Walter Luis J, Quoika Patrick K, Zacharias Martin
Center for Functional Protein Assemblies, Technical University of Munich, Ernst-Otto-Fischer-Str. 8, Garching 85748, Germany.
J Chem Inf Model. 2024 Apr 22;64(8):3465-3476. doi: 10.1021/acs.jcim.4c00212. Epub 2024 Apr 11.
Many biological functions are mediated by large complexes formed by multiple proteins and other cellular macromolecules. Recent progress in experimental structure determination, as well as in integrative modeling and protein structure prediction using deep learning approaches, has resulted in a rapid increase in the number of solved multiprotein assemblies. However, the assembly process of large complexes from their components is much less well-studied. We introduce a rapid computational structure-based (SB) model, GoCa, that allows to follow the assembly process of large multiprotein complexes based on a known native structure. Beyond existing SB Go̅-type models, it distinguishes between intra- and intersubunit interactions, allowing us to include coupled folding and binding. It accounts automatically for the permutation of identical subunits in a complex and allows the definition of multiple minima (native) structures in the case of proteins that undergo global transitions during assembly. The model is successfully tested on several multiprotein complexes. The source code of the GoCa program including a tutorial is publicly available on Github: https://github.com/ZachariasLab/GoCa. We also provide a web source that allows users to quickly generate the necessary input files for a GoCa simulation: https://goca.t38webservices.nat.tum.de.
许多生物学功能是由多种蛋白质和其他细胞大分子形成的大型复合物介导的。实验结构测定以及使用深度学习方法进行的整合建模和蛋白质结构预测方面的最新进展,导致已解析的多蛋白组装体数量迅速增加。然而,大型复合物从其组成成分进行组装的过程却鲜为人知。我们引入了一种基于结构的快速计算模型GoCa,它能够基于已知的天然结构追踪大型多蛋白复合物的组装过程。与现有的基于结构的Go̅型模型不同,它区分亚基内和亚基间的相互作用,使我们能够纳入耦合折叠和结合。它会自动考虑复合物中相同亚基的排列,并允许在组装过程中经历全局转变的蛋白质的情况下定义多个极小值(天然)结构。该模型已在几种多蛋白复合物上成功测试。包括教程在内的GoCa程序的源代码可在Github上公开获取:https://github.com/ZachariasLab/GoCa。我们还提供了一个网络资源,允许用户快速生成GoCa模拟所需的输入文件:https://goca.t38webservices.nat.tum.de。