CCDD

CCDD provides a Python-based database of curcumin and curcumin chalcone derivatives with curated two-dimensional and three-dimensional structures to support virtual screening and analysis of drug-like analogs.

Key Features:

• Database Construction: Contains curated 2D and 3D structural representations of curcumin and its derivatives created from ChemBioOffice drawings and converted to 3D with Discovery Studio Visualizer V 2021 (DS).
• Python Integration: Uses Python modules and packages to manage 3D structural data and assemble a comprehensive compound data frame.
• Visualization Capabilities: Provides functionalities for molecular visualization of compounds and their structural properties.
• Virtual Screening Tools: Implements screening based on Lipinski's rule of five to assess the drug-likeness of compounds.
• Data Accessibility: Supplies compound structure and metadata exports in .sdf, .mol, and .csv file formats.

Scientific Applications:

• Virtual Screening: Enables identification and prioritization of curcumin derivatives based on Lipinski's rule of five.
• Compound Analysis and Development: Supports structural analysis and visualization to aid exploration and development of potential therapeutic curcumin analogs.

Methodology:

2D structures were drawn using ChemBioOffice, converted to 3D models with Discovery Studio Visualizer V 2021 (DS), and integrated into a Python-based framework to construct the database.