Myasthenia Gravis is an autoimmune neuromuscular disorder primarily caused by IgG1 and IgG3 autoantibodies that target the AChR at the neuromuscular junction, impairing muscle activation and causing weakness through antibody blocking, antigenic modulation, and complement activation. The α1-subunit of AChR, particularly its Main Immunogenic Region (MIR), is the primary site recognized by IgG1.

In-silico modeling was conducted using Schrödinger Suite (BioLuminate, Maestro). Protein-protein interactions between AChR and IgG1 (PDB: 5HBT), were analyzed to identify key residue interactions. Residue scanning was performed to predict beneficial mutations enhancing stability and Prime-MMGBSA calculations were used to evaluate the binding free energies of the engineered decoys.

Protein interaction analysis (PIA) revealed key interactions on residues 30-39 and 8-10 inclusively on the AChR receptor. The results from PIA were carried forward for the residue scanning calculations to identify multiple α1-subunit fragments that could be mutated and truncated into smaller engineered Pepenzymes (Peptide nano enzymes). Prime-MMGBSA (Molecular Mechanics Generalized Born Surface Area) calculations showed that specific mutated Pepenzymes significantly lowered binding free energy, suggesting stronger and more stable antibody interactions compared to native AChR. The mutants that showed significant improvement in the MMGBSA scores were 71F (-46.55 kcal/mol) and 70T (-45.78 kcal/mol)  compared to the WT (-29.36 kcal/mol). Structural visualization confirmed that these designed decoys preserved critical epitope structural elements.

This study demonstrates that computationally designed nanobody decoys can mimic the AChR α1-subunit and preferentially bind to pathogenic IgG1 autoantibodies, as the decoy had ~1.5x the binding free energy compared to the wild type. By diverting antibody activity away from native receptors, this approach offers a targeted, non-immunosuppressive therapeutic strategy for Myasthenia Gravis.