Literature DB >> 28885833

The Face of a Molecule.

William H Gerwick1.   

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".

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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


  7 in total

1.  Searching for Small Molecules with an Atomic Sort.

Authors:  Brendan M Duggan; Reiko Cullum; William Fenical; Luis A Amador; Abimael D Rodríguez; James J La Clair
Journal:  Angew Chem Int Ed Engl       Date:  2019-12-02       Impact factor: 15.336

2.  Applying molecular networking for targeted isolation of depsipeptides.

Authors:  Xiao Lin; Ling Chai; Hong Rui Zhu; Yongjun Zhou; Yaoyao Shen; Kai Hao Chen; Fan Sun; Bu Ming Liu; Shi Hai Xu; Hou Wen Lin
Journal:  RSC Adv       Date:  2021-01-13       Impact factor: 4.036

3.  Learning Drug Functions from Chemical Structures with Convolutional Neural Networks and Random Forests.

Authors:  Jesse G Meyer; Shengchao Liu; Ian J Miller; Joshua J Coon; Anthony Gitter
Journal:  J Chem Inf Model       Date:  2019-10-03       Impact factor: 4.956

4.  Exploring Verrucosidin Derivatives with Glucose-Uptake-Stimulatory Activity from Penicillium cellarum Using MS/MS-Based Molecular Networking.

Authors:  Junjie Han; Baosong Chen; Rui Zhang; Jinjin Zhang; Huanqin Dai; Tao Wang; Jingzu Sun; Guoliang Zhu; Wei Li; Erwei Li; Xueting Liu; Wenbing Yin; Hongwei Liu
Journal:  J Fungi (Basel)       Date:  2022-01-30

Review 5.  Metabolomics on the study of marine organisms.

Authors:  Lina M Bayona; Nicole J de Voogd; Young Hae Choi
Journal:  Metabolomics       Date:  2022-03-02       Impact factor: 4.290

Review 6.  Marine Cyanobacteria: A Source of Lead Compounds and their Clinically-Relevant Molecular Targets.

Authors:  Lik Tong Tan; Ma Yadanar Phyo
Journal:  Molecules       Date:  2020-05-08       Impact factor: 4.411

7.  Insight into Unprecedented Diversity of Cyanopeptides in Eutrophic Ponds Using an MS/MS Networking Approach.

Authors:  Andreja Kust; Klára Řeháková; Jaroslav Vrba; Vincent Maicher; Jan Mareš; Pavel Hrouzek; Maria-Cecilia Chiriac; Zdeňka Benedová; Blanka Tesařová; Kumar Saurav
Journal:  Toxins (Basel)       Date:  2020-08-31       Impact factor: 4.546

  7 in total

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