MakroLyzer: A Graph-Based Software to Comb through Molecular Hairballs using the Example of Nanoplastics

Area of Science:

• Computational chemistry and materials science.
• Biophysics and polymer science.

Background:

• Analyzing the structure of natural and synthetic macromolecules (e.g., peptides, nanoplastics) is crucial for understanding their properties and functions.
• Existing methods may lack comprehensive analysis capabilities for diverse polymeric structures.

Purpose of the Study:

• To introduce MakroLyzer, a freely available software for detailed macromolecular structure analysis.
• To provide a robust computational tool for characterizing polymers, including peptides and nanoplastics.
• To enable advanced structural investigations using graph theory and Python libraries.

Main Methods:

• Leveraging graph theory and multiple Python libraries for structural analysis.
• Identifying the macromolecular backbone and assigning atoms to repeating units.
• Calculating structural parameters such as end-to-end distance, radius of gyration tensor, anisotropy factor, and asphericity.

Main Results:

• MakroLyzer successfully identifies key structural features of macromolecules.
• The software computes parameters like end-to-end distance, anisotropy, and asphericity.
• Order parameter and hydrogen bond analysis provide deeper structural insights.

Conclusions:

• MakroLyzer offers a comprehensive and accessible platform for macromolecular structure analysis.
• The tool is effective for deciphering the structures of various polymers, including nanoplastics and peptides.
• This software provides a valuable resource for researchers in materials science and biophysics.