ZClass

ZClass converts Protein Data Bank (PDB) structures into voxelized three-dimensional images and computes three-dimensional Zernike polynomial expansions to enable quantitative comparison and analysis of protein shapes and structural variability.

Key Features:

• Voxelization of Protein Structures: ZClass converts PDB file data into a three-dimensional voxel representation of proteins, enabling spatial analysis beyond atomic coordinates.
• Zernike Polynomial Expansion: It represents voxelized images using Zernike polynomials to capture and compare protein shapes efficiently.
• Handling Structural Variability: The method accounts for positional variance and uncertainty in atomic coordinates to represent continuous motion and structural heterogeneity.
• Mathematical Framework for Shape Analysis: ZClass leverages three-dimensional Zernike moments to describe functions across the entire protein volume, not solely the surface.

Scientific Applications:

• Protein Function Analysis: Captures conformational changes to relate structural dynamics to biological function.
• Structural Comparison: Enables rapid quantitative comparison of protein shapes across large datasets of structures.
• Uncertainty Quantification: Supports characterization of positional variance and modeling of structural uncertainties in atomic coordinates.

Methodology:

ZClass reads PDB files, voxelizes structures into three-dimensional grids, expands the voxelized images using Zernike polynomials, and computes three-dimensional Zernike moments to represent shape and movement.