Here, we represent protein structures as residue interacting networks, which are assumed to involve a permanent flow of information between amino acids. By removal of nodes from the protein network, we identify fold centrally conserved residues, which are crucial for sustaining the shortest pathways and thus play key roles in long-range interactions. Analysis of seven protein families (myoglobins, G-protein-coupled receptors, the trypsin class of serine proteases, hemoglobins, oligosaccharide phosphorylases, nuclear receptor ligand-binding domains and retroviral proteases) confirms that experimentally many of these residues are important for allosteric communication.The agreement between the centrally conserved residues, which are key in preserving short path lengths, and residues experimentally suggested to mediate signaling further illustrates that topology plays an important role in network communication. Protein folds have evolved under constraints imposed by function. To maintain function, protein structures need to be robust to mutational events. On the other hand, robustness is accompanied by an extreme sensitivity at some crucial sites. Thus, here we propose that centrally conserved residues, whose removal increases the characteristic path length in protein networks, may relate to the system fragility.
The representation of protein structures as small-world networks facilitates the search for topological determinants, which may relate to functionally important residues. Here, we aimed to investigate the performance of residue centrality, viewed as a family fold characteristic, in identifying functionally important residues in protein families. Our study is based on 46 families, including 29 enzyme and 17 nonenzyme families. A total of 80% of these central positions corresponded to active site residues or residues in direct contact with these sites. For enzyme families, this percentage increased to 91%, while for nonenzyme families the percentage decreased substantially to 48%. A total of 70% of these central positions are located in catalytic sites in the enzyme families, 64% are in hetero-atom binding sites in those families binding hetero-atoms, and only 16% belong to protein-protein interfaces in families with protein-protein interaction data. These differences reflect the active site shape: enzyme active sites locate in surface clefts, hetero-atom binding residues are in deep cavities, while protein-protein interactions involve a more planar configuration. On the other hand, not all surface cavities or clefts are comprised of central residues. Thus, closeness centrality identifies functionally important residues in enzymes. While here we focus on binding sites, we expect to identify key residues for the integration and transmission of the information to the rest of the protein, reflecting the relationship between fold and function. Residue centrality is more conserved than the protein sequence, emphasizing the robustness of protein structures. Article published online ahead of print. Article and publication date are at http://www.proteinscience.org/cgi
http://www.fujirebio.co.jp/support/index.php (under construction).
The measurement of the spatial profile of root elongation needs to determine matching points between time-lapse images and calculate their displacement. These data have been obtained by laborious manual methods in the past. Some computer-based programs have been developed to improve the measurement, but they require many time-series digital images or sprinkling graphite particles on the root prior to image capture. Here, we have developed GrowthTracer, a new image-analysis program for the kinematic study of root elongation. GrowthTracer employs a multiresolution image matching method with a nonlinear filter called the critical point filter (CPF), which extracts critical points from images at each resolution and can determine precise matching points by analysis of only two intact images, without pre-marking by graphite particles. This program calculates the displacement of each matching point and determines the displacement velocity profile along the medial axis of the root. In addition, a manual input of distinct matching points increases the matching accuracy. We show a successful application of this novel program for the kinematic analysis of root growth in Arabidopsis thaliana.
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