Toulouse Biotechnology Institute, TBI, Université de Toulouse, CNRS, INRAE, INSA, Toulouse Cedex 04, France.
Methods Mol Biol. 2023;2553:57-77. doi: 10.1007/978-1-0716-2617-7_4.
Many biological molecules are assembled into supramolecular complexes that are necessary to perform functions in the cell. Better understanding and characterization of these molecular assemblies are thus essential to further elucidate molecular mechanisms and key protein-protein interactions that could be targeted to modulate the protein binding affinity or develop new binders. Experimental access to structural information on these supramolecular assemblies is often hampered by the size of these systems that make their recombinant production and characterization rather difficult. Computational methods combining both structural data, molecular modeling techniques, and sequence coevolution information can thus offer a good alternative to gain access to the structural organization of protein complexes and assemblies. Herein, we present some computational methods to predict structural models of the protein partners, to search for interacting regions using coevolution information, and to build molecular assemblies. The approach is exemplified using a case study to model the succinate-quinone oxidoreductase heterocomplex.
许多生物分子组装成超分子复合物,这些复合物对于在细胞中执行功能是必要的。因此,更好地理解和表征这些分子组装对于进一步阐明分子机制和关键的蛋白质-蛋白质相互作用至关重要,这些相互作用可以作为调节蛋白质结合亲和力或开发新结合物的靶点。实验获取这些超分子组装的结构信息通常受到这些系统的大小的限制,这使得它们的重组生产和表征变得相当困难。因此,结合结构数据、分子建模技术和序列共进化信息的计算方法为获得蛋白质复合物和组装体的结构组织提供了一个很好的替代方法。本文介绍了一些计算方法,用于预测蛋白质伴侣的结构模型,使用共进化信息搜索相互作用区域,并构建分子组装体。该方法使用琥珀酸-醌氧化还原酶异源复合物的案例研究进行了举例说明。