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See detailResidue centrality, functionally important residues, and active site shape: analysis of enzyme and non-enzyme families.
del Sol Mesa, Antonio UL; Fujihashi, Hirotomo; Amoros, Dolors et al

in Protein science : a publication of the Protein Society (2006), 15(9), 2120-8

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 ... [more ▼]

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 non-enzyme 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 non-enzyme 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. [less ▲]

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See detailSELECTION OF REPRESENTATIVE PROTEIN DATA SETS
HOBOHM, U.; SCHARF, M.; Schneider, Reinhard UL et al

in Protein Science : A Publication of the Protein Society (1992), 1(3), 409-417

The Protein Data Bank currently contains about 600 data sets of three-dimensional protein coordinates determined by X-ray crystallography or NMR. There is considerable redundancy in the data base, as many ... [more ▼]

The Protein Data Bank currently contains about 600 data sets of three-dimensional protein coordinates determined by X-ray crystallography or NMR. There is considerable redundancy in the data base, as many protein pairs are identical or very similar in sequence. However, statistical analyses of protein sequence-structure relations require nonredundant data. We have developed two algorithms to extract from the data base representative sets of protein chains with maximum coverage and minimum redundancy. The first algorithm focuses on optimizing a particular property of the selected proteins and works by successive selection of proteins from an ordered list and exclusion of all neighbors of each selected protein. The other algorithm aims at maximizing the size of the selected set and works by successive thinning out of clusters of similar proteins. Both algorithms are generally applicable to other data bases in which criteria of similarity can be defined and relate to problems in graph theory. The largest nonredundant set extracted from the current release of the Protein Data Bank has 155 protein chains. In this set, no two proteins have sequence similarity higher than a certain cutoff (30% identical residues for aligned subsequences longer than 80 residues), yet all structurally unique protein families are represented. Periodically updated lists of representative data sets are available by electronic mail from the file server "netserv @ embl-heidelberg.de." The selection may be useful in statistical approaches to protein folding as well as in the analysis and documentation of the known spectrum of three-dimensional protein structures. [less ▲]

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See detailCOMPREHENSIVE SEQUENCE-ANALYSIS OF THE 182 PREDICTED OPEN READING FRAMES OF YEAST CHROMOSOME-III
BORK, P.; OUZOUNIS, C.; SANDER, C. et al

in Protein Science : A Publication of the Protein Society (1992), 1(12), 1677-1690

With the completion of the first phase of the European yeast genome sequencing project, the complete DNA sequence of chromosome III of Saccharomyces cerevisiae has become available (Oliver, S.G., et al ... [more ▼]

With the completion of the first phase of the European yeast genome sequencing project, the complete DNA sequence of chromosome III of Saccharomyces cerevisiae has become available (Oliver, S.G., et al., 1992, Nature 357, 38-46). We have tested the predictive power of computer sequence analysis on the 176 probable protein products of this chromosome, after exclusion of six problem cases. When the results of database similarity searches are pooled with prior knowledge, a likely function can be assigned to 42% of the proteins, and a predicted three-dimensional structure to a third of these (140% of the total). The function of the remaining 58% remains to be determined. Of these, about one-third have one or more probable transmembrane segments. Among the most interesting proteins with predicted functions are a new member of the type X polymerase family, a transcription factor with an N-terminal DNA-binding domain related to GAL4, a ''fork head'' DNA-binding domain previously known only in Drosophila and in mammals, and a putative methyltransferase. Our analysis increased the number of known significant sequence similarities on chromosome III by 13, to now 67. Although the near 40% success rate of identifying unknown protein function by sequence analysis is surprisingly high, the information gap between known protein sequences and unknown function is expected to widen and become a major bottleneck of genome projects in the near future. Based on the experience gained in this test study, we suggest that the development of an automated computer workbench for protein sequence analysis must be an important item in genome projects. [less ▲]

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