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ECOD: an evolutionary classification of protein domains.

Cheng H, Schaeffer RD, Liao Y, Kinch LN, Pei J, Shi S, Kim BH, Grishin NV - PLoS Comput. Biol. (2014)

Bottom Line: 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 case studies of homologous proteins not recorded in other classifications, illustrating the potential of how ECOD can be used to further biological and evolutionary studies.

View Article: PubMed Central - PubMed

Affiliation: Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.

ABSTRACT
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 case studies of homologous proteins not recorded in other classifications, illustrating the potential of how ECOD can be used to further biological and evolutionary studies.

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Number of ECOD H-groups containing 1 or more SCOP superfamily (blue) or CATH homologous superfamily(red).The majority contain only a single SCOP superfamily(88%) or CATH homologous superfamily (81%). The most merged (not shown) ECOD H-group is the Immunoglobulin-related domains, which contains 47 SCOP superfamilies and 81 CATH homologous superfamiles.
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pcbi-1003926-g003: Number of ECOD H-groups containing 1 or more SCOP superfamily (blue) or CATH homologous superfamily(red).The majority contain only a single SCOP superfamily(88%) or CATH homologous superfamily (81%). The most merged (not shown) ECOD H-group is the Immunoglobulin-related domains, which contains 47 SCOP superfamilies and 81 CATH homologous superfamiles.

Mentions: An ECOD H-group can contain more distant homologous links than the equivalent SCOP superfamily or CATH homologous superfamily. Although the majority of ECOD H-groups contain only a single SCOP superfamily (88%) or CATH homologous superfamily (81%), some H-groups contain many more (Fig. 3). For example, the Immunoglobulin-related and the Rossmann-related H-groups contain the most SCOP superfamiles (47 and 28, respectively) and CATH homologous superfamilies (81 and 40, respectively). Superfamilies were merged based on multiple high-scoring homologous links between domains. These merges reflect the homology between domain members of these previously split groups.


ECOD: an evolutionary classification of protein domains.

Cheng H, Schaeffer RD, Liao Y, Kinch LN, Pei J, Shi S, Kim BH, Grishin NV - PLoS Comput. Biol. (2014)

Number of ECOD H-groups containing 1 or more SCOP superfamily (blue) or CATH homologous superfamily(red).The majority contain only a single SCOP superfamily(88%) or CATH homologous superfamily (81%). The most merged (not shown) ECOD H-group is the Immunoglobulin-related domains, which contains 47 SCOP superfamilies and 81 CATH homologous superfamiles.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4256011&req=5

pcbi-1003926-g003: Number of ECOD H-groups containing 1 or more SCOP superfamily (blue) or CATH homologous superfamily(red).The majority contain only a single SCOP superfamily(88%) or CATH homologous superfamily (81%). The most merged (not shown) ECOD H-group is the Immunoglobulin-related domains, which contains 47 SCOP superfamilies and 81 CATH homologous superfamiles.
Mentions: An ECOD H-group can contain more distant homologous links than the equivalent SCOP superfamily or CATH homologous superfamily. Although the majority of ECOD H-groups contain only a single SCOP superfamily (88%) or CATH homologous superfamily (81%), some H-groups contain many more (Fig. 3). For example, the Immunoglobulin-related and the Rossmann-related H-groups contain the most SCOP superfamiles (47 and 28, respectively) and CATH homologous superfamilies (81 and 40, respectively). Superfamilies were merged based on multiple high-scoring homologous links between domains. These merges reflect the homology between domain members of these previously split groups.

Bottom Line: 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 case studies of homologous proteins not recorded in other classifications, illustrating the potential of how ECOD can be used to further biological and evolutionary studies.

View Article: PubMed Central - PubMed

Affiliation: Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.

ABSTRACT
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 case studies of homologous proteins not recorded in other classifications, illustrating the potential of how ECOD can be used to further biological and evolutionary studies.

Show MeSH