Binding affinity optimization and structural evaluation of designed antibodies against PD-1 and PD-L1 as critical immune checkpoints involved in cancer treatment

Abstract

Abstract Cancer control and treatment remain a significant challenge in cancer therapy and recently immune checkpoints has considered as a novel treatment strategy to develop anti-cancer drugs. Many cancer types use the immune checkpoints and its ligand, PD-1/PD-L1 pathway, to evade detection and destruction by the immune system, which is associated with altered effector function of PD-1 and PD-L1 overexpression on cancer cells to deactivate T cells. In recent years, mAbs have been employed to block immune checkpoints, therefore normalization of the anti-tumor response has enabled the scientists to develop novel biopharmaceuticals. In vivo antibody affinity maturation in targeted therapy has sometimes been failed and highlight the importance of in silico design methods in this area. Here, we used the in silico methods to design improved mAbs with high affinity for PD-1 and PD-L1. At first, using the RosettaDesign protocol, thousands of antibodies have been generated for 11 different regions on PD-1 and PD-L1 and then the designs with higher stability, affinity, and shape complementarity were selected. We obtained high affinity antibodies with success rates of 33.2% and 30.6% for PD-1 and PD-L1. Then, MD simulation and MM-PBSA techniques were used to understand the dynamic, structural features of the complexes, measure the stability and binding affinity of the final designs. This study provides comprehensive information regarding the potential binding epitopes on PD-1 which could be considered as hotspots for designing potential biopharmaceuticals. We also showed that mutations in the CDRs regions will rearrange the interaction pattern between the designed antibodies and targets (PD-1 and PD-L1) with improved affinity to effectively inhibit protein-protein interaction and block the immune checkpoint.