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Release of novel software “GRable” for mass spectrometry-based glycoproteomic analysis

This is an announcement of the release of a novel web tool for semi-automated glycoproteomics analysis, which was developed by several research groups, including those of Chiaki Nagai-Okatani (Senior researcher), Hiroyuki Kaji (Visiting Scientist), Hiroaki Sakaue (Researcher), and Atsushi Kuno (Group leader) of the Molecular and Cellular Glycoproteomics Research Group, Cellular and Molecular Biotechnology Research Institute, AIST; Prof. Kiyoko F. Aoki-Kinoshita and Dr. Akihiro Fujita of Soka University; and Prof. Daisuke Tominaga of Meiji Pharmaceutical University.

AIST has been developing a site-specific glycoform analysis method named “Glyco-RIDGE” (Glycan heterogeneity-based Relational Identification of Glycopeptide signals on Elution profile). This methodology has been applied to in-depth analyses of target glycoproteins and large-scale analyses of crude glycoprotein samples. Recently, we developed a novel software, named “GRable Version 1.0”, for semi-automated Glyco-RIDGE analysis, which was developed in collaboration with Dr. Shigeru Ko and Dr. Norio Goda (at the time) of the Keio University School of Medicine [2]. This software allows for investigation of disease-related glycosylation alterations and thus can facilitate the accelerated development of “glycomedicine”.

This web tool is freely available from the GlyCosmos Portal [3-5].

GRable Version 1.0: a web tool (released on the GlyCosmos Portal) for semi-automated Glyco-RIDGE analysis

GRable Version 1.0

Collaboration

Soka University, Nagoya University, Keio University, and Meiji Pharmaceutical University

References

Websites

Acknowledgements

This study was funded by a project for utilizing glycans in the development of innovative drug discovery technologies (grant number: JP20ae0101021h0005) from the Japan Agency for Medical Research and Development (AMED) and Database Integration Coordination Program (DICP) of the National Bioscience Database Center (NBDC) / the Japan Science and Technology Agency (JST) (grant number: JPMJND2204).

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