The continuous re-isolation of the known and non-applicable compounds are critical problems in the discovery of biologically active compounds from natural resources that is wasting time and resources. To efficiently solve this problem, HPLC-DAD-microfractionation directed by disk agar diffusion assay was performed, and the active compounds were further dereplicated using the tandem mass spectrometry-based molecular networking [1]. Moreover, utilizing the 13C NMR spectral database to deal with the problem of diastereoisomers and precisely determined the chemical structures from the results of dereplication among the numerous active samples. In this case, we were able to verify the presence of all the bioactive entities in the early research stage, no matter they are new or known compounds. The methanolic extracts of Phoma herbarum PPM7487, Cryptosporiopsis ericae PPM7504, and Albifimbria sp. PPM945 showed significant antimicrobial activity against the Candida albicans and Cryptococcus neoformans among 150 fungal strains in a preliminary agar diffusion assay. Off-line antimicrobial activity-based HPLC profiling of these extracts enabled a precise localization of the active compounds in the chromatogram. The purified active compounds were dereplicated based mainly on MS/MS database [2], and the stereoisomers were further identified by 13C NMR spectra in comparison with the literature values. In addition to seventeen known compounds 2‒18, a new trichothecenoid analogue, namely trichoverrin C (1), was isolated and identified through this protocol. This report has demonstrated the combination of HPLC microfractination, antimicrobial assay, and dereplication with tandem MS assisted by 13C NMR for speeding up the antimicrobial natural products discovery process.
References:
[1] Yang JY, Sanchez LM, Rath CM, Liu X et al. Molecular networking as a dereplication strategy. J. Nat. Prod. 2013; 76: 1686‒1699.
[2] Wang M, Carver JJ, Phelan VV, Sanchez LM et al. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking. Nat. Biotechnol. 2016; 34: 828‒837.
