INTERCAAT

INTERCAAT identifies and classifies atomic interactions in macromolecular interfaces to map intermolecular contacts for structural and functional analysis.


Key Features:

  • Voronoi tessellation-based interaction definition: Uses Voronoi tessellation with each atom as a seed point to determine spatial relationships and partition space around atoms for interaction mapping.
  • Hyperplane sharing and distance criteria: Defines contacts when atoms share a Voronoi hyperplane and their distance is less than the sum of their Van der Waals radii plus the diameter of a solvent molecule.
  • Adaptive atom classification: Implements an adaptive atom classification system to accommodate diverse atom types across macromolecular interfaces.
  • Interaction filtering based on compatibility: Applies compatibility-based filtering to retain physically and chemically relevant contacts.

Scientific Applications:

  • Protein-Protein Interaction Studies: Produces detailed atomic contact maps to analyze protein complexes and interface mechanisms.
  • Drug Design and Discovery: Provides precise descriptions of intermolecular contacts to inform design of molecules that target or modulate interfaces.
  • Macromolecular Complex Analysis: Maps interfaces within large assemblies to study structural organization and intermolecular networks.

Methodology:

Computational geometry via Voronoi tessellation partitions space around atoms; interactions are detected by Voronoi hyperplane sharing combined with distance thresholds defined as the sum of Van der Waals radii plus a solvent molecule diameter, followed by adaptive atom classification and compatibility-based filtering, grounded in molecular physics.

Topics

Details

License:
Not licensed
Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Mac, Linux
Programming Languages:
Python
Added:
2/24/2022
Last Updated:
2/24/2022

Operations

Publications

Grudman S, Fajardo JE, Fiser A. INTERCAAT: identifying interface residues between macromolecules. Bioinformatics. 2021;38(2):554-555. doi:10.1093/bioinformatics/btab596. PMID:34499117. PMCID:PMC8722752.

PMID: 34499117
Funding: - NIH: AI141816, GM136357