Curcumin Chalcone Derivatives Database (CCDD): a Python framework for natural compound derivatives database

Author:

Rampogu Shailima1,Balasubramaniyam Thananjeyan2,Lee Joon-Hwa2

Affiliation:

1. Cachet Big Data Labs, Hyderabad, Telangana, India

2. Department of Chemistry, Gyeongsang National University, Jinju, Gyeongnam, South Korea

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/.

Funder

National Research Foundation of Korea

Samsung Science and Technology Foundation

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

Reference52 articles.

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