| Literature DB >> 28885833 |
Abstract
Recent technological advances in mass spectrometry and NMR spectroscopy have enabled new approaches for the rapid and insightful profiling of natural product mixtures. MALDI-MS with the provision of biosynthetic heavy-isotope-labeled precursors can be a powerful method by which to interrogate a natural product metabolome and to gain insight into its unique constituents; this is illustrated herein by the detection, isolation, and characterization of cryptomaldamide. MS/MS-based Molecular Networks, facilitated by the Global Natural Products Social (GNPS) platform, is rapidly changing the way in which we dereplicate known natural products in mixtures, find new analogues in desired structure classes, and identify fundamentally new chemical entities. This method can be linked to genomic information to assist in genome-driven natural products discovery and is illustrated here with the characterization of the columbamides. Similarly, algorithmic interpretation of NMR data is facilitating the automatic identification or classification of new natural products. We developed such a tool named the Small Molecule Accurate Recognition Technology (SMART), which employs a convolutional neural network to classify HSQC spectra of organic molecules using pattern recognition principles. The discovery and rapid classification of several new peptides from a marine cyanobacterium as members of the viequeamide class provides an example of its utility in natural products research. These three illustrations represent different methods by which to look at the external features of a chemical substance and derive valuable insights into its identity or, as described herein, the "face of a molecule".Entities:
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Year: 2017 PMID: 28885833 DOI: 10.1021/acs.jnatprod.7b00624
Source DB: PubMed Journal: J Nat Prod ISSN: 0163-3864 Impact factor: 4.050