Antibody Engineering to Enhancement of Ranibizumab Binding Affinity for the Prevention and Treatment of Diabetic Retinopathy

Abstract

Objective: The VEGF function blockage effectively reduces the progression of diabetic retinopathy. Ranibizumab and bevacizumab are some anti-VEGF monoclonal antibodies (mAb). Considering the importance of affinity maturation of ranibizumab, we aimed to find the essential amino acids of the ranibizumab antibody (Ab). Materials and Methods: We tried to find the important amino acids of this antibody via Paratome, Meta-PPISP, and the WESA web server. Subsequently, these amino acids were mutated to improve the binding affinity of the Ab variants to antigen (Ag). In this regard, the ranibizumab anti-VEGF-A was mutated. The structural docking prediction of the ranibizumab-VEGF-A complex was used for the design and validation of ranibizumab with a higher affinity for binding to VEGF-A. Finally, we measured the binding affinity of Ab variants to Ag by computational docking. Results: Bioinformatic analyzes such as molecular docking and dynamics showed that several mutant variants successfully improved the properties of Ab binding compared to the wild-type Ab. Conclusion: Consistent with the use of anti-VEGF monoclonal antibodies in the treatment of diabetic retinopathy, the mutant variants of ranibizumab may be potential candidates for stronger affinity binding to VEGF, which may affect the specificity and sensitivity of the antibody.

Keywords

• antibody engineering
• anti-vegf-a
• bioinformatic
• binding affinity
• ranibizumab