PGN_MS2: In silico MS/MS prediction for peptidoglycan profiling

Our lab built a computational tool PGN_MS2 that generates a customizable peptidoglycan (PGN) database from user-defined parameters. PNG_MS2 can simulate MS/MS spectra for each PGN and compile these predicted MS/MS spectra to a spectral library in the NIST format (.msp). The spectral library (.msp) is compatible with open-access and vendor software, e.g. MS-DIAL, for automated matching and scoring of experimental MS/MS peaks, greatly reducing the amount of manual work needed to identify PGN from complex MS/MS data. (Kwan et al, Chem Sci 2024)

Software prerequisites




User guide

Refer to the links below for step-by-step guides: 

PGN_MS2 user guide    &       MS-DIAL tutorial 


1.JMC. Kwan, Y. Liang, EWL. Ng, E. Sviriaeva, C. Li, Y. Zhao, XL. Zhang, XW. Liu , S. Wong, Y. Qiao.* In silico MS/MS prediction for peptidoglycan profiling uncovers novel anti-inflammatory peptidoglycan fragments of the gut microbiota. Chem. Sci. 2024, 15, 1846-1859, doi: 10.1039/D3SC05819K

2.H. Tsugawa, K. Ikeda, M. Takahashi, A. Satoh, Y. Mori, H. Uchino, N. Okahashi, Y. Yamada, I. Tada, P. Bonini, Y. Higashi, Y. Okazaki, Z. Zhou, ZJ Zhu, J. Koelmel, T. Cajka, O. Fiehn, K. Saito, M Arita, M. Arita.* A lipidome atlas in MS-DIAL 4. Nat Biotechnol 2020, 38, 1159–1163, doi: 10.1038/s41587-020-0531-2

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