Jupyter and IPython extensions for rich drug discovery visualizations. Display ADMET dashboards, 3D molecular structures, and SMILES drawings inline in any notebook.
Refua Notebook is the visualization layer for the Refua ecosystem. It provides an
IPython extension that automatically registers rich HTML
representations for Refua objects. Simply display a Protein,
SM, Complex, or FoldResult in a cell, and
the extension renders an interactive widget with structure views, property summaries,
and ADMET dashboards.
The package ships with a prebuilt JupyterLab renderer that handles Mol* and SmilesDrawer locally, requiring no manual extension installation or lab build step.
Load the extension once and every Refua object renders automatically as a rich interactive widget, no extra code needed.
Display proteins with sequence information, property summaries, and 3D structure visualization when a fold result is available.
Show 2D structure drawings with RDKit-computed properties, Lipinski rule-of-five compliance, and ADMET dashboard integration.
Folded complexes render a tabbed view with 3D structure, binding affinity metrics, and per-component molecule details.
pip install refua-notebook# In a notebook cell:
%load_ext refua_notebook
# Or programmatically:
import refua_notebook
refua_notebook.activate()from refua import SM, Protein, Complex
# Proteins show sequence info and 3D structure if folded
Protein("MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQ", ids="A")
# Small molecules show 2D structure and properties
SM("Cn1cnc2n(C)c(=O)n(C)c(=O)c12")
# Complexes show tabbed 3D + affinity view
complex = Complex([
Protein("MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQ", ids="A"),
SM("CCO"),
]).request_affinity()
result = complex.fold()
complex # Renders automaticallyRefua Notebook brings publication-quality molecular visualizations directly into your research notebooks with zero configuration.