ArticlePloS one2012
Composite structural motifs of binding sites for delineating biological functions of proteins.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A SNARE Protein Identification Method Based on iLearnPlus to Efficiently Solve the Data Imbalance Problem.Frontiers in genetics · 2021Article
- The archiving and dissemination of biological structure data.Current opinion in structural biology · 2016Review
- Identifying emerging motif in growing networks.PloS one · 2014Article
- Article
- GIRAF: a method for fast search and flexible alignment of ligand binding interfaces in proteins at atomic resolution.Biophysics (Nagoya-shi, Japan) · 2012Article
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2 authors.
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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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