Mechanistic studies on chorismate mutase-prephenate dehydrogenase from E. coli

Chorismate mutase-prephenate dehydrogenase is a bifunctional enzyme that catalyzes two sequential reactions in the biosynthesis of tyrosine in E. coli and other enteric bacteria. Chorismate mutase catalyzes the pericyclic rearrangement of chorismate to prephenate which is subsequently converted to (4-hydroxyphenyl)pyruvate through an oxidative decarboxylation reaction catalyzed by prephenate dehydrogenase. Through chemical modification and site-directed mutagenesis we have identified residues that are critical in both the mutase and dehydrogenase mechanisms and have provided evidence that these two reactions occur at separate active sites on the enzyme. We have identified Lys37 as a residue that is important in the mutase reaction by differential peptide mapping. This result was confirmed by site-directed mutagenesis. The crystal structures of other chorismate mutases indicate that Lys37 may provide important hydrogen bonds in the transition state of the mutase reaction. We chemically modified mutase-dehydrogenase to show that a histidine is important for dehydrogenase activity. The pH rate profile for the dehydrogenase reaction indicates that a protonated residue is important for catalysis. By comparing the pH profile for wild-type and mutant mutase-dehydrogenase we have identified His197 as this catalytic group. Sequence alignments with other prephenate dehydrogenase enzymes show that this histidine is highly conserved. We propose that His197 may be the catalytic base involved in the hydride transfer from prephenate to NAD + . We have identified three positively charged residues, Lys178, Arg286 and Arg294, that are conserved amongst prephenate dehydrogenases from different organisms. We conducted site-directed mutagenesis on these residues and compared the wild-type enzyme and selected mutants with respect to their stability, pH rate profiles and ability to bind prephenate and a series of inhibitory substrate analogues. Our results indicate that Arg294 plays an important role in prephenate binding by interacting electrostatically with the ring carboxylate of the substrate. Our studies also show that a group with a p K of 8.8 interacts with the pyruvyl side chain carboxylate of prephenate. Further characterization of mutant proteins is being conducted to determine if this binding group is either Lys178 or Arg28

Identification of a functionally essential amino acid for Arabidopsis cyclic nucleotide gated ion channels using the chimeric AtCNGC11/12 gene

We used the chimeric Arabidopsis cyclic nucleotide-gated ion channel AtCNGC11/12 to conduct a structure-function study of plant cyclic nucleotide-gated ion channels (CNGCs). AtCNGC11/12 induces multiple pathogen resistance responses in the Arabidopsis mutant constitutive expresser of PR genes 22 (cpr22). A genetic screen for mutants that suppress cpr22-conferred phenotypes identified an intragenic mutant, #73, which has a glutamate to lysine substitution (E519K) at the beginning of the eighth β-sheet of the cyclic nucleotide-binding domain in AtCNGC11/12. The #73 mutant is morphologically identical to wild-type plants and has lost cpr22-related phenotypes including spontaneous cell death and enhanced pathogen resistance. Heterologous expression analysis using a K+-uptake-deficient yeast mutant revealed that this Glu519 is important for AtCNGC11/12 channel function, proving that the occurrence of cpr22 phenotypes requires active channel function of AtCNGC11/12. Additionally, Glu519 was also found to be important for the function of the wild-type channel AtCNGC12. Computational structural modeling and in vitro cAMP-binding assays suggest that Glu519 is a key residue for the structural stability of AtCNGCs and contributes to the interaction of the cyclic nucleotide-binding domain and the C-linker domain, rather than the binding of cAMP. Furthermore, a mutation in the α-subunit of the human cone receptor CNGA3 that causes total color blindness aligned well to the position of Glu519 in AtCNGC11/12. This suggests that AtCNGC11/12 suppressors could be a useful tool for discovering important residues not only for plant CNGCs but also for CNGCs in general. © 2008 The Authors

Heterologous Expression and Purification Systems for Structural Proteomics of Mammalian Membrane Proteins

Membrane proteins (MPs) are responsible for the interface between the exterior and the interior of the cell. These proteins are implicated in numerous diseases, such as cancer, cystic fibrosis, epilepsy, hyperinsulinism, heart failure, hypertension and Alzheimer's disease. However, studies on these disorders are hampered by a lack of structural information about the proteins involved. Structural analysis requires large quantities of pure and active proteins. The majority of medically and pharmaceutically relevant MPs are present in tissues at very low concentration, which makes heterologous expression in large-scale production-adapted cells a prerequisite for structural studies. Obtaining mammalian MP structural data depends on the development of methods that allow the production of large quantities of MPs. This review focuses on the different heterologous expression systems, and the purification strategies, used to produce large amounts of pure mammalian MPs for structural proteomics

Efficient Identification of Critical Residues Based Only on Protein Structure by Network Analysis

Despite the increasing number of published protein structures, and the fact that each protein's function relies on its three-dimensional structure, there is limited access to automatic programs used for the identification of critical residues from the protein structure, compared with those based on protein sequence. Here we present a new algorithm based on network analysis applied exclusively on protein structures to identify critical residues. Our results show that this method identifies critical residues for protein function with high reliability and improves automatic sequence-based approaches and previous network-based approaches. The reliability of the method depends on the conformational diversity screened for the protein of interest. We have designed a web site to give access to this software at http://bis.ifc.unam.mx/jamming/. In summary, a new method is presented that relates critical residues for protein function with the most traversed residues in networks derived from protein structures. A unique feature of the method is the inclusion of the conformational diversity of proteins in the prediction, thus reproducing a basic feature of the structure/function relationship of proteins

Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies

<p>Abstract</p> <p>Background</p> <p>All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloidosis would actually occur under physiological conditions depends largely on the amino acid composition of a protein. We explore using a naive Bayesian classifier and a weighted decision tree for predicting the amyloidogenicity of immunoglobulin sequences.</p> <p>Results</p> <p>The average accuracy based on leave-one-out (LOO) cross validation of a Bayesian classifier generated from 143 amyloidogenic sequences is 60.84%. This is consistent with the average accuracy of 61.15% for a holdout test set comprised of 103 AM and 28 non-amyloidogenic sequences. The LOO cross validation accuracy increases to 81.08% when the training set is augmented by the holdout test set. In comparison, the average classification accuracy for the holdout test set obtained using a decision tree is 78.64%. Non-amyloidogenic sequences are predicted with average LOO cross validation accuracies between 74.05% and 77.24% using the Bayesian classifier, depending on the training set size. The accuracy for the holdout test set was 89%. For the decision tree, the non-amyloidogenic prediction accuracy is 75.00%.</p> <p>Conclusions</p> <p>This exploratory study indicates that both classification methods may be promising in providing straightforward predictions on the amyloidogenicity of a sequence. Nevertheless, the number of available sequences that satisfy the premises of this study are limited, and are consequently smaller than the ideal training set size. Increasing the size of the training set clearly increases the accuracy, and the expansion of the training set to include not only more derivatives, but more alignments, would make the method more sound. The accuracy of the classifiers may also be improved when additional factors, such as structural and physico-chemical data, are considered. The development of this type of classifier has significant applications in evaluating engineered antibodies, and may be adapted for evaluating engineered proteins in general.</p

ePlant and the 3D Data Display Initiative: Integrative Systems Biology on the World Wide Web

Visualization tools for biological data are often limited in their ability to interactively integrate data at multiple scales. These computational tools are also typically limited by two-dimensional displays and programmatic implementations that require separate configurations for each of the user's computing devices and recompilation for functional expansion. Towards overcoming these limitations we have developed “ePlant” (http://bar.utoronto.ca/eplant) – a suite of open-source world wide web-based tools for the visualization of large-scale data sets from the model organism Arabidopsis thaliana. These tools display data spanning multiple biological scales on interactive three-dimensional models. Currently, ePlant consists of the following modules: a sequence conservation explorer that includes homology relationships and single nucleotide polymorphism data, a protein structure model explorer, a molecular interaction network explorer, a gene product subcellular localization explorer, and a gene expression pattern explorer. The ePlant's protein structure explorer module represents experimentally determined and theoretical structures covering >70% of the Arabidopsis proteome. The ePlant framework is accessed entirely through a web browser, and is therefore platform-independent. It can be applied to any model organism. To facilitate the development of three-dimensional displays of biological data on the world wide web we have established the “3D Data Display Initiative” (http://3ddi.org)

Evolutionary Diversification of Plant Shikimate Kinase Gene Duplicates

Shikimate kinase (SK; EC 2.7.1.71) catalyzes the fifth reaction of the shikimate pathway, which directs carbon from the central metabolism pool to a broad range of secondary metabolites involved in plant development, growth, and stress responses. In this study, we demonstrate the role of plant SK gene duplicate evolution in the diversification of metabolic regulation and the acquisition of novel and physiologically essential function. Phylogenetic analysis of plant SK homologs resolves an orthologous cluster of plant SKs and two functionally distinct orthologous clusters. These previously undescribed genes, shikimate kinase-like 1 (SKL1) and -2 (SKL2), do not encode SK activity, are present in all major plant lineages, and apparently evolved under positive selection following SK gene duplication over 400 MYA. This is supported by functional assays using recombinant SK, SKL1, and SKL2 from Arabidopsis thaliana (At) and evolutionary analyses of the diversification of SK-catalytic and -substrate binding sites based on theoretical structure models. AtSKL1 mutants yield albino and novel variegated phenotypes, which indicate SKL1 is required for chloroplast biogenesis. Extant SKL2 sequences show a strong genetic signature of positive selection, which is enriched in a protein–protein interaction module not found in other SK homologs. We also report the first kinetic characterization of plant SKs and show that gene expression diversification among the AtSK inparalogs is correlated with developmental processes and stress responses. This study examines the functional diversification of ancient and recent plant SK gene duplicates and highlights the utility of SKs as scaffolds for functional innovation

Synthesis, structural and solid-state, multinuclear magnetic resonance studies of some manganese and nickel complexes containing silicon, tin, lead and phosphorus ligands

A number of organometallic complexes involving manganese, bonded to silicon, tin, lead and phosphorus ligands, and nickel, bonded to various trialkylphosphine ligands, has been synthesized and their crystal structures, vibrational, and multinuclear magnetic resonance spectra have been obtained. The FT-IR and FT-Raman spectra of the manganese carbonyl compounds in the carbonyl region (2200--1850 cm--1) have been assigned. Solid-state, CP-MAS, 13C, 29Si, 31P, 117Sn, 119Sn and 207Pb NMR spectra of substituted pentacarbonylmanganese(I) and tetracarbonylmanganese(I) complexes feature asymmetric sextets, whereas those containing a group 14 (IVA) element bridging two pentacarbonylmanganese(I) moieties show asymmetric sextets. The uneven splitting arises from spin-spin coupling and second-order quadrupole-dipole effects, which are not eliminated by magic angle spinning. The solid-state NMR spectra of the manganese complexes have been analyzed to give the isotropic chemical shifts, the chemical shift tensors, one-bond spin-spin coupling constants, 55Mn nuclear quadrupole coupling constants, effective dipolar coupling constants and the anisotropies; in the spin-spin coupling for each complex. The results provide new insights into the relationship between spin-spin coupling and quadrupolar coupling in bimetallic complexes involving a quadrupole transition-metal and a spin-1/2 nucleus.For the para-substituted triaryltin complexes, the 13C, 55Mn and 119Sn chemical shifts and one-bond spin-spin constants in solution show excellent correlations with pairs of substituent constants (sigmaI, sigmaR). However, there is no correlation of the chemical shifts or spin-spin coupling with either Hammett (sigmaP) or Taft (sigmaP o) constants or the Mn-Sn bond lengths, rMn-Sn. The results obtained from dual substituent parameter (DSP) analysis indicate that both resonance effects (sigmaR) and inductive effects (sigma I) are important in determining the NMR parameters.Crystal structures and high-resolution solution and solid-state 31P NMR spectra were obtained for several dihalobis(trialkylphosphine)nickel(II) complexes. The crystal structures and NMR results indicate that these complexes are trans square-planar in the solid-state. The chemical shifts and shift tensors were obtained and found to vary with the electronic properties of the halogens. The 31P isotropic chemical shifts in the solution spectra of dibromo- and diiodiobis(tribenzylphosphine)nickel(II) are very different from those found for the solid-state, and chemical exchange effects were observed in all spectra. The mechanism of exchange appears to involve the formation of dimers with bridging halides