Contributions
Part 1 Machine learning
To improve the stability and acid-base tolerance of plastic-degrading enzymes, we used the machine learning tool MutCompute for mutation prediction of enzymes. The tool analyzes protein structures using a 3D self-supervised convolutional neural network to identify amino acid sites that do not match the chemical environment. Through virtual mutation scanning, we performed comprehensive mutation prediction for IsPETasePA and FAST-PETase-217/277, screening several potential mutation sites. Combined with glycosylation sites, S29A, T59S, T122P, N183A of IsPETasePA and N212D, S223T, S92E, S169A, N190D of FAST-PETase-217/277 were finally identified as optimal mutation sites.Subsequently, we verified the validity of some of the above mutation sites and their enhancement of degradation rate and efficiency by wet experiments and molecular docking.It provides an innovative direction for future modifications in terms of iGEM and plastic-degrading enzymes, and it is hoped that the accuracy of the machine-learning algorithm can be continuously improved and upgraded in the future, which will in turn lead to finding more efficient and accurate plastic-degrading enzymes.
Part 2 Molecular docking
In order to verify whether our mutation sites are truly optimal, we employed Autodock to dock PET, HEMT, and BHET with our screened mutant enzymes and analyzed the overall analysis in terms of binding energy, root-mean-square deviation (RMSD), number and length of hydrogen bonds, and validation of wet experiments, and came to the conclusion that the enzymes based on the screened mutations do indeed play a role in enhancing the stability, heat resistance, and acid/base resistance of the plastics degradation enzyme stability, heat resistance and acid/base tolerance.
SUPERB hopes that the molecular docking we used will be an effective aid and validation tool for teams working on plastic-degrading enzyme mutation and enzyme metabolism as their main topics.
Part 3 Plastics degradation
SUPERB has developed a highly efficient plastic-degrading enzyme, the IsPETase PA mutant T122P,. Under optimal conditions ,40°C and pH 9.0, T122P, maintained its highest enzyme activity, achieving a 130% increase compared to IsPETase PA . Notably, under acidic conditions ,30°C and pH 6.0, the enzyme activity increased by 475.1%, significantly enhancing its plastic degradation capabilities in acidic environments. Furthermore, under neutral conditions ,30°C and pH 7.0, its enzyme activity improved by 66%, demonstrating its potential in applications such as bacterial cellulose production. The results indicate that the mutant enzyme exhibits significantly improved acid-alkali tolerance and enhanced activity, providing a solid foundation for broader research and applications. This study offers valuable insights for optimizing enzyme performance and enhancing plastic degradation efficiency. It establishes a robust foundation for exploring the adaptability of plastic-degrading enzymes under various environmental conditions. SUPERB’s findings deepen the understanding of enzyme activity regulation and provide strong support for industrial-scale applications. This innovation makes a significant contribution to advancing plastic waste treatment technologies and offers practical solutions for addressing global plastic pollution challenges.
Part 4 Product Recovery
SUPERB has pioneered an innovative approach to recycling plastic waste by efficiently converting PET degradation products, ethylene glycol (EG) and terephthalic acid (TPA), into bacterial cellulose (BC). The study revealed that under medium BMMY at pH 6.0 or pH 7.0, the yield of BC in fermentation broth containing both PET degradation products and enzymes increased by 25% and 11%, respectively, compared to the broth containing only enzymes. This research provides a crucial foundation for the further exploration of bacterial cellulose applications across various industrial fields. It also establishes a solid theoretical and technological basis for optimizing the conversion process, improving conversion efficiency, and achieving industrial-scale applications.
Part 5 Software tools
This experiment developed a calculation service software named “ratio calculator”, which is mainly designed to provide calculation service for experimenters in the process of experiments, and can realize the core function of helping experimenters to calculate the specific amount of a particular substance when adjusting the pH value of a solution. Its accuracy, convenience, and continuous optimization can improve the accuracy and efficiency of experiments, reduce the uncertainty and time consumption in the experimental process, and help the experimenters to better control the experimental conditions, thus improving the success rate and quality of experiments.