Structure-based active site profiles for genome analysis and functional family subclassification.

In previous work, structure-based functional site descriptors, fuzzy functional forms (FFFs), were developed to recognize structurally conserved active sites in proteins. These descriptors identify members of protein families according to active-site structural similarity, rather than overall sequence or structure similarity. FFFs are defined by a minimal number of highly conserved residues and their three-dimensional arrangement. This approach is advantageous for function assignment across broad families, but is limited when applied to detailed subclassification within these families. In the work described here, we developed a method of three-dimensional, or structure-based, active-site profiling that utilizes FFFs to identify residues located in the spatial environment around the active site. Three-dimensional active-site profiling reveals similarities and differences among active sites across protein families. Using this approach, active-site profiles were constructed from known structures for 193 functional families, and these profiles were verified as distinct and characteristic. To achieve this result, a scoring function was developed that discriminates between true functional sites and those that are geometrically most similar, but do not perform the same function. In a large-scale retrospective analysis of human genome sequences, this profile score was shown to identify specific functional families correctly. The method is effective at recognizing the likely subtype of structurally uncharacterized members of the diverse family of protein kinases, categorizing sequences correctly that were misclassified by global sequence alignment methods. Subfamily information provided by this three-dimensional active-site profiling method yields key information for specific and selective inhibitor design for use in the pharmaceutical industry.

The EF-hand domain: a globally cooperative structural unit.

EF-hand Ca(2+)-binding proteins participate in both modulation of Ca(2+) signals and direct transduction of the ionic signal into downstream biochemical events. The range of biochemical functions of these proteins is correlated with differences in the way in which they respond to the binding of Ca(2+). The EF-hand domains of calbindin D(9k) and calmodulin are homologous, yet they respond to the binding of calcium ions in a drastically different manner. A series of comparative analyses of their structures enabled the development of hypotheses about which residues in these proteins control the calcium-induced changes in conformation. To test our understanding of the relationship between protein sequence and structure, we specifically designed the F36G mutation of the EF-hand protein calbindin D(9k) to alter the packing of helices I and II in the apoprotein. The three-dimensional structure of apo F36G was determined in solution by nuclear magnetic resonance spectroscopy and showed that the design was successful. Surprisingly, significant structural perturbations also were found to extend far from the site of mutation. The observation of such long-range effects provides clear evidence that four-helix EF-hand domains should be treated as a single globally cooperative unit. A hypothetical mechanism for how the long-range effects are transmitted is described. Our results support the concept of energetic and structural coupling of the key residues that are crucial for a protein's fold and function.

Protein tyrosine phosphatases: strategies for distinguishing proteins in a family containing multiple drug targets and anti-targets.

PTP1B, but also proteins that are essential to cell development and survival. The availability of sequences and representative structures for the PTP family allows better identification of anti-targets, closely related family members likely to cross-react with directed inhibitors. Eight PTP subfamilies, classified by active site information and overall PTP catalytic domain structure similarity, are reviewed here: 1) the tyrosine-specific PTPs, 2) the dual-specificity PTPs, 3) the cdc25 subclass; 4) the Pten subclass; 5) the myotubularins, 6) the PRL subclass, 7) the low molecular weight PTPs, and 8) the newly defined cdc14 subclass. PTP subfamily classification and structure information can be incorporated into design strategies aimed at identifying potent and selective small molecule inhibitors. The accumulating inhibition data for compounds screened against panels of PTPs is reviewed. The in vitro data can yield clues to specificity so that individual subfamilies can be matched with effective scaffolds to jumpstart lead design and reduce false starts.

Designing sequence to control protein function in an EF-hand protein.

The extent of conformational change that calcium binding induces in EF-hand proteins is a key biochemical property specifying Ca(2+) sensor versus signal modulator function. To understand how differences in amino acid sequence lead to differences in the response to Ca(2+) binding, comparative analyses of sequence and structures, combined with model building, were used to develop hypotheses about which amino acid residues control Ca(2+)-induced conformational changes. These results were used to generate a first design of calbindomodulin (CBM-1), a calbindin D(9k) re-engineered with 15 mutations to respond to Ca(2+) binding with a conformational change similar to that of calmodulin. The gene for CBM-1 was synthesized, and the protein was expressed and purified. Remarkably, this protein did not exhibit any non-native-like molten globule properties despite the large number of mutations and the nonconservative nature of some of them. Ca(2+)-induced changes in CD intensity and in the binding of the hydrophobic probe, ANS, implied that CBM-1 does undergo Ca(2+) sensorlike conformational changes. The X-ray crystal structure of Ca(2+)-CBM-1 determined at 1.44 A resolution reveals the anticipated increase in hydrophobic surface area relative to the wild-type protein. A nascent calmodulin-like hydrophobic docking surface was also found, though it is occluded by the inter-EF-hand loop. The results from this first calbindomodulin design are discussed in terms of progress toward understanding the relationships between amino acid sequence, protein structure, and protein function for EF-hand CaBPs, as well as the additional mutations for the next CBM design.

Synergistic computational and experimental proteomics approaches for more accurate detection of active serine hydrolases in yeast.

An analysis of the structurally and catalytically diverse serine hydrolase protein family in the Saccharomyces cerevisiae proteome was undertaken using two independent but complementary, large-scale approaches. The first approach is based on computational analysis of serine hydrolase active site structures; the second utilizes the chemical reactivity of the serine hydrolase active site in complex mixtures. These proteomics approaches share the ability to fractionate the complex proteome into functional subsets. Each method identified a significant number of sequences, but 15 proteins were identified by both methods. Eight of these were unannotated in the Saccharomyces Genome Database at the time of this study and are thus novel serine hydrolase identifications. Three of the previously uncharacterized proteins are members of a eukaryotic serine hydrolase family, designated as Fsh (family of serine hydrolase), identified here for the first time. OVCA2, a potential human tumor suppressor, and DYR-SCHPO, a dihydrofolate reductase from Schizosaccharomyces pombe, are members of this family. Comparing the combined results to results of other proteomic methods showed that only four of the 15 proteins were identified in a recent large-scale, "shotgun" proteomic analysis and eight were identified using a related, but similar, approach (neither identifies function). Only 10 of the 15 were annotated using alternate motif-based computational tools. The results demonstrate the precision derived from combining complementary, function-based approaches to extract biological information from complex proteomes. The chemical proteomics technology indicates that a functional protein is being expressed in the cell, while the computational proteomics technology adds details about the specific type of function and residue that is likely being labeled. The combination of synergistic methods facilitates analysis, enriches true positive results, and increases confidence in novel identifications. This work also highlights the risks inherent in annotation transfer and the use of scoring functions for determination of correct annotations.