USP Electronic Research Repository

LC - HRMS - database screening metrics for rapid prioritization of samples to accelerate the discovery of structurally new natural products

Tabudravu, Jioji N. and Pellissier, Léonie and Smith, Alan J. and Subko, Karolina and Autréau, Caroline and Feussner, Klaus D. and Hardy, David and Butler, Daniel and Kidd, Richard and Milton, Edward J. and Deng, Hai and Ebel, Rainer and Salonna, Marika and Gissi, Carmela and Montesanto, Federica and Kelly, Sharon M. and Milne, Bruce F. and Cimpan, Gabriela and Jaspars, Marcel (2019) LC - HRMS - database screening metrics for rapid prioritization of samples to accelerate the discovery of structurally new natural products. Journal of Natural Products, 82 (2). pp. 211-220. ISSN 0163-3864

[img] PDF - Accepted Version
Restricted to Repository staff only

Download (1859Kb)

    Abstract

    In order to accelerate the isolation and characterization of structurally new or novel secondary metabolites, it is crucial to develop efficient strategies that prioritize samples with greatest promise early in the workflow so that resources can be utilized in a more efficient and costeffective manner. We have developed a metrics-based prioritization approach using exact LC-HRMS, which uses data for 24 618 marine natural products held in the PharmaSea database. Each sample was evaluated and allocated a metric score by a software algorithm based on the ratio of new masses over the total (sample novelty), ratio of known masses over the total (chemical novelty), number of peaks above a defined peak area threshold (sample complexity), and peak area (sample diversity). Samples were then ranked and prioritized based on these metric scores. To validate the approach, eight marine sponges and six tunicate samples collected from the Fiji Islands were analyzed, metric scores calculated, and samples targeted for isolation and characterization of new compounds. Structures of new compounds were elucidated by spectroscopic techniques, including 1D and 2D NMR, MS, and MS/MS. Structures were confirmed by computer-assisted structure elucidation methods (CASE) using the ACD/Structure Elucidator Suite.

    Item Type: Journal Article
    Subjects: Q Science > Q Science (General)
    Divisions: Faculty of Science, Technology and Environment (FSTE) > Institute of Applied Science
    Depositing User: Komal Devi
    Date Deposited: 25 Feb 2019 12:28
    Last Modified: 25 Feb 2019 12:28
    URI: http://repository.usp.ac.fj/id/eprint/11325
    UNSPECIFIED

    Actions (login required)

    View Item

    Document Downloads

    More statistics for this item...