SistematX
SistematX provides a curated database and analytical platform for plant secondary metabolites to support compound identification, structural elucidation, physicochemical property assessment, and biological activity profiling for drug discovery.
Key Features:
- Curated Database: A repository of plant-derived secondary metabolites with detailed compound information including the exact collection location of source plants.
- 1H and 13C NMR Spectra Generation and Visualization: Generation and visualization of 1H and 13C NMR spectra to aid structural elucidation of secondary metabolites.
- Physicochemical Property Calculations: Calculation of drug-like and lead-like physicochemical properties to assess compound suitability for drug development.
- Biological Activity Profiles: Integration and presentation of biological activity data associated with each compound to inform prioritization.
- Batch Download: Export of large datasets for downstream computational analysis.
Scientific Applications:
- Natural Product Chemistry: Support for identification and structural characterization of plant secondary metabolites using spectral and property data.
- Medicinal Chemistry and Drug Discovery: Assessment and prioritization of compounds based on drug-like and lead-like properties and biological activity for progression toward preclinical testing.
- Pharmacognosy and Biological Research: Provision of provenance and activity information to support studies of bioactive natural products.
Methodology:
Computational methods include 1H and 13C NMR spectra generation and visualization, physicochemical property calculations for drug- and lead-likeness, curation and integration of biological activity profiles, and batch data export.
Topics
Details
- Tool Type:
- web application
- Added:
- 12/6/2021
- Last Updated:
- 12/6/2021
Operations
Publications
Costa RPO, Lucena LF, Silva LMA, Zocolo GJ, Herrera-Acevedo C, Scotti L, Da-Costa FB, Ionov N, Poroikov V, Muratov EN, Scotti MT. The SistematX Web Portal of Natural Products: An Update. Journal of Chemical Information and Modeling. 2021;61(6):2516-2522. doi:10.1021/acs.jcim.1c00083. PMID:34014674.