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

Puri, Munish; Robin, Gautier; Cowieson, Nathan; Forwood, Jade K.; Listwan, Pawel; Hu, Shuhong; Gunčar, Gregor; Huber, Thomas; Kellie, Stuart; Hume, David; Kobe, Boštjan; Martin, Jennifer L.

doi:10.1016/j.bioeng.2006.09.002

Cited by 13 publications

(7 citation statements)

References 57 publications

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“…We screened several constructs of human BinCARD using a small-scale parallel processing approach that allowed us to rapidly identify which of these constructs could be produced in a soluble form (Puri et al, 2006). Two constructs met these criteria: BinCARD-CARD (residues 3-101, corresponding to the CARD fold common to both human BinCARD isoforms) and BinCARD-2-Á124-183 (equivalent to human BinCARD-2 residues 1-123 and lacking the transmembrane domain and C-terminal residues).…”

Section: Bincard-card Is Monomericmentioning

confidence: 99%

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

Chen

Richards

Caradoc-Davies

et al. 2013

Acta Crystallogr D Biol Crystallogr

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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.

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Section: Bincard-card Is Monomericmentioning

confidence: 99%

“…We are interested in the structure and function of proteins that play a role in immunity (Puri et al, 2006). Microarray experiments suggested that BinCARD mRNA was highly expressed in mouse macrophages.…”

Section: Introductionmentioning

confidence: 99%

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

Chen

Richards

Caradoc-Davies

et al. 2013

Acta Crystallogr D Biol Crystallogr

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“…This lectin is composed of four identical C-type carbohydraterecognition domains (CRDs). X-ray crystallographic analysis of CEL-IV revealed that its tetrameric structure was stabilized by multiple interchain disulfide bonds among the subunits [1]. Although CEL-IV has the EPN motif in its carbohydrate-binding sites, which is known to be characteristic of mannose binding C-type CRDs, it showed preferential binding of galactose and N-acetylgalactosamine.…”

Section: Ms50p13mentioning

confidence: 99%

Crystal structure of CEL-IV, isolated from a sea cucumber,Cucumaria echinata

Unno¹,

Hatakeyama²,

Kamiya³

et al. 2011

Acta Cryst Sect A

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novel, biologically interesting and crystallization-feasible targets that were then designed into 96 different constructs. Processing of the 96 constructs was performed in parallel using simple automated applications of ligation-independent cloning, small-scale bacterial expression and purification, and solubility assessment. After processing the 96 constructs of 12 targets, I found that 16 constructs of three targets (25%) yielded soluble protein. From the three soluble targets, I have spent most time on two of these protein.The first protein is a CARD domain containing protein that interacts with Bcl10. The primary function of Bcl10 is to interact with CARD proteins through CARD-CARD interactions to regulate its activity [2]. The crystal structure of this CARD containing protein solved at 1.5 Å resolution revealed six anti-parallel α-helices, showing that this protein is indeed similar to other CARD proteins with known structures. Approaches to determine the interaction between these two CARD domain containing proteins are currently being applied.The second protein I worked on is a DUF59 domain containing protein with no function characterized yet. However, it has been reported that a family member is part of the MMXD protein complex involved in chromosome segregation [3]. I solved two crystal structures of this DUF59 domain protein to 1.8 Å resolution revealing, unusually, two different types of domain swapped-dimer. Functional characterization of this DUF59 domain containing protein, and of its domain swapping, is currently being investigated.

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“…During the last decade, the number of known protein structures has increased enormously due to rapid advancement in structural genomics, which has inspired the development of various prediction tools for the characterization of novel protein sequences [ 8 ]. The SVM approach has been successfully applied to predict peptide features and to various types of protein classification/prediction methods including structure and function prediction.…”

Section: Introductionmentioning

confidence: 99%

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

Krishnan

Puri

Dikshit

et al. 2016

Advances in Bioinformatics

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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.

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

Cited by 13 publications

References 57 publications

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

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

Crystal structure of CEL-IV, isolated from a sea cucumber,Cucumaria echinata

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

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