Department of Bioengineering, Stanford University, Stanford, California 94305, USA.
Department of Physics, Indian Institute of Technology Palakkad, Palakkad 678623, India.
Soft Matter. 2022 Feb 23;18(8):1653-1665. doi: 10.1039/d2sm00077f.
Curvature induced sorting of lipid membrane bound proteins has been widely studied through experiments that induce curvature variation in a giant unilamellar lipid-bilayer vesicle with adsorbed proteins by pulling thin cylindrical tethers. In the theoretical space, this has been supplemented with models that capture curvature dependent interaction between membrane and idealized protein particles, through free energy contributions. Many membrane proteins such as the BAR domain proteins are known to have extremely anisotropic shapes and soft interacting potentials, whereas the idealizations of protein particles explored in models have only assumed them as hard disk-like particles with curvature anisotropy. Here, we present a model of sorting of the proteins while including the effects of softness in their interaction potentials, shape anisotropy in the protein structure, and curvature anisotropy in the interactions with the membrane. This is based on a clean separation of free energy contributions from non-ideal fluid behavior of soft anisotropic particles and curvature interactions between proteins and membranes. We probe the behavior of the sorting function under limiting conditions and show that it converges to the previously derived models. In addition to this, we present a comparison of the variation in sorting ratio due to the observed variation in the shape parameter values in known membrane proteins. Finally, using published experimental data for membrane proteins, we perform fitting and derive model parameters. We observe that shape anisotropy adversely affects the sorting of proteins to a high curvature region, whereas curvature anisotropy and softer interaction between proteins favor sorting.
脂质膜结合蛋白的曲率诱导分选已通过实验广泛研究，该实验通过拉动薄的圆柱形系绳在吸附有蛋白质的巨大单分子层脂质双层泡囊上诱导曲率变化。在理论空间中，这通过自由能贡献来补充捕获膜和理想化蛋白质粒子之间曲率相关相互作用的模型。众所周知，许多膜蛋白，如 BAR 结构域蛋白，具有非常各向异性的形状和柔软的相互作用势，而模型中探索的理想化蛋白质粒子仅假设它们为具有曲率各向异性的硬圆盘状粒子。在这里，我们提出了一种在包括其相互作用势的柔软性、蛋白质结构的形状各向异性以及与膜相互作用的曲率各向异性的情况下对蛋白质进行分选的模型。这是基于从软各向异性粒子的非理想流体行为和蛋白质与膜之间的曲率相互作用中分离自由能贡献的干净分离。我们在极限条件下探测分选函数的行为，并表明它收敛于先前推导的模型。除此之外，我们还比较了由于已知膜蛋白中形状参数值的观察到的变化导致的分选比的变化。最后，使用膜蛋白的已发表实验数据，我们进行拟合并得出模型参数。我们观察到形状各向异性对蛋白质向高曲率区域的分选产生不利影响，而曲率各向异性和蛋白质之间更柔软的相互作用有利于分选。
