Protein Structure and Function: Looking through the Network of Side-Chain Interactions

Network theory has become an excellent method of choice through which biological data are smoothly integrated to gain insights into complex biological problems. Understanding protein structure, folding, and function has been an important problem, which is being extensively investigated by the network approach. Since the sequence uniquely determines the structure, this review focuses on the networks of non-covalently connected amino acid side chains in proteins. Questions in structural biology are addressed within the framework of such a formalism. While general applications are mentioned in this review, challenging problems which have demanded the attention of scientific community for a long time, such as allostery and protein folding, are considered in greater detail. Our aim has been to explore these important problems through the eyes of networks. Various methods of constructing protein structure networks (PSN) are consolidated. They include the methods based on geometry, edges weighted by different schemes, and also bipartite network of protein-nucleic acid complexes. A number of network metrics that elegantly capture the general features as well as specific features related to phenomena, such as allostery and protein model validation, are described. Additionally, an integration of network theory with ensembles of equilibrium structures of a single protein or that of a large number of structures from the data bank has been presented to perceive complex phenomena from network perspective. Finally, we discuss briefly the capabilities, limitations, and the scope for further explorations of protein structure networks.

Error exponent analysis of energy-based Bayesian decentralized spectrum sensing under fading

This paper considers decentralized spectrum sensing, i.e., detection of occupancy of the primary users' spectrum by a set of Cognitive Radio (CR) nodes, under a Bayesian set-up. The nodes use energy detection to make their individual decisions, which are combined at a Fusion Center (FC) using the K-out-of-N fusion rule. The channel from the primary transmitter to the CR nodes is assumed to undergo fading, while that from the nodes to the FC is assumed to be error-free. In this scenario, a novel concept termed as the Error Exponent with a Confidence Level (EECL) is introduced to evaluate and compare the performance of different detection schemes. Expressions for the EECL under general fading conditions are derived. As a special case, it is shown that the conventional error exponent both at individual sensors, and at the FC is zero. Further, closed-form lower bounds on the EECL are derived under Rayleigh fading and lognormal shadowing. As an example application, it answers the question of whether to use pilot-signal based narrowband sensing, where the signal undergoes Rayleigh fading, or to sense over the entire bandwidth of a wideband signal, where the signal undergoes lognormal shadowing. Theoretical results are validated using Monte Carlo simulations. (C) 2015 Elsevier B.V. All rights reserved.

Dissecting pi-helices: sequence, structure and function

A new procedure for the identification of regular secondary structures using a C-alpha trace has identified 659 pi-helices in 3582 protein chains, solved at high resolution. Taking advantage of this significantly expanded database of pi-helices, we have analysed the functional and structural roles of helices and determined the position-wise amino acid propensity within and around them. These helices range from 5 to 18 residues in length with the average twist and rise being 85.2 +/- 7.2 and 1.28 +/- 0.31 angstrom, respectively. A total of 546 (similar to 83%) out of 659 pi-helices occur in conjunction with alpha-helices, with 101 pi-helices being interspersed between two alpha-helices. The majority of interspersed pi-helices were found to be conserved across a large number of structures within a protein family and produce a significant bend in the overall helical segment as well as local distortions in the neighbouring a-helices. The presence of a pi-helical fragment leads to appropriate orientation of the constituent residues, so as to facilitate favourable interactions and also help in proper folding of the protein chain. In addition to intra helical 6 -> 1 N H center dot center dot center dot O hydrogen bonds, pi-helices are also stabilized by several other non-bonded interactions. pi-Helices show distinct positional residue preferences, which are different from those of a-helices.

Mutations in the nucleotide binding and hydrolysis domains of Helicobacter pylori MutS2 lead to altered biochemical activities and inactivation of its in vivo function

Background: Helicobacter pylori MutS2 (HpMutS2), an inhibitor of recombination during transformation is a non-specific nuclease with two catalytic sites, both of which are essential for its anti-recombinase activity. Although HpMutS2 belongs to a highly conserved family of ABC transporter ATPases, the role of its ATP binding and hydrolysis activities remains elusive. Results: To explore the putative role of ATP binding and hydrolysis activities of HpMutS2 we specifically generated point mutations in the nucleotide-binding Walker-A (HpMutS2-G338R) and hydrolysis Walker-B (HpMutS2-E413A) domains of the protein. Compared to wild-type protein, HpMutS2-G338R exhibited similar to 2.5-fold lower affinity for both ATP and ADP while ATP hydrolysis was reduced by similar to 3-fold. Nucleotide binding efficiencies of HpMutS2-E413A were not significantly altered; however the ATP hydrolysis was reduced by similar to 10-fold. Although mutations in the Walker-A and Walker-B motifs of HpMutS2 only partially reduced its ability to bind and hydrolyze ATP, we demonstrate that these mutants not only exhibited alterations in the conformation, DNA binding and nuclease activities of the protein but failed to complement the hyper-recombinant phenotype displayed by mutS2-disrupted strain of H. pylori. In addition, we show that the nucleotide cofactor modulates the conformation, DNA binding and nuclease activities of HpMutS2. Conclusions: These data describe a strong crosstalk between the ATPase, DNA binding, and nuclease activities of HpMutS2. Furthermore these data show that both, ATP binding and hydrolysis activities of HpMutS2 are essential for the in vivo anti-recombinase function of the protein.

The Feedback Capacity of the Binary Erasure Channel With a No-Consecutive-Ones Input Constraint

The input-constrained erasure channel with feedback is considered, where the binary input sequence contains no consecutive ones, i.e., it satisfies the (1, infinity)-RLL constraint. We derive the capacity for this setting, which can be expressed as C-is an element of = max(0 <= p <= 0.5) (1-is an element of) H-b (p)/1+(1-is an element of) p, where is an element of is the erasure probability and Hb(.) is the binary entropy function. Moreover, we prove that a priori knowledge of the erasure at the encoder does not increase the feedback capacity. The feedback capacity was calculated using an equivalent dynamic programming (DP) formulation with an optimal average-reward that is equal to the capacity. Furthermore, we obtained an optimal encoding procedure from the solution of the DP, leading to a capacity-achieving, zero-error coding scheme for our setting. DP is, thus, shown to be a tool not only for solving optimization problems, such as capacity calculation, but also for constructing optimal coding schemes. The derived capacity expression also serves as the only non-trivial upper bound known on the capacity of the input-constrained erasure channel without feedback, a problem that is still open.

Spatio-temporal Map Formation Based on a Potential Function

We revisit the problem of temporal self organization using activity diffusion based on the neural gas (NGAS) algorithm. Using a potential function formulation motivated by a spatio-temporal metric, we derive an adaptation rule for dynamic vector quantization of data. Simulations results show that our algorithm learns the input distribution and time correlation much faster compared to the static neural gas method over the same data sequence under similar training conditions.

Error Correcting Functional Source Coding with Decoder Side Information using Row-Latin Rectangles

The functional source coding problem in which the receiver side information (Has-set) and demands (Want-set) include functions of source messages is studied using row-Latin rectangle. The source transmits encoded messages, called the functional source code, in order to satisfy the receiver's demands. We obtain a minimum length using the row-Latin rectangle. Next, we consider the case of transmission errors and provide a necessary and sufficient condition that a functional source code must satisfy so that the receiver can correctly decode the values of the functions in its Want-set.

IMAGE DENOISING IN MULTIPLICATIVE NOISE

We address the problem of denoising images corrupted by multiplicative noise. The noise is assumed to follow a Gamma distribution. Compared with additive noise distortion, the effect of multiplicative noise on the visual quality of images is quite severe. We consider the mean-square error (MSE) cost function and derive an expression for an unbiased estimate of the MSE. The resulting multiplicative noise unbiased risk estimator is referred to as MURE. The denoising operation is performed in the wavelet domain by considering the image-domain MURE. The parameters of the denoising function (typically, a shrinkage of wavelet coefficients) are optimized for by minimizing MURE. We show that MURE is accurate and close to the oracle MSE. This makes MURE-based image denoising reliable and on par with oracle-MSE-based estimates. Analogous to the other popular risk estimation approaches developed for additive, Poisson, and chi-squared noise degradations, the proposed approach does not assume any prior on the underlying noise-free image. We report denoising results for various noise levels and show that the quality of denoising obtained is on par with the oracle result and better than that obtained using some state-of-the-art denoisers.

Direct numerical test of the B-G-K model equation by the DSMC method

In the present paper the rarefied gas how caused by the sudden change of the wall temperature and the Rayleigh problem are simulated by the DSMC method which has been validated by experiments both in global flour field and velocity distribution function level. The comparison of the simulated results with the accurate numerical solutions of the B-G-K model equation shows that near equilibrium the BG-K equation with corrected collision frequency can give accurate result but as farther away from equilibrium the B-G-K equation is not accurate. This is for the first time that the error caused by the B-G-K model equation has been revealed.

An New Area Function for Sharp indenter Tips in Nanoindentation

A new area function is introduced and applied to a Berkovich tip in order to characterize the contact projected area between an indenter and indented material. The function can be related directly to tip-rounding, thereby having obviously physical meaning. Nanoindentation experiments are performed on a commercial Nano Indenter XPsystem. The other two area functions introduced by Oliver and Pharr and by Thurn and Cook respectively are involved in this paper for comparison. By comparison from experimental results among different area functions, the indenter tip described by the proposed area function here is very close to the experimental indenter.

Effects of Noise and Detection Error in a Dynamic Adaptive Optics System

It is well known that noise and detection error can affect the performances of an adaptive optics (AO) system. Effects of noise and detection error on the phase compensation effectiveness in a dynamic AO system are investigated by means of a pure numerical simulation in this paper. A theoretical model for numerically simulating effects of noise and detection error in a static AO system and a corresponding computer program were presented in a previous article. A numerical simulation of effects of noise and detection error is combined with our previous numeral simulation of a dynamic AO system in this paper and a corresponding computer program has been compiled. Effects of detection error, readout noise and photon noise are included and investigated by a numerical simulation for finding the preferred working conditions and the best performances in a practical dynamic AO system. An approximate model is presented as well. Under many practical conditions such approximate model is a good alternative to the more accurate one. A simple algorithm which can be used for reducing the effect of noise is presented as well. When signal to noise ratio is very low, such method can be used to improve the performances of a dynamic AO system.