Part:BBa_K5271003

HER2-binding peptide -scrambled

A scrambled amino acid sequence that acts as a control for the HER2 binding region of the dual targeting nanobody -Panobody.

Profile

• Name: HER2-binding peptide -scrambled
• Base Pairs: 345 bp
• Amino acid: 115 a.a
• Origin: Synthetic
• Properties: A scrambled control for the dual targeting nanobody -Panobody.

Usage and Biology

The design of this basic part began with an in-house bioinformatics analysis. Based on the dry lab result, we chose EGFR and HER2 as the dual targets for our Biobrick design. We created a dual targeting nanobody -Panobody for EGFR and HER2. To verify our design, we used Alphafold to create a three-dimensional model of Panobody and its scrambled control, Panobody-scrambled. [Jumper et al., 2021] Subsequently, we perform a molecular docking analysis to examine the binding affinity of the scrambled control.

The molecular docking analysis of Panobody- scrambled revealed a less extensive and intricate binding network. The scrambled HER2 binding region of Panobody- scrambled interacts with significant residues of the HER2 receptor, such as Lys765, Thr759, and Ash838, forming key hydrogen bonds and salt bridges and π-π stacking interactions, with Tyr835 playing a stabilizing role (Fig. 1a). However, the overall interaction network was less comprehensive than that observed for the Panobody.

Figure 1. (a) 3D and 2D visualizations of molecular docking between the HER2 binding region of Panobody -scrambled the HER2 receptor. (b) 3D and 2D visualizations of molecular docking between the EGFR binding region of Panobody -scrambled and the EGFR receptor.

Design Note

Our preliminary results when it is joined with the EGFR nanobody by a linker, the linker should avoid cysteine residues since it potentially reduces the solubility of the dual targeting nanobody in prokaryotic expression system.

Source

The sequence of the HER2-binding peptide -scrambled was randomly generated and had a same length with the HER2 binding region of Panobody.

Reference

• Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., ... & Hassabis, D. (2021). Highly accurate protein structure prediction with AlphaFold. nature, 596(7873), 583-589.

Sequence and Features

Assembly Compatibility:

• 10
  COMPATIBLE WITH RFC[10]
• 12
  COMPATIBLE WITH RFC[12]
• 21
  COMPATIBLE WITH RFC[21]
• 23
  COMPATIBLE WITH RFC[23]
• 25
  COMPATIBLE WITH RFC[25]
• 1000
  COMPATIBLE WITH RFC[1000]