Roy J. Carver Department of Biochemistry, Biophysics, and Molecular Biology, Iowa State University, Ames, Iowa.
Department of Structural, Geotechnical, and Building Engineering, Politecnico di Torino, Torino, Italy.
Biophys J. 2021 Nov 16;120(22):4955-4965. doi: 10.1016/j.bpj.2021.10.017. Epub 2021 Oct 21.
Hinge motions are essential for many protein functions, and their dynamics are important to understand underlying biological mechanisms. The ways that these motions are represented by various computational methods differ significantly. By focusing on a specific class of motion, we have developed a new hinge-domain anisotropic network model (hdANM) that is based on the prior identification of flexible hinges and rigid domains in the protein structure and the subsequent generation of global hinge motions. This yields a set of motions in which the relative translations and rotations of the rigid domains are modulated and controlled by the deformation of the flexible hinges, leading to a more restricted, specific view of these motions. hdANM is the first model, to our knowledge, that combines information about protein hinges and domains to model the characteristic hinge motions of a protein. The motions predicted with this new elastic network model provide important conceptual advantages for understanding the underlying biological mechanisms. As a matter of fact, the generated hinge movements are found to resemble the expected mechanisms required for the biological functions of diverse proteins. Another advantage of this model is that the domain-level coarse graining makes it significantly more computationally efficient, enabling the generation of hinge motions within even the largest molecular assemblies, such as those from cryo-electron microscopy. hdANM is also comprehensive as it can perform in the same way as the well-known protein dynamics models (anisotropic network model, rotations-translations of blocks, and nonlinear rigid block normal mode analysis), depending on the definition of flexible and rigid parts in the protein structure and on whether the motions are extrapolated in a linear or nonlinear fashion. Furthermore, our results indicate that hdANM produces more realistic motions as compared to the anisotropic network model. hdANM is an open-source software, freely available, and hosted on a user-friendly website.
铰链运动对于许多蛋白质功能至关重要,其动态对于理解潜在的生物学机制很重要。各种计算方法表示这些运动的方式有很大的不同。通过专注于特定类别的运动,我们开发了一种新的铰链域各向异性网络模型(hdANM),该模型基于蛋白质结构中柔性铰链和刚性域的预先识别,以及随后生成的全局铰链运动。这产生了一组运动,其中刚性域的相对平移和旋转由柔性铰链的变形调制和控制,从而对这些运动进行更受限、更具体的观察。据我们所知,hdANM 是第一个结合蛋白质铰链和结构域信息来模拟蛋白质特征铰链运动的模型。该新弹性网络模型预测的运动为理解潜在生物学机制提供了重要的概念优势。事实上,生成的铰链运动被发现类似于不同蛋白质的生物功能所需的预期机制。该模型的另一个优点是,基于域级的粗粒化使得它在计算效率上显著提高,即使在最大的分子组装体(如冷冻电子显微镜)中也能生成铰链运动。hdANM 还具有全面性,因为它可以根据蛋白质结构中柔性和刚性部分的定义以及运动是否以线性或非线性方式外推,以与著名的蛋白质动力学模型(各向异性网络模型、块的旋转平移和非线性刚性块正则模态分析)相同的方式执行。此外,我们的结果表明,与各向异性网络模型相比,hdANM 产生的运动更逼真。hdANM 是一个开源软件,免费提供,并托管在一个用户友好的网站上。