Machine learning-aided engineering ofhydrolases for PET depolymerization.Nature, 2022, 604:662-667 DOI: 10.1038/s41586-022-04599-z. https://www.nature.com/articles/s41586-022-04599-z 【2】Eggo U. Thoden van Velzen & GiusySantomasi. Tailor-made enzymes for plastic recycling.Nature, 2022 ...
参考文献 Machine learning-aided engineering of hydrolases for PET depolymerization. Nature, 2022, 604, 662-667.
Nature volume 604, pages 662–667 (2022)Cite this article 124k Accesses 2132 Altmetric Metrics details Abstract Plastic waste poses an ecological challenge1,2,3 and enzymatic degradation offers one, potentially green and scalable, route for polyesters waste recycling4. Poly(ethylene terephthalate) (...
[2]https://www.nature.com/articles/d41586-022-01075-6#ref-CR1 [3]Lu H, Diaz DJ, Czarnecki NJ, et al. Machine learning-aided engineering of hydrolases for PET depolymerization. Nature. 2022 Apr;604(7907):662-667. doi: 10.1038/s41586-022-04599-z. Epub 2022 Apr 27. PMID: 35478237....
参考文献: LuH, Diaz DJ, Czarnecki NJ, et al. Machine learning-aided engineering of hydrolases for PET depolymerization. Nature. 2022 Apr;604(7907):662-667. doi:10.1038/s41586-022-04599-z. Epub 2022 Apr 27. PMID: 35478237. 责任编辑:白芨...
【1】Hal S. Alper et. al. Machine learning-aided engineering ofhydrolases for PET depolymerization.Nature, 2022, 604:662-667 DOI: 10.1038/s41586-022-04599-z. https://www./articles/s41586-022-04599-z 【2】Eggo U. Thoden van Velzen & GiusySantomasi. Tailor-made enzymes ...
LuH, Diaz DJ, Czarnecki NJ, et al. Machine learning-aided engineering of hydrolases for PET depolymerization. Nature. 2022 Apr;604(7907):662-667. doi:10.1038/s41586-022-04599-z. Epub 2022 Apr 27. PMID: 35478237. 您的浏览器版本过低或该浏览器不支持,可能导致网站不能正常运行 ...
Nature 604, 662–667 (2022). Article Google Scholar Tournier, V. et al. An engineered PET depolymerase to break down and recycle plastic bottles. Nature 580, 216–219 (2020). Article Google Scholar Son, H. F. et al. Rational protein engineering of thermo-stable PETase from Ideonella ...
Nature 604, 662–667 (2022). Article CAS PubMed Google Scholar Ulissi, Z. W., Medford, A. J., Bligaard, T. & Nørskov, J. K. To address surface reaction network complexity using scaling relations machine learning and DFT calculations. Nat. Commun. 8, 14621 (2017). Article PubMed...
Nature 604, 662–667 (2022). Article Google Scholar Norn, C. et al. Protein sequence design by conformational landscape optimization. Proc. Natl Acad. Sci. USA 118, e2017228118 (2021). Article Google Scholar Hsu, C. et al. Learning inverse folding from millions of predicted structures....