Department of Chemistry, The University of Chicago, Chicago, IL, USA.
Molecular Biophysics Unit, Indian Institute of Science Bangalore, C. V. Raman Road, Bangalore, Karnataka 560012, India.
Biophys Chem. 2024 Oct;313:107284. doi: 10.1016/j.bpc.2024.107284. Epub 2024 Jun 21.
Understanding the thermodynamic and kinetic properties of biomolecules requires elucidation of their complex energy landscape. A disconnectivity graph analysis of the energy landscape provides a framework for mapping the multi-dimensional landscape onto a two-dimensional representation while preserving the key features of the energy landscape. Several studies show that the structure or shape of the disconnectity graph is directly associated with the function of protein and nucleic acid molecules. In this review, we discuss how disconnectivity analysis of the potential energy surface can be extended to lipid molecules to glean important information about membrane organization. The shape of the disconnectivity graphs can be used to predict the lateral organization of multi-component lipid bilayer. We hope that this review encourages the use of disconnectivity graphs routinely by membrane biophysicists to predict the lateral organization of lipids.
理解生物分子的热力学和动力学性质需要阐明它们复杂的能量景观。能量景观的不连续性图分析为将多维景观映射到二维表示提供了一个框架，同时保留了能量景观的关键特征。几项研究表明，不连续性图的结构或形状与蛋白质和核酸分子的功能直接相关。在这篇综述中，我们讨论了如何将势能表面的不连续性分析扩展到脂质分子，以获取有关膜组织的重要信息。不连续性图的形状可用于预测多组分脂质双层的侧向组织。我们希望这篇综述鼓励膜生物物理学家常规使用不连续性图来预测脂质的侧向组织。
