Novel feature for catalytic protein residues reflecting interactions with other residues

Owing to their potential for systematic analysis, complex networks have been widely used in proteomics. Representing a protein structure as a topology network provides novel insight into understanding protein folding mechanisms, stability and function. Here, we develop a new feature to reveal correlations between residues using a protein structure network. In an original attempt to quantify the effects of several key residues on catalytic residues, a power function was used to model interactions between residues. The results indicate that focusing on a few residues is a feasible approach to identifying catalytic residues. The spatial environment surrounding a catalytic residue was analyzed in a layered manner. We present evidence that correlation between residues is related to their distance apart most environmental parameters of the outer layer make a smaller contribution to prediction and ii catalytic residues tend to be located near key positions in enzyme folds. Feature analysis revealed satisfactory performance for our features, which were combined with several conventional features in a prediction model for catalytic residues using a comprehensive data set from the Catalytic Site Atlas. Values of 88.6 for sensitivity and 88.4 for specificity were obtained by 10-fold cross-validation. These results suggest that these features reveal the mutual dependence of residues and are promising for further study of structure-function relationship.     

Improving prediction of burial state of residues by exploiting correlation among residues

Background

Residues in a protein might be buried inside or exposed to the solvent surrounding the protein. The buried residues usually form hydrophobic cores to maintain the structural integrity of proteins while the exposed residues are tightly related to protein functions. Thus, the accurate prediction of solvent accessibility of residues will greatly facilitate our understanding of both structure and functionalities of proteins. Most of the state-of-the-art prediction approaches consider the burial state of each residue independently, thus neglecting the correlations among residues.

Results

In this study, we present a high-order conditional random field model that considers burial states of all residues in a protein simultaneously. Our approach exploits not only the correlation among adjacent residues but also the correlation among long-range residues. Experimental results showed that by exploiting the correlation among residues, our approach outperformed the state-of-the-art approaches in prediction accuracy. In-depth case studies also showed that by using the high-order statistical model, the errors committed by the bidirectional recurrent neural network and chain conditional random field models were successfully corrected.

Conclusions

Our methods enable the accurate prediction of residue burial states, which should greatly facilitate protein structure prediction and evaluation.

     

Sugar residues on proteins

Glycoproteins have become increasingly important in the structure and function of many different mammalian systems; for example, membrane glycoproteins and glycoprotein hormones. It is, therefore, important to understand their chemistry, which would include an understanding of both the carbohydrate and protein parts of the molecule. Since the chemical characterization of the protein moiety has been extensively examined and the techniques for its characterization are well worked out, only the carbohydrate portion of glycoproteins will be reviewed in this article. The chemical nature of the carbohydrate moiety of glycoproteins will be examined. First, the types of monosaccharides present in animal systems, especially those in the mammalian systems, will be described. Next, various types of simple and complex carbohydrate chains will be discussed to establish the diversity, size, and number of chains present in the carbohydrate units in different glycoproteins. Then, the type of linkages of the carbohydrate to the protein will be examined to determine if the primary sequence of protein is important in determining the size and type of carbohydrate chains present in glycoproteins. Finally, the current methods of structural elucidation such as monosaccharide sequence, intersugar bonds, and anomeric linkages in the carbohydrate moiety of glycoproteins will be reviewed. These methods include the techniques of periodate oxidation, methylation, partial acid hydrolysis, and specific glycosidase digestion of glycoproteins, as well as the latest techniques using micromethods of carbohydrate quantitation and characterization involving gas chromatography and mass spectrometry. The function of the carbohydrate in glycoproteins will also be considered. First, hormone glycoproteins will be discussed in their relationship to the immunological and biological function of the glycoprotein when the carbohydrate is sequentially removed. Next, the function of the carbohydrate in the turnover of glycoproteins will be discussed. These topics will be considered in order to develop an understanding of a specific function(s) of the carbohydrate in glycoproteins.     

Conservation of metal-coordinating residues

As a result of rapid advances in genome sequencing, the pace of discovery of new protein sequences has surpassed that of structure and function determination by orders of magnitude. This is also true for metal-binding proteins, that is, proteins that bind one or more metal atoms necessary for their biological function. While metal binding site geometry and composition have been extensively studied, no large scale investigation of metal-coordinating residue conservation has been pursued so far. In pursuing this analysis, we were able to corroborate anecdotal evidence that certain residues are preferred to others for binding to certain metals. The conservation of most metal-coordinating residues is correlated with residue preference in a statistically significant manner. Additionally, we also established a statistically significant difference in conservation between metal-coordinating and noncoordinating residues. These results could be useful for providing better insight to functional importance of metal-coordinating residues, possibly aiding metal binding site prediction and design, metal-protein complex structure prediction, drug discovery, as well as model fitting to electron-density maps produced by X-ray crystallography.     

Phytotoxicity from plant residues

Summary Proximity of new wheat straw residues to sown wheat seed has an effect on germination, plant growth and ultimate yield. Decomposition of wheat straw may produce toxins or it may cause immobilization of nitrogen in, or applied to the soil. In pot experiments, it has been shown that germination of wheat was depressed when large amounts of straw were decomposed on the surface for up to 18 days; after 54 days it had no effect on germination. Immobilization of nitrogen occurred mainly when the straw was mixed with the soil, or when surface-rotted straw was ploughed into the soil just before seeding. The latter effect could not be overcome by the addition of mineral nitrogen. Part II, Plant and Soil 38, 347–361 (1973).     

Phytotoxicity from plant residues

Summary Cold aqueous extracts of several grasses and legumes that had been rotted for periods up to 21 days have been shown to inhibit the growth of wheat grown under aseptic conditions. The degree of inhibition varied from one species to another and also with rotting period. Straws which were cut while still green produced a higher level of toxicity than those cut when fully matured. Growth of roots was inhibited more than that of shoots and generally the degree of inhibition decreased with time of rotting. All toxic extracts showed a trough in conductivity values during rotting. Values of pH increased with period of rotting, generally up to pH 8.0–8.5.Toxic extracts contained material of a large range of molecular weights. However, the most toxic material from extracts of rye straw rotted for 4 days had molecular weights from 10,000 to 50,000.Part I,Aust. J. agric. Res., 1967,18, 361.     

Improved performance by replacing iminodiacetic residues with glyceryl residues in symmetrically branched oligoglycerols

Synthesis of a symmetrically branched diglycerol (BGL002, involving one iminodiacetic residue) as a G2 dendron, and the tetradecaglycerol (BGL014, involving one iminodiacetic residue) as a G4 dendron, is described. Several members of the BGL family of G2-G4 dendrons were assembled, with G2 bearing four hydroxyl groups at the terminus region, G3 bearing eight, and G4 bearing sixteen. It is noteworthy that triglycerol (BGL003, including no iminodiacetic residue), has a water-solubility ten times higher than BGL002, and the liposome surrounded by BGL014 has a duration period in blood vessel roughly two times longer than the liposome surrounded by dodecaglycerol (BGL012, including three iminodiacetic residues).     

Mutational properties of amino acid residues: implications for evolvability of phosphorylatable residues

As Fran?ois Jacob pointed out over 30 years ago, evolution is a tinkering process, and, as such, relies on the genetic diversity produced by mutation subsequently shaped by Darwinian selection. However, there is one implicit assumption that is made when studying this tinkering process; it is typically assumed that all amino acid residues are equally likely to mutate or to result from a mutation. Here, by reconstructing ancestral sequences and computing mutational probabilities for all the amino acid residues, we refute this assumption and show extensive inequalities between different residues in terms of their mutational activity. Moreover, we highlight the importance of the genetic code and physico-chemical properties of the amino acid residues as likely causes of these inequalities and uncover serine as a mutational hot spot. Finally, we explore the consequences that these different mutational properties have on phosphorylation site evolution, showing that a higher degree of evolvability exists for phosphorylated threonine and, to a lesser extent, serine in comparison with tyrosine residues. As exemplified by the suppression of serine's mutational activity in phosphorylation sites, our results suggest that the cell can fine-tune the mutational activities of amino acid residues when they reside in functional protein regions.     

Phylogeny-independent detection of functional residues

MOTIVATION: Current projects for the massive characterization of proteomes are generating protein sequences and structures with unknown function. The difficulty of experimentally determining functionally important sites calls for the development of computational methods. The first techniques, based on the search for fully conserved positions in multiple sequence alignments (MSAs), were followed by methods for locating family-dependent conserved positions. These rely on the functional classification implicit in the alignment for locating these positions related with functional specificity. The next obvious step, still scarcely explored, is to detect these positions using a functional classification different from the one implicit in the sequence relationships between the proteins. Here, we present two new methods for locating functional positions which can incorporate an arbitrary external functional classification which may or may not coincide with the one implicit in the MSA. The Xdet method is able to use a functional classification with an associated hierarchy or similarity between functions to locate positions related to that classification. The MCdet method uses multivariate statistical analysis to locate positions responsible for each one of the functions within a multifunctional family. RESULTS: We applied the methods to different cases, illustrating scenarios where there is a disagreement between the functional and the phylogenetic relationships, and demonstrated their usefulness for the phylogeny-independent prediction of functional positions.     

Brodifacoum residues in possums (

The presence of brodifacoum residues in possum (Trichosurus vulpecula) livers following routine possum control was investigated. Possums were poisoned in six nature reserves in the Wellington Region, New Zealand, using cereal baits containing 20 mg kg(-1) brodifacoum dispensed from bait stations. Thirty-five surviving possums, and five dead possums were sampled from the reserves following poisoning, and their livers analysed for the presence of brodifacoum. The majority (83%) of samples contained brodifacoum at concentrations ranging from 0.007 mg kg(-1) to 6.2 mg kg(-1). The presence of significant quantities of brodifacoum in possum carcasses following poisoning operations creates potential for secondary and tertiary poisoning of non-target species.     

Structure-based identification of catalytic residues

The identification of catalytic residues is an essential step in functional characterization of enzymes. We present a purely structural approach to this problem, which is motivated by the difficulty of evolution-based methods to annotate structural genomics targets that have few or no homologs in the databases. Our approach combines a state-of-the-art support vector machine (SVM) classifier with novel structural features that augment structural clues by spatial averaging and Z scoring. Special attention is paid to the class imbalance problem that stems from the overwhelming number of non-catalytic residues in enzymes compared to catalytic residues. This problem is tackled by: (1) optimizing the classifier to maximize a performance criterion that considers both Type I and Type II errors in the classification of catalytic and non-catalytic residues; (2) under-sampling non-catalytic residues before SVM training; and (3) during SVM training, penalizing errors in learning catalytic residues more than errors in learning non-catalytic residues. Tested on four enzyme datasets, one specifically designed by us to mimic the structural genomics scenario and three previously evaluated datasets, our structure-based classifier is never inferior to similar structure-based classifiers and comparable to classifiers that use both structural and evolutionary features. In addition to the evaluation of the performance of catalytic residue identification, we also present detailed case studies on three proteins. This analysis suggests that many false positive predictions may correspond to binding sites and other functional residues. A web server that implements the method, our own-designed database, and the source code of the programs are publicly available at http://www.cs.bgu.ac.il/～meshi/functionPrediction.     

Puckering transitions of pseudoproline residues

The puckering transitions of pesudoprolines such as oxazolidine and thiazolidine residues (Oxa and Thz dipeptides) with trans and cis prolyl peptide bonds were explored by optimizations along the endocyclic torsion angle χ¹ using quantum‐chemical methods in the gas phase and in water. The overall shapes of the potential energy surfaces for Oxa and Thz dipeptides in the gas phase and in water are similar to those for the Pro dipeptide, although there are some differences in relative stabilities of local minima and in barriers to puckering transition. On the whole, the barriers to puckering transition for Oxa and Thz dipeptides are computed to be 0.8–3.2 kcal/mol at the B3LYP/6‐311++G(d,p) level in the gas phase and in water, which are lower by 0.5–1.9 kcal/mol than those for the Pro dipeptide. The n → σ* interactions for the delocalization of the lone pair of the prolyl amide nitrogen into the antibonding orbitals that are anti to the lone pair appear to play a role in stabilizing the nonplanar puckered transition states over the corresponding planar structures. The calculated barriers indicate that the down‐to‐up puckering transition can proceed in the orders Pro < Oxa < Thz in the gas phase and Pro ≈ Oxa < Thz in water. © 2009 Wiley Periodicals, Inc. Biopolymers 91: 444–455, 2009. This article was originally published online as an accepted preprint. The “Published Online” date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com