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Composite structural motifs of binding sites for delineating biological functions of proteins.

Kinjo AR, Nakamura H - PLoS ONE (2012)

Bottom Line: It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites.By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process.The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures.

View Article: PubMed Central - PubMed

Affiliation: Institute for Protein Research, Osaka University, Suita, Osaka, Japan. akinjo@protein.osaka-u.ac.jp

ABSTRACT
Most biological processes are described as a series of interactions between proteins and other molecules, and interactions are in turn described in terms of atomic structures. To annotate protein functions as sets of interaction states at atomic resolution, and thereby to better understand the relation between protein interactions and biological functions, we conducted exhaustive all-against-all atomic structure comparisons of all known binding sites for ligands including small molecules, proteins and nucleic acids, and identified recurring elementary motifs. By integrating the elementary motifs associated with each subunit, we defined composite motifs that represent context-dependent combinations of elementary motifs. It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites. By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process. It is shown that meta-composite motifs provide richer annotations of biological processes than sequence clusters. The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures.

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Characteristics of meta motif networks.A: Average counts of composite motifs or sequence clusters (denoted CM/SC), connected components (CC) as well as edges representing sharing of common elementary motifs (CEM) for non-polymer, protein and nucleic acid binding sites, common sequences (CS) and protein-protein interactions (PPI). B: The same counts for nodes and various edges, but only for the meta motifs for the UniProt keyword “Transcription” (corresponding to the diagrams in Fig. 6).
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pone-0031437-g007: Characteristics of meta motif networks.A: Average counts of composite motifs or sequence clusters (denoted CM/SC), connected components (CC) as well as edges representing sharing of common elementary motifs (CEM) for non-polymer, protein and nucleic acid binding sites, common sequences (CS) and protein-protein interactions (PPI). B: The same counts for nodes and various edges, but only for the meta motifs for the UniProt keyword “Transcription” (corresponding to the diagrams in Fig. 6).

Mentions: To evaluate the properties of networks of meta motifs more generally and more quantitatively, we identified the meta motif for each upper-most keyword in the hierarchy of the UniProt Biological process category, and compared various network characteristics of meta-composite motifs against those of meta-sequence motifs (Fig. 7). On average (Fig. 7A), meta-composite motifs include more nodes (i.e., composite motifs), more connected components, as well as more connections between nodes representing common sequences (identified by the UniProt accession) and protein-protein interactions, compared to both type-1 and type-2 meta-sequence motifs. In particular, the increased number of edges representing common sequences indicates that many identical proteins are split into different composite motifs. The same trend is also observed for a particular meta-composite motif obtained for the keyword “Transcription” (Fig. 7B). As expected, the type-1 meta-sequence motifs exhibit rather poor characteristics in most aspects because many homologs are grouped into large clusters so that differences in interaction states of proteins cannot be differentiated. While the type-2 meta-sequence motifs sometimes contain more edges for common elementary motifs, this is simply because many elementary motifs shared among homologous proteins are split into different sequence clusters irrespective of interaction states, which is reflected in the lower number of edges representing common sequences. Thus, the classification of proteins in terms of composite motifs allows us to inspect the organization of proteins involved in individual biological processes.


Composite structural motifs of binding sites for delineating biological functions of proteins.

Kinjo AR, Nakamura H - PLoS ONE (2012)

Characteristics of meta motif networks.A: Average counts of composite motifs or sequence clusters (denoted CM/SC), connected components (CC) as well as edges representing sharing of common elementary motifs (CEM) for non-polymer, protein and nucleic acid binding sites, common sequences (CS) and protein-protein interactions (PPI). B: The same counts for nodes and various edges, but only for the meta motifs for the UniProt keyword “Transcription” (corresponding to the diagrams in Fig. 6).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3275580&req=5

pone-0031437-g007: Characteristics of meta motif networks.A: Average counts of composite motifs or sequence clusters (denoted CM/SC), connected components (CC) as well as edges representing sharing of common elementary motifs (CEM) for non-polymer, protein and nucleic acid binding sites, common sequences (CS) and protein-protein interactions (PPI). B: The same counts for nodes and various edges, but only for the meta motifs for the UniProt keyword “Transcription” (corresponding to the diagrams in Fig. 6).
Mentions: To evaluate the properties of networks of meta motifs more generally and more quantitatively, we identified the meta motif for each upper-most keyword in the hierarchy of the UniProt Biological process category, and compared various network characteristics of meta-composite motifs against those of meta-sequence motifs (Fig. 7). On average (Fig. 7A), meta-composite motifs include more nodes (i.e., composite motifs), more connected components, as well as more connections between nodes representing common sequences (identified by the UniProt accession) and protein-protein interactions, compared to both type-1 and type-2 meta-sequence motifs. In particular, the increased number of edges representing common sequences indicates that many identical proteins are split into different composite motifs. The same trend is also observed for a particular meta-composite motif obtained for the keyword “Transcription” (Fig. 7B). As expected, the type-1 meta-sequence motifs exhibit rather poor characteristics in most aspects because many homologs are grouped into large clusters so that differences in interaction states of proteins cannot be differentiated. While the type-2 meta-sequence motifs sometimes contain more edges for common elementary motifs, this is simply because many elementary motifs shared among homologous proteins are split into different sequence clusters irrespective of interaction states, which is reflected in the lower number of edges representing common sequences. Thus, the classification of proteins in terms of composite motifs allows us to inspect the organization of proteins involved in individual biological processes.

Bottom Line: It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites.By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process.The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures.

View Article: PubMed Central - PubMed

Affiliation: Institute for Protein Research, Osaka University, Suita, Osaka, Japan. akinjo@protein.osaka-u.ac.jp

ABSTRACT
Most biological processes are described as a series of interactions between proteins and other molecules, and interactions are in turn described in terms of atomic structures. To annotate protein functions as sets of interaction states at atomic resolution, and thereby to better understand the relation between protein interactions and biological functions, we conducted exhaustive all-against-all atomic structure comparisons of all known binding sites for ligands including small molecules, proteins and nucleic acids, and identified recurring elementary motifs. By integrating the elementary motifs associated with each subunit, we defined composite motifs that represent context-dependent combinations of elementary motifs. It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites. By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process. It is shown that meta-composite motifs provide richer annotations of biological processes than sequence clusters. The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures.

Show MeSH
Related in: MedlinePlus