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Mol Endocrinol. 2001 May;15(5):681-94.

Evolution and classification of cystine knot-containing hormones and related extracellular signaling molecules.

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  • 1Division of Reproductive Biology Department of Gynecology and Obstetrics Stanford University School of Medicine Stanford, California 94305-5317, USA. aaron.hsueh@stanford.edu

Abstract

The cystine knot three-dimensional structure is found in many extracellular molecules and is conserved among divergent species. The identification of proteins with a cystine knot structure is difficult by commonly used pairwise alignments because the sequence homology among these proteins is low. Taking advantage of complete genome sequences in diverse organisms, we used a complementary approach of pattern searches and pairwise alignments to screen the predicted protein sequences of five model species (human, fly, worm, slime mold, and yeast) and retrieved proteins with low sequence homology but containing a typical cystine knot signature. Sequence comparison between proteins known to have a cystine knot three-dimensional structure (transforming growth factor-beta, glycoprotein hormone, and platelet-derived growth factor subfamily members) identified new crucial amino acid residues (two hydrophilic amino acid residues flanking cysteine 5 of the cystine knot). In addition to the well known members of the cystine knot superfamily, novel subfamilies of proteins (mucins, norrie disease protein, von Willebrand factor, bone morphogenetic protein antagonists, and slit-like proteins) were identified as putative cystine knot-containing proteins. Phylogenetic analysis revealed the ancient evolution of these proteins and the relationship between hormones [e.g. transforming growth factor-beta (TGFbeta)] and extracellular matrix proteins (e.g. mucins). They are absent in the unicellular yeast genome but present in nematode, fly, and higher species, indicating that the cystine knot structure evolved in extracellular signaling molecules of multicellular organisms. All data retrieved by this study can be viewed at http://hormone.stanford.edu/.

PMID:
11328851
[PubMed - indexed for MEDLINE]
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