Part:BBa_K5291050

PE-binding peptide

Plastic-binding peptides are adsorbed to the plastic surface by hydrogen bonding and other intermolecular forces. Considering that PE-binding peptides（PEBP） has not been extensively studied and we did not find the sequence of PEBP in the paper, we decided to predict PEBP sequence by modeling method. We performed machine learning training; then performed special processing and tried to introduce neural networks. Finally, several predictors were given.

Usage and Biology

In degradation module we constructed pAB1-pS-PEBP-PEase aand pAB1-PEBP-GFP to depolymerize PE microplastics and verify the adsorption capacity of PEBP to PE by fluorescence microscopy.

If you want to know more details, please refer to BBa_K5291051BBa_K5291052.

Experiment result: A PEBP-GFP fusion protein was contructed,expressed and purified. A (G₄S)linker was added between the GFP and the PEBP. We co-incubated the PEBP-GFP with 5mm PE microplastics. Control group co-incubated with GFP protein and blank group was also setted.

After being immersed in PBS and cleaned twice by the vortex shaker, the microplastics incubated with PEBP-GFP still generally showed obvious fluorescence. The microplastics incubated with GFP can see weak fluorescence of GFP residue after intense exposure, while the blank group can not see any fluorescence under the fluorescence microscope. It can be concluded that PEBP has strong binding ability with microplastics.

Structure prediction was also conducted. Since the structure of PEBP (polyethylene-binding peptide) is unknown, we used AlphaFold2 (AF2), a powerful deep learning model, along with ChimeraX for visualization and ColabFold for structure prediction. We obtained the PEBP amino acid sequence in a FASTA file, entered it into the AlphaFold panel in ChimeraX, and selected options for energy minimization, structure alignment, and using PDB templates for enhanced accuracy. Despite the longer processing time, these settings allowed for more accurate 3D predictions of the PEBP structure, generated through Google's ColabFold environment. The relevant predictions are as follows:

Next, we need to know the spatial structure of PE(polyethylene). We used Avogadro for drawing and obtaining pdb files for subsequent molecular docking. The result is shown as figure.

We also used alpha fold3 to predict the structure of the PEBP-PEase fusion protein.

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]