Biomedical subjects

Sara Cheek

Publications and source records attributed to Sara Cheek.

6 recordsLinked to original sources

PubMed2006

Structural classification of small, disulfide-rich protein domains.

Disulfide-rich domains are small protein domains whose global folds are stabilized primarily by the formation of disulfide bonds and, to a much lesser extent, by secondary structure and hydrophobic interactions. Disulfide-rich domains perform a wide variety of roles functioning as growth factors, toxins, enzyme inhibitors, hormones, pheromones, allergens, etc. These domains are commonly found both as independent (single-domain) proteins and as domains within larger polypeptides. Here, we present a comprehensive structural classification of approximately 3000 small, disulfide-rich protein domains. We find that these domains can be arranged into 41 fold groups on the basis of structural similarity. Our fold groups, which describe broader structural relationships than existing groupings of these domains, bring together representatives with previously unacknowledged similarities; 18 of the 41 fold groups include domains from several SCOP folds. Within the fold groups, the domains are assembled into families of homologs. We define 98 families of disulfide-rich domains, some of which include newly detected homologs, particularly among knottin-like domains. On the basis of this classification, we have examined cases of convergent and divergent evolution of functions performed by disulfide-rich proteins. Disulfide bonding patterns in these domains are also evaluated. Reducible disulfide bonding patterns are much less frequent, while symmetric disulfide bonding patterns are more common than expected from random considerations. Examples of variations in disulfide bonding patterns found within families and fold groups are discussed.

Amino Acid Sequence↗

PubMed2005

A comprehensive update of the sequence and structure classification of kinases.

BACKGROUND: A comprehensive update of the classification of all available kinases was carried out. This survey presents a complete global picture of this large functional class of proteins and confirms the soundness of our initial kinase classification scheme. RESULTS: The new survey found the total number of kinase sequences in the protein database has increased more than three-fold (from 17,310 to 59,402), and the number of determined kinase structures increased two-fold (from 359 to 702) in the past three years. However, the framework of the original two-tier classification scheme (in families and fold groups) remains sufficient to describe all available kinases. Overall, the kinase sequences were classified into 25 families of homologous proteins, wherein 22 families (approximately 98.8% of all sequences) for which three-dimensional structures are known fall into 10 fold groups. These fold groups not only include some of the most widely spread proteins folds, such as the Rossmann-like fold, ferredoxin-like fold, TIM-barrel fold, and antiparallel beta-barrel fold, but also all major classes (all alpha, all beta, alpha+beta, alpha/beta) of protein structures. Fold predictions are made for remaining kinase families without a close homolog with solved structure. We also highlight two novel kinase structural folds, riboflavin kinase and dihydroxyacetone kinase, which have recently been characterized. Two protein families previously annotated as kinases are removed from the classification based on new experimental data. CONCLUSION: Structural annotations of all kinase families are now revealed, including fold descriptions for all globular kinases, making this the first large functional class of proteins with a comprehensive structural annotation. Potential uses for this classification include deduction of protein function, structural fold, or enzymatic mechanism of poorly studied or newly discovered kinases based on proteins in the same family.

Algorithms↗

PubMed2005

EDD, a novel phosphotransferase domain common to mannose transporter EIIA, dihydroxyacetone kinase, and DegV.

Using a recently developed program (SCOPmap) designed to automatically assign new protein structures to existing evolutionary-based classification schemes, we identify a evolutionarily conserved domain (EDD) common to three different folds: mannose transporter EIIA domain (EIIA-man), dihydroxyacetone kinase (Dak), and DegV. Several lines of evidence support unification of these three folds into a single superfamily: statistically significant sequence similarity detected by PSI-BLAST; "closed structural grouping" using DALI Z-scores (each protein inside a group finds all other group members with scores higher than those to proteins outside the group) that includes only these proteins sharing a unique alpha-helical hairpin at the C-terminus and excludes all other proteins with similar topology; similar domain fusions connect Dak and DegV, and genomic neighborhood organizations connect Dak and EIIA-man. Finally, both Dak and EIIA-man perform similar phosphotransfer reactions, suggesting a phosphotransferase activity for the DegV-like family of proteins, whose function other than lipid binding revealed in the crystal structure remains unknown.

Amino Acid Sequence↗

PubMed2004

4SCOPmap: automated assignment of protein structures to evolutionary superfamilies.

BACKGROUND: Inference of remote homology between proteins is very challenging and remains a prerogative of an expert. Thus a significant drawback to the use of evolutionary-based protein structure classifications is the difficulty in assigning new proteins to unique positions in the classification scheme with automatic methods. To address this issue, we have developed an algorithm to map protein domains to an existing structural classification scheme and have applied it to the SCOP database. RESULTS: The general strategy employed by this algorithm is to combine the results of several existing sequence and structure comparison tools applied to a query protein of known structure in order to find the homologs already classified in SCOP database and thus determine classification assignments. The algorithm is able to map domains within newly solved structures to the appropriate SCOP superfamily level with approximately 95% accuracy. Examples of correctly mapped remote homologs are discussed. The algorithm is also capable of identifying potential evolutionary relationships not specified in the SCOP database, thus helping to make it better. The strategy of the mapping algorithm is not limited to SCOP and can be applied to any other evolutionary-based classification scheme as well. SCOPmap is available for download. CONCLUSION: The SCOPmap program is useful for assigning domains in newly solved structures to appropriate superfamilies and for identifying evolutionary links between different superfamilies.

Algorithms↗

PubMed2002

Sequence and structure classification of kinases.

Kinases are a ubiquitous group of enzymes that catalyze the phosphoryl transfer reaction from a phosphate donor (usually ATP) to a receptor substrate. Although all kinases catalyze essentially the same phosphoryl transfer reaction, they display remarkable diversity in their substrate specificity, structure, and the pathways in which they participate. In order to learn the relationship between structural fold and functional specificities in kinases, we have done a comprehensive survey of all available kinase sequences (>17,000) and classified them into 30 distinct families based on sequence similarities. Of these families, 19, covering nearly 98% of all sequences, fall into seven general structural folds for which three-dimensional structures are known. These fold groups include some of the most widespread protein folds, such as Rossmann fold, ferredoxin fold, ribonuclease H fold, and TIM beta/alpha-barrel. On the basis of this classification system, we examined the shared substrate binding and catalytic mechanisms as well as variations of these mechanisms in the same fold groups. Cases of convergent evolution of identical kinase activities occurring in different folds are discussed.

Amino Acid Sequence↗

PubMed2002

Crystal structures of E. coli nicotinate mononucleotide adenylyltransferase and its complex with deamido-NAD.

Nicotinamide/Nicotinate mononucleotide (NMN/NaMN) adenylyltransferase is an indispensable enzyme in both de novo biosynthesis and salvage of NAD+ and NADP+. In prokaryotes, it is absolutely required for cell survival, thus representing an attractive target for the development of new broad-spectrum antibacteria inhibitors. The crystal structures of E. coli NaMN adenylyltransferase (NMNAT) and its complex with deamido-NAD (NaAD) revealed that ligand binding causes large conformational changes in several loop regions around the active site. The enzyme specifically recognizes the deamidated pyridine nucleotide through interactions between nicotinate carboxylate with several protein main chain amides and a positive helix dipole. Comparison of E. coli NMNAT with those from archaeal organisms revealed extensive differences in the active site architecture, enzyme-ligand interaction mode, and bound dinucleotide conformations. The bacterial NaMN adenylyltransferase structures described here provide a foundation for structure-based design of specific inhibitors that may have therapeutic potential.

Amino Acid Sequence↗