Guiding Competitive Binding Assays Using Protein-Protein Interaction Prediction: The HER2-Affitin Use Case

Area of Science:

• Biochemistry
• Structural Biology
• Computational Biology

Background:

• Affitins are artificial proteins designed as alternatives to antibodies for various applications.
• Overexpression of human epidermal growth-factor receptor 2 (HER2) is linked to poor prognosis in several cancers.
• Engineered affitins have shown potential for in vivo imaging of HER2 levels.

Purpose of the Study:

• To computationally model the binding interactions of two engineered affitins with HER2.
• To identify the binding sites and understand the structural basis of affitin-HER2 interactions.
• To provide a framework for developing improved diagnostic and therapeutic strategies targeting HER2.

Main Methods:

• Protein-protein docking simulations were employed to predict affitin-HER2 complex structures.
• Molecular dynamics simulations were used to assess the stability of the predicted complexes.
• The DockQ parameter and local coupling energies were utilized to evaluate and refine docking poses.

Main Results:

• The study identified likely binding poses for the two affitins on HER2.
• Comparative analysis suggested that affitins may bind to epitopes similar to those targeted by antibody fragments and affibodies.
• The computational approach provided structural insights into affitin-HER2 interactions.

Conclusions:

• The findings provide crucial structural information for the development of HER2-targeted affitin-based imaging probes and therapeutics.
• The identified binding sites and interactions can guide the design of more effective diagnostic tools.
• The proposed computational framework is applicable to other affitin-protein systems, facilitating future research.