0.52 A:L = 0.51 A:I = 0.51 A:F = 0.50 A:W = 0.50 A:P = 0.52 A:S = 0.54 A:C = 0.54 A:R = 0.54 |
74 | G | 1.34 | 1.16 | 0.53 | G:I = 0.2 | 0.51 |
75 | T | 3.3 | 1.4 | 0.50 | T:M = −0.01 T:F = −0.01 T:W = 0.13 T:Y = 0.19 T:C = −0.002 T:D = −0.70 | T:M = 0.54 T:F = 0.55 T:W = 0.54 T:Y = 0.53 T:C = 0.53 T:D = 0.51 |
77 | S | 4.9 | 4.3 | 0.7 | S:V = 0.2 S:L = −0.01 S:I = 0.05 S:M = 0.13 S:F = 0.03 S:W = 0.2 S:Y = 0.3 S:A = 0.5 E S:P = 1.04 E | S:V = 0.54 S:L = 0.54 S:I = 0.54 S:M = 0.54 S:F = 0.54 S:W = 0.53 S:Y = 0.53 S:A = 0.53 S:P = 0.53 |
160 | S | 4.1 | 1.0 | 1.27 | S:V = 0.78 S:L = 0.55 S:D = 1.42 | S:V = 0.48 S:L = 0.49 S:D = 0.47 |
161 | S | 3.7 | 1.9 | 1.57 | S:V = 1.08 S:L = 0.85 S:I = 0.92 S:F = 0.90 S:W = 1.15 S:D = 1.7 | S:V = 0.47 S:L = 0.46 S:I = 0.46 S:F = 0.45 S:W = 0.45 S:D = 0.47 |
162 | S | 5.3 | 1.82 | 1.89 | S:V = 1.40 E S:L = 1.17 E S:I = 1.24 E S:F = 1.25 E S:D = 2.03 E | S:V = 0.53 S:L = 0.52 S:I = 0.52 S:F = 0.52 S:D = 0.53 |
B Cell Epitopes (Native) | IEDB Score | VaxiJen | Mutation Positions | Alternative Amino Acids | IEDB Score | VaxiJen |
---|---|---|---|---|---|---|
LQGSSAVNESKWNINVRQLLSGE (12–34) | 1.9 | 0.88 | 19 | F | 0.78 | 0.31 |
LGTRSRPNM (73–81) | 1.2 | 0.49 | 74 | I | 1.1 | −0.31 |
SSSSPPERRVYS (160–171) | 2.51 | 0.59 | 161 | W F | 1.9 1.7 | 0.16 0.25 |
Sequences | IEDB Score | VaxiJen |
---|---|---|
Native | 2.22 | 0.53 |
Mutein 1 (N19F, G74I, and S161F) | 1.80 | 0.49 |
Mutein 2 (N19F, G74I, and S161W) | 1.88 | 0.48 |
Protein Structures | ERRAT * | Verify3D ** |
---|---|---|
Native | 95.635% | 99.23% |
Mut 1 | 86.905% | 98.85% |
Mut 2 | 90.873% | 98.85% |
Specifications | Mutein 1 (N19F, G74I, and S161F) | Mutein 2 (N19F, G74I, and S161W) |
---|---|---|
Ramachandran plot | 89.7% | 90.1% |
RMSD profile | a steady state and a considerable thermostability through the simulation period | same pattern with the native model |
RMSF factor | Less movements | more movements |
The radius of gyration (Rg) | proper structural folding | proper structural folding |
solvent- accessible surface area | The solvent accessible | The solvent accessible |
Secondary structure | Stable β-sheet structures | Changes from alpha-helix to the coil and turn in some points |
Server Name | Porpuse | Address |
---|---|---|
UniProt | Amino acid sequence | https://www.uniprot.org |
PDB | 3D structure | https://www.rcsb.org/structure/ |
VaxiJen tool | Antigen probability | www.ddg-pharmfac.net/vaxijen |
BepiPred | Linear B-cell epitopes | http://www.cbs.dtu.dk/services/BepiPred/ |
ABCpred | Linear B-cell epitopes | http://crdd.osdd.net/raghava/abcpred/ |
SVMtrip | Linear B-cell epitopes | http://sysbio.unl.edu/SVMTriP/ |
BCPred | Linear B-cell epitopes | http://ailab-projects1.ist.psu.edu:8080/bcpred/ |
DiscoTope 2.0 | Conformational B-cell epitopes | http://www.cbs.dtu.dk/services/DiscoTope/ |
ElliPro | Conformational B-cell epitopes | http://tools.iedb.org/ellipro/ |
ProBis tool | Functional residues | http://probis.cmm.ki.si/ |
PredictProtein tool | Identify enzymatic sites | https://www.predictprotein.org/ |
I-Mutant2.0 | Mutability residues | http://folding.biofold.org/i-mutant/i-mutant2.0.html |
SWISS-MODEL | 3D structure prediction with homology modeling method | https://swissmodel.expasy.org/ |
PROCHECK program | Ramachandran plot | http://servicesn.mbi.ucla.edu/PROCHECK/ |
Verify3D | Validation of 3D Models | http://services.mbi.ucla.edu/Verify_3D/ |
ERRAT | Validation of 3D Models | http://services.mbi.ucla.edu/ERRAT/ |
ProSA-web | Overall model quality | https://prosa.services.came.sbg.ac.at/prosa.php |
MD simulations | Thermodynamic stability | GROMACS simulation package, version 5.1.4 |
Immune Epitope Data Base and analysis resource (IEDB) | Antigenic B-cell epitope scores | http://tools.iedb.org/bcell |
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Keshtvarz, M.; Mahboobi, M.; Kieliszek, M.; Miecznikowski, A.; Sedighian, H.; Rezaei, M.; Haghighi, M.A.; Zareh, Z.; Rezaei, E. Engineering of Cytolethal Distending Toxin B by Its Reducing Immunogenicity and Maintaining Stability as a New Drug Candidate for Tumor Therapy; an In Silico Study. Toxins 2021, 13, 785. https://doi.org/10.3390/toxins13110785
Keshtvarz M, Mahboobi M, Kieliszek M, Miecznikowski A, Sedighian H, Rezaei M, Haghighi MA, Zareh Z, Rezaei E. Engineering of Cytolethal Distending Toxin B by Its Reducing Immunogenicity and Maintaining Stability as a New Drug Candidate for Tumor Therapy; an In Silico Study. Toxins. 2021; 13(11):785. https://doi.org/10.3390/toxins13110785
Chicago/Turabian StyleKeshtvarz, Maryam, Mahdieh Mahboobi, Marek Kieliszek, Antoni Miecznikowski, Hamid Sedighian, Milad Rezaei, Mohammad Ali Haghighi, Zahra Zareh, and Ehsan Rezaei. 2021. "Engineering of Cytolethal Distending Toxin B by Its Reducing Immunogenicity and Maintaining Stability as a New Drug Candidate for Tumor Therapy; an In Silico Study" Toxins 13, no. 11: 785. https://doi.org/10.3390/toxins13110785