Coding

Part:BBa_K5175002:Design

Designed by: Zhengdong Wu   Group: iGEM24_HUST-China   (2024-09-29)


PETase-G4S-MHETase


Assembly Compatibility:
  • 10
    INCOMPATIBLE WITH RFC[10]
    Illegal PstI site found at 1536
    Illegal PstI site found at 1879
  • 12
    INCOMPATIBLE WITH RFC[12]
    Illegal PstI site found at 1536
    Illegal PstI site found at 1879
  • 21
    INCOMPATIBLE WITH RFC[21]
    Illegal BamHI site found at 1419
    Illegal XhoI site found at 2677
  • 23
    INCOMPATIBLE WITH RFC[23]
    Illegal PstI site found at 1536
    Illegal PstI site found at 1879
  • 25
    INCOMPATIBLE WITH RFC[25]
    Illegal PstI site found at 1536
    Illegal PstI site found at 1879
    Illegal NgoMIV site found at 57
    Illegal NgoMIV site found at 1218
    Illegal NgoMIV site found at 1606
    Illegal NgoMIV site found at 1969
  • 1000
    COMPATIBLE WITH RFC[1000]


Design Notes

FAST-PETase and MHETase are introduced to degrade PET polymers into the monomers TPA and EG.
FAST-PETase is a machine-learning obtained PETase with properties suitable for in situ PET degradation at mild temperatures and moderate pH conditions.And the main product of PETase degradation is MHET.
And the MHET intermediate tends to bind tightly to PET degrading enzyme in a non-catalytic pose, which leads to the inhibition of PET degrading enzyme.
An efficient MHET hydrolase is needed to degrade the intermediate product in time to further depolymerise MHET into its monomers TPA and EG.
Multi-enzyme systems promote substrate channeling and proximity effects between enzymes. This greatly reduces the diffusion limitation between enzyme active centers, thus promoting enzyme synergy and improving catalytic efficiency.

Source

Ideonella sakaiensis 201-F6

References

[1] YOSHIDA S, HIRAGA K, TAKEHANA T, et al. A bacterium that degrades and assimilates poly(ethylene terephthalate) [J]. Science, 2016, 351(6278): 1196-9.
[2] LU H, DIAZ D J, CZARNECKI N J, et al. Machine learning-aided engineering of hydrolases for PET depolymerization [J]. Nature, 2022, 604(7907): 662-7.
[3] ZHANG J, WANG H, LUO Z, et al. Computational design of highly efficient thermostable MHET hydrolases and dual enzyme system for PET recycling [J]. Communications Biology, 2023, 6(1): 1135.
[4] ZHANG Y, HESS H. Toward Rational Design of High-efficiency Enzyme Cascades [J]. ACS Catalysis, 2017, 7(9): 6018-27.