- İstanbul Journal of Pharmacy
- Vol: 52 Issue: 3
- Comparative assessment of different nanobodies that inhibit the interaction of B7-1/2 with CD28 as a...
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
Authors : Halil İbrahim BULUT, Nail BEŞLİ, Güven YENMİŞ
Pages : 289-296
Doi:10.26650/IstanbulJPharm.2022.1058189
View : 9 | Download : 3
Publication Date : 2022-12-30
Article Type : Research
Abstract :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 immunosuppressive Methods: 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