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Sialidase-like Asp-boxes: sequence-similar structures within different protein folds.

ABSTRACT: Sequence similarity is the most common measure currently used to infer homology between proteins. Typically, homologous protein domains show sequence similarity over their entire lengths. Here we identify Asp box motifs, initially found as repeats in sialidases and neuraminidases, in new structural and sequence contexts. These motifs represent significantly similar sequences, localized to beta hairpins within proteins that are otherwise different in sequence and three-dimensional structure. By performing a combined sequence- and structure-based analysis we detect Asp boxes in more than nine protein families, including bacterial ribonucleases, sulfite oxidases, reelin, netrins, some lipoprotein receptors, and a variety of glycosyl hydrolases. Although the function common to each of these proteins, if any, remains unclear, we discuss possible functions of Asp boxes on the basis of previously determined experimental results and discuss different evolutionary scenarios for the origin of Asp-box containing proteins.

SUBMITTER: Copley RR

PROVIDER: S-EPMC2373934 | biostudies-literature | 2001 Feb

REPOSITORIES: biostudies-literature

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Sialidase-like Asp-boxes: sequence-similar structures within different protein folds.

Copley R R RR Russell R B RB Russell R B RB Ponting C P CP

Protein science : a publication of the Protein Society 20010201 2

Sequence similarity is the most common measure currently used to infer homology between proteins. Typically, homologous protein domains show sequence similarity over their entire lengths. Here we identify Asp box motifs, initially found as repeats in sialidases and neuraminidases, in new structural and sequence contexts. These motifs represent significantly similar sequences, localized to beta hairpins within proteins that are otherwise different in sequence and three-dimensional structure. By p ...[more]

PMID: 11266614

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Project description:BACKGROUND: Most of the currently used methods for protein function prediction rely on sequence-based comparisons between a query protein and those for which a functional annotation is provided. A serious limitation of sequence similarity-based approaches for identifying residue conservation among proteins is the low confidence in assigning residue-residue correspondences among proteins when the level of sequence identity between the compared proteins is poor. Multiple sequence alignment methods are more satisfactory--still, they cannot provide reliable results at low levels of sequence identity. Our goal in the current work was to develop an algorithm that could help overcome these difficulties by facilitating the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures. RESULTS: Here we present StralSV (structure-alignment sequence variability), a new algorithm for detecting closely related structure fragments and quantifying residue frequency from tight local structure alignments. We apply StralSV in a study of the RNA-dependent RNA polymerase of poliovirus, and we demonstrate that the algorithm can be used to determine regions of the protein that are relatively unique, or that share structural similarity with proteins that would be considered distantly related. By quantifying residue frequencies among many residue-residue pairs extracted from local structural alignments, one can infer potential structural or functional importance of specific residues that are determined to be highly conserved or that deviate from a consensus. We further demonstrate that considerable detailed structural and phylogenetic information can be derived from StralSV analyses. CONCLUSIONS: StralSV is a new structure-based algorithm for identifying and aligning structure fragments that have similarity to a reference protein. StralSV analysis can be used to quantify residue-residue correspondences and identify residues that may be of particular structural or functional importance, as well as unusual or unexpected residues at a given sequence position. StralSV is provided as a web service at http://proteinmodel.org/AS2TS/STRALSV/.

Project description:Kinases that catalyze phosphorylation of sugars, called here sugar kinases, can be divided into at least three distinct nonhomologous families. The first is the hexokinase family, which contains many prokaryotic and eukaryotic sugar kinases with diverse specificities, including a new member, rhamnokinase from Salmonella typhimurium. The three-dimensional structure of hexokinase is known and can be used to build models of functionally important regions of other kinases in this family. The second is the ribokinase family, of unknown three-dimensional structure, and comprises pro- and eukaryotic ribokinases, bacterial fructokinases, the minor 6-phosphofructokinase 2 from Escherichia coli, 6-phosphotagatokinase, 1-phosphofructokinase, and, possibly, inosine-guanosine kinase. The third family, also of unknown three-dimensional structure, contains several bacterial and yeast galactokinases and eukaryotic mevalonate and phosphomevalonate kinases and may have a substrate binding region in common with homoserine kinases. Each of the three families of sugar kinases appears to have a distinct three-dimensional fold, since conserved sequence patterns are strikingly different for the three families. Yet each catalyzes chemically equivalent reactions on similar or identical substrates. The enzymatic function of sugar phosphorylation appears to have evolved independently on the three distinct structural frameworks, by convergent evolution. In addition, evolutionary trees reveal that (1) fructokinase specificity has evolved independently in both the hexokinase and ribokinase families and (2) glucose specificity has evolved independently in different branches of the hexokinase family. These are examples of independent Darwinian adaptation of a structure to the same substrate at different evolutionary times. The flexible combination of active sites and three-dimensional folds observed in nature can be exploited by protein engineers in designing and optimizing enzymatic function.

Dataset Information

Sialidase-like Asp-boxes: sequence-similar structures within different protein folds.

Publications

Sialidase-like Asp-boxes: sequence-similar structures within different protein folds.

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