WatCon: A Python Tool for Analysis of Conserved Water Networks Across Protein Families.

Area of Science:

• Biochemistry and Structural Biology
• Computational Biology
• Bioinformatics

Background:

• Water molecules play a critical role in protein structure, function, and catalysis.
• Complex hydrogen-bonding networks involving water and protein residues are essential but challenging to analyze across protein families.
• Existing tools for water network analysis lack comprehensive capabilities for cross-protein family comparisons.

Purpose of the Study:

• To introduce WatCon, an open-source Python package for analyzing water positions and network structures across protein families.
• To provide a method for classifying conserved water networks and characterizing their structural variations.
• To facilitate the visualization and interpretation of water network analysis results.

Main Methods:

• Development of WatCon, a Python package utilizing graph-theory principles.
• Analysis of both static protein structures and dynamic molecular dynamics trajectories.
• Implementation of functions for water network classification, characterization, and projection.

Main Results:

• WatCon enables the classification and characterization of water networks across diverse protein structures.
• The tool can analyze water networks using static data and dynamic simulations.
• Demonstrated utility through five example applications, including cross-family analysis.

Conclusions:

• WatCon enhances the understanding of biochemical systems by analyzing conserved water networks.
• The tool aids in predicting functionally important water hotspots for protein engineering.
• WatCon can assist in identifying pathogenic mutations by analyzing alterations in water networks.