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Cited 2 time in webofscience Cited 2 time in scopus
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Curcumin Chalcone Derivatives Database (CCDD): a Python framework for natural compound derivatives databaseopen access

Authors
Rampogu, ShailimaBalasubramaniyam, ThananjeyanLee, 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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