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Sequential Voxel-Based Leaflet Segmentation of Complex Lipid Morphologies.

Bart M H Bruininks¹, Albert S Thie², Paulo C T Souza^1,3

¹Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, 9712 CP Groningen, The Netherlands.

Journal of Chemical Theory and Computation

|October 5, 2021

Summary

Researchers developed a new method to track lipid leaflets in molecular dynamics simulations. This tool efficiently detects topological changes in complex lipid structures like vesicles and membranes, even for millions of particles.

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Area of Science:

Computational biophysics
Molecular modeling and simulation
Materials science

Background:

Molecular dynamics (MD) simulations are crucial for understanding complex biological systems.
Lipids self-assemble into diverse morphologies (micelles, vesicles, membranes) due to their amphipathic nature.
Analyzing large-scale lipid behavior at the particle level is computationally expensive and challenging.

Purpose of the Study:

To develop an efficient computational tool for analyzing complex lipid structures in MD simulations.
To enable the detection of mesoscale topological changes in lipid assemblies.
To overcome the limitations of particle-level analysis for large lipid systems.

Main Methods:

A novel voxel-based method tracks individual lipid leaflets.
Focus on locality and the Jaccard index for chronological segmentation of lipid segments.
Avoids computationally intensive geometric operations while preserving essential details.

Main Results:

Consistent sequential segmentation of various lipid systems, including monolayers, bilayers, vesicles, and mitochondrial membranes.
Successful discrimination between lipid leaflet adhesion and fusion events.
Efficient segmentation of millions of particles achievable on standard desktop hardware.

Conclusions:

The developed method provides a robust and efficient way to analyze complex lipid mesoscale phenomena.
It offers a significant improvement over traditional particle-level analysis for large MD simulations.
The tool is versatile and applicable to a wide range of lipid-based systems without parameter pre-fitting.