The binding site distance test score: a robust method for the assessment of predicted protein binding sites

We propose a novel method for scoring the accuracy of protein binding site predictions – the Binding-site Distance Test (BDT) score. Recently, the Matthews Correlation Coefficient (MCC) has been used to evaluate binding site predictions, both by developers of new methods and by the assessors for the community wide prediction experiment – CASP8. Whilst being a rigorous scoring method, the MCC does not take into account the actual 3D location of the predicted residues from the observed binding site. Thus, an incorrectly predicted site that is nevertheless close to the observed binding site will obtain an identical score to the same number of nonbinding residues predicted at random. The MCC is somewhat affected by the subjectivity of determining observed binding residues and the ambiguity of choosing distance cutoffs. By contrast the BDT method produces continuous scores ranging between 0 and 1, relating to the distance between the predicted and observed residues. Residues predicted close to the binding site will score higher than those more distant, providing a better reflection of the true accuracy of predictions. The CASP8 function predictions were evaluated using both the MCC and BDT methods and the scores were compared. The BDT was found to strongly correlate with the MCC scores whilst also being less susceptible to the subjectivity of defining binding residues. We therefore suggest that this new simple score is a potentially more robust method for future evaluations of protein-ligand binding site predictions.

Pharmacological characterisation of the agonist radioligand binding site of 5-HT2A, 5-HT2B and 5-HT2C receptors

In the present study we compared the affinity of various drugs for the high affinity "agonist-preferring" binding site of human recombinant 5-HT2A, 5-HT2B and 5-HT2C receptors stably expressed in monoclonal mammalian cell lines. To ensure that the "agonist-preferring" conformation of the receptor was preferentially labelled in competition binding experiments, saturation analysis was conducted using antagonist and agonist radiolabels at each receptor. Antagonist radiolabels ([H-3]-ketanserin for 5-HT2A receptor and [H-3]-mesulergine for 5-HT2B and 5-HT2C receptor) bound to a larger population of receptors in each preparation than the corresponding agonist radiolabel ([I-125]-DOI for 5-HT2A receptor binding and [H-3]-5-HT for 5-HT2B and 5-HT2C receptor binding). Competition experiments were subsequently conducted against appropriate concentrations of the agonist radiolabels bound to the "agonist-preferring" subset of receptors in each preparation. These studies confirmed that there are a number of highly selective antagonists available to investigate 5-HT2 receptor subtype function (for example, MDL 100907, RS-127445 and RS-102221 for 5-HT2A, 5-HT2B and 5-HT2C receptors respectively). There remains, however, a lack of highly selective agonists. (-)DOI is potent and moderately selective for 5-HT2A receptors, BW723C86 has poor selectivity for human 5-HT2B receptors, while Org 37684 and VER-3323 display some selectivity for the 5-HT2C receptor. We report for the first time in a single study, the selectivity of numerous serotonergic drugs for 5-HT2 receptors from the same species, in mammalian cell lines and using, exclusively, agonist radiolabels. The results indicate the importance of defining the selectivity of pharmacological tools, which may have been over-estimated in the past, and highlights the need to find more selective agonists to investigate 5-HT2 receptor pharmacology.

Predicting metal-binding site residues in low-resolution structural models

The accurate prediction of the biochemical function of a protein is becoming increasingly important, given the unprecedented growth of both structural and sequence databanks. Consequently, computational methods are required to analyse such data in an automated manner to ensure genomes are annotated accurately. Protein structure prediction methods, for example, are capable of generating approximate structural models on a genome-wide scale. However, the detection of functionally important regions in such crude models, as well as structural genomics targets, remains an extremely important problem. The method described in the current study, MetSite, represents a fully automatic approach for the detection of metal-binding residue clusters applicable to protein models of moderate quality. The method involves using sequence profile information in combination with approximate structural data. Several neural network classifiers are shown to be able to distinguish metal sites from non-sites with a mean accuracy of 94.5%. The method was demonstrated to identify metal-binding sites correctly in LiveBench targets where no obvious metal-binding sequence motifs were detectable using InterPro. Accurate detection of metal sites was shown to be feasible for low-resolution predicted structures generated using mGenTHREADER where no side-chain information was available. High-scoring predictions were observed for a recently solved hypothetical protein from Haemophilus influenzae, indicating a putative metal-binding site.

FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions

The estimation of prediction quality is important because without quality measures, it is difficult to determine the usefulness of a prediction. Currently, methods for ligand binding site residue predictions are assessed in the function prediction category of the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment, utilizing the Matthews Correlation Coefficient (MCC) and Binding-site Distance Test (BDT) metrics. However, the assessment of ligand binding site predictions using such metrics requires the availability of solved structures with bound ligands. Thus, we have developed a ligand binding site quality assessment tool, FunFOLDQA, which utilizes protein feature analysis to predict ligand binding site quality prior to the experimental solution of the protein structures and their ligand interactions. The FunFOLDQA feature scores were combined using: simple linear combinations, multiple linear regression and a neural network. The neural network produced significantly better results for correlations to both the MCC and BDT scores, according to Kendall’s τ, Spearman’s ρ and Pearson’s r correlation coefficients, when tested on both the CASP8 and CASP9 datasets. The neural network also produced the largest Area Under the Curve score (AUC) when Receiver Operator Characteristic (ROC) analysis was undertaken for the CASP8 dataset. Furthermore, the FunFOLDQA algorithm incorporating the neural network, is shown to add value to FunFOLD, when both methods are employed in combination. This results in a statistically significant improvement over all of the best server methods, the FunFOLD method (6.43%), and one of the top manual groups (FN293) tested on the CASP8 dataset. The FunFOLDQA method was also found to be competitive with the top server methods when tested on the CASP9 dataset. To the best of our knowledge, FunFOLDQA is the first attempt to develop a method that can be used to assess ligand binding site prediction quality, in the absence of experimental data.

Proteins and their interacting partners: an introduction to protein–ligand binding site prediction methods

Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein–ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein–ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein–ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

Small guanine nucleotide-binding proteins and myocardial hypertrophy.

The small (21 kDa) guanine nucleotide-binding protein (small G protein) superfamily comprises 5 subfamilies (Ras, Rho, ADP ribosylation factors [ARFs], Rab, and Ran) that act as molecular switches to regulate numerous cellular responses. Cardiac myocyte hypertrophy is associated with cell growth and changes in the cytoskeleton and myofibrillar apparatus. In other cells, the Ras subfamily regulates cell growth whereas the Rho subfamily (RhoA, Rac1, and Cdc42) regulates cell morphology. Thus, the involvement of small G proteins in hypertrophy has become an area of significant interest. Hearts from transgenic mice expressing activated Ras develop features consistent with hypertrophy, whereas mice overexpressing RhoA develop lethal heart failure. In isolated neonatal rat cardiac myocytes, transfection or infection with activated Ras, RhoA, or Rac1 induces many of the features of hypertrophy. We discuss the mechanisms of activation of the small G proteins and the downstream signaling pathways involved. The latter may include protein kinases, particularly the mitogen-activated or Rho-activated protein kinases. We conclude that although there is significant evidence implicating Ras, RhoA, and Rac1 in hypertrophy, the mechanisms are not fully understood.

Nuclear magnetic resonance structure of the nucleic acid-binding domain of severe acute respiratory syndrome coronavirus nonstructural protein 3

The nuclear magnetic resonance (NMR) structure of a globular domain of residues 1071 to 1178 within the previously annotated nucleic acid-binding region (NAB) of severe acute respiratory syndrome coronavirus nonstructural protein 3 (nsp3) has been determined, and N- and C-terminally adjoining polypeptide segments of 37 and 25 residues, respectively, have been shown to form flexibly extended linkers to the preceding globular domain and to the following, as yet uncharacterized domain. This extension of the structural coverage of nsp3 was obtained from NMR studies with an nsp3 construct comprising residues 1066 to 1181 [ nsp3(1066-1181)] and the constructs nsp3(1066-1203) and nsp3(1035-1181). A search of the protein structure database indicates that the globular domain of the NAB represents a new fold, with a parallel four-strand beta-sheet holding two alpha-helices of three and four turns that are oriented antiparallel to the beta-strands. Two antiparallel two-strand beta-sheets and two 3(10)-helices are anchored against the surface of this barrel-like molecular core. Chemical shift changes upon the addition of single-stranded RNAs (ssRNAs) identified a group of residues that form a positively charged patch on the protein surface as the binding site responsible for the previously reported affinity for nucleic acids. This binding site is similar to the ssRNA-binding site of the sterile alpha motif domain of the Saccharomyces cerevisiae Vts1p protein, although the two proteins do not share a common globular fold.

Thermodynamic analysis of ferrous ion binding to Escherichia coli ferritin EcFtnA

Iron oxidation in the bacterial ferritin EcFtnA from Escherichia coli shows marked differences from its homologue human H-chain ferritin (HuHF). While the amino acid residues that constitute the dinuclear center in these proteins are highly conserved, EcFtnA has a third iron-binding site (C site) in close proximity to the dinuclear center that is seemingly responsible for these differences. Here, we describe the first thermodynamic study of Fe2+ binding to EcFtnA and its variants to determine the location of the primary ferrous ion-binding sites on the protein and to better understand the role of the third C site in iron binding. Isothermal titration calorimetric analyses of the wild-type protein reveal the presence of two main classes of binding sites in the pH range of 6.5-7.5, ascribed to Fe2+ binding, first at the A and then the B sites. Site-directed mutagenesis of ligands in the A, B, or C sites affects the apparent Fe2+-binding stoichiometries at the unaltered sites. The data imply some degree of inter- and intrasubunit negative cooperative interaction between sites. Unlike HuHF where only the A site initially binds Fe2+, both A and B sites in EcFtnA bind Fe2+, implying a role for the C site in influencing the binding of Fe2+ at the B site of the di-iron center of EcFtnA. The ITC equations describing a binding model for three classes of independent binding sites are reported here for the first time.

Mass spectroscopic characterization of the coronavirus infectious bronchitis virus nucleoprotein and elucidation of the role of phosphorylation in RNA binding by using surface plasmon resonance

Phosphorylation of the coronavirus nucleoprotein (N protein) has been predicted to play a role in RNA binding. To investigate this hypothesis, we examined the kinetics of RNA binding between nonphosphorylated and phosphorylated infectious bronchitis virus N protein with nonviral and viral RNA by surface plasmon resonance (Biacore). Mass spectroscopic analysis of N protein identified phosphorylation sites that were proximal to RNA binding domains. Kinetic analysis, by surface plasmon resonance, indicated that nonphospborylated N protein bound with the same affinity to viral RNA as phosphorylated N protein. However, phosphorylated N protein bound to viral RNA with a higher binding affinity than nonviral RNA, suggesting that phosphorylation of N protein determined the recognition of virus RNA. The data also indicated that a known N protein binding site (involved in transcriptional regulation) consisting of a conserved core sequence present near the 5' end of the genome (in the leader sequence) functioned by promoting high association rates of N protein binding. Further analysis of the leader sequence indicated that the core element was not the only binding site for N protein and that other regions functioned to promote high-affinity binding.

Oligomers of D-2 dopamine receptors - Evidence from ligand binding

There is increasing evidence that G protein-coupled receptors form oligomers and that this might be important for their function. We have studied this phenomenon for the D-2 dopamine receptor and have shown-using a variety of biochemical and biophysical techniques-that this receptor forms dimers or higher-order oligomers. Using ligand-binding studies, we have also found evidence that this oligomer formation has functional relevance. Thus, for the receptor expressed in either CHO cells or Sf 9 insect cells, the binding properties of several radioligands (in saturation, competition, and dissociation assays) do not conform to those expected for a monomeric receptor with a single binding site. We propose that the receptors exist in oligomers with homotropic and heterotropic negatively cooperative interactions between ligands.

Insights into the effects on metal binding of the systematic substitution of five key glutamate ligands in the ferritin of Escherichia coli

Ferritins are nearly ubiquitous iron storage proteins playing a fundamental role in iron metabolism. They are composed of 24 subunits forming a spherical protein shell encompassing a central iron storage cavity. The iron storage mechanism involves the initial binding and subsequent O-2-dependent oxidation of two Fe2+ ions located at sites A and B within the highly conserved dinuclear "ferroxidase center" in individual subunits. Unlike animal ferritins and the heme-containing bacterioferritins, the Escherichia coli ferritin possesses an additional iron-binding site (site C) located on the inner surface of the protein shell close to the ferroxidase center. We report the structures of five E. coli ferritin variants and their Fe3+ and Zn2+ (a redox-stable alternative for Fe2+) derivatives. Single carboxyl ligand replacements in sites A, B, and C gave unique effects on metal binding, which explain the observed changes in Fe2+ oxidation rates. Binding of Fe2+ at both A and B sites is clearly essential for rapid Fe2+ oxidation, and the linking of Fe-B(2+) to Fe-C(2+) enables the oxidation of three Fe2+ ions. The transient binding of Fe2+ at one of three newly observed Zn2+ sites may allow the oxidation of four Fe2+ by one dioxygen molecule.

Oligomers of D-2 dopamine receptors: evidence from ligand binding

There is increasing evidence that G protein-coupled receptors form oligomers and that this might be important for their function. We have studied this phenomenon for the D-2 dopamine receptor and have shown-using a variety of biochemical and biophysical techniques-that this receptor forms dimers or higher-order oligomers. Using ligand-binding studies, we have also found evidence that this oligomer formation has functional relevance. Thus, for the receptor expressed in either CHO cells or Sf 9 insect cells, the binding properties of several radioligands (in saturation, competition, and dissociation assays) do not conform to those expected for a monomeric receptor with a single binding site. We propose that the receptors exist in oligomers with homotropic and heterotropic negatively cooperative interactions between ligands

Titanocene anticancer complexes and their binding mode of action to human serum albumin: a computational study

Due to the pivotal role played by human serum albumin (HSA) in the transport and cytotoxicity of titanocene complexes, a docking study has been performed on a selected set of titanocene complexes to aid in the current understanding of the potential mode of action of these titanocenes upon binding HSA. Analysis of the docking results has revealed potential binding at the known drug binding sites in HSA and has provided some explanation for the specificity and subsequent cytotoxicity of these titanocenes. Additionally, a new alternative binding site for these titanocenes has been postulated.

Activation of the small GTP-binding protein Ras in the heart by hypertrophic agonists.

The small (21-kDa) guanine nucleotide-binding protein Ras plays a central role in the regulation of cell growth and division. In the cardiac myocyte, it has been implicated in the hypertrophic adaptation. We have recently examined the ability of hypertrophic agonists such as endothelin-1, phenylephrine and phorbol esters to increase the "activity" (GTP loading) of Ras. We have also studied the signaling events that lead to activation of Ras and the processes that respond to Ras activation. In this brief review, we describe these studies and set them within the context of the hypertrophic response.