Conformational basis for substrate recognition and regulation of catalytic activity in Staphylococcus aureus nucleoside di-phosphate kinase

Nucleoside diphosphate kinases (NDK) are characterized by high catalytic turnover rates and diverse substrate specificity. These features make this enzyme an effective activator of a pro-drug an application that has been actively pursued for a variety of therapeutic strategies. The catalytic mechanism of this enzyme is governed by a conserved histidine that coordinates a magnesium ion at the active site. Despite substantial structural and biochemical information on NDK, the mechanistic feature of the phospho-transfer that leads to auto-phosphorylation remains unclear. While the role of the histidine residue is well documented, the other active site residues, in particular the conserved serine remains poorly characterized. Studies on some homologues suggest no role for the serine residue at the active site, while others suggest a crucial role for this serine in the regulation and quaternary association of this enzyme in some species. Here we report the biochemical features of the Staphylococcus aureus NDK and the mutant enzymes. We also describe the crystal structures of the apo-NDK, as a transition state mimic with vanadate and in complex with different nucleotide substrates. These structures formed the basis for molecular dynamics simulations to understand the broad substrate specificity of this enzyme and the role of active site residues in the phospho-transfer mechanism and oligomerization. Put together, these data suggest that concerted changes in the conformation of specific residues facilitate the stabilization of nucleotide complexes thereby enabling the steps involved in the ping-pong reaction mechanism without large changes to the overall structure of this enzyme. (C) 2011 Elsevier B.V. All rights reserved.

Structural basis for the functional and inhibitory mechanisms of beta-hydroxyacyl-acyl carrier protein dehydratase (FabZ) of Plasmodium falciparum

The beta-hydroxyacyl-acyl carrier protein dehydratase of Plasmodium falciparum (PfFabZ) catalyzes the third and important reaction of the fatty acid elongation cycle. The crystal structure of PfFabZ is available in hexameric (active) and dimeric (inactive) forms. However, PfFabZ has not been crystallized with any bound inhibitors until now. We have designed a new condition to crystallize PfFabZ with its inhibitors bound in the active site, and determined the crystal structures of four of these complexes. This is the first report on any FabZ enzyme with active site inhibitors that interact directly with the catalytic residues. Inhibitor binding not only stabilized the substrate binding loop but also revealed that the substrate binding tunnel has an overall shape of ``U''. In the crystal structures, residue Phe169 located in the middle of the tunnel was found to be in two different conformations, open and closed. Thus, Phe169, merely by changing its side chain conformation, appears to be controlling the length of the tunnel to make it suitable for accommodating longer substrates. The volume of the substrate binding tunnel is determined by the sequence as well as by the conformation of the substrate binding loop region and varies between organisms for accommodating fatty acids of different chain lengths. This report on the crystal structures of the complexes of PfFabZ provides the structural basis of the inhibitory mechanism of the enzyme that could be used to improve the potency of inhibitors against an important component of fatty acid synthesis common to many infectious organisms. (C) 2011 Elsevier Inc. All rights reserved.

Fault-Diagnostic System using Support Vector Machines for Power Transmission Systems

This paper presents an approach for identifying the faulted line section and fault location on transmission systems using support vector machines (SVMs) for diagnosis/post-fault analysis purpose. Power system disturbances are often caused by faults on transmission lines. When fault occurs on a transmission system, the protective relay detects the fault and initiates the tripping operation, which isolates the affected part from the rest of the power system. Based on the fault section identified, rapid and corrective restoration procedures can thus be taken to minimize the power interruption and limit the impact of outage on the system. The approach is particularly important for post-fault diagnosis of any mal-operation of relays following a disturbance in the neighboring line connected to the same substation. This may help in improving the fault monitoring/diagnosis process, thus assuring secure operation of the power systems. In this paper we compare SVMs with radial basis function neural networks (RBFNN) in data sets corresponding to different faults on a transmission system. Classification and regression accuracy is reported for both strategies. Studies on a practical 24-Bus equivalent EHV transmission system of the Indian Southern region is presented for indicating the improved generalization with the large margin classifiers in enhancing the efficacy of the chosen model.

Conformational Basis for Substrate Recruitment in Protein Tyrosine Phosphatase 10D

The coordinated activity of protein tyrosine phosphatases (PTPs) is crucial for the initiation, modulation, and termination of diverse cellular processes. The catalytic activity of this protein depends on a nucleophilic cysteine at the active site that mediates the hydrolysis of the incoming phosphotyrosine substrate. While the role of conserved residues in the catalytic mechanism of PTPs has been extensively examined, the diversity in the mechanisms of substrate recognition and modulation of catalytic activity suggests that other, less conserved sequence and structural features could contribute to this process. Here we describe the crystal structures of Drosophila melanogaster PTP10D in the apo form as well as in a complex with a substrate peptide and an inhibitor. These studies reveal the role of aromatic ring stacking interactions at the boundary of the active site of PTPs in mediating substrate recruitment. We note that phenylalanine 76, of the so-called KNRY loop, is crucial for orienting the phosphotyrosine residue toward the nucleophilic cysteine. Mutation of phenylalanine 76 to leucine results in a 60-fold decrease in the catalytic efficiency of the enzyme. Fluorescence measurements with a competitive inhibitor, p-nitrocatechol sulfate, suggest that Phe76 also influences the formation of the enzyme-substrate intermediate. The structural and biochemical data for PTP10D thus highlight the role of relatively less conserved residues in PTP domains in both substrate recruitment and modulation of reaction kinetics.

Transport and magnetic properties of Nd1-xPbxMnO3 single crystals

Transport and magnetic properties of flux-grown Nd1−xPbxMnO3 single crystals (x=0.15–0.5) are studied in the temperature range 300–77 K and 280–2 K, respectively. Magnetization measurements with a superconducting quantum interference device confirm a paramagnetic to ferromagnetic transition around 110, 121, 150, 160, and 178 K for x=0.15, 0.2, 0.3, 0.4, and 0.5, respectively. Four probe resistivity measurements at low temperatures show a monotonic increase for x=0.15 which represents a ferromagnetic insulating (FMI) phase. For Nd0.8Pb0.2MnO3 there is a slope change present in the resistivity profile at 127 K where metal to insulator transition (MI) sets in. For x=0.3 this MI transition is more prominent. However, both these samples have FMI phase at low temperature. When the concentration of lead increases (x>0.3) the sample displays a clear insulator to metal transition with a low temperature ferromagnetic metallic phase. On the basis of these measurements we have predicted the phase diagram of Nd1−xPbxMnO3. Magnetization measurements by a vibration sample magnetometer point out the appreciable differences between zero field cooled and field cooled profiles below the ferromagnetic to paramagnetic transition temperature for all x. These are indicative of magnetic frustration.

A general construction of space-time trellis codes for PSK signal sets

The diversity order and coding gain are crucial for the performance of a multiple antenna communication system. It is known that space-time trellis codes (STTC) can be used to achieve these objectives. In particular, we can use STTCs to obtain large coding gains. Many attempts have been made to construct STTCs which achieve full-diversity and good coding gains, though a general method of construction does not exist. Delay diversity code (rate-1) is known to achieve full-diversity, for any number of transmit antennas and any signal set, but does not give a good coding gain. A product distance code based delay diversity scheme (Tarokh, V. et al., IEEE Trans. Inform. Theory, vol.44, p.744-65, 1998) enables one to improve the coding gain and construct STTCs for any given number of states using coding in conjunction with delay diversity; it was stated as an open problem. We achieve such a construction. We assume a shift register based model to construct an STTC for any state complexity. We derive a sufficient condition for this STTC to achieve full-diversity, based on the delay diversity scheme. This condition provides a framework to do coding in conjunction with delay diversity for any signal constellation. Using this condition, we provide a formal rate-1 STTC construction scheme for PSK signal sets, for any number of transmit antennas and any given number of states, which achieves full-diversity and gives a good coding gain.

Composite instantaneous comparators basis for design and their transient performance

Principles of design of composite instantaneous comparators (a combination of amplitude- and phase- comparison techniques) are laid out to provide directional, directional-reactance, nonoffset-resistance and conductance characteristices. The respective signals provided by the voltage transformer and the current transformer are directly used as relaying signals without resorting to any form of mixing. Phase shifts required, are obtained by using magnetic ferrite cores in a novel manner. Sampling units employing a combination of ferrite cores and semiconductor devices provide highly reliable designs. Special attention is paid to the choice of relaying signals, to eliminate the need for any synchronisation or modification and to avoid `image¿ characteristics. These factors have resulted in a considerable simplification of the practical circuitry. A thyristor AND circuit is employed in dual comparator units to provide the final tripping, and leads to a circuit which is much less sensitive to extraneous signals than a single-thyristor unit.

An (O)over-bar(m(2)n) randomized algorithm to compute a minimum cycle basis of a directed graph

We consider the problem of computing a minimum cycle basis in a directed graph G. The input to this problem is a directed graph whose arcs have positive weights. In this problem a {- 1, 0, 1} incidence vector is associated with each cycle and the vector space over Q generated by these vectors is the cycle space of G. A set of cycles is called a cycle basis of G if it forms a basis for its cycle space. A cycle basis where the sum of weights of the cycles is minimum is called a minimum cycle basis of G. The current fastest algorithm for computing a minimum cycle basis in a directed graph with m arcs and n vertices runs in O(m(w+1)n) time (where w < 2.376 is the exponent of matrix multiplication). If one allows randomization, then an (O) over tilde (m(3)n) algorithm is known for this problem. In this paper we present a simple (O) over tilde (m(2)n) randomized algorithm for this problem. The problem of computing a minimum cycle basis in an undirected graph has been well-studied. In this problem a {0, 1} incidence vector is associated with each cycle and the vector space over F-2 generated by these vectors is the cycle space of the graph. The fastest known algorithm for computing a minimum cycle basis in an undirected graph runs in O(m(2)n + mn(2) logn) time and our randomized algorithm for directed graphs almost matches this running time.

Minimal unsatisfiable sets: Classification and bounds

Proving the unsatisfiability of propositional Boolean formulas has applications in a wide range of fields. Minimal Unsatisfiable Sets (MUS) are signatures of the property of unsatisfiability in formulas and our understanding of these signatures can be very helpful in answering various algorithmic and structural questions relating to unsatisfiability. In this paper, we explore some combinatorial properties of MUS and use them to devise a classification scheme for MUS. We also derive bounds on the sizes of MUS in Horn, 2-SAT and 3-SAT formulas.

Intelligent Approach for Fault Diagnosis in Power Transmission Systems Using Support Vector Machines

This paper presents an approach for identifying the faulted line section and fault location on transmission systems using support vector machines (SVMs) for diagnosis/post-fault analysis purpose. Power system disturbances are often caused by faults on transmission lines. When fault occurs on a transmission system, the protective relay detects the fault and initiates the tripping operation, which isolates the affected part from the rest of the power system. Based on the fault section identified, rapid and corrective restoration procedures can thus be taken to minimize the power interruption and limit the impact of outage on the system. The approach is particularly important for post-fault diagnosis of any mal-operation of relays following a disturbance in the neighboring line connected to the same substation. This may help in improving the fault monitoring/diagnosis process, thus assuring secure operation of the power systems. In this paper we compare SVMs with radial basis function neural networks (RBFNN) in data sets corresponding to different faults on a transmission system. Classification and regression accuracy is reported for both strategies. Studies on a practical 24-Bus equivalent EHV transmission system of the Indian Southern region is presented for indicating the improved generalization with the large margin classifiers in enhancing the efficacy of the chosen model.

Network properties of protein-decoy structures

Convergence of the vast sequence space of proteins into a highly restricted fold/conformational space suggests a simple yet unique underlying mechanism of protein folding that has been the subject of much debate in the last several decades. One of the major challenges related to the understanding of protein folding or in silico protein structure prediction is the discrimination of non-native structures/decoys from the native structure. Applications of knowledge-based potentials to attain this goal have been extensively reported in the literature. Also, scoring functions based on accessible surface area and amino acid neighbourhood considerations were used in discriminating the decoys from native structures. In this article, we have explored the potential of protein structure network (PSN) parameters to validate the native proteins against a large number of decoy structures generated by diverse methods. We are guided by two principles: (a) the PSNs capture the local properties from a global perspective and (b) inclusion of non-covalent interactions, at all-atom level, including the side-chain atoms, in the network construction accommodates the sequence dependent features. Several network parameters such as the size of the largest cluster, community size, clustering coefficient are evaluated and scored on the basis of the rank of the native structures and the Z-scores. The network analysis of decoy structures highlights the importance of the global properties contributing to the uniqueness of native structures. The analysis also exhibits that the network parameters can be used as metrics to identify the native structures and filter out non-native structures/decoys in a large number of data-sets; thus also has a potential to be used in the protein `structure prediction' problem.

On maximum entropy and minimum KL-divergence optimization by Grobner basis methods

In this paper we study constrained maximum entropy and minimum divergence optimization problems, in the cases where integer valued sufficient statistics exists, using tools from computational commutative algebra. We show that the estimation of parametric statistical models in this case can be transformed to solving a system of polynomial equations. We give an implicit description of maximum entropy models by embedding them in algebraic varieties for which we give a Grobner basis method to compute it. In the cases of minimum KL-divergence models we show that implicitization preserves specialization of prior distribution. This result leads us to a Grobner basis method to embed minimum KL-divergence models in algebraic varieties. (C) 2012 Elsevier Inc. All rights reserved.

Badly approximable numbers and vectors in Cantor-like sets

We show that a large class of Cantor-like sets of R-d, d >= 1, contains uncountably many badly approximable numbers, respectively badly approximable vectors, when d >= 2. An analogous result is also proved for subsets of R-d arising in the study of geodesic flows corresponding to (d+1)-dimensional manifolds of constant negative curvature and finite volume, generalizing the set of badly approximable numbers in R. Furthermore, we describe a condition on sets, which is fulfilled by a large class, ensuring a large intersection with these Cantor-like sets.

Rainbow connection number and connected dominating sets

The rainbow connection number of a connected graph is the minimum number of colors needed to color its edges, so that every pair of its vertices is connected by at least one path in which no two edges are colored the same. In this article we show that for every connected graph on n vertices with minimum degree delta, the rainbow connection number is upper bounded by 3n/(delta + 1) + 3. This solves an open problem from Schiermeyer (Combinatorial Algorithms, Springer, Berlin/Hiedelberg, 2009, pp. 432437), improving the previously best known bound of 20n/delta (J Graph Theory 63 (2010), 185191). This bound is tight up to additive factors by a construction mentioned in Caro et al. (Electr J Combin 15(R57) (2008), 1). As an intermediate step we obtain an upper bound of 3n/(delta + 1) - 2 on the size of a connected two-step dominating set in a connected graph of order n and minimum degree d. This bound is tight up to an additive constant of 2. This result may be of independent interest. We also show that for every connected graph G with minimum degree at least 2, the rainbow connection number, rc(G), is upper bounded by Gc(G) + 2, where Gc(G) is the connected domination number of G. Bounds of the form diameter(G)?rc(G)?diameter(G) + c, 1?c?4, for many special graph classes follow as easy corollaries from this result. This includes interval graphs, asteroidal triple-free graphs, circular arc graphs, threshold graphs, and chain graphs all with minimum degree delta at least 2 and connected. We also show that every bridge-less chordal graph G has rc(G)?3.radius(G). In most of these cases, we also demonstrate the tightness of the bounds.