Suppr超能文献

局部定义的蛋白质系统发育谱揭示了以前遗漏的蛋白质相互作用和功能关系。

Locally defined protein phylogenetic profiles reveal previously missed protein interactions and functional relationships.

作者信息

Kim Yohan, Subramaniam Shankar

机构信息

Department of Chemistry and Biochemistry, University of California at San Diego, La Jolla, California 92093-0505, USA.

出版信息

Proteins. 2006 Mar 1;62(4):1115-24. doi: 10.1002/prot.20830.

Abstract

Phylogenetic profiles encode patterns of presence or absence of genes across genomes, and these profiles can be used to assign functional relationships to nonhomologous pairs of proteins (Pellegrini et al., Proc Natl Acad Sci USA 1999;96:4284-4288). Although it is well known that many proteins were created from combinations of domains, most of the existing implementations of phylogenetic profiles do not consider this fact. Here, we introduce an extension that considers the multidomain nature of proteins and test the method against the known interaction data sets. Whereas earlier implementations associated one entire sequence with one protein phylogenetic profile (Single-Profile), our method instead breaks the sequence into a set of segments of predetermined size and constructs a separate profile for each segment (Multiple-Profile). The results show that the Multiple-Profile method performs as well as the Single-Profile method. However, the two methods share, surprisingly, a small fraction of their predictions, indicating that the Multiple-Profile method can detect known interactions missed by the Single-Profile method. Thus, the Multiple-Profile method can be used with other methods to determine functional relationships on a genome scale with wider coverage.

摘要

系统发育谱编码了跨基因组基因存在或缺失的模式,这些谱可用于为非同源蛋白质对指定功能关系(佩莱格里尼等人,《美国国家科学院院刊》1999年;96:4284 - 4288)。虽然众所周知许多蛋白质是由结构域组合而成,但系统发育谱的大多数现有实现方式并未考虑这一事实。在此,我们引入一种考虑蛋白质多结构域性质的扩展方法,并针对已知的相互作用数据集测试该方法。早期的实现方式是将一个完整序列与一个蛋白质系统发育谱相关联(单谱),而我们的方法则是将序列分解为一组预定大小的片段,并为每个片段构建一个单独的谱(多谱)。结果表明,多谱方法的表现与单谱方法相当。然而,令人惊讶的是,这两种方法只有一小部分预测结果相同,这表明多谱方法能够检测到单谱方法遗漏的已知相互作用。因此,多谱方法可与其他方法一起用于在更广泛覆盖的基因组规模上确定功能关系。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验