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GlycoMME, a Markov modeling platform for studying N-glycosylation biosynthesis from glycomics data
Variations in N-glycosylation, which is crucial to glycoprotein functions, impact many diseases and the safety and efficacy of biotherapeutic drugs. Here, we present a protocol for using GlycoMME (Glycosylation Markov Model Evaluator) to study N-glycosylation biosynthesis from glycomics data. We des...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10160804/ https://www.ncbi.nlm.nih.gov/pubmed/37086409 http://dx.doi.org/10.1016/j.xpro.2023.102244 |
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author | Liang, Chenguang Chiang, Austin W.T. Lewis, Nathan E. |
author_facet | Liang, Chenguang Chiang, Austin W.T. Lewis, Nathan E. |
author_sort | Liang, Chenguang |
collection | PubMed |
description | Variations in N-glycosylation, which is crucial to glycoprotein functions, impact many diseases and the safety and efficacy of biotherapeutic drugs. Here, we present a protocol for using GlycoMME (Glycosylation Markov Model Evaluator) to study N-glycosylation biosynthesis from glycomics data. We describe steps for annotating glycomics data and quantifying perturbations to N-glycan biosynthesis with interpretable models. We then detail procedures to predict the impact of mutations in disease or potential glycoengineering strategies in drug development. For complete details on the use and execution of this protocol, please refer to Liang et al. (2020).(1) |
format | Online Article Text |
id | pubmed-10160804 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-101608042023-05-06 GlycoMME, a Markov modeling platform for studying N-glycosylation biosynthesis from glycomics data Liang, Chenguang Chiang, Austin W.T. Lewis, Nathan E. STAR Protoc Protocol Variations in N-glycosylation, which is crucial to glycoprotein functions, impact many diseases and the safety and efficacy of biotherapeutic drugs. Here, we present a protocol for using GlycoMME (Glycosylation Markov Model Evaluator) to study N-glycosylation biosynthesis from glycomics data. We describe steps for annotating glycomics data and quantifying perturbations to N-glycan biosynthesis with interpretable models. We then detail procedures to predict the impact of mutations in disease or potential glycoengineering strategies in drug development. For complete details on the use and execution of this protocol, please refer to Liang et al. (2020).(1) Elsevier 2023-04-21 /pmc/articles/PMC10160804/ /pubmed/37086409 http://dx.doi.org/10.1016/j.xpro.2023.102244 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Protocol Liang, Chenguang Chiang, Austin W.T. Lewis, Nathan E. GlycoMME, a Markov modeling platform for studying N-glycosylation biosynthesis from glycomics data |
title | GlycoMME, a Markov modeling platform for studying N-glycosylation biosynthesis from glycomics data |
title_full | GlycoMME, a Markov modeling platform for studying N-glycosylation biosynthesis from glycomics data |
title_fullStr | GlycoMME, a Markov modeling platform for studying N-glycosylation biosynthesis from glycomics data |
title_full_unstemmed | GlycoMME, a Markov modeling platform for studying N-glycosylation biosynthesis from glycomics data |
title_short | GlycoMME, a Markov modeling platform for studying N-glycosylation biosynthesis from glycomics data |
title_sort | glycomme, a markov modeling platform for studying n-glycosylation biosynthesis from glycomics data |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10160804/ https://www.ncbi.nlm.nih.gov/pubmed/37086409 http://dx.doi.org/10.1016/j.xpro.2023.102244 |
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