Focusing in on structural genomics: The University of Queensland structural biology pipeline

BacHbpred: Support Vector Machine Methods for the Prediction of Bacterial Hemoglobin-Like Proteins

The recent upsurge in microbial genome data has revealed that hemoglobin-like (HbL) proteins may be widely distributed among bacteria and that some organisms may carry more than one HbL encoding gene. However, the discovery of HbL proteins has been limited to a small number of bacteria only. This study describes the prediction of HbL proteins and their domain classification using a machine learning approach. Support vector machine (SVM) models were developed for predicting HbL proteins based upon amino acid composition (AC), dipeptide composition (DC), hybrid method (AC + DC), and position specific scoring matrix (PSSM). In addition, we introduce for the first time a new prediction method based on max to min amino acid residue (MM) profiles. The average accuracy, standard deviation (SD), false positive rate (FPR), confusion matrix, and receiver operating characteristic (ROC) were analyzed. We also compared the performance of our proposed models in homology detection databases. The performance of the different approaches was estimated using fivefold cross-validation techniques. Prediction accuracy was further investigated through confusion matrix and ROC curve analysis. All experimental results indicate that the proposed BacHbpred can be a perspective predictor for determination of HbL related proteins. BacHbpred, a web tool, has been developed for HbL prediction.

Addition of magnesium chloride to enhance mono-dispersity of a coiled-coil recombinant mouse macrophage protein

X-ray crystallography for the determination of three-dimensional structures of protein macromolecules represents an important tool in function assignment of uncharacterized proteins. However, crystallisation is often difficult to achieve. A protein sample fully characterized in terms of dispersity may increase the likelihood of successful crystallisation by improving the predictability of the crystallisation process. To maximize the probability of crystallisation of a novel mouse macrophage protein (rMMP), target molecule was characterized and refined to improve monodispersity. Addition of MgCl2 at low concentrations resolves the rMMP into a monodisperse solution, and finally successful crystallization of rMMP was achieved. The effect of MgCl2 was studied using gel filtration chromatography and dynamic light scattering.

The structure of the caspase recruitment domain of BinCARD reveals that all three cysteines can be oxidized

The caspase recruitment domain (CARD) is present in death-domain superfamily proteins involved in inflammation and apoptosis. BinCARD is named for its ability to interact with Bcl10 and inhibit downstream signalling. Human BinCARD is expressed as two isoforms that encode the same N-terminal CARD region but which differ considerably in their C-termini. Both isoforms are expressed in immune cells, although BinCARD-2 is much more highly expressed. Crystals of the CARD fold common to both had low symmetry (space group P1). Molecular replacement was unsuccessful in this low-symmetry space group and, as the construct contains no methionines, first one and then two residues were engineered to methionine for MAD phasing. The double-methionine variant was produced as a selenomethionine derivative, which was crystallized and the structure was solved using data measured at two wavelengths. The crystal structures of the native and selenomethionine double mutant were refined to high resolution (1.58 and 1.40 Å resolution, respectively), revealing the presence of a cis-peptide bond between Tyr39 and Pro40. Unexpectedly, the native crystal structure revealed that all three cysteines were oxidized. The mitochondrial localization of BinCARD-2 and the susceptibility of its CARD region to redox modification points to the intriguing possibility of a redox-regulatory role.

Protein crystallization in restricted geometry: advancing old ideas for modern times in structural proteomics

In the structural genomics period traditional methods for protein crystallization have been eclipsed by automation using batch or vapor diffusion equilibration to find conditions conducive for protein crystal growth. Although many globular and soluble proteins predominantly from prokaryotes have been crystallized and their structures solved by high throughput approaches, the remaining difficult proteins require more systematic and reflective methods combining miniaturization and integration of modern and traditional crystallography techniques. One of these conventional methods is growing crystals in restricted geometry, which is a historically well-known concept and a practical technique under-used by today's crystallographers. This chapter presents practical guidelines to use capillaries for microbatch crystallization screening and counter-diffusion crystallization as valuable techniques to obtain protein crystals in confined volumes. The emphasis in the authors' application is to perform broad-based screening with a microgram amount of protein, optimize crystal growth in a supersaturation gradient, and undergo in situ x-ray data analysis for x-ray crystallography without invasive manipulation. Applications and concepts presented here bring to light future prerequisites for the next generation of automation for structural genomics.

Overview of the pipeline for structural and functional characterization of macrophage proteins at the university of queensland

This chapter describes the methodology adopted in a project aimed at structural and functional characterization of proteins that potentially play an important role in mammalian macrophages. The methodology that underpins this project is applicable to both small research groups and larger structural genomics consortia. Gene products with putative roles in macrophage function are identified using gene expression information obtained via DNA microarray technology. Specific targets for structural and functional characterization are then selected based on a set of criteria aimed at maximizing insight into function. The target proteins are cloned using a modification of Gateway cloning technology, expressed with hexa-histidine tags in E. coli, and purified to homogeneity using a combination of affinity and size exclusion chromatography. Purified proteins are finally subjected to crystallization trials and/or NMR-based screening to identify candidates for structure determination. Where crystallography and NMR approaches are unsuccessful, chemical cross-linking is employed to obtain structural information. This resulting structural information is used to guide cell biology experiments to further investigate the cellular and molecular function of the targets in macrophage biology. Jointly, the data sheds light on the molecular and cellular functions of macrophage proteins.

Fragment-based screening using X-ray crystallography and NMR spectroscopy

Approaches which start from a study of the interaction of very simple molecules (fragments) with the protein target are proving to be valuable additions to drug design. Fragment-based screening allows the complementarity between a protein active site and drug-like molecules to be rapidly and effectively explored, using structural methods. Recent improvements in the intensities of laboratory X-ray sources permits the collection of greater amounts of high-quality diffraction data and have been matched by developments in automation, crystallisation and data analysis. Developments in NMR screening, including the use of cryogenically cooled NMR probes and (19)F-containing reporter molecules have expanded the scope of this technique, while increasing the availability of binding site and quantitative affinity data for the fragments. Application of these methods has led to a greater knowledge of the chemical variety, structural features and energetics of protein-fragment interactions. While fragment-based screening has already been shown to reduce the timescales of the drug discovery process, a more detailed characterisation of fragment screening hits can reveal unexpected similarities between fragment chemotypes and protein active sites leading to improved understanding of the pharmacophores and the re-use of this information against other protein targets.