Curcumin Chalcone Derivatives Database (CCDD): a Python framework for natural compound derivatives databaseopen access
- Authors
- Rampogu, Shailima; Balasubramaniyam, Thananjeyan; Lee, Joon-Hwa
- Issue Date
- Aug-2023
- Publisher
- PeerJ
- Keywords
- Curcumin; Chalcones; Python; Streamlit; CADD; Curcumin chalcone derivatives database CCDD
- Citation
- PeerJ, v.11
- Indexed
- SCIE
SCOPUS
- Journal Title
- PeerJ
- Volume
- 11
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/67703
- DOI
- 10.7717/peerj.15885
- ISSN
- 2167-8359
- Abstract
- We built the Curcumin Chalcone Derivatives Database (CCDD) to enable the effective virtual screening of highly potent curcumin and its analogs. The two-dimensional (2D) structures were drawn using the ChemBioOffice package and converted to 3D structures using Discovery Studio Visualizer V 2021 (DS). The database was built using different Python modules. For the 3D structures, different Python packages were used to obtain the data frame of compounds. This framework is also used to visualize the compounds. The webserver enables the users to screen the compounds according to Lipinski's rule of five. The structures can be downloaded in .sdf and .mol format. The data frame (df) can be downloaded in .csv format. Our webserver can help computational drug discovery researchers find new therapeutics and build new webservers. The CCDD is freely available at: https:// srampogu-ccdd-ccdd-8uldk8.streamlit.app/.
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