An improved protein decoy set for testing energy functions for protein structure prediction

We have improved the original Rosetta centroid/backbone decoy set by increasing the number of proteins and frequency of near native models and by building on sidechains and minimizing clashes. The new set consists of 1,400 model structures for 78 different and diverse protein targets and provides a challenging set for the testing and evaluation of scoring functions. We evaluated the extent to which a variety of all-atom energy functions could identify the native and close-to-native structures in the new decoy sets. Of various implicit solvent models, we found that a solvent-accessible surface area-based solvation provided the best enrichment and discrimination of close-to-native decoys. The combination of this solvation treatment with Lennard Jones terms and the original Rosetta energy provided better enrichment and discrimination than any of the individual terms. The results also highlight the differences in accuracy of NMR and X-ray crystal structures: a large energy gap was observed between native and non-native conformations for X-ray structures but not for NMR structures.     

Representative transcript sets for evaluating a translational initiation sites predictor

Background  

Translational initiation site (TIS) prediction is a very important and actively studied topic in bioinformatics. In order to complete a comparative analysis, it is desirable to have several benchmark data sets which can be used to test the effectiveness of different algorithms. An ideal benchmark data set should be reliable, representative and readily available. Preferably, proteins encoded by members of the data set should also be representative of the protein population actually expressed in cellular specimens.     

Discrimination of native loop conformations in membrane proteins: decoy library design and evaluation of effective energy scoring functions

The recent determination of crystal structures for several important membrane proteins opens the way for comparative modeling of their membrane-spanning regions. However, the ability to predict correctly the structures of loop regions, which may be critical, for example, in ligand binding, remains a considerable challenge. To meet this challenge, accurate scoring methods have to discriminate between candidate conformations of an unknown loop structure. Some success in loop prediction has been reported for globular proteins; however, the proximity of membrane protein loops to the lipid bilayer casts doubt on the applicability of the same scoring methods to this problem. In this work, we develop "decoy libraries" of non-native folds generated, using the structures of two membrane proteins, with molecular dynamics and Monte Carlo techniques over a range of temperatures. We introduce a new approach for decoy library generation by constructing a flat distribution of conformations covering a wide range of Calpha-root-mean-square deviation (RMSD) from the native structure; this removes possible bias in subsequent scoring stages. We then score these decoy conformations with effective energy functions, using increasingly more cpu-intensive implicit solvent models, including (1) simple Coulombic electrostatics with constant or distance-dependent dielectrics; (2) atomic solvation parameters; (3) the effective energy function (EEF1) of Lazaridis and Karplus; (4) generalized Born/Analytical Continuum Solvent; and (5) finite-difference Poisson-Boltzmann energy functions. We show that distinction of native-like membrane protein loops may be achieved using effective energies with the assumption of a homogenous environment; thus, the absence of the adjacent lipid bilayer does not affect the scoring ability. In particular, the Analytical Continuum Solvent and finite-difference Poisson-Boltzmann energy functions are seen to be the most powerful scoring functions. Interestingly, the use of the uncharged states of ionizable sidechains is shown to aid prediction, particularly for the simplest energy functions.     

Protein decoy assembly using short fragments under geometric constraints

A small set of protein fragments can represent adequately all known local protein structure. This set of fragments, along with a construction scheme that assembles these fragments into structures, defines a discrete (relatively small) conformation space, which approximates protein structures accurately. We generate protein decoys by sampling geometrically valid structures from this conformation space, biased by the secondary structure prediction for the protein. Unlike other methods, secondary structure prediction is the only protein-specific information used for generating the decoys. Nevertheless, these decoys are qualitatively similar to those found by others. The method works well for all-alpha proteins, and shows promising results for alpha and beta proteins.     

Potential energy functions for protein design

Different potential energy functions have predominated in protein dynamics simulations, protein design calculations, and protein structure prediction. Clearly, the same physics applies in all three cases. The differences in potential energy functions reflect differences in how the calculations are performed. With improvements in computer power and algorithms, the same potential energy function should be applicable to all three problems. In this review, we examine energy functions currently used for protein design, and look to the molecular mechanics field for advances that could be used in the next generation of design algorithms. In particular, we focus on improved models of the hydrophobic effect, polarization and hydrogen bonding.     

EXProt--a database for EXPerimentally verified Protein functions

EXProt (database for EXPerimentally verified Protein functions) is a new non-redundant database containing protein sequences for which the function has been experimentally verified. It is a selection of 3976 entries from the Prokaryotes section of the EMBL Nucleotide Sequence Database, Release 66, and 375 entries from the Pseudomonas Community Annotation Project (PseudoCAP). The entries in EXProt all have a unique ID number and provide information about the organism, protein sequence, functional annotation, link to entry in original database, and if known, gene name and link to references in PubMed/Medline. The EXProt web page (http://www.cmbi.nl/EXProt) provides further details of the database and a link to a BLAST search (blastp & blastx) of the database. The EXProt entries are indexed in SRS (http://www.cmbi.nl/srs/) and can be searched by means of keywords. Authors can be reached by email (exprot(cmbi.kun.nl).     

Method for evaluating metabolic functions of drugs in bioartificial liver

Lidocaine and galactose loading tests were performed on a bioartificial liver (BAL), an extracorporeal medical device incorporating living hepatocytes in a cartridge without a transport barrier across the membranes. The concentration changes were analyzed using pharmacokinetic equations to evaluate the efficacy and limitation of the proposed method. Lidocaine and galactose were found to be suitable drugs for a quantitative evaluation of the BAL functions, as they did not interact with the plasma proteins or blood vessels, making their concentrations easy to determine. The drug concentration changes after drug loading were easily analyzed using pharmacokinetic equations, and the BAL functions quantitatively expressed by pharmacokinetic parameters, such as the clearance (CL) and galactose elimination capacity (GEC). In addition, these two drugs have already been used in clinical tests to evaluate human liver functions over long periods, and lidocaineCL values andGEC values reported for a normal human liver. Thus, a comparison of theCL andGEC values for theBAL and a natural liver revealed what proportion of normal liver functions could be replaced by the BAL.     

Effective energy functions for protein structure prediction

Protein structure prediction, fold recognition, homology modeling and design rely mainly on statistical effective energy functions. Although the theoretical foundation of such functions is not clear, their usefulness has been demonstrated in many applications. Molecular mechanics force fields, particularly when augmented by implicit solvation models, provide physical effective energy functions that are beginning to play a role in this area.     

Tests and confidence sets for comparing two mean residual life functions

The mean residual life function of a population gives an intuitive and interesting perspective on the aging process. Here we present new nonparametric methods for comparing mean residual life functions based on two independent samples. These methods have the flexibility to handle crossings of the functions and result in a new type of confidence set. We also discuss similar methods for comparison of median residual life functions.     

LeEix1 functions as a decoy receptor to attenuate LeEix2 signaling

The receptors for the fungal elicitor EIX (LeEix1 and LeEix2) belong to a class of leucine-rich repeat cell-surface glycoproteins with a signal for receptor-mediated endocytosis. Both receptors are able to bind the EIX elicitor while only the LeEix2 receptor mediates defense responses. We show that LeEix1 acts as a decoy receptor and attenuates EIX induced internalization and signaling of the LeEix2 receptor. We demonstrate that BAK1 binds LeEix1 but not LeEix2. In plants where BAK1 was silenced, LeEix1 was no longer able to attenuate plant responses to EIX, indicating that BAK1 is required for this attenuation. We suggest that LeEix1 functions as a decoy receptor for LeEix2, a function which requires the kinase activity of BAK1.Key words: LRR-RLP, LeEix, Bak1, decoy receptor, endocytosisLeucine-rich-repeat receptor proteins (LRR-RLPs) have been linked with defense response signaling in plants.^1–5 The tomato Cf genes which mediate resistance to Cladosporium fulvum encode LRR-RLPs. Additional LRR-RLPs include the tomato Verticillium (Ve) resistant proteins^6,7 and the LeEix proteins.⁸ The Eix receptors (LeEix1 and LeEix2) contain a signal for receptor-mediated endocytosis, which we have previously shown to be essential for proper induction of defense responses.^9,10 Both receptors are able to bind Eix, but only LeEix2 mediates EIX-induced defense.⁸ In a recent work we demonstrate that LeEix1 attenuates Eix-induced internalization and signaling, and heterodimerizes with LeEix2 upon application of Eix.¹¹ Our work further shows that the brassinosteroid co-receptor Bri-Associated Kinase 1 (BAK1) binds LeEix1 but not LeEix2. In BAK1-silenced plants, LeEix1 was no longer able to attenuate plant responses to Eix, indicating that BAK1 is required for this attenuation and leading to the hypothesis that LeEix1 functions as a decoy receptor for LeEix2.¹¹     

Designing potential energy functions for protein folding.

By following a consistent line of physical reasoning, some fundamental understanding about the foldability of proteins has been achieved. In recent years, this has led to the development of a number of successful algorithms for optimizing potential energy functions for folding protein models. The differences between the folding mechanisms of simple, contact-based lattice proteins and more traditional, realistic protein models, however, still call for further development of the potentials in addition to the optimization approaches.     

Orchestrating nuclear functions: ubiquitin sets the rhythm

The nucleus of the eukaryotic cell must carry out many functions simultaneously. These tasks include ensuring that the cell is continuously supplied with an appropriate, changing set of proteins on its way through cell divisions and differentiation. During these processes, the integrity of the genetic material must be maintained against a constant onslaught of damaging physiological and environmental factors. Fulfilling these complex tasks requires the dynamic integration and synchronization of different nuclear functions. Protein modification by ubiquitin is proving to be a crucial tool for nuclear functioning, and is emerging as a decisive mechanism that enables the concerted regulation of nuclear pathways.     

A phylogenetic comparative method for evaluating trait coevolution across two phylogenies for sets of interacting species

Evaluating trait correlations across species within a lineage via phylogenetic regression is fundamental to comparative evolutionary biology, but when traits of interest are derived from two sets of lineages that coevolve with one another, methods for evaluating such patterns in a dual‐phylogenetic context remain underdeveloped. Here, we extend multivariate permutation‐based phylogenetic regression to evaluate trait correlations in two sets of interacting species while accounting for their respective phylogenies. This extension is appropriate for both univariate and multivariate response data, and may use one or more independent variables, including environmental covariates. Imperfect correspondence between species in the interacting lineages can also be accommodated, such as when species in one lineage associate with multiple species in the other, or when there are unmatched taxa in one or both lineages. For both univariate and multivariate data, the method displays appropriate type I error, and statistical power increases with the strength of the trait covariation and the number of species in the phylogeny. These properties are retained even when there is not a 1:1 correspondence between lineages. Finally, we demonstrate the approach by evaluating the evolutionary correlation between traits in fig species and traits in their agaonid wasp pollinators. R computer code is provided.     

Protein kinases and ovarian functions

The present focus survey represents a short review of current knowledge concerning involvement of protein kinases in control of basic ovarian functions. Ovarian cells produce a number of protein kinases, whose expression depends on type of cells, their state and action of hormones and other protein kinases. A number of protein kinases are involved in control of ovarian cell proliferation, apoptosis, oocyte maturation, hormone release, reception and response to hormones, as well as in mediating action of hormones on these ovarian functions. Complexity of interrelationships between different protein kinase‐dependent signaling pathways occurs. Protein kinases and their regulators could be used for characterization, prediction and control of ovarian folliculogenesis and atresia, Corpus luteum functions, oocyte maturation, fertility, release of hormones, response of ovarian structures to hormonal regulators, as well as for treatment of some reproductive disorders. The present data demonstrate importance of protein kinases in control of basic ovarian function and potential usage of protein kinases for characterization, prediction and control of these functions. J. Cell. Physiol. 226: 37–45, 2010. © 2010 Wiley‐Liss, Inc.     

Protein/peptide based nanomaterials for energy application

1. Download : Download high-res image (292KB)
2. Download : Download full-size image

Highlights► This review focuses on the application of protein based nanomaterials for the energy application. ► Assembled peptides and engineered proteins. ► Hybrid structures of protein and inorganic nanomaterials. ► Supramolecular structures of proteins for energy application.     

Protein and energy value of vinasse for pigs

A vinasse, originating as the condensed molasses residue from the microbial production of citric acid, was chemically analyzed and given to growing pigs to determine its protein and energy value. It contained, per kg dry matter (62.6%), 185 g crude protein, 538 g N-free extracts, 48 g total sugar, 277 g ash and 12.8 MJ gross energy. Ammonia, betaine and amino acids (about half glutamic acid) accounted for 3.5, 9.1 and 28.6%, respectively, of the crude-protein N. In a 25-day balance trial with the final 10 days as collection period, ten pigs initially weighing 33 kg were pair-fed daily an average of about 1 kg of dry matter of either a basal diet (95% ground barley plus 5% cellulose) or of a mixed diet composed of, on dry basis, 77% basal diet plus 23% vinasse. Partial digestibility of components in the vinasse was: organic matter, 52%; crude protein, 45%; N-free extract, 58%; ash, 83%; and gross energy, 42%. Average daily gain and N retention were not different between dietary groups. The vinasse contained, per kg dry matter, 5.40 MJ DE and 3.61 MJ ME compared with 14.96 MJ DE and 14.48 MJ ME for the dry basal diet. The conclusion is that this vinasse, according to its low protein and energy value, can provide only a small percentage of the daily ration for pigs.     

On statistical energy functions for biomolecular modeling and design

Statistical energy functions are general models about atomic or residue-level interactions in biomolecules, derived from existing experimental data. They provide quantitative foundations for structural modeling as well as for structure-based protein sequence design. Statistical energy functions can be derived computationally either based on statistical distributions or based on variational assumptions. We present overviews on the theoretical assumptions underlying the various types of approaches. Theoretical considerations underlying important pragmatic choices are discussed.     

Searching for foldable protein structures using optimized energy functions

During evolution, the effective interactions between residues in a protein can be adjusted through mutations to allow the protein to fold to its native structure on an adequate time scale. We seek to address the question: Are there some structures that can be better optimized than others? Using exhaustive enumeration of the compact conformations of short proteins confined to simple lattices, we find that the best structures are those that contain contacts rare in random structures, indicating the importance of nonlocal contacts for assisting the folding process. Certain structural motifs such as long β-hairpins, Greek-key motifs, and jelly rolls, commonly found in proteins of known structure, have a high degree of optimizability. Contrary to what might be expected, positive correlations between the various interactions reduce optimizability. The optimization procedure produces a correlated energy landscape, which might assist folding. © 1995 John Wiley & Sons, Inc.     

Protein interaction-targeted drug discovery: evaluating critical issues

Employment of the decision strategies outlined in this general discussion should help to pinpoint mode of activity in drug development and validation. Overall, as a paradigm for drug development, a search for small molecules that can interfere with PPIs would seem to have significant long term potential. At present, the level of structural knowledge in databases is not sufficient to predict in toto the protein binding properties of a modeled drug, but as databases improve, this may become generally feasible. A major point that remains to be determined is how much specificity of protein binding can be incorporated into molecules of generally less than 500 Da. Finally, integration of PPI-targeting strategies with other approaches towards drug design will enhance the number of signaling pathways that can effectively be targeted. These points will be particularly pertinent as technologies permit a systematic identification of encoded protein interactions that govern the proteornic complement of cells.