Abstract
Human epidermal growth factor receptor 2 (HER2) contributes to the development of breast cancers and malignancies. On the other hand, engineered affibody Z(HER2:342) that binds to HER2 can be successfully used for both diagnostic purposes and specific ablation of malignant HER2-positive cell lines. In the current study, electrostatics-based prediction was applied for improving Z(HER2:342) binding affinity using computational design. The affibody Z(HER2:342) alone and in complex with HER2 was energetically minimized, solvated in explicit water, and neutralized. After heating and equilibration steps, the system was studied by isothermal-isobaric (NPT) MD simulation. According to trajectories, Z(HER2:342) specifically binds to HER2 through hydrogen bonds and salt bridges. Based on the electrostatic binding contributions, two affinity-matured variants namely V1 (Tyr35Arg) and V2 (Asn6Asp and Met9Glu) were rationally designed. More investigations through MD simulation show that V1 interacts with HER2 receptor more strongly, compared to Z(HER2:342) and V2.
Acknowledgment
The authors are grateful to School of Computer Science, Institute for Research in Fundamental Science (IPM), Tehran, Iran, for professional technical assistance.