Signature peptide selection workflow for biomarker quantification using LC–MS-based targeted proteomics
| العنوان: | Signature peptide selection workflow for biomarker quantification using LC–MS-based targeted proteomics |
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| المؤلفون: | Xiazi I Qiu, Kenneth J Ruterbories, Qin C Ji, Gary J Jenkins |
| المصدر: | Bioanalysis. 15:295-300 |
| بيانات النشر: | Future Science Ltd, 2023. |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Medical Laboratory Technology, Clinical Biochemistry, General Medicine, General Pharmacology, Toxicology and Pharmaceutics, Analytical Chemistry |
| الوصف: | In contrast to quantification of biotherapeutics, endogenous protein biomarker and target quantification using LC–MS based targeted proteomics can require a much more stringent and time-consuming tryptic signature peptide selection for each specific application. While some general criteria exist, there are no tools currently available in the public domain to predict the ionization efficiency for a given signature peptide candidate. Lack of knowledge of the ionization efficiencies forces investigators to choose peptides blindly, thus hindering method development for low abundant protein quantification. Here, the authors propose a tryptic signature peptide selection workflow to achieve a more efficient method development and to improve success rates in signature peptide selection for low abundant endogenous target and protein biomarker quantification. |
| تدمد: | 1757-6199 1757-6180 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::8f46c99ba09544003642a8a61205c46b https://doi.org/10.4155/bio-2022-0241 |
| رقم الأكسشن: | edsair.doi...........8f46c99ba09544003642a8a61205c46b |
| قاعدة البيانات: | OpenAIRE |
PDF full text from Publisher | تدمد: | 17576199 17576180 |
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