TeroKit
TeroKit integrates a comprehensive, annotated terpenome database with computational modules for target profiling and conformer generation to support analysis of terpenoid- and steroid-derived natural products.
Key Features:
- Comprehensive terpenome database: Houses over 110,000 annotated terpenome molecules compiled from 14,351 species across 1,109 families.
- Compound-target associations: Links terpenome compounds to 1,366 distinct biological targets.
- Target profiling module: Provides computational target profiling of terpenoid-like compounds.
- Conformer generation module: Generates molecular conformers for terpenome compounds.
- Coverage of terpenoid and steroid chemical space: Includes terpenoids, terpenoid-like and terpenoid-derived compounds, including steroids and their derivatives.
- Computational predictions and annotations: Supplies annotated information and computational predictions related to terpenoid compounds.
Scientific Applications:
- Natural product and terpenome research: Characterizes chemical diversity and structural complexity across terpenoids and related compounds.
- Drug discovery and pharmacology: Supports identification and analysis of bioactive terpenoids, with relevance to compounds such as artemisinin and paclitaxel.
- Target identification and profiling: Enables profiling of compound–target relationships for biological target exploration.
- Comparative chemotaxonomy: Facilitates cross-species and cross-family comparison of terpenome composition and annotations.
Methodology:
Compilation and annotation of >110,000 terpenome molecules across 14,351 species and 1,109 families, combined with computational modules for target profiling and conformer generation.
Topics
Details
- Added:
- 1/18/2021
- Last Updated:
- 2/27/2021
Operations
Publications
Zeng T, Liu Z, Zhuang J, Jiang Y, He W, Diao H, Lv N, Jian Y, Liang D, Qiu Y, Zhang R, Zhang F, Tang X, Wu R. TeroKit: A Database-Driven Web Server for Terpenome Research. Journal of Chemical Information and Modeling. 2020;60(4):2082-2090. doi:10.1021/acs.jcim.0c00141. PMID:32286817.
PMID: 32286817
Funding: - National Natural Science Foundation of China: 21773313, 81703416
- Guangdong Natural Science Founds for Distinguished Young Scholars: 2016A030306038
- GDAS' Project of Science and Technology Development: 2019GDASYL-0103009