Wu Min, Li Xiaoli, Kwoh Chee-Keong, Ng See-Kiong
School of Computer Engineering, Nanyang Technological University, Singapore.
BMC Bioinformatics. 2009 Jun 2;10:169. doi: 10.1186/1471-2105-10-169.
How to detect protein complexes is an important and challenging task in post genomic era. As the increasing amount of protein-protein interaction (PPI) data are available, we are able to identify protein complexes from PPI networks. However, most of current studies detect protein complexes based solely on the observation that dense regions in PPI networks may correspond to protein complexes, but fail to consider the inherent organization within protein complexes.
To provide insights into the organization of protein complexes, this paper presents a novel core-attachment based method (COACH) which detects protein complexes in two stages. It first detects protein-complex cores as the "hearts" of protein complexes and then includes attachments into these cores to form biologically meaningful structures. We evaluate and analyze our predicted protein complexes from two aspects. First, we perform a comprehensive comparison between our proposed method and existing techniques by comparing the predicted complexes against benchmark complexes. Second, we also validate the core-attachment structures using various biological evidence and knowledge.
Our proposed COACH method has been applied on two different yeast PPI networks and the experimental results show that COACH performs significantly better than the state-of-the-art techniques. In addition, the identified complexes with core-attachment structures are demonstrated to match very well with existing biological knowledge and thus provide more insights for future biological study.
在后基因组时代,如何检测蛋白质复合物是一项重要且具有挑战性的任务。随着蛋白质-蛋白质相互作用(PPI)数据量的不断增加,我们能够从PPI网络中识别蛋白质复合物。然而,目前大多数研究仅基于PPI网络中的密集区域可能对应蛋白质复合物这一观察来检测蛋白质复合物,却未能考虑蛋白质复合物内部的固有组织。
为了深入了解蛋白质复合物的组织情况,本文提出了一种基于核心-附件的新方法(COACH),该方法分两个阶段检测蛋白质复合物。它首先将蛋白质复合物核心检测为蛋白质复合物的“核心”,然后将附件纳入这些核心以形成具有生物学意义的结构。我们从两个方面评估和分析预测的蛋白质复合物。首先,通过将预测的复合物与基准复合物进行比较,我们对所提出的方法与现有技术进行了全面比较。其次,我们还使用各种生物学证据和知识验证了核心-附件结构。
我们提出的COACH方法已应用于两个不同的酵母PPI网络,实验结果表明COACH的性能明显优于现有技术。此外,所识别的具有核心-附件结构的复合物被证明与现有生物学知识非常匹配,从而为未来的生物学研究提供了更多见解。