Topological Learning Approach to Characterizing Biological Membranes.

ABSTRACT: Biological membranes play key roles in cellular compartmentalization, structure, and its signaling pathways. At varying temperatures, individual membrane lipids sample from different configurations, a process that frequently leads to higher-order phase behavior and phenomena. Here we present a persistent homology-based method for quantifying the structural features of individual and bulk lipids, providing local and contextual information on lipid tail organization. Our method leverages the mathematical machinery of algebraic topology and machine learning to infer temperature-dependent structural information of lipids from static coordinates. To train our model, we generated multiple molecular dynamics trajectories of DPPC membranes at varying temperatures. A fingerprint was then constructe

SUBMITTER: Arango AS 

PROVIDER: S-EPMC10705453 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature