| Title | Deep learning guided enzyme engineering of Thermobifida fusca cutinase for increased PET depolymerization |
|---|---|
| ID_Doc | 6541 |
| Authors | Meng, SQ; Li, ZY; Zhang, P; Contreras, F; Ji, Y; Schwaneberg, U |
| Title | Deep learning guided enzyme engineering of Thermobifida fusca cutinase for increased PET depolymerization |
| Year | 2023 |
| Published | |
| Abstract | A responsible and sustainable circular economy of polymers requires efficient recycling processes with a low CO2 footprint. Enzymatic depolymerization of polyethylene terephthalate (PET) is a first step to make PET polymers a part of a circular economy of polymers. In this study, a structure-based deep learning model was utilized to identify residues in TfCut2 that are responsible for improved hydrolytic activity and enhanced stability. Machine learning guided design identified novel beneficial positions (L32E, S35E, H77Y, R110L, S113E, T237Q, R245Q, and E253H), which were evaluated and stepwise recombined yielding finally the beneficial variant L32E/S113E/T237Q. The latter TfCut2 variant exhibited improved PET depolymerization when compared with TfCut2 WT (amorphous PET film, 2.9-fold improvement // crystalline PET powder (crystallinity > 40%), 5.3-fold improvement). In terms of thermal resistance the variant L32E/S113E/T237Q showed a 5.7 degrees C increased half-inactivation temperature (T-50(60)). The PET-hydrolysis process was monitored via a quartz crystal microbalance with dissipation monitoring (QCM-D) in real-time to determine depolymerization kinetics of PET coated onto the gold sensor. Finally, conformational dynamics analysis revealed that the substitutions induced a conformational change in the variant L32E/S113E/T237Q, in which the dominant conformation enabled a closer contact between the catalytic site and PET resulting in increased PET-hydrolysis. Overall, this study demonstrates the potential of deep learning models in protein engineering for identifying and designing efficient PET depolymerization enzymes. (c) 2023, Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved. |
| https://www.cjcatal.com/EN/article/downloadArticleFile.do?attachType=PDF&id=29457 |
Similar Articles
| ID | Score | Article |
|---|---|---|
8221
|
Shi, LX; Zhu, LL Recent Advances and Challenges in Enzymatic Depolymerization and Recycling of PET Wastes(2024)Chembiochem, 25.0, 2 | |
| 15009
|
Jayasekara, SK; Joni, HD; Jayantha, B; Dissanayake, L; Mandrell, C; Sinharage, MMS; Molitor, R; Jayasekara, T; Sivakumar, P; Jayakody, LN Trends in in-silico guided engineering of efficient polyethylene terephthalate (PET) hydrolyzing enzymes to enable bio-recycling and upcycling of PET(2023) | |
| 8160
|
Patel, SKS; Lee, JK Plastic Eating Enzymes: A Step Towards Sustainability(2022)Indian Journal Of Microbiology, 62.0, 4 | |
| 29433
|
Zheng, Y; Li, QB; Liu, P; Yuan, YB; Dian, LY; Wang, Q; Liang, QF; Su, TY; Qi, QS Dynamic Docking-Assisted Engineering of Hydrolases for Efficient PET Depolymerization(2024)Acs Catalysis, 14.0, 5 | |
| 10754
|
Bååth, JA; Novy, V; Carneiro, LV; Guebitz, GM; Olsson, L; Westh, P; Ribitsch, D Structure-function analysis of two closely related cutinases from Thermobifida cellulosilytica(2022)Biotechnology And Bioengineering, 119, 2 | |
| 13748
|
Sui, BB; Wang, T; Fang, JX; Hou, ZX; Shu, T; Lu, ZH; Liu, F; Zhu, YS Recent advances in the biodegradation of polyethylene terephthalate with cutinase-like enzymes(2023) | |
| 10353
|
Lens-Pechakova, LS Recent studies on enzyme-catalysed recycling and biodegradation of synthetic polymers(2021)Advanced Industrial And Engineering Polymer Research, 4, 3 |