Structure dissection of human progranulin identifies well-folded granulin/epithelin modules with unique functional activities

Progranulin is a secreted protein with important functions in several physiological and pathological processes, such as embryonic development, host defense, and wound repair. Autosomal dominant mutations in the progranulin gene cause frontotemporal dementia, while overexpression of progranulin promotes the invasive progression of a range of tumors, including those of the breast and the brain. Structurally, progranulin consists of seven-and-a-half tandem repeats of the granulin/epithelin module (GEM), several of which have been isolated as discrete 6-kDa GEM peptides. We have expressed all seven human GEMs using recombinant DNA in Escherichia coli. High-resolution NMR showed that only the three GEMs, hGrnA, hGrnC, and hGrnF, contain relatively well-defined three-dimensional structures in solution, while others are mainly mixtures of poorly structured disulfide isomers. The three-dimensional structures of hGrnA, hGrnC, and hGrnF contain a stable stack of two beta-hairpins in their N-terminal subdomains, but showed a more flexible C-terminal subdomain. Interestingly, of the well-structured GEMs, hGrnA demonstrated potent growth inhibition of a breast cancer cell line, while hGrnF was stimulatory. Poorly folded peptides were either weakly inhibitory or without activity. The functionally active and structurally well-characterized human hGrnA offers a unique opportunity for detailed structure-function studies of these important GEM proteins as novel members of mammalian growth factors.     

Robust recognition of zinc binding sites in proteins

Metals play a variety of roles in biological processes, and hence their presence in a protein structure can yield vital functional information. Because the residues that coordinate a metal often undergo conformational changes upon binding, detection of binding sites based on simple geometric criteria in proteins without bound metal is difficult. However, aspects of the physicochemical environment around a metal binding site are often conserved even when this structural rearrangement occurs. We have developed a Bayesian classifier using known zinc binding sites as positive training examples and nonmetal binding regions that nonetheless contain residues frequently observed in zinc sites as negative training examples. In order to allow variation in the exact positions of atoms, we average a variety of biochemical and biophysical properties in six concentric spherical shells around the site of interest. At a specificity of 99.8%, this method achieves 75.5% sensitivity in unbound proteins at a positive predictive value of 73.6%. We also test its accuracy on predicted protein structures obtained by homology modeling using templates with 30%-50% sequence identity to the target sequences. At a specificity of 99.8%, we correctly identify at least one zinc binding site in 65.5% of modeled proteins. Thus, in many cases, our model is accurate enough to identify metal binding sites in proteins of unknown structure for which no high sequence identity homologs of known structure exist. Both the source code and a Web interface are available to the public at http://feature.stanford.edu/metals.     

Enhanced performance in prediction of protein active sites with THEMATICS and support vector machines

Theoretical microscopic titration curves (THEMATICS) is a computational method for the identification of active sites in proteins through deviations in computed titration behavior of ionizable residues. While the sensitivity to catalytic sites is high, the previously reported sensitivity to catalytic residues was not as high, about 50%. Here THEMATICS is combined with support vector machines (SVM) to improve sensitivity for catalytic residue prediction from protein 3D structure alone. For a test set of 64 proteins taken from the Catalytic Site Atlas (CSA), the average recall rate for annotated catalytic residues is 61%; good precision is maintained selecting only 4% of all residues. The average false positive rate, using the CSA annotations is only 3.2%, far lower than other 3D-structure-based methods. THEMATICS-SVM returns higher precision, lower false positive rate, and better overall performance, compared with other 3D-structure-based methods. Comparison is also made with the latest machine learning methods that are based on both sequence alignments and 3D structures. For annotated sets of well-characterized enzymes, THEMATICS-SVM performance compares very favorably with methods that utilize sequence homology. However, since THEMATICS depends only on the 3D structure of the query protein, no decline in performance is expected when applied to novel folds, proteins with few sequence homologues, or even orphan sequences. An extension of the method to predict non-ionizable catalytic residues is also presented. THEMATICS-SVM predicts a local network of ionizable residues with strong interactions between protonation events; this appears to be a special feature of enzyme active sites.     

Neural correlates of economic game playing

The theory of games provides a mathematical formalization of strategic choices, which have been studied in both economics and neuroscience, and more recently has become the focus of neuroeconomics experiments with human and non-human actors. This paper reviews the results from a number of game experiments that establish a unitary system for forming subjective expected utility maps in the brain, and acting on these maps to produce choices. Social situations require the brain to build an understanding of the other person using neuronal mechanisms that share affective and intentional mental states. These systems allow subjects to better predict other players' choices, and allow them to modify their subjective utility maps to value pro-social strategies. New results for a trust game are presented, which show that the trust relationship includes systems common to both trusting and trustworthy behaviour, but they also show that the relative temporal positions of first and second players require computations unique to that role.     

Focusing the view on nature's water-splitting catalyst

Nature invented a catalyst about 3Gyr ago, which splits water with high efficiency into molecular oxygen and hydrogen equivalents (protons and electrons). This reaction is energetically driven by sunlight and the active centre contains relatively cheap and abundant metals: manganese and calcium. This biological system therefore forms the paradigm for all man-made attempts for direct solar fuel production, and several studies are underway to determine the electronic and geometric structures of this catalyst. In this report we briefly summarize the problems and the current status of these efforts and propose a density functional theory-based strategy for obtaining a reliable high-resolution structure of this unique catalyst that includes both the inorganic core and the first ligand sphere.     

Anticipatory affect: neural correlates and consequences for choice

'Anticipatory affect' refers to emotional states that people experience while anticipating significant outcomes. Historically, technical limitations have made it difficult to determine whether anticipatory affect influences subsequent choice. Recent advances in the spatio-temporal resolution of functional magnetic resonance imaging, however, now allow researchers to visualize changes in neural activity seconds before choice occurs. We review evidence that activation in specific brain circuits changes during anticipation of monetary incentives, that this activation correlates with affective experience and that activity in these circuits may influence subsequent choice. Specifically, an activation likelihood estimate meta-analysis of cued response studies indicates that nucleus accumbens (NAcc) activation increases during gain anticipation relative to loss anticipation, while anterior insula activation increases during both loss and gain anticipation. Additionally, anticipatory NAcc activation correlates with self-reported positive arousal, whereas anterior insula activation correlates with both self-reported negative and positive arousal. Finally, NAcc activation precedes the purchase of desirable products and choice of high-risk gambles, whereas anterior insula activation precedes the rejection of overpriced products and choice of low-risk gambles. Together, these findings support a neurally plausible framework for understanding how anticipatory affect can influence choice.     

The electronic structure of Ti(BH4)3: Photoelectron spectra and calculation of vertical ionization energies

He I and He II PE spectra of Ti(BH₄)₃ are reported and assigned by reference to density functional calculations on the molecule and cation. The performance of different functionals in predicting the first vertical ionization energy is assessed. Calculations based on hybrid functionals are found to give ionisation energies closer to the experimental value than those using pure density functionals. The accuracy of the ΔSCF method and time dependent density functional theory in calculating higher vertical ionization energies is also examined.     

Solution structure of molybdic acid from Raman spectroscopy and DFT analysis

Protonation of produces the well-characterized polymolybdates, but at concentrations below 10⁻³ M the dominant species is monomeric molybdic acid, H₂MoO₄. It is likely to be the species adsorbed on manganese oxide, a process thought to control levels in the ocean, because of the strong proton dependence of adsorption. The molecular structure of H₂MoO₄ is elusive, since it occurs only in dilute solutions. Using 244 nm laser excitation, near resonance with O → Mo charge-transfer electronic transitions of H₂MoO₄, we have detected a 919 cm⁻¹ Raman band assignable to ν_sMoO. Using DFT, we have computed geometries and vibrational modes for the various structures consistent with the H₂MoO₄ formula. We tested the computations on a series of Mo(VI) oxo complexes with known vibrational frequencies, at several levels of theory. Best agreement with experimental values, at reasonable computational cost, was obtained with the B3LYP functional, employing a LANL2DZ ECP basis set for Mo and the 6-311+G(2df,p) basis set for O and H. Among the possible H₂MoO₄ structures only those based on the MoO₃ unit, with one, two or three coordinated water molecules, gave a scaled frequency for ν_sMoO that was within two standard deviations of 919 cm⁻¹. Best agreement was obtained for MoO₃(H₂O)₃. The MoO₂ and MoO structures gave frequencies that were too high. The Mo(OH)₆ structure could be excluded, because its vibrational frequencies shift down strongly upon H/D exchange, whereas the 919 cm⁻¹H₂MoO₄ band shifts up 1 cm⁻¹ in D₂O.