Sim Jaehyun, Sim Jun, Park Eunsung, Lee Julian
Department of Oral Microbiology and Immunology, School of Dentistry, Seoul National University, Seoul, 110-749, Korea.
Department of Bioinformatics and Life Science, Soongsil University, Seoul, 156-743, Korea.
Proteins. 2015 Jun;83(6):1054-67. doi: 10.1002/prot.24799. Epub 2015 Apr 22.
Many proteins undergo large-scale motions where relatively rigid domains move against each other. The identification of rigid domains, as well as the hinge residues important for their relative movements, is important for various applications including flexible docking simulations. In this work, we develop a method for protein rigid domain identification based on an exhaustive enumeration of maximal rigid domains, the rigid domains not fully contained within other domains. The computation is performed by mapping the problem to that of finding maximal cliques in a graph. A minimal set of rigid domains are then selected, which cover most of the protein with minimal overlap. In contrast to the results of existing methods that partition a protein into non-overlapping domains using approximate algorithms, the rigid domains obtained from exact enumeration naturally contain overlapping regions, which correspond to the hinges of the inter-domain bending motion. The performance of the algorithm is demonstrated on several proteins.
许多蛋白质会经历大规模运动,其中相对刚性的结构域会相互移动。识别刚性结构域以及对其相对运动重要的铰链残基,对于包括柔性对接模拟在内的各种应用都很重要。在这项工作中,我们开发了一种基于最大刚性结构域(即不完全包含在其他结构域内的刚性结构域)的穷举枚举来识别蛋白质刚性结构域的方法。通过将该问题映射到在图中寻找最大团的问题来进行计算。然后选择一组最小的刚性结构域,它们以最小的重叠覆盖了大部分蛋白质。与使用近似算法将蛋白质划分为非重叠结构域的现有方法的结果不同,通过精确枚举获得的刚性结构域自然包含重叠区域,这些区域对应于结构域间弯曲运动的铰链。该算法的性能在几种蛋白质上得到了验证。