X-ray structure of a bifunctional protein kinase in complex with its protein substrate HPr

CcpA-dependent carbon catabolite repression in bacteria

Carbon catabolite repression (CCR) by transcriptional regulators follows different mechanisms in gram-positive and gram-negative bacteria. In gram-positive bacteria, CcpA-dependent CCR is mediated by phosphorylation of the phosphoenolpyruvate:sugar phosphotransferase system intermediate HPr at a serine residue at the expense of ATP. The reaction is catalyzed by HPr kinase, which is activated by glycolytic intermediates. In this review, the distribution of CcpA-dependent CCR among bacteria is investigated by searching the public databases for homologues of HPr kinase and HPr-like proteins throughout the bacterial kingdom and by analyzing their properties. Homologues of HPr kinase are commonly observed in the phylum Firmicutes but are also found in the phyla Proteobacteria, Fusobacteria, Spirochaetes, and Chlorobi, suggesting that CcpA-dependent CCR is not restricted to gram-positive bacteria. In the alpha and beta subdivisions of the Proteobacteria, the presence of HPr kinase appears to be common, while in the gamma subdivision it is more of an exception. The genes coding for the HPr kinase homologues of the Proteobacteria are in a gene cluster together with an HPr-like protein, termed XPr, suggesting a functional relationship. Moreover, the XPr proteins contain the serine phosphorylation sequence motif. Remarkably, the analysis suggests a possible relation between CcpA-dependent gene regulation and the nitrogen regulation system (Ntr) found in the gamma subdivision of the Proteobacteria. The relation is suggested by the clustering of CCR and Ntr components on the genome of members of the Proteobacteria and by the close phylogenetic relationship between XPr and NPr, the HPr-like protein in the Ntr system. In bacteria in the phylum Proteobacteria that contain HPr kinase and XPr, the latter may be at the center of a complex regulatory network involving both CCR and the Ntr system.

Solid state NMR sequential resonance assignments and conformational analysis of the 2x10.4 kDa dimeric form of the Bacillus subtilis protein Crh

Solid state NMR sample preparation and resonance assignments of the U-[13C,15N] 2x10.4 kDa dimeric form of the regulatory protein Crh in microcrystalline, PEG precipitated form are presented. Intra- and interresidue correlations using dipolar polarization transfer methods led to nearly complete sequential assignments of the protein, and to 88% of all 15N, 13C chemical shifts. For several residues, the resonance assignments differ significantly from those reported for the monomeric form analyzed by solution state NMR. Dihedral angles obtained from a TALOS-based statistical analysis suggest that the microcrystalline arrangement of Crh must be similar to the domain-swapped dimeric structure of a single crystal form recently solved using X-ray crystallography. For a limited number of protein residues, a remarkable doubling of the observed NMR resonances is observed indicative of local static or dynamic conformational disorder. Our study reports resonance assignments for the largest protein investigated by solid state NMR so far and describes the conformational dimeric variant of Crh with previously unknown chemical shifts.

Assessment of blind predictions of protein-protein interactions: current status of docking methods

The current status of docking procedures for predicting protein-protein interactions starting from their three-dimensional structure is assessed from a first major evaluation of blind predictions. This evaluation was performed as part of a communitywide experiment on Critical Assessment of PRedicted Interactions (CAPRI). Seven newly determined structures of protein-protein complexes were available as targets for this experiment. These were the complexes between a kinase and its protein substrate, between a T-cell receptor beta-chain and a superantigen, and five antigen-antibody complexes. For each target, the predictors were given the experimental structures of the free components, or of one free and one bound component in a random orientation. The structure of the complex was revealed only at the time of the evaluation. A total of 465 predictions submitted by 19 groups were evaluated. These groups used a wide range of algorithms and scoring functions, some of which were completely novel. The quality of the predicted interactions was evaluated by comparing residue-residue contacts and interface residues to those in the X-ray structures and by analyzing the fit of the ligand molecules (the smaller of the two proteins in the complex) or of interface residues only, in the predicted versus target complexes. A total of 14 groups produced predictions, ranking from acceptable to highly accurate for five of the seven targets. The use of available biochemical and biological information, and in one instance structural information, played a key role in achieving this result. It was essential for identifying the native binding modes for the five correctly predicted targets, including the kinase-substrate complex where the enzyme changes conformation on association. But it was also the cause for missing the correct solution for the two remaining unpredicted targets, which involve unexpected antigen-antibody binding modes. Overall, this analysis reveals genuine progress in docking procedures but also illustrates the remaining serious limitations and points out the need for better scoring functions and more effective ways for handling conformational flexibility.

ZDOCK predictions for the CAPRI challenge

The CAPRI Challenge is a blind test of protein-protein-docking algorithms that predict the complex structure from the crystal structures of the interacting proteins. We participated in both rounds of this blind test and submitted predictions for all seven targets, relying mainly on our Fast Fourier Transform based algorithm ZDOCK that combines shape complementarity, desolvation, and electrostatics. Our group made good predictions for three targets and had at least some success with three others. Implications of the treatment of prior biological information as well as contributions of manual inspection to docking predictions are also discussed.

Evaluation of the 3D-Dock protein docking suite in rounds 1 and 2 of the CAPRI blind trial

The 3D-Dock suite of programs has been used to make predictions for the seven targets in rounds 1 and 2 of the CAPRI method evaluation exercise. Some correct contacts were obtained in at least one prediction for four of seven targets. Target 06 was predicted very well, with an RMSD of the ligand after superimposition of the receptor of only 0.77 A. We investigate the performance of the various stages of the method, with the aim of finding where improvements need to be made, and in particular whether the manual interventions that were made were essential, and whether results of the level of accuracy obtained for target 06 may be expected with confidence.

Successful discrimination of protein interactions

We present results from the prediction of protein complexes associated with the first Critical Assessment of PRediction of Interactions (CAPRI) experiment. Our algorithm, SmoothDock, comprises four steps: (1) we perform rigid body docking using the program DOT, keeping the top 20,000 structures as ranked by surface complementarity; (2) we rerank these structures according to a free energy estimate that includes both desolvation and electrostatics and retain the top 2000 complexes; (3) we cluster the filtered complexes using a pairwise root-mean-square deviation (RMSD) criterion; (4) the 25 largest clusters are subject to a smooth docking discrimination algorithm where van der Waals forces are taken into account. We predicted targets 1, 6, and 7 with RMSDs of 9.5, 2.4, and 2.6 A, respectively. More importantly, from the perspective of biological applications, our approach consistently ranked the correct model first (i.e., with highest confidence). For target 5 we identified the binding region but not the correct orientation. Although we were able to find reasonable clusters for all targets, low-affinity complexes (K(d) < nM) were harder to discriminate. For four of seven targets, the top models predicted by our automated procedure were among the best communitywide predictions.

ICM-DISCO docking by global energy optimization with fully flexible side-chains

The ICM-DISCO (Docking and Interface Side-Chain Optimization) protein-protein-docking method is a direct stochastic global energy optimization from multiple starting positions of the ligand. The first step is performed by docking of a rigid all-atom ligand molecule to a set of soft receptor potentials precalculated on a 0.5 A grid from realistic solvent-corrected force-field energies. This step finds the correct solution as the lowest energy conformation in almost 100% of the cases in which interfaces do not change on binding. The second step is needed to deal with the induced changes and includes the global optimization of the interface side-chains of up to 400 best solutions. The CAPRI predictions were performed fully automatically with this method. Available experimental information was included as a filtering step to favor expected docking surfaces. In three of the seven proposed targets, the ICM-DISCO method found a good solution (>50% of correct contacts) within the five submitted models. The procedure is global and fully automated. We demonstrate that the algorithm handles the induced changes of surface side-chains but is less successful if the backbone undergoes large-scale rearrangements.

CAPRI: a Critical Assessment of PRedicted Interactions

CAPRI is a communitywide experiment to assess the capacity of protein-docking methods to predict protein-protein interactions. Nineteen groups participated in rounds 1 and 2 of CAPRI and submitted blind structure predictions for seven protein-protein complexes based on the known structure of the component proteins. The predictions were compared to the unpublished X-ray structures of the complexes. We describe here the motivations for launching CAPRI, the rules that we applied to select targets and run the experiment, and some conclusions that can already be drawn. The results stress the need for new scoring functions and for methods handling the conformation changes that were observed in some of the target systems. CAPRI has already been a powerful drive for the community of computational biologists who development docking algorithms. We hope that this issue of Proteins will also be of interest to the community of structural biologists, which we call upon to provide new targets for future rounds of CAPRI, and to all molecular biologists who view protein-protein recognition as an essential process.

GAPDOCK: a Genetic Algorithm Approach to Protein Docking in CAPRI round 1

As part of the first Critical Assessment of PRotein Interactions, round 1, we predict the structure of two protein-protein complexes, by using a genetic algorithm, GAPDOCK, in combination with surface complementarity, buried surface area, biochemical information, and human intervention. Among the five models submitted for target 1, HPr phosphocarrier protein (B. subtilis) and the hexameric HPr kinase (L. lactis), the best correctly predicts 17 of 52 interprotein contacts, whereas for target 2, bovine rotavirus VP6 protein-monoclonal antibody, the best model predicts 27 of 52 correct contacts. Given the difficult nature of the targets, these predictions are very encouraging and compare well with those obtained by other methods. Nevertheless, it is clear that there is a need for improved methods for distinguishing between "correct" and "plausible but incorrect" complexes.

Evaluation of protein docking predictions using Hex 3.1 in CAPRI rounds 1 and 2

This article describes and reviews our efforts using Hex 3.1 to predict the docking modes of the seven target protein-protein complexes presented in the CAPRI (Critical Assessment of Predicted Interactions) blind docking trial. For each target, the structure of at least one of the docking partners was given in its unbound form, and several of the targets involved large multimeric structures (e.g., Lactobacillus HPr kinase, hemagglutinin, bovine rotavirus VP6). Here we describe several enhancements to our original spherical polar Fourier docking correlation algorithm. For example, a novel surface sphere smothering algorithm is introduced to generate multiple local coordinate systems around the surface of a large receptor molecule, which may be used to define a small number of initial ligand-docking orientations distributed over the receptor surface. High-resolution spherical polar docking correlations are performed over the resulting receptor surface patches, and candidate docking solutions are refined by using a novel soft molecular mechanics energy minimization procedure. Overall, this approach identified two good solutions at rank 5 or less for two of the seven CAPRI complexes. Subsequent analysis of our results shows that Hex 3.1 is able to place good solutions within a list of <or=20 for four of the seven targets. This finding shows that useful in silico protein-protein docking predictions can now be made with increasing confidence, even for very large macromolecular complexes.

Prediction of the unknown: inspiring experience with the CAPRI experiment

We submitted predictions for all seven targets in the CAPRI experiment. For four targets, our submitted models included acceptable, medium accuracy predictions of the structures of the complexes, and for a fifth target we identified the location of the binding site of one of the molecules. We used a weighted-geometric docking algorithm in which contacts involving specified parts of the surfaces of either one or both molecules were up-weighted or down-weighted. The weights were based on available structural and biochemical data or on sequence analyses. The weighted-geometric docking proved very useful for five targets, improving the complementarity scores and the ranks of the nearly correct solutions, as well as their statistical significance. In addition, the weighted-geometric docking promoted formation of clusters of similar solutions, which include more accurate predictions.

Genome-wide studies of protein-protein interaction

Recent large-scale studies of protein complexes in yeast have demonstrated that the wide majority of proteins exist in the cell as parts of multicomponent assemblies, mostly novel and of unknown function. The structural and functional analysis of these complexes should be a priority for structural biologists in coming years. In silico methods such as docking simulations, which may contribute to this analysis, are being tested in the CAPRI community-wide experiment, which assesses blind predictions of the structure of protein-protein complexes.

Solution structure of the N-terminal amphitropic domain of Escherichia coli glucose-specific enzyme IIA in membrane-mimetic micelles

The N-terminal domain of enzyme IIA(Glc) of the Escherichia coli phosphoenolpyruvate:sugar phosphotransferase system confers amphitropism to the protein, allowing IIA(Glc) to shuttle between the cytoplasm and the membrane. To further understand this amphitropic protein, we have elucidated, by NMR spectroscopy, the solution structure of a synthetic peptide corresponding to the N-terminal domain of IIA(Glc). In water, this peptide is predominantly disordered, consistent with previous data obtained in the absence of membranes. In detergent micelles of dihexanoylphosphatidylglycerol (DHPG) or sodium dodecylsulfate (SDS), however, residues Phe 3-Val 10 of the peptide adopt a helical conformation in the ensemble of structures calculated on the basis of NOE-derived distance restraints. The root mean square deviations for superimposing the backbone atoms of the helical region are 0.18 A in DHPG and 0.22 A in SDS. The structure, chemical shifts, and spin-spin coupling constants all indicate that, of the four lysines in the N-terminal domain of IIA(Glc), only Lys 5 and Lys 7 in the amphipathic helical region interact with DHPG. In addition, the peptide-detergent interactions were investigated using intermolecular NOESY experiments. The aliphatic chains of anionic detergents DHPG, SDS, and 2,2-dimethyl-2-silapentane-5-sulfonate sodium salt (DSS) all showed intermolecular NOE cross-peaks to the peptide, providing direct evidence for the putative membrane anchor of IIA(Glc) in binding to the membrane-mimicking micelles.

Pyrophosphate-producing protein dephosphorylation by HPr kinase/phosphorylase: a relic of early life?

In most Gram-positive bacteria, serine-46-phosphorylated HPr (P-Ser-HPr) controls the expression of numerous catabolic genes ( approximately 10% of their genome) by acting as catabolite corepressor. HPr kinase/phosphorylase (HprK/P), the bifunctional sensor enzyme for catabolite repression, phosphorylates HPr, a phosphocarrier protein of the sugar-transporting phosphoenolpyruvate/glycose phosphotransferase system, in the presence of ATP and fructose-1,6-bisphosphate but dephosphorylates P-Ser-HPr when phosphate prevails over ATP and fructose-1,6-bisphosphate. We demonstrate here that P-Ser-HPr dephosphorylation leads to the formation of HPr and pyrophosphate. HprK/P, which binds phosphate at the same site as the beta phosphate of ATP, probably uses the inorganic phosphate to carry out a nucleophilic attack on the phosphoryl bond in P-Ser-HPr. HprK/P is the first enzyme known to catalyze P-protein dephosphorylation via this phospho-phosphorolysis mechanism. This reaction is reversible, and at elevated pyrophosphate concentrations, HprK/P can use pyrophosphate to phosphorylate HPr. Growth of Bacillus subtilis on glucose increased intracellular pyrophosphate to concentrations ( approximately 6 mM), which in in vitro tests allowed efficient pyrophosphate-dependent HPr phosphorylation. To effectively dephosphorylate P-Ser-HPr when glucose is exhausted, the pyrophosphate concentration in the cells is lowered to 1 mM. In B. subtilis, this might be achieved by YvoE. This protein exhibits pyrophosphatase activity, and its gene is organized in an operon with hprK.