LC-HRMS-Database Screening Metrics for Rapid Prioritization of Samples to Accelerate the Discovery of Structurally New Natural Products.
J Nat Prod
; 82(2): 211-220, 2019 02 22.
Article
em En
| MEDLINE
| ID: mdl-30735391
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 cost-effective manner. We have developed a metrics-based prioritization approach using exact LC-HRMS, which uses data for 24â¯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.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Poríferos
/
Espectrometria de Massas
/
Urocordados
/
Produtos Biológicos
/
Cromatografia Líquida
/
Descoberta de Drogas
Tipo de estudo:
Diagnostic_studies
/
Screening_studies
Limite:
Animals
Idioma:
En
Revista:
J Nat Prod
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
Reino Unido