Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA; E-Mails:
Int J Mol Sci. 2010 Sep 29;11(10):3725-47. doi: 10.3390/ijms11103725.
Many cell functions in all living organisms rely on protein-based molecular recognition involving disorder-to-order transitions upon binding by molecular recognition features (MoRFs). A well accepted computational tool for identifying likely protein-protein interactions is sequence alignment. In this paper, we propose the combination of sequence alignment and disorder prediction as a tool to improve the confidence of identifying MoRF-based protein-protein interactions. The method of reverse sequence alignment is also rationalized here as a novel approach for finding additional interaction regions, leading to the concept of a retro-MoRF, which has the reversed sequence of an identified MoRF. The set of retro-MoRF binding partners likely overlap the partner-sets of the originally identified MoRFs. The high abundance of MoRF-containing intrinsically disordered proteins in nature suggests the possibility that the number of retro-MoRFs could likewise be very high. This hypothesis provides new grounds for exploring the mysteries of protein-protein interaction networks at the genome level.
许多生物的细胞功能依赖于基于蛋白质的分子识别，这种识别涉及到分子识别特征（MoRFs）结合后的无序到有序的转变。序列比对是一种识别可能的蛋白质-蛋白质相互作用的公认计算工具。在本文中，我们提出将序列比对和无序预测相结合，作为提高基于 MoRF 的蛋白质-蛋白质相互作用识别置信度的工具。我们还将反向序列比对方法合理化，将其作为寻找额外相互作用区域的新方法，从而提出了 retro-MoRF 的概念，即识别出的 MoRF 的反向序列。retro-MoRF 的结合伴侣集可能与最初识别出的 MoRF 的伴侣集重叠。自然界中含有 MoRF 的内在无序蛋白质的大量存在表明，retro-MoRF 的数量可能也非常多。这一假设为在基因组水平上探索蛋白质-蛋白质相互作用网络的奥秘提供了新的依据。
