Molecular dynamics simulations along with the synthesis of innovative engineered nanobodies targeting Interleukin-2

Interleukin-2 (IL-2) is an essential cytokine that plays a significant role in the immune response. The use of anti-IL-2 antibodies to inhibit IL-2 may help mitigate the excessive immune response observed in conditions such as lupus, rheumatoid arthritis, and multiple sclerosis. Single-domain VHH antibodies (nanobodies) offer advantages over traditional antibodies, including their small size, enhanced thermal stability, reduced immunogenicity, superior tissue penetration, and cost-effective production. Consequently, nanobodies have become a promising approach for the diagnosis and treatment of diseases.

We employed a structure-guided complementarity-determining region (CDR) grafting approach to design two anti-IL-2 nanobodies, denoted Nb-IL2-01 (derived from 7DR4) and Nb-IL2-02 (derived from 6YE3), by transplanting CDRs from established monoclonal antibodies into a nanobody framework. Molecular dynamics simulations were used to assess the predicted structural stability of the designed constructs and their potential molecular interactions with IL-2. Following expression in E. coli and purification, the capacity of the designed nanobodies to bind immobilized IL-2 was evaluated by enzyme-linked immunosorbent assay (ELISA). Molecular dynamics simulations predicted that the Nb-IL2-02/IL-2 complex would exhibit greater conformational stability than the Nb-IL2-01/IL-2 complex. Experimentally, both nanobodies demonstrated specific, concentration-dependent binding to IL-2 in ELISA, confirming that the designed constructs possess antigen-binding functionality.

We successfully generated IL-2-binding nanobody constructs using a CDR grafting-based design approach. The integration of computational design with experimental characterization demonstrates a feasible pipeline for developing functional single-domain binders against therapeutic targets. The specific binding of the designed nanobodies supports their potential as candidates for further development and optimization.