Prediction of catalytic residues using Support Vector Machine with selected protein sequence and structural properties

BACKGROUND: The number of protein sequences deriving from genome sequencing projects is outpacing our knowledge about the function of these proteins. With the gap between experimentally characterized and uncharacterized proteins continuing to widen, it is necessary to develop new computational methods and tools for functional prediction. Knowledge of catalytic sites provides a valuable insight into protein function. Although many computational methods have been developed to predict catalytic residues and active sites, their accuracy remains low, with a significant number of false positives. In this paper, we present a novel method for the prediction of catalytic sites, using a carefully selected, supervised machine learning algorithm coupled with an optimal discriminative set of protein sequence conservation and structural properties. RESULTS: To determine the best machine learning algorithm, 26 classifiers in the WEKA software package were compared using a benchmarking dataset of 79 enzymes with 254 catalytic residues in a 10-fold cross-validation analysis. Each residue of the dataset was represented by a set of 24 residue properties previously shown to be of functional relevance, as well as a label {+1/-1} to indicate catalytic/non-catalytic residue. The best-performing algorithm was the Sequential Minimal Optimization (SMO) algorithm, which is a Support Vector Machine (SVM). The Wrapper Subset Selection algorithm further selected seven of the 24 attributes as an optimal subset of residue properties, with sequence conservation, catalytic propensities of amino acids, and relative position on protein surface being the most important features. CONCLUSION: The SMO algorithm with 7 selected attributes correctly predicted 228 of the 254 catalytic residues, with an overall predictive accuracy of more than 86%. Missing only 10.2% of the catalytic residues, the method captures the fundamental features of catalytic residues and can be used as a "catalytic residue filter" to facilitate experimental identification of catalytic residues for proteins with known structure but unknown function

Structure and Inhibition of the SARS Coronavirus Envelope Protein Ion Channel

The envelope (E) protein from coronaviruses is a small polypeptide that contains at least one α-helical transmembrane domain. Absence, or inactivation, of E protein results in attenuated viruses, due to alterations in either virion morphology or tropism. Apart from its morphogenetic properties, protein E has been reported to have membrane permeabilizing activity. Further, the drug hexamethylene amiloride (HMA), but not amiloride, inhibited in vitro ion channel activity of some synthetic coronavirus E proteins, and also viral replication. We have previously shown for the coronavirus species responsible for severe acute respiratory syndrome (SARS-CoV) that the transmembrane domain of E protein (ETM) forms pentameric α-helical bundles that are likely responsible for the observed channel activity. Herein, using solution NMR in dodecylphosphatidylcholine micelles and energy minimization, we have obtained a model of this channel which features regular α-helices that form a pentameric left-handed parallel bundle. The drug HMA was found to bind inside the lumen of the channel, at both the C-terminal and the N-terminal openings, and, in contrast to amiloride, induced additional chemical shifts in ETM. Full length SARS-CoV E displayed channel activity when transiently expressed in human embryonic kidney 293 (HEK-293) cells in a whole-cell patch clamp set-up. This activity was significantly reduced by hexamethylene amiloride (HMA), but not by amiloride. The channel structure presented herein provides a possible rationale for inhibition, and a platform for future structure-based drug design of this potential pharmacological target

Positive Evolutionary Selection of an HD Motif on Alzheimer Precursor Protein Orthologues Suggests a Functional Role

HD amino acid duplex has been found in the active center of many different enzymes. The dyad plays remarkably different roles in their catalytic processes that usually involve metal coordination. An HD motif is positioned directly on the amyloid beta fragment (Aβ) and on the carboxy-terminal region of the extracellular domain (CAED) of the human amyloid precursor protein (APP) and a taxonomically well defined group of APP orthologues (APPOs). In human Aβ HD is part of a presumed, RGD-like integrin-binding motif RHD; however, neither RHD nor RXD demonstrates reasonable conservation in APPOs. The sequences of CAEDs and the position of the HD are not particularly conserved either, yet we show with a novel statistical method using evolutionary modeling that the presence of HD on CAEDs cannot be the result of neutral evolutionary forces (p<0.0001). The motif is positively selected along the evolutionary process in the majority of APPOs, despite the fact that HD motif is underrepresented in the proteomes of all species of the animal kingdom. Position migration can be explained by high probability occurrence of multiple copies of HD on intermediate sequences, from which only one is kept by selective evolutionary forces, in a similar way as in the case of the “transcription binding site turnover.” CAED of all APP orthologues and homologues are predicted to bind metal ions including Amyloid-like protein 1 (APLP1) and Amyloid-like protein 2 (APLP2). Our results suggest that HDs on the CAEDs are most probably key components of metal-binding domains, which facilitate and/or regulate inter- or intra-molecular interactions in a metal ion-dependent or metal ion concentration-dependent manner. The involvement of naturally occurring mutations of HD (Tottori (D7N) and English (H6R) mutations) in early onset Alzheimer's disease gives additional support to our finding that HD has an evolutionary preserved function on APPOs

Magnetorheology in an aging, yield stress matrix fluid

Field-induced static and dynamic yield stresses are explored for magnetorheological (MR) suspensions in an aging, yield stress matrix fluid composed of an aqueous dispersion of Laponite® clay. Using a custom-built magnetorheometry fixture, the MR response is studied for magnetic field strengths up to 1 T and magnetic particle concentrations up to 30 v%. The yield stress of the matrix fluid, which serves to inhibit sedimentation of dispersed carbonyl iron magnetic microparticles, is found to have a negligible effect on the field-induced static yield stress for sufficient applied fields, and good agreement is observed between field-induced static and dynamic yield stresses for all but the lowest field strengths and particle concentrations. These results, which generally imply a dominance of inter-particle dipolar interactions over the matrix fluid yield stress, are analyzed by considering a dimensionless magnetic yield parameter that quantifies the balance of stresses on particles. By characterizing the applied magnetic field in terms of the average particle magnetization, a rheological master curve is generated for the field-induced static yield stress that indicates a concentration–magnetization superposition. The results presented herein will provide guidance to formulators of MR fluids and designers of MR devices who require a field-induced static yield stress and a dispersion that is essentially indefinitely stable to sedimentation.Petroleum Research Fund (ACS-PRF Grant No. 49956-ND9)American Chemical Society (ACS-PRF Grant No. 49956-ND9

Finite-Step Algorithms for Single-Controller and Perfect Information Stochastic Games

Abstract. After a brief survey of iterative algorithms for general stochas-tic games, we concentrate on finite-step algorithms for two special classes of stochastic games. They are Single-Controller Stochastic Games and Per-fect Information Stochastic Games. In the case of single-controller games, the transition probabilities depend on the actions of the same player in all states. In perfect information stochastic games, one of the players has exactly one action in each state. Single-controller zero-sum games are effi-ciently solved by linear programming. Non-zero-sum single-controller stochastic games are reducible to linear complementary problems (LCP). In the discounted case they can be modified to fit into the so-called LCPs of Eave’s class L. In the undiscounted case the LCP’s are reducible to Lemke’s copositive plus class. In either case Lemke’s algorithm can be used to find a Nash equilibrium. In the case of discounted zero-sum perfect informa-tion stochastic games, a policy improvement algorithm is presented. Many other classes of stochastic games with orderfield property still await efficient finite-step algorithms. 1

Rapid Reversal of Chondroitin Sulfate Proteoglycan Associated Staining in Subcompartments of Mouse Neostriatum during the Emergence of Behaviour

BACKGROUND: The neostriatum, the mouse homologue of the primate caudate/putamen, is the input nucleus for the basal ganglia, receiving both cortical and dopaminergic input to each of its sub-compartments, the striosomes and matrix. The coordinated activation of corticostriatal pathways is considered vital for motor and cognitive abilities, yet the mechanisms which underlie the generation of these circuits are unknown. The early and specific targeting of striatal subcompartments by both corticostriatal and nigrostriatal terminals suggests activity-independent mechanisms, such as axon guidance cues, may play a role in this process. Candidates include the chondroitin sulfate proteoglycan (CSPG) family of glycoproteins which have roles not only in axon guidance, but also in the maturation and stability of neural circuits where they are expressed in lattice-like perineuronal nets (PNNs). METHODOLOGY/PRINCIPAL FINDINGS: The expression of CSPG-associated structures and PNNs with respect to neostriatal subcompartments has been examined qualitatively and quantitatively using double-labelling for Wisteria floribunda agglutinin (WFA), and the mu-opioid receptor (muOR), a marker for striosomes, at six postnatal ages in mice. We find that at the earliest ages (postnatal day (P)4 and P10), WFA-positive clusters overlap preferentially with the striosome compartment. By P14, these clusters disappear. In contrast, PNNs were first seen at P10 and continued to increase in density and spread throughout the caudate/putamen with maturation. Remarkably, the PNNs overlap almost exclusively with the neostriatal matrix. CONCLUSIONS/SIGNIFICANCE: This is the first description of a reversal in the distribution of CSPG associated structures, as well as the emergence and maintenance of PNNs in specific subcompartments of the neostriatum. These results suggest diverse roles for CSPGs in the formation of functional corticostriatal and nigrostriatal connectivity within the striosome and matrix compartments of the developing caudate/putamen

SPIRITS: Uncovering Unusual Infrared Transients with Spitzer

We present an ongoing, five-year systematic search for extragalactic infrared transients, dubbed SPIRITS—SPitzer InfraRed Intensive Transients Survey. In the first year, using Spitzer/IRAC, we searched 190 nearby galaxies with cadence baselines of one month and six months. We discovered over 1958 variables and 43 transients. Here, we describe the survey design and highlight 14 unusual infrared transients with no optical counterparts to deep limits, which we refer to as SPRITEs (eSPecially Red Intermediate-luminosity Transient Events). SPRITEs are in the infrared luminosity gap between novae and supernovae, with [4.5] absolute magnitudes between −11 and −14 (Vega-mag) and [3.6]–[4.5] colors between 0.3 mag and 1.6 mag. The photometric evolution of SPRITEs is diverse, ranging from 7 mag yr−1. SPRITEs occur in star-forming galaxies. We present an in-depth study of one of them, SPIRITS 14ajc in Messier 83, which shows shock-excited molecular hydrogen emission. This shock may have been triggered by the dynamic decay of a non-hierarchical system of massive stars that led to either the formation of a binary or a protostellar merger