Halil İbrahim BULUT, Nail BEŞLİ, Güven YENMİŞ

Comparative assessment of different nanobodies that inhibit the interaction of B7-1/2 with CD28 as a potential therapeutic target for immune-related diseases by molecular modeling

Background and Aims: Active T cells are central players in the self-defense system as well as in immune-related diseases. Being crucial for T cell activation, the interaction of B7-1/2 with CD28 is associated with T cell activation-related diseases such as alloreactivity in transplantation and autoreactivity in autoimmune disorders. Nanobodies are the recombinant vari- able and single-domain smallest antigen-binding fragments. The focus of this study is to investigate the interactions be- tween B7-1/2 and eight antibodies at the molecular level utilizing computational methods, and to guide the best nanobody for in-vitro and in-vivo studies about immunosuppressiveMethods: After receiving the 3D models of agents via Robetta, molecular docking techniques were used to compare the bind- ing modes and affinities of six nanobodies and two FDA-approved fusion protein models against B7-1/2(CD80/CD86).Results: According to our in silico outputs, we selected the top of model clusters from HADDOCK 2.4 (Z-Score of CD80/CD86:- 2.7 to -1.3/-2.1 to -2.1) and distinguished that 1A1 and 1B2 have higher affinities than Belatacept and Abatacept for the percentage of a calculation scale.Conclusion: Our findings suggest that selected nanobodies show higher affinity by interacting with the CD80/86 epitope regions and provide helpful insights into the design and improvement of further computational investigations of nanobody modeling.

Keywords:

Immunosuppression, Immune-related diseases Nanobody, B7 Antigens, Molecular modeling,

PDF

___

Abbas, A. K., Lichtman, A. H., & Pillai, S. (2019). Basic immunology e-book: Functions and disorders of the immune system. Amsterdam, Netherlands: Elsevier Health Sciences.
Ansari, A. W., Khan, M. A., Schmidt, R. E., & Broering, D. C. (2017). Harnessing the immunotherapeutic potential of T-lymphocyte co-signaling molecules in transplantation. Immunology Letters, 183, 8–16.
Crepeau, R. L., & Ford, M. L. (2017). Challenges and opportuni- ties in targeting the CD28/CTLA-4 pathway in transplantation and autoimmunity. Expert Opinion on Biological Therapy, 17(8), 1001–1012.
Goronzy, J. J., & Weyand, C. M. (2008). T-cell co-stimulatory path- ways in autoimmunity. Arthritis Research & Therapy, 10(1), 1–10.
Green, J. M., Noel, P. J., Sperling, A. I., Walunas, T. L., Gray, G. S., Blue- stone, J. A., & Thompson, C. B. (1994). Absence of B7-dependent responses in CD28-deficient mice. Immunity, 1(6), 501–508.
Janeway, C. A. J., Travers, P., Walport, M., & Shlomchik, M. J. (2001). Immunopiology: the immune system in health and disease. 5” ed. New York.
Jovčevska, I., & Muyldermans, S. (2020). The therapeutic potential of nanobodies. BioDrugs, 34(1), 11–26.
Khan, U., & Ghazanfar, H. (2018). T lymphocytes and autoimmuni- ty. International Review of Cell and Molecular Biology, 341, 125–168.
Krupa Pawełand Spodzieja, M., & Sieradzan, A. K. (2021). Predic- tion of CD28-CD86 protein complex structure using different level of resolution approach. Journal of Molecular Graphics and Modelling, 103, 107802.
Larsen, C. P., Pearson, T. C., Adams, A. B., Tso, P., Shirasugi, N., Strob- ert, M. E., ... Peach, R. J. (2005). Rational development of LEA29Y (belatacept), a high‐affinity variant of CTLA4‐Ig with potent im- munosuppressive properties. American Journal of Transplanta- tion, 5(3), 443-453.
Leem, J., Dunbar, J., Georges, G., Shi, J., & Deane, C. M. (2016). A Body Builder: Automated antibody structure prediction with data--driven accuracy estimation. MAbs, 8(7), 1259–1268.
Mifsud, N. A., Illing, P. T., Lai, J. W., Fettke, H., Hensen, L., Huang, Z.,... & Purcell, A. W. (2021). Carbamazepine induces focused T cell responses in resolved Stevens-Johnson syndrome and toxic epi- dermal necrolysis cases but does not perturb the immunopepti- dome for T cell recognition. Frontiers in Immunology, 12, 653710.
Noble, J., Jouve, T., Janbon, B., Rostaing, L., & Malvezzi, P. (2019). Belatacept in kidney transplantation and its limitations. Expert Re- view of Clinical Immunology, 15(4), 359–367.
Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Green- blatt, D. M., Meng, E. C., & Ferrin, T. E. (2004). UCSF Chimera—a visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605–1612.
Ramagopal, U. A., Liu, W., Garrett-Thomson, S. C., Bonanno, J. B., Yan, Q., Srinivasan, M., ... Almo, S. C. (2017). Structural basis for can- cer immunotherapy by the first-in-class checkpoint inhibitor ipili- mumab. Proceedings of the National Academy of Sciences, 114(21), E4223-E4232.
Raman, S., Vernon, R., Thompson, J., Tyka, M., Sadreyev, R., Pei, J. & Baker, D. (2009). Structure prediction for CASP8 with all‐atom refinement using Rosetta. Proteins: Structure, Function, and Bioin- formatics, 77(S9), 89-99.
Schrodinger, LLC. (2015). The {PyMOL} Molecular Graphics Sys- tem, Version~1.8.
Siontorou, C. G. (2013). Nanobodies as novel agents for disease diagnosis and therapy. International Journal of Nanomedicine, 8, 4215.
Song, Y., DiMaio, F., Wang, R. Y.-R., Kim, D., Miles, C., Brunette, T. J., Thompson, J., & Baker, D. (2013). High-resolution comparative modeling with Rosetta CM. Structure, 21(10), 1735–1742.
Sun, S., Ding, Z., Yang, X., Zhao, X., Zhao, M., Gao, L., ... Lu, X. (2021).
Nanobody: a small antibody with big implications for tumor ther- apeutic strategy. International Journal of Nanomedicine, 16, 2337.
Van Balen, P., Kester, M. G., de Klerk, W., Crivello, P., Arrieta-Bolanos, E., de Ru, A. H., ... Falkenburg, J. F. (2020). Immunopeptidome analysis of HLA-DPB1 allelic variants reveals new functional hier- archies. The Journal of Immunology, 204(12), 3273-3282.
Vita, R., Zarebski, L., Greenbaum, J. A., Emami, H., & Hoof, I. (2012). Immune Epitope Database and Analysis Resource.
Waterhouse, A. M., Procter, J. B., Martin, D. M. A., Clamp, M., & Barton, G. J. (2009). Jalview Version 2—a multiple sequence alignment editor and analysis workbench. Bioinformatics, 25(9), 1189–1191.
Waterhouse, A., Bertoni, M., Bienert, S., Studer, G., Tauriello, G., Gumienny, R., ... Schwede, T. (2018). SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic acids re- search, 46(W1), W296-W303.
Weitzner, B. D., Jeliazkov, J. R., Lyskov, S., Marze, N., Kuroda, D., Frick, R., ... Gray, J. J. (2017). Modeling and docking of antibody struc- tures with Rosetta. Nature protocols, 12(2), 401-416.