Mutation of Enzyme Active Pocket Based on Structural Homology and Molecular Docking Results
To directly enhance the catalytic activity of the 05PET enzyme, we first utilized structural homology and molecular docking to locate its active pocket, then selected hotspot amino acids, performed mutations, and finally conducted wet experimental validation.
First, we performed molecular docking between the 05PET enzyme and the trimeric long-chain PET molecule using AutoDock Vina[1]. Unexpectedly, among multiple docking conformations, we did not identify fixed and groove-like binding sites.
Therefore, by comparing with the structure of LCC[2], we excluded some regions of non-active pockets and redock.
As shown in the figure, the left panel depicts the predicted structure of 05PET (generated by AlphaFold 3), while the right panel illustrates the crystal structure of LCC. The two structures are similar: the β-sheets are situated among multiple α-helices, and the central β-sheets all orient toward the same direction, which point to the notch-shaped enzyme active pocket located on the left part of the figure.
Setting off from this, we defined more reliable docking regions, re-performed molecular docking, and gained the following enzyme pocket interaction results.
Docking results from AutoDock Vina showed that PHE215, HIS214, SER134, ILE186, THR66, GLY65, THR67, TYR73, and ASP184 are amino acid residues that closely interact with the PET substrate, with SER134-HIS214-ASP184 forming its catalytic triad. Considering the active pocket in a spatial context, the amino acids of the active pocket include G54, T55, T56, A57, T62, S124, F145, Q146, Y148, L162, D174, I176, H204, F205, V208, and G209, as shown in the second figure above. Since there are additional sites capable of docking with the PET molecule at exterior region out of active pocket, the zone was appropriately expanded, yielding the first figure above, which was chosen as the structure for modification.
Inspired by evolution, after selecting the sequence sites corresponding to the spatial region, we used the 05PET enzyme as the basis and designed mutations based on the sequences of other PET enzymes, ultimately determining the following single-point mutation schemes:
G55A
T56A T56Y T56F
T57A
T58G
T62S T62A
Y63I Y63L Y63A
H123A H123W
S124A
Q125M Q125A
Y148A Y148W
I150A I150T I150L I150S
G151A
G152A
D174A
I186A I186V
L199A L199I
S200N S200A S200D S200R
G201A G201N
A202G
S203A S203T
H204A
F205A F205L F205S
E206A E206C E206V
V208N V208A
G209A G209I G209T G209S
S210A S210N S210G S210P
A211N A211D
G212A G212T G212K G212S
D213A D213I D213N D213T
D234A
D242A
D246A
D248A D248E
References
1. Eberhardt, J., Santos-Martins, D., Tillack, A. F., & Forli, S. (2021). AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings. Journal of chemical information and modeling, 61(8), 3891–3898. https://doi.org/10.1021/acs.jcim.1c00203 ↑ go back
2. Sulaiman, S., Yamato, S., Kanaya, E., Kim, J. J., Koga, Y., Takano, K., & Kanaya, S. (2012). Isolation of a novel cutinase homolog with polyethylene terephthalate-degrading activity from leaf-branch compost by using a metagenomic approach. Applied and environmental microbiology, 78(5), 1556–1562. https://doi.org/10.1128/AEM.06725-11 https://doi.org/10.1128/AEM.06725-11 ↑ go back