iCn3D

iCn3D visualizes and analyzes three-dimensional macromolecular structures to support structural interpretation, annotation, and batch processing of large molecular datasets.

Key Features:

• DelPhi Electrostatic Potential: Calculates electrostatic potentials on molecular surfaces using DelPhi.
• 3D View of Mutations: Visualizes the structural impact of mutations in three-dimensional context.
• Alignment of Multiple Chains: Aligns and compares polypeptide chains within or between structures.
• Assembly of Multiple Structures by Realignment: Integrates multiple structural datasets by realignment for assembled models.
• Dynamic Symmetry Calculation: Computes dynamic molecular symmetry properties.
• 2D Cartoons at Different Levels: Generates simplified 2D representations of structures at multiple levels of detail.
• Interactive Contact Maps: Produces contact maps to visualize intra- and intermolecular interactions.
• Python/Node.js Batch Scripting (icn3dpython): Supports Python scripts (icn3dpython GitHub repository) that can be adapted for Node.js to automate analyses.
• Conversion of Interactive Features to Node.js Scripts: Converts interactive operations into Node.js scripts for batch processing.
• Export of Annotations and Images: Exports annotations such as secondary structure and PNG images.
• Integration with Jupyter Notebook (icn3dpy): Provides integration for use within Jupyter Notebook via the icn3dpy package.

Scientific Applications:

• Electrostatic Analysis: Mapping electrostatic potentials on molecular surfaces to study charge-related properties.
• Mutation Impact Assessment: Visualizing and assessing structural consequences of amino acid substitutions.
• Chain Comparison and Alignment: Comparing and aligning multiple polypeptide chains to analyze structural conservation and variation.
• Structure Assembly: Realigning and assembling multiple structures to construct larger complexes or models.
• Symmetry Analysis: Determining molecular symmetry for structural characterization.
• Interaction Mapping: Using contact maps to analyze intra- and intermolecular interactions.
• Multi-scale Visualization: Generating 2D cartoons and 3D views at different levels for structural interpretation.
• High-throughput Structural Analysis: Scaling analyses from individual complexes to large ensembles and structural databases such as AlphaFold, RoseTTAFold, and electron microscopy datasets.
• Workflow Integration: Embedding structure analyses and exports within programmatic workflows and Jupyter Notebook environments.

Methodology:

Calculates electrostatic potentials with DelPhi, computes dynamic symmetry, performs chain alignment and realignment-based assembly, and executes Python scripts (icn3dpython) adaptable to Node.js to export annotations (e.g., secondary structure, PNG) and convert interactive features into batch-processable Node.js scripts; supports execution within Jupyter via icn3dpy.