Literature DB >> 25202878

Systems glycobiology for glycoengineering.

Philipp N Spahn1, Nathan E Lewis2.   

Abstract

Glycosylation serves essential functions on many proteins produced in biopharmaceutical manufacturing, making it mandatory to thoroughly consider its biogenesis during the production process. Glycoengineering efforts involve the rational design of glycosylation through adjustments in culturing conditions or genetic modifications. Computational models have been developed to aid this process, aiming to offer cheaper and faster alternatives to costly screening strategies. Recently, these models have been successfully utilized to predict glycosylation of products of industrial relevance. Furthermore, systems-level analyses of glycan diversity are elucidating deeper insights into the mechanisms underlying glycosylation. As computational models of glycosylation continue to be expanded, refined, and leveraged for detailed analysis of glycomics data, they will become invaluable resources for cell line development and glycoengineering.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2014        PMID: 25202878     DOI: 10.1016/j.copbio.2014.08.004

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  20 in total

1.  A Markov chain model for N-linked protein glycosylation--towards a low-parameter tool for model-driven glycoengineering.

Authors:  Philipp N Spahn; Anders H Hansen; Henning G Hansen; Johnny Arnsdorf; Helene F Kildegaard; Nathan E Lewis
Journal:  Metab Eng       Date:  2015-10-29       Impact factor: 9.783

Review 2.  Integration of systems glycobiology with bioinformatics toolboxes, glycoinformatics resources, and glycoproteomics data.

Authors:  Gang Liu; Sriram Neelamegham
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2015-04-13

Review 3.  Engineering the supply chain for protein production/secretion in yeasts and mammalian cells.

Authors:  Tobias Klein; Jens Niklas; Elmar Heinzle
Journal:  J Ind Microbiol Biotechnol       Date:  2015-01-06       Impact factor: 3.346

Review 4.  Using glyco-engineering to produce therapeutic proteins.

Authors:  Martina Dicker; Richard Strasser
Journal:  Expert Opin Biol Ther       Date:  2015-07-14       Impact factor: 4.388

5.  Production of homogeneous glycoprotein with multisite modifications by an engineered N-glycosyltransferase mutant.

Authors:  Qitao Song; Zhigang Wu; Yueyuan Fan; Woran Song; Peiru Zhang; Li Wang; Faxing Wang; Yangyang Xu; Peng G Wang; Jiansong Cheng
Journal:  J Biol Chem       Date:  2017-04-05       Impact factor: 5.157

6.  Predictive glycoengineering of biosimilars using a Markov chain glycosylation model.

Authors:  Philipp N Spahn; Anders H Hansen; Stefan Kol; Bjørn G Voldborg; Nathan E Lewis
Journal:  Biotechnol J       Date:  2016-12-28       Impact factor: 4.677

7.  Applying transcriptomics to studyglycosylation at the cell type level.

Authors:  Leo Alexander Dworkin; Henrik Clausen; Hiren Jitendra Joshi
Journal:  iScience       Date:  2022-05-18

8.  A semi-empirical glycosylation model of a camelid monoclonal antibody under hypothermia cell culture conditions.

Authors:  Hengameh Aghamohseni; Maureen Spearman; Kaveh Ohadi; Katrin Braasch; Murray Moo-Young; Michael Butler; Hector M Budman
Journal:  J Ind Microbiol Biotechnol       Date:  2017-03-11       Impact factor: 3.346

9.  Glycan Microarray Reveal the Sweet Side of Cancer Vaccines.

Authors:  Vered Padler-Karavani
Journal:  Cell Chem Biol       Date:  2016-12-22       Impact factor: 8.116

Review 10.  Systems glycobiology for discovering drug targets, biomarkers, and rational designs for glyco-immunotherapy.

Authors:  Austin W T Chiang; Hratch M Baghdassarian; Benjamin P Kellman; Bokan Bao; James T Sorrentino; Chenguang Liang; Chih-Chung Kuo; Helen O Masson; Nathan E Lewis
Journal:  J Biomed Sci       Date:  2021-06-22       Impact factor: 8.410

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.