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Machine learning prediction of methionine and tryptophan photooxidation susceptibility
Photooxidation of methionine (Met) and tryptophan (Trp) residues is common and includes major degradation pathways that often pose a serious threat to the success of therapeutic proteins. Oxidation impacts all steps of protein production, manufacturing, and shelf life. Prediction of oxidation liabil...
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| Pubblicato in: | Mol Ther Methods Clin Dev |
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| Autori principali: | , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
American Society of Gene & Cell Therapy
2021
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8060516/ https://ncbi.nlm.nih.gov/pubmed/33898635 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.omtm.2021.03.023 |
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