Current trends in α-helical membrane protein crystallization: An update

α-Helical membrane proteins (MPs) are the targets for many pharmaceutical drugs and play important roles in human physiology. In recent years, significant progress has been made in determining their atomic structure using X-ray crystallography. However, a major bottleneck in MP crystallography still remains, namely, the identification of conditions that give crystals that are suitable for structural determination. In 2008, we undertook an analysis of the crystallization conditions for 121 α-helical MPs to design a rationalized sparse matrix crystallization screen, MemGold. We now report an updated analysis that includes a further 133 conditions. The results reveal the current trends in α-helical MP crystallization with notable differences since 2008. The updated information has been used to design new crystallization and additive screens that should prove useful for both initial crystallization scouting and subsequent crystal optimization.     

How do point amino acid substitutions affect the protein structure?

In order to estimate the influence of point mutations on the protein structure, 552 pairs of structurally aligned proteins with pairwise sequence identities greater than 60% were analyzed. We selected all isolated point mismatches from these alignments. The statistics of local conformational changes corresponding to these mismatches was studied. This study revealed two surprising aspects: (a) only an extremely minor fraction (< 3%) of all observed mutations leads to significant changes in local conformations; (b) observed substitutions, which affect local conformation are more frequently those of similar (high scoring) amino acid pairs rather than the substitutions thought of as "hazardous" (low scoring), although the overall average score of the changing substitutions is still lower than the corresponding average score for the substitutions that leave the structure unchanged.     

Structural role of compensatory amino acid replacements in the α-synuclein protein

A subset of familial Parkinson's disease (PD) cases is associated with the presence of disease-causing point mutations in human α-synuclein [huAS(wt)], including A53T. Surprisingly, the human neurotoxic amino acid 53T is present in non-primate, wild-type sequences of α-synucleins, including that expressed by mice [mAS(wt)]. Because huAS(A53T) causes neurodegeneration when expressed in rodents, the amino acid changes between the wild-type human protein [huAS(wt)] and mAS(wt) might act as intramolecular suppressors of A53T toxicity in the mouse protein, restoring its physiological structure and function. The lack of structural information for mAS(wt) in aqueous solution has prompted us to conduct a comparative molecular dynamics study of huAS(wt), huAS(A53T), and mAS(wt) in water at 300 K. The calculations are based on an ensemble of nuclear magnetic resonance-derived huAS(wt) structures. huAS(A53T) turns out to be more flexible and less compact than huAS(wt). Its central (NAC) region, involved in fibril formation by the protein, is more solvent-exposed than that of the wild-type protein, in agreement with nuclear magnetic resonance data. The compactness of mAS(wt) is similar to that of the human protein. In addition, its NAC region is less solvent-exposed and more rigid than that of huAS(A53T). All of these features may be caused by an increase in the level of intramolecular interactions on passing from huAS(A53T) to mAS(wt). We conclude that the presence of "compensatory replacements" in the mouse protein causes a significant change in the protein relative to huAS(A53T), restoring features not too dissimilar to those of the human protein.     

Recognizing protein–protein interfaces with empirical potentials and reduced amino acid alphabets

Background  

In structural genomics, an important goal is the detection and classification of protein–protein interactions, given the structures of the interacting partners. We have developed empirical energy functions to identify native structures of protein–protein complexes among sets of decoy structures. To understand the role of amino acid diversity, we parameterized a series of functions, using a hierarchy of amino acid alphabets of increasing complexity, with 2, 3, 4, 6, and 20 amino acid groups. Compared to previous work, we used the simplest possible functional form, with residue–residue interactions and a stepwise distance-dependence. We used increased computational ressources, however, constructing 290,000 decoys for 219 protein–protein complexes, with a realistic docking protocol where the protein partners are flexible and interact through a molecular mechanics energy function. The energy parameters were optimized to correctly assign as many native complexes as possible. To resolve the multiple minimum problem in parameter space, over 64000 starting parameter guesses were tried for each energy function. The optimized functions were tested by cross validation on subsets of our native and decoy structures, by blind tests on series of native and decoy structures available on the Web, and on models for 13 complexes submitted to the CAPRI structure prediction experiment.     

Resonance assignments for Oncostatin M, a 24-kDa α-helical protein

Summary Oncostatin M (OM) is a cytokine that shares a structural and functional relationship with interleukin-6, leukemia inhibitory factor, and granulocyte-colony stimulating factor, which regulate the proliferation and differentiation of a variety of cell types. A mutant version of human OM in which two N-linked glycosylation sites and an unpaired cysteine have been mutated to alanine (N76A/C81A/N193A) has been expressed and shown to be active. The triple mutant has been doubly isotope-labeled with ¹³C and ¹⁵N in order to utilize heteronuclear multidimensional NMR techniques for structure determination. Approximately 90% of the backbone resonances were assigned from a combination of triple-resonance data (HNCA, HNCO, CBCACONH, HBHACONH, HNHA and HCACO), intraresidue and sequential NOEs (3D ¹⁵N-NOESY-HMQC and ¹³C-HSQC-NOESY) and side-chain information obtained from the CCONH and HCCONH experiments. Preliminary analysis of the NOE pattern in the ¹⁵N-NOESY-HMQC spectrum and the ¹³C secondary chemical shifts predicts a secondary structure for OM consisting of four -helices with three intervening helical regions, consistent with the four-helix-bundle motif found for this cytokine family. As a 203-residue protein with a molecular weight of 24 kDa, Oncostatin M is the largest -helical protein yet assigned.To whom correspondence should be addressed.     

Differences in properties between aromatic amino acid: Aromatic keto acid aminotransferases and aromatic amino acid: α-ketoglutarate aminotransferases

Homogenates of rat liver transaminate phenylpyruvate (PP), as well as α-ketoglutarate (α-KG), in the presence of L-tyrosine, 3,4-dihydroxyphenylalanine (L-DOPA) or L-tryptophan. Aminotransferase activity with phenylpyruvate and DOPA, but not with tyrosine, was inhibited by excess phenylpyruvate. Tyrosine and DOPA aminotransferase activities with phenylpyruvate were more heat stable than the corresponding activities with α-ketoglutarate. Aminotransferase activities with phenylpyruvate were not significantly induced following intraperitoneal injections of cortisol, glucagon or serotonin, compared with a 3 to 7-fold increase in the aminotransferase activities with α-ketoglutarate. Tyrosine:phenylpyruvate aminotransferase activity rose 40% at night, compared with a 300% increase in tyrosine:α-ketoglutarate aminotransferase activity. The results suggest that aminotransferases catalysing transfers between aromatic keto acids and aromatic amino acids are separate enzymes from those utilizing α-ketoglutarate as the acceptor keto acid.     

δ-Aminolaevulinic acid and amino acid neurotransmitters

Summary The effects of the porphyrin precursor -aminolaevulinic acid (ALA) on -aminobutyric acid (GABA) and L-glutamate transmitter systems was investigated in rat brain. It was found that ALA inhibited GABA and glutamate uptake and stimulated basal efflux of the amino acids in purified nerve endings. These effects were evident only at relatively high concentrations of ALA (at least 100 M). Such concentrations probably do not occur in the nervous systems of patients suffering from acute porphyria. In addition, it was found that ALA inhibited the stimulated release of GABA from nerve endings probably by acting as an agonist at GABA autoreceptors. This effect was found at very low concentrations of ALA (1 M). It is therefore likely that the neuropsychiatric manifestations of the acute porphyric attack are attributable, to some extent, to reduced GABA release at central synapses.     

Are the same or different amino acid residues responsible for correct and incorrect protein folding?

It has been shown for 20 proteins that amino acid residues included into the protein folding nucleus, determined experimentally, are often involved in the theoretically determined amyloidogenic fragments. For 18 proteins, Φ-values indicative of the extent of residue involvement into the folding nucleus are on average higher for amino acid residues within amyloidogenic regions. Amyloidogenic fragments were predicted for 20 proteins by two methods chosen from four on the basis of comparison of prediction of amyloidogenic regions known from experimental data. Since theoretical folding nuclei are detected by the protein three-dimensional structure and amyloidogenic regions by the protein chain primary structure, the detected regularity makes possible predictions of folding nucleation sites on the basis of amino acid sequence.     

Intramolecular distortion of the α-helical structure of polypeptides

Broadening of the infrared amide A, amide I and amide II bands of α-helical polypeptides has been observed for thermodynamically unstable α-helices. This spectroscopic fact can be explained now by the geometrical distortions of the backbone of the helical structure. Two models for distorted helices which include regular or irregular distortions of the angles of internal rotation of the main polypeptide chain have been considered. It is pointed out that the instability of α-helix is associated with irregular distortions of the polypeptide backbone.     

Effects of α-ketoglutarate on neutrophil intracellular amino and α-keto acid profiles and ROS production

The aim of this study was to determine the effects of α-ketoglutarate on neutrophil (PMN), free α-keto and amino-acid profiles as well as important reactive oxygen species (ROS) produced [superoxide anion (O₂ ^?), hydrogen peroxide (H₂O₂)] and released myeloperoxidase (MPO) acitivity. Exogenous α-ketoglutarate significantly increased PMN α-ketoglutarate, pyruvate, asparagine, glutamine, asparatate, glutamate, arginine, citrulline, alanine, glycine and serine in a dose as well as duration of exposure dependent manner. Additionally, in parallel with intracellular α-ketoglutarate changes, increases in O₂ ^– formation, H₂O₂-generation and MPO acitivity have also been observed. We therefore believe that α-ketoglutarate is important for affecting PMN “susceptible free amino- and α-keto acid pools” although important mechanisms and backgrounds are not yet completely explored. Moreover, our results also show very clearly that changes in intragranulocytic α-ketoglutarate levels are relevant metabolic determinants in PMN nutrition considerably influencing and modulating the magnitude and quality of the granulocytic host defense capability as well as production of ROS.     

Advances in protein–amino acid nutrition of poultry

The ideal protein concept has allowed progress in defining requirements as well as the limiting order of amino acids in corn, soybean meal, and a corn–soybean meal mixture for growth of young chicks. Recent evidence suggests that glycine (or serine) is a key limiting amino acid in reduced protein [23% crude protein (CP) reduced to 16% CP] corn–soybean meal diets for broiler chicks. Research with sulfur amino acids has revealed that small excesses of cysteine are growth depressing in chicks fed methionine-deficient diets. Moreover, high ratios of cysteine:methionine impair utilization of the hydroxy analog of methionine, but not of methionine itself. A high level of dietary l-cysteine (2.5% or higher) is lethal for young chicks, but a similar level of dl-methionine, l-cystine or N-acetyl-l-cysteine causes no mortality. A supplemental dietary level of 3.0% l-cysteine (7× requirement) causes acute metabolic acidosis that is characterized by a striking increase in plasma sulfate and decrease in plasma bicarbonate. S-Methylmethionine, an analog of S-adenosylmethionine, has been shown to have choline-sparing activity, but it only spares methionine when diets are deficient in choline and(or) betaine. Creatine, or its precursor guanidinoacetic acid, can spare dietary arginine in chicks.     

Combined chemical shift changes and amino acid specific chemical shift mapping of protein–protein interactions

Protein–protein interactions are often studied by chemical shift mapping using solution NMR spectroscopy. When heteronuclear data are available the interaction interface is usually predicted by combining the chemical shift changes of different nuclei to a single quantity, the combined chemical shift perturbation In this paper different procedures (published and non-published) to calculate are examined that include a variety of different functional forms and weighting factors for each nucleus. The predictive power of all shift mapping methods depends on the magnitude of the overlap of the chemical shift distributions of interacting and non-interacting residues and the cut-off criterion used. In general, the quality of the prediction on the basis of chemical shift changes alone is rather unsatisfactory but the combination of chemical shift changes on the basis of the Hamming or the Euclidian distance can improve the result. The corrected standard deviation to zero of the combined chemical shift changes can provide a reasonable cut-off criterion. As we show combined chemical shifts can also be applied for a more reliable quantitative evaluation of titration data.     

An information-theoretic classification of amino acids for the assessment of interfaces in protein–protein docking

Docking represents a versatile and powerful method to predict the geometry of protein–protein complexes. However, despite significant methodical advances, the identification of good docking solutions among a large number of false solutions still remains a difficult task. We have previously demonstrated that the formalism of mutual information (MI) from information theory can be adapted to protein docking, and we have now extended this approach to enhance its robustness and applicability. A large dataset consisting of 22,934 docking decoys derived from 203 different protein–protein complexes was used for an MI-based optimization of reduced amino acid alphabets representing the protein–protein interfaces. This optimization relied on a clustering analysis that allows one to estimate the mutual information of whole amino acid alphabets by considering all structural features simultaneously, rather than by treating them individually. This clustering approach is fast and can be applied in a similar fashion to the generation of reduced alphabets for other biological problems like fold recognition, sequence data mining, or secondary structure prediction. The reduced alphabets derived from the present work were converted into a scoring function for the evaluation of docking solutions, which is available for public use via the web service score-MI: http://score-MI.biochem.uni-erlangen.de     

Inhibition of protein kinase activity and amino acid and α-methyl-d-glucoside transport by diamide

Dizene dicarboxylic acid $\text{bis}\text{-(N,N-}\text{dimethylamide}\text{)}$, commonly called diamide, is known to oxidize stoichiometrically intracellular pools of reduced glutathione and inhibit the accumulation of sugars and amino acids by rat kidney slices. Incubation of rat renal cortical slices in diamide also leads to a significant decrease in the level of endogenous protein kinase activity. The inhibition of sugar and amino acid transport and protein kinase activity by diamide is partially reversible by the addition of exogenous glutathione or other thiols. A comparison of protein kinase activity with amino acid and sugar transport at various concentrations of diamide indicates that there is a high degree of correlation between these two processes.     

A guideline to proteome-wide α-helical membrane protein topology predictions

For current state-of-the-art methods, the prediction of correct topology of membrane proteins has been reported to be above 80%. However, this performance has only been observed in small and possibly biased data sets obtained from protein structures or biochemical assays. Here, we test a number of topology predictors on an "unseen" set of proteins of known structure and also on four "genome-scale" data sets, including one recent large set of experimentally validated human membrane proteins with glycosylated sites. The set of glycosylated proteins is also used to examine the ability of prediction methods to separate membrane from nonmembrane proteins. The results show that methods utilizing multiple sequence alignments are overall superior to methods that do not. The best performance is obtained by TOPCONS, a consensus method that combines several of the other prediction methods. The best methods to distinguish membrane from nonmembrane proteins belong to the "Phobius" group of predictors. We further observe that the reported high accuracies in the smaller benchmark sets are not quite maintained in larger scale benchmarks. Instead, we estimate the performance of the best prediction methods for eukaryotic membrane proteins to be between 60% and 70%. The low agreement between predictions from different methods questions earlier estimates about the global properties of the membrane proteome. Finally, we suggest a pipeline to estimate these properties using a combination of the best predictors that could be applied in large-scale proteomics studies of membrane proteins.