Predicting function from structure: examples of the serine protease inhibitor canonical loop conformation found in extracellular proteins

Multi-Approach Analysis for the Identification of Proteases within Birch Pollen

Birch pollen allergy is highly prevalent, with up to 100 million reported cases worldwide. Proteases in such allergen sources have been suggested to contribute to primary sensitisation and exacerbation of allergic disorders. Until now the protease content of Betula verrucosa, a birch species endemic to the northern hemisphere has not been studied in detail. Hence, we aim to identify and characterise pollen and bacteria-derived proteases found within birch pollen. The pollen transcriptome was constructed via de novo transcriptome sequencing and analysis of the proteome was achieved via mass spectrometry; a cross-comparison of the two databases was then performed. A total of 42 individual proteases were identified at the proteomic level. Further clustering of proteases into their distinct catalytic classes revealed serine, cysteine, aspartic, threonine, and metallo-proteases. Further to this, protease activity of the pollen was quantified using a fluorescently-labelled casein substrate protease assay, as 0.61 ng/mg of pollen. A large number of bacterial strains were isolated from freshly collected birch pollen and zymographic gels with gelatinase and casein, enabled visualisation of proteolytic activity of the pollen and the collected bacterial strains. We report the successful discovery of pollen and bacteria-derived proteases of Betula verrucosa.

Fishing with (Proto)Net-a principled approach to protein target selection

Structural genomics strives to represent the entire protein space. The first step towards achieving this goal is by rationally selecting proteins whose structures have not been determined, but that represent an as yet unknown structural superfamily or fold. Once such a structure is solved, it can be used as a template for modelling homologous proteins. This will aid in unveiling the structural diversity of the protein space. Currently, no reliable method for accurate 3D structural prediction is available when a sequence or a structure homologue is not available. Here we present a systematic methodology for selecting target proteins whose structure is likely to adopt a new, as yet unknown superfamily or fold. Our method takes advantage of a global classification of the sequence space as presented by ProtoNet-3D, which is a hierarchical agglomerative clustering of the proteins of interest (the proteins in Swiss-Prot) along with all solved structures (taken from the PDB). By navigating in the scaffold of ProtoNet-3D, we yield a prioritized list of proteins that are not yet structurally solved, along with the probability of each of the proteins belonging to a new superfamily or fold. The sorted list has been self-validated against real structural data that was not available when the predictions were made. The practical application of using our computational–statistical method to determine novel superfamilies for structural genomics projects is also discussed.

HotPatch: a statistical approach to finding biologically relevant features on protein surfaces

We describe a fully automated algorithm for finding functional sites on protein structures. Our method finds surface patches of unusual physicochemical properties on protein structures, and estimates the patches' probability of overlapping functional sites. Other methods for predicting the locations of specific types of functional sites exist, but in previous analyses, it has been difficult to compare methods when they are applied to different types of sites. Thus, we introduce a new statistical framework that enables rigorous comparisons of the usefulness of different physicochemical properties for predicting virtually any kind of functional site. The program's statistical models were trained for 11 individual properties (electrostatics, concavity, hydrophobicity, etc.) and for 15 neural network combination properties, all optimized and tested on 15 diverse protein functions. To simulate what to expect if the program were run on proteins of unknown function, as might arise from structural genomics, we tested it on 618 proteins of diverse mixed functions. In the higher-scoring top half of all predictions, a functional residue could typically be found within the first 1.7 residues chosen at random. The program may or may not use partial information about the protein's function type as an input, depending on which statistical model the user chooses to employ. If function type is used as an additional constraint, prediction accuracy usually increases, and is particularly good for enzymes, DNA-interacting sites, and oligomeric interfaces. The program can be accessed online (at http://hotpatch.mbi.ucla.edu).

Expression, purification, crystallization and preliminary X-ray analysis of YaeQ (XAC2396) from Xanthomonas axonopodis pv. citri

Xanthomonas axonopodis pv. citri YaeQ (XAC2396) is a member of a family of bacterial proteins conserved in several Gram-negative pathogens. Here, the cloning, expression, purification and crystallization of the 182-residue (20.6 kDa) YaeQ protein are described. Recombinant YaeQ containing selenomethionine was crystallized in space group P2(1) and crystals diffracted to 1.9 A resolution at a synchrotron source. The unit-cell parameters are a = 39.75, b = 91.88, c = 48.03 A, beta = 108.37 degrees. The calculated Matthews coefficient suggests the presence of two YaeQ molecules in the asymmetric unit. Initial experimental phases were calculated by the multiple-wavelength anomalous dispersion technique and an interpretable electron-density map was obtained.

Potential folding-function interrelationship in proteins

The possibility is addressed that protein folding and function may be related via regions that are critical for both folding and function. This approach is based on the building blocks folding model that describes protein folding as binding events of conformationally fluctuating building blocks. Within these, we identify building block fragments that are critical for achieving the native fold. A library of such critical building blocks (CBBs) is constructed. Then, it is asked whether the functionally important residues fall in these CBB fragments. We find that for over two-thirds of the proteins in our library with available functional information, the catalytic or binding site residues lie within the CBB regions. From the evolutionary standpoint, a folding-function relationship is advantageous, since the need to guard against mutations is limited to one region. Furthermore, conformationally similar CBBs are found in globally unrelated proteins with different functions. Hence, substituting CBBs may lead to designed proteins with altered functions. We further find that the CBBs in our library are conformationally unstable.

High-throughput screening of structural proteomics targets using NMR

We applied a high-throughput strategy for the screening of targets for structural proteomics of Xanthomonas axonopodis pv citri. This strategy is based on the rapid (1)H-(15)N HSQC NMR analysis of bacterial lysates containing selectively (15)N-labelled heterologous proteins. Our analysis permitted us to classify the 19 soluble candidates in terms of 'foldedness', that is, the extent to which they present a well-folded solution structure, as reflected by the quality of their NMR spectra. This classification allowed us to define a priority list to be used as a guide to select protein candidates for further structural studies.