Active site interactions in oligomeric structures of inorganic pyrophosphatases

Recent progress in studies of the mode of action of cytoplasmic inorganic pyrophosphatases is mainly due to the analysis of a dozen and a half structures of the apoenzyme, its complexes, and mutants. However, despite considerable research on the mechanism of action of these enzymes, many important problems remain unclear. Among them is the problem of active site interactions in oligomeric structures and their role in catalysis; this review focuses on this problem. The abundant experimental data requires generalization and comprehensive analysis. A characteristic feature of the spatial structure of inorganic pyrophosphatases is a flexible system of noncovalent interactions between protein groups penetrating the whole molecule of the oligomeric enzyme. Binding of metal ions, sulfate (an analog of the product of the enzymatic reaction), and affinity phosphorus-containing inhibitors at the active site or site-directed mutagenesis induce rearrangements in the set of hydrogen and ionic interactions, which change active site properties and in some instances, cause molecule asymmetry. In the trimeric form of Escherichia coli pyrophosphatase obtained by dissociation of a hexamer, active sites also interact with each other, which is manifested by negative cooperativity upon substrate binding. The association of trimers into the hexamer leads to perfect organization of active sites and to their coordinated functioning, probably due to the restoration of communication channels between the trimers.     

Active site model of cytochrome P-450 LM2

Based on (i) a detailed analysis of the physicochemical properties of selected benzphetamine derived substrates and (ii) the identification of Tyr-380 as active site residue trans to thiolate theoretical studies (computer aided molecular design) revealed a model of the substrate binding site of cytochrome P-450 LM2. The results indicate that substrates with a butterfly-like bulky conformation exhibit the highest intrinsic activity. Those substrates which preferably exist in an extended conformation are sterically hindered to intensively interact with the binding site which is demonstrated by computer graphics.     

Highly accurate method for ligand-binding site prediction in unbound state (apo) protein structures

This article describes a new method for predicting ligand-binding sites of proteins. The method involves calculating the van der Waals interaction energy between a protein and probes placed on the protein surface, and then clustering the probes with attractive interaction to find the energetically most favorable locus. In 80% (28/35) of the test cases, the ligand-binding site was successfully predicted on a ligand-bound protein structure, and in 77% (27/35) was successfully predicted on an unbound structure. Our method was used to successfully predict ligand-binding sites unaffected by induced-fit as long as its scales were not very large, and it contributed to a significant improvement in prediction with unbound state protein structures. This represents a significant advance over conventional methods in detecting ligand-binding sites on uncharacterized proteins. Moreover, our method can predict ligand-binding sites with a narrower locus than those achieved using conventional methods.     

Active site model for gamma-aminobutyrate aminotransferase explains substrate specificity and inhibitor reactivities.

A homology model for the pig isozyme of the pyridoxal phosphate-dependent enzyme gamma-aminobutyrate (GABA) aminotransferase has been built based mainly on the structure of dialkylglycine decarboxylase and on a multiple sequence alignment of 28 evolutionarily related enzymes. The proposed active site structure is presented and analyzed. Hypothetical structures for external aldimine intermediates explain several characteristics of the enzyme. In the GABA external aldimine model, the pro-S proton at C4 of GABA, which abstracted in the 1,3-azaallylic rearrangement interconverting the aldimine and ketimine intermediates, is oriented perpendicular to the plane of the pyridoxal phosphate ring. Lys 329 is in close proximity and is probably the general base catalyst for the proton transfer reaction. The carboxylate group of GABA interacts with Arg 192 and Lys 203, which determine the specificity of the enzyme for monocarboxylic omega-amino acids such as GABA. In the proposed structure for the L-glutamate external aldimine, the alpha-carboxylate interacts with Arg 445. Glu 265 is proposed to interact with this same arginine in the GABA external aldimine, enabling the enzyme to act on omega-amino acids in one half-reaction and on alpha-amino acids in the other. The reactivities of inhibitors are well explained by the proposed active site structure. The R and S isomers of beta-substituted phenyl and p-chlorophenyl GABA would bind in very different modes due to differential steric interactions, with the reactive S isomer leaving the orientation of the GABA moiety relatively unperturbed compared to that of the natural substrate. In our model, only the reactive S isomer of the mechanism-based inhibitor vinyl-GABA, an effective anti-epileptic drug known clinically as Vigabatrin, would orient the scissile C4-H bond perpendicular to the coenzyme ring plane and present the proton to Lys 329, the proposed general base catalyst of the reaction. The R isomer would direct the vinyl group toward Lys 329 and the C4-H bond toward Arg 445. The active site model presented provides a basis for site-directed mutagenesis and drug design experiments.     

Active site ligand stabilization of quaternary structures of glutamine synthetase from Escherichia coli

Auto-inactivated EScherichia coli glutamine synthetase contains 1 eq each of L-methionine-S-sulfoximine phosphate and ADP and 2 eq of Mn2+ tightly bound to the active site of each subunit of the dodecameric enzyme (Maurizi, M. R., and Ginsburg, A. (1982) J. Biol. Chem. 257, 4271-4278). Complete dissociation and unfolding in 6 M guanidine HCl at pH 7.2 and 37 degrees C requires greater than 4 h for the auto-inactivated enzyme complex (less than 1 min for uncomplexed enzyme). Release of ligands and dissociation and unfolding of the protein occur in parallel but follow non-first order kinetics, suggesting stable intermediates and multiple pathways for the dissociation reactions. Treatment of Partially inactivated glutamine synthetase (2-6 autoinactivated subunits/dodecamer) with EDTA and dithiobisnitrobenzoic acid at pH 8 modifies approximately 2 of the 4 sulfhydryl groups of unliganded subunits and causes dissociation of the enzyme to stable oligomeric intermediates with 4, 6, 8, and 10 subunits, containing equal numbers of uncomplexed subunits and autoinactivated subunits. With greater than 70% inactivated enzyme, no dissociation occurs under these conditions. Electron micrographs of oligomers, presented in the appendix (Haschemeyer, R. H., Wall, J. S., Hainfeld, J., and Maurizi, M. R., (1982) J. Biol. Chem. 257, 7252-7253) suggest that dissociation of partially liganded dodecamers occurs by cleavage of intra-ring subunit contacts across both hexagonal rings and that these intra-ring subunit contacts across both hexagonal rings and that these intra-ring subunit interactions are stabilized by active site ligand binding. Isolated tetramers (Mr = 200,000; s20,w = 9.5 S) retain sufficient native structure to express significant enzymatic activity; tetramers reassociate to dodecamers and show a 5-fold increase in activity upon removal of the thionitrobenzoate groups with 2-mercaptoethanol. Thus, the tight binding of ligands to the subunit active site strengthens both intra- and inter-subunit bonding domains in dodecameric glutamine synthetase.     

Thermodynamic electron equivalents model for bacterial yield prediction: modifications and comparative evaluations

Modifications are made to an earlier thermodynamic model (TEEM1) for prediction of maximum microbial yields from aerobic and anaerobic as well as heterotrophic and autotrophic growth. The revised model (TEEM2) corrects for lower yields found with aerobic oxidations of organic compounds where an oxygenase is involved and with growth on single-carbon (C1) compounds. TEEM1 and TEEM2 are based on energy release and consumption as determined from the reduction potential or Gibbs free energy of (1/2)-reaction reduction equations together with losses of energy during energy transfer. Energy transfer efficiency is a key parameter needed to make predictions with TEEM2, and was determined through evaluations with extensive data sets on aerobic heterotrophic yield available in the literature. For compounds following normal catabolic pathways, the best-fit value for energy transfer efficiency was 0.37, which permitted accurate predictions of growth with a precision of 15%-20% as determined by standard deviation. Using the same energy transfer efficiency, a similar precision, but somewhat less accuracy was found for organic compounds where oxidation involves an oxygenase (estimates 8% too high) and for C1 compounds (estimates 17% too high). In spite of the somewhat lower accuracy, the TEEM2 modifications resulted in improved predictions over TEEM1 and the comparison models.     

Active site studies of bovine alpha1-->3-galactosyltransferase and its secondary structure prediction

The catalytic domain of bovine alpha1-->3-galactosyltransferase (alpha3GalT), residues 80-368, have been cloned and expressed, in Escherichia coli. Using a sequential purification protocol involving a Ni(2+) affinity column followed by a UDP-hexanolamine affinity column, we have obtained a pure and active protein from the soluble fraction which catalyzes the transfer of galactose (Gal) from UDP-Gal to N-acetyllactosamine (LacNAc) with a specific activity of 0.69 pmol/min/ng. The secondary structural content of alpha3GalT protein was analyzed by Fourier transform infrared (FTIR) spectroscopy, which shows that the enzyme has about 35% beta-sheet and 22% alpha-helix. This predicted secondary structure content by FTIR spectroscopy was used in the protein sequence analysis algorithm, developed by the Biomolecular Engineering Research Center at Boston University and Tasc Inc., for the assignment of secondary structural elements to the amino acid sequence of alpha3GalT. The enzyme appears to have three major and three minor helices and five sheet-like structures. The studies on the acceptor substrate specificity of the enzyme, alpha3GalT, show that in addition to LacNAc, which is the natural substrate, the enzyme accepts various other disaccharides as substrates such as lactose and Gal derivatives, beta-O-methylgalactose and beta-D-thiogalactopyranoside, albeit with lower specific activities. There is an absolute requirement for Gal to be at the non-reducing end of the acceptor molecule which has to be beta1-->4-linked to a second residue that can be more diverse in structure. The kinetic parameters for four acceptor molecules were determined. Lactose binds and functions in a similar way as LacNAc. However, beta-O-methylgalactose and Gal do not bind as tightly as LacNAc or lactose, as their K(ia) and K(A) values indicate, suggesting that the second monosaccharide is critical for holding the acceptor molecule in place. The 2' and 4' hydroxyl groups of the receiving Gal moiety are important in binding. Even though there is large structural variability associated with the second residue of the acceptor molecule, there are constraints which do not allow certain Gal-R sugars to be good acceptors for the enzyme. The beta1-->4-linked residue at the second position of the acceptor molecule is preferred, but the interactions between the enzyme and the second residue are likely to be non-specific.     

Active site dynamics of acyl-chymotrypsin

The motions of water molecules, the acyl moiety, the catalytic triad, and the oxyanion binding site of acyl-chymotrypsin were studied by means of a stochastic boundary molecular dynamics simulation. A water molecule that could provide the nucleophilic OH^? for the deacylation stage of the catalysis was found to be trapped between the imidazole ring of His-57 and the carbonyl carbon of the acyl group. It makes a hydrogen bond with the N^ε2 of His-57 and is heldin place through a network of hydrogen-bonded water molecules in theactive site. The water molecule was found as close as 2.8 Å to the carbonyl carbon. This appears to be due to the constraints imposed by nonbonded interaction in the active site. Configurations were found in which one hydrogen of the trapped water shared a bifurcated hydrogen bond with His-57-N^ε2 and Ser-195-0^γ with the water oxygen very close to the carbonyl carbon. The existence of such a water molecule suggests that large movement of the His-57 imidazole ring between positions suitable for providing general-base catalyzed assistance and for providing general-acid catalyzed assistance may notbe required during the reaction. The simulation indicates that the side chains of residues involved in catalysis (i.e., His-57, Ser-195, and Asp-102) are significantly less flexible than other side chains in the protein. The 40% reduction in rms fluctuations is consistent with a comparable reduction calculated from the temperature factors obtained in the X-ray crystal-lographic data of γ-chymotrypsin. The greater rigidity of active site residues seems to result from interconnected hydrogen bonding networks among the residues and between the residues and the solvent water in the active site. © Wiley-Liss, Inc.     

Boosting phosphorylation site prediction with sequence feature-based machine learning

Protein phosphorylation is one of the essential posttranslation modifications playing a vital role in the regulation of many fundamental cellular processes. We propose a LightGBM-based computational approach that uses evolutionary, geometric, sequence environment, and amino acid-specific features to decipher phosphate binding sites from a protein sequence. Our method, while compared with other existing methods on 2429 protein sequences taken from standard Phospho.ELM (P.ELM) benchmark data set featuring 11 organisms reports a higher F₁ score = 0.504 (harmonic mean of the precision and recall) and ROC AUC = 0.836 (area under the curve of the receiver operating characteristics). The computation time of our proposed approach is much less than that of the recently developed deep learning-based framework. Structural analysis on selected protein sequences informs that our prediction is the superset of the phosphorylation sites, as mentioned in P.ELM data set. The foundation of our scheme is manual feature engineering and a decision tree-based classification. Hence, it is intuitive, and one can interpret the final tree as a set of rules resulting in a deeper understanding of the relationships between biophysical features and phosphorylation sites. Our innovative problem transformation method permits more control over precision and recall as is demonstrated by the fact that if we incorporate output probability of the existing deep learning framework as an additional feature, then our prediction improves (F₁ score = 0.546; ROC AUC = 0.849). The implementation of our method can be accessed at http://cse.iitkgp.ac.in/~pralay/resources/PPSBoost/ and is mirrored at https://cosmos.iitkgp.ac.in/PPSBoost .     

Bacterial start site prediction.

With the growing number of completely sequenced bacterial genes, accurate gene prediction in bacterial genomes remains an important problem. Although the existing tools predict genes in bacterial genomes with high overall accuracy, their ability to pinpoint the translation start site remains unsatisfactory. In this paper, we present a novel approach to bacterial start site prediction that takes into account multiple features of a potential start site, viz., ribosome binding site (RBS) binding energy, distance of the RBS from the start codon, distance from the beginning of the maximal ORF to the start codon, the start codon itself and the coding/non-coding potential around the start site. Mixed integer programing was used to optimize the discriminatory system. The accuracy of this approach is up to 90%, compared to 70%, using the most common tools in fully automated mode (that is, without expert human post-processing of results). The approach is evaluated using Bacillus subtilis, Escherichia coli and Pyrococcus furiosus. These three genomes cover a broad spectrum of bacterial genomes, since B.subtilis is a Gram-positive bacterium, E.coli is a Gram-negative bacterium and P. furiosus is an archaebacterium. A significant problem is generating a set of 'true' start sites for algorithm training, in the absence of experimental work. We found that sequence conservation between P. furiosus and the related Pyrococcus horikoshii clearly delimited the gene start in many cases, providing a sufficient training set.     

Signal peptide cleavage site prediction

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A novel sequence-based method for phosphorylation site prediction with feature selection and analysis

Phosphorylation is one of the most important post-translational modifications, and the identification of protein phosphorylation sites is particularly important for studying disease diagnosis. However, experimental detection of phosphorylation sites is labor intensive. It would be beneficial if computational methods are available to provide an extra reference for the phosphorylation sites. Here we developed a novel sequence-based method for serine, threonine, and tyrosine phosphorylation site prediction. Nearest Neighbor algorithm was employed as the prediction engine. The peptides around the phosphorylation sites with a fixed length of thirteen amino acid residues were extracted via a sliding window along the protein chains concerned. Each of such peptides was coded into a vector with 6,072 features, derived from Amino Acid Index (AAIndex) database, for the classification/detection. Incremental Feature Selection, a feature selection algorithm based on the Maximum Relevancy Minimum Redundancy (mRMR) method was used to select a compact feature set for a further improvement of the classification performance. Three predictors were established for identifying the three types of phosphorylation sites, achieving the overall accuracies of 66.64%, 66.11%% and 66.69%, respectively. These rates were obtained by rigorous jackknife cross-validation tests.