Chinese Journal of Catalysis ›› 2023, Vol. 50: 229-238.DOI: 10.1016/S1872-2067(23)64470-5
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Shuaiqi Menga,1, Zhongyu Lib,1, Peng Zhanga, Francisca Contrerasa, Yu Jia,*(), Ulrich Schwaneberga,c,*()
Received:
2023-03-16
Accepted:
2023-06-15
Online:
2023-07-18
Published:
2023-07-25
Contact:
*E-mail: About author:
1 These authors contributed equally to this work.
Supported by:
Shuaiqi Meng, Zhongyu Li, Peng Zhang, Francisca Contreras, Yu Ji, Ulrich Schwaneberg. Deep learning guided enzyme engineering of Thermobifida fusca cutinase for increased PET depolymerization[J]. Chinese Journal of Catalysis, 2023, 50: 229-238.
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URL: https://www.cjcatal.com/EN/10.1016/S1872-2067(23)64470-5
Fig. 1. The deep-learning-based prediction for performance enhancement of TfCut2 based on the Mutcompute methodology. (a) Within the Mutcompute methodology [14] the local environment of TfCut2 was firstly analyzed based on its crystal structure. After extracting the features of the microenvironment, the data is sent to a series of convolution and pooling layers, and then proceed by fully connected layers. As the outputs, each amino acid was assigned a probability that reflecting the chemical congruency. Top ten ranked substitutions were experimentally generated by site-directed mutagenesis. (b) Shows the positions at which the beneficial substitutions are predicted. The catalytic trial of TfCut2 is shown in orange stick, and the selected positions were shown in cyan stick.
Fig. 2. The enzymatic depolymerization efficiency of PET (nanoparticles, film, and powders) by TfCut2 variants. (a) Enzyme activity of TfCut2 variants towards PET nanoparticles (size < 100 nm, amorphous). The depolymerization products were qualitied by absorbance measurement on 240 nm. All formed products (TPA, MHET, and BHET) were considered as TPA and quantified using the TPA standard curve. (b) Enzyme activity of TfCut2 variants towards PET film (0.25 mm thickness, amorphous, from Goodfellow) at 65 and 70 °C. The products were identified and quantified by HPLC analysis. (c) Enzyme activity of TfCut2 variant towards PET powders (crystallinity > 40%, maximum particle size: 300 microns, from Goodfellow). The products were identified and quantified by HPLC analysis.
TfCut2 variants | Tm (°C) | T5060 (°C) |
---|---|---|
WT | 72.8 | 64.8 |
L32E/H77Y | 74.3 | 70.4 |
L32E/R110L | 72.3 | 70.6 |
L32E/S113E | 74.2 | 67.3 |
L32E/H77Y/R110L | 74.5 | 68.9 |
L32E/S113E/T237Q | 72.2 | 70.5 |
Table 1 The melting temperatures (Tm) and half-inactivation temperatures (T5060) of TfCut2 variants. The Tm values were determined by Prometheus NT.48 (NanoTemper Technologies GmbH, München, Germany). The Tm of TfCut2 enzymes was measured on the heating ramp trace as the midpoint value at half-height. The T5060 was measured by residual activity measurements against pNPB, and was determined at half of the maximum activity.
TfCut2 variants | Tm (°C) | T5060 (°C) |
---|---|---|
WT | 72.8 | 64.8 |
L32E/H77Y | 74.3 | 70.4 |
L32E/R110L | 72.3 | 70.6 |
L32E/S113E | 74.2 | 67.3 |
L32E/H77Y/R110L | 74.5 | 68.9 |
L32E/S113E/T237Q | 72.2 | 70.5 |
Fig. 3. The conformation dynamics of TfCut2 WT (a) and variant L32E/S113E/T237Q (b). Both two enzymes contain three metastable states. The percentage represents the equilibrium probability of the corresponding state. The arrows thickness represents the transition probability between each metastable, and the corresponding time on arrows indicates the transition time between metastable states. The zoom view showed the conformation of substrate PET2mer and the catalytic triad (S130, D176, H208).
Fig. 4. The substrate binding mode in the dominant conformation of TfCut2 WT (a) and variant L32E/S113E/T237Q (b). The left figure shown the substrate configuration in the TfCut2 enzyme, in which the residue S130 was shown in red. The right Fig. shown the enzyme-ligand interactions, in which the brick red spoked arcs represent the residues involved in hydrophobic interactions, and the green dotted lines indicate the hydrogen bond.
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