作者
Hua Cheng, R Dustin Schaeffer, Yuxing Liao, Lisa N Kinch, Jimin Pei, Shuoyong Shi, Bong-Hyun Kim, Nick V Grishin
发表日期
2014/12/4
期刊
PLoS computational biology
卷号
10
期号
12
页码范围
e1003926
出版商
Public Library of Science
简介
Understanding the evolution of a protein, including both close and distant relationships, often reveals insight into its structure and function. Fast and easy access to such up-to-date information facilitates research. We have developed a hierarchical evolutionary classification of all proteins with experimentally determined spatial structures, and presented it as an interactive and updatable online database. ECOD (Evolutionary Classification of protein Domains) is distinct from other structural classifications in that it groups domains primarily by evolutionary relationships (homology), rather than topology (or “fold”). This distinction highlights cases of homology between domains of differing topology to aid in understanding of protein structure evolution. ECOD uniquely emphasizes distantly related homologs that are difficult to detect, and thus catalogs the largest number of evolutionary links among structural domain classifications. Placing distant homologs together underscores the ancestral similarities of these proteins and draws attention to the most important regions of sequence and structure, as well as conserved functional sites. ECOD also recognizes closer sequence-based relationships between protein domains. Currently, approximately 100,000 protein structures are classified in ECOD into 9,000 sequence families clustered into close to 2,000 evolutionary groups. The classification is assisted by an automated pipeline that quickly and consistently classifies weekly releases of PDB structures and allows for continual updates. This synchronization with PDB uniquely distinguishes ECOD among all protein classifications. Finally, we present several …
引用总数
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学术搜索中的文章
H Cheng, RD Schaeffer, Y Liao, LN Kinch, J Pei, S Shi… - PLoS computational biology, 2014