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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Detalles Bibliográficos
Autores principales: Delmar, Jared A., Buehler, Eugen, Chetty, Ashwin K., Das, Agastya, Quesada, Guillermo Miro, Wang, Jihong, Chen, Xiaoyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society of Gene & Cell Therapy 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8060516/
https://www.ncbi.nlm.nih.gov/pubmed/33898635
http://dx.doi.org/10.1016/j.omtm.2021.03.023

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8060516/
https://www.ncbi.nlm.nih.gov/pubmed/33898635
http://dx.doi.org/10.1016/j.omtm.2021.03.023

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