Identifying functionally important cis-peptide containing segments in proteins and their utility in molecular function annotation

Cis-peptide embedded segments are rare in proteins but often highlight their important role in molecular function when they do occur. The high evolutionary conservation of these segments illustrates this observation almost universally, although no attempt has been made to systematically use this information for the purpose of function annotation. In the present study, we demonstrate how geometric clustering and level-specific Gene Ontology molecular-function terms (also known as annotations) can be used in a statistically significant manner to identify cis-embedded segments in a protein linked to its molecular function. The present study identifies novel cis-peptide fragments, which are subsequently used for fragment-based function annotation. Annotation recall benchmarks interpreted using the receiver-operator characteristic plot returned an area-under-curve >0.9, corroborating the utility of the annotation method. In addition, we identified cis-peptide fragments occurring in conjunction with functionally important trans-peptide fragments, providing additional insights into molecular function. We further illustrate the applicability of our method in function annotation where homology-based annotation transfer is not possible. The findings of the present study add to the repertoire of function annotation approaches and also facilitate engineering, design and allied studies around the cis-peptide neighborhood of proteins.

An iterative framework for sparse signal reconstruction algorithms

It has been shown that iterative re-weighted strategies will often improve the performance of many sparse reconstruction algorithms. However, these strategies are algorithm dependent and cannot be easily extended for an arbitrary sparse reconstruction algorithm. In this paper, we propose a general iterative framework and a novel algorithm which iteratively enhance the performance of any given arbitrary sparse reconstruction algorithm. We theoretically analyze the proposed method using restricted isometry property and derive sufficient conditions for convergence and performance improvement. We also evaluate the performance of the proposed method using numerical experiments with both synthetic and real-world data. (C) 2014 Elsevier B.V. All rights reserved.

Directing peptide conformation with centrally positioned pre-organized dipeptide segments: studies of a 12-residue helix and beta-hairpin

Secondary structure formation in oligopeptides can be induced by short nucleating segments with a high propensity to form hydrogen bonded turn conformations. Type I/III turns facilitate helical folding while type II'/I' turns favour hairpin formation. This principle is experimentally verified by studies of two designed dodecapeptides, Boc-Val-Phe-Leu-Phe-Val-Aib-Aib-Val-Phe-Leu-Phe-Val-OMe 1 and Boc-Val-Phe-Leu-Phe-Val- (D) Pro- (L) Pro-Val-Phe-Leu-Phe-Val-OMe 2. The N- and C-terminal flanking pentapeptide sequences in both cases are identical. Peptide 1 adopts a largely alpha-helical conformation in crystals, with a small 3(10) helical segment at the N-terminus. The overall helical fold is maintained in methanol solution as evidenced by NMR studies. Peptide 2 adopts an antiparallel beta-hairpin conformation stabilized by 6 interstrand hydrogen bonds. Key nuclear Overhauser effects (NOEs) provide evidence for the antiparallel beta-hairpin structure. Aromatic proton chemical shifts provide a clear distinction between the conformation of peptides 1 (helical) and 2 (beta-hairpin). The proximity of facing aromatic residues positioned at non-hydrogen bonding positions in the hairpin results in extensively ring current shifted proton resonances in peptide 2.

Small signal Nonquasi-Static Model for Common Double-Gate MOSFETs Adapted to Gate Oxide Thickness Asymmetry

We present a physics-based closed form small signal Nonquasi-static (NQS) model for a long channel Common Double Gate MOSFET (CDG) by taking into account the asymmetry that may prevail between the gate oxide thickness. We use the unique quasi-linear relationship between the surface potentials along the channel to solve the governing continuity equation (CE) in order to develop the analytical expressions for the Y parameters. The Bessel function based solution of the CE is simplified in form of polynomials so that it could be easily implemented in any circuit simulator. The model shows good agreement with the TCAD simulation at-least till 4 times of the cut-off frequency for different device geometries and bias conditions.

Al3+-Ion-Triggered Conformational Isomerization of a Rhodamine B Derivative Evidenced by a Fluorescence Signal - A Crystallographic Proof

A newly designed rhodamine B anisaldehyde hydrazone exhibits Al3+-ion-induced cis (L) to trans (L) conformational isomerization with respect to the xanthene moiety through a rotation about a N-N bond; the isomerization is indicated by a detectable naked-eye color change and a turn-on red fluorescence in 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) buffer (EtOH/Water 1:9 v/v; pH 7.4) at 25 degrees C. In support of this observation, detailed spectroscopic and physicochemical studies along with density function theory (DFT) calculations have been performed. This cis-to-trans conformational isomerization is due to Al3+ ion coordination, which induces this visual color change and the turn-on fluorescence response. To strengthen our knowledge of the conformational isomerization, detailed structural characterizations of the cis and trans isomers in the solid state were performed by single-crystal X-ray diffraction. To the best of our knowledge, this is the first structural report of both cis and trans conformational isomers for this family of compounds. Moreover, this noncytotoxic probe could be used to image the accumulation of Al3+ ions in HeLa and MCF-7 cell lines.

The peptide NCbz-Val-Tyr-OMe and aromatic pi-pi interactions

The peptide N-benzyloxycarbonyl-L-valyl-L-tyrosine methyl ester or NCbz-Val-Tyr-OMe (where NCbz is N-benzyloxycarbonyl and OMe indicates the methyl ester), C23H28N2O6, has an extended backbone conformation. The aromatic rings of the Tyr residue and the NCbz group are involved in various attractive intra- and intermolecular aromatic - interactions which stabilize the conformation and packing in the crystal structure, in addition to NH...O and OH...O hydrogen bonds. The aromatic - interactions include parallel-displaced, perpendicular T-shaped, perpendicular L-shaped and inclined orientations.

Effects of hydrogen bonding on amide-proton chemical shift anisotropy in a proline-containing model peptide

Longitudinal relaxation due to cross-correlation between dipolar ((HN-1H alpha)-H-1) and amide-proton chemical shift anisotropy (H-1(N) CSA) has been measured in a model tripeptide Piv-(L)Pro-(L)Pro-(L)Phe-OMe. The peptide bond across diproline segment is known to undergo cis/trans isomerization and only in the cis form does the lone Phe amide-proton become involved in intramolecular hydrogen bonding. The strength of the cross correlated relaxation interference is found to be significantly different between cis and trans forms, and this difference is shown as an influence of intramolecular hydrogen bonding on the amide-proton CSA. (C) 2015 Elsevier B.V. All rights reserved.

PERCOLATION ON THE INFORMATION-THEORETICALLY SECURE SIGNAL TO INTERFERENCE RATIO GRAPH

We consider a continuum percolation model consisting of two types of nodes, namely legitimate and eavesdropper nodes, distributed according to independent Poisson point processes in R-2 of intensities lambda and lambda(E), respectively. A directed edge from one legitimate node A to another legitimate node B exists provided that the strength of the signal transmitted from node A that is received at node B is higher than that received at any eavesdropper node. The strength of the signal received at a node from a legitimate node depends not only on the distance between these nodes, but also on the location of the other legitimate nodes and an interference suppression parameter gamma. The graph is said to percolate when there exists an infinitely connected component. We show that for any finite intensity lambda(E) of eavesdropper nodes, there exists a critical intensity lambda(c) < infinity such that for all lambda > lambda(c) the graph percolates for sufficiently small values of the interference parameter. Furthermore, for the subcritical regime, we show that there exists a lambda(0) such that for all lambda < lambda(0) <= lambda(c) a suitable graph defined over eavesdropper node connections percolates that precludes percolation in the graphs formed by the legitimate nodes.

Robust Whisper Activity Detection Using Long-Term Log Energy Variation of Sub-Band Signal

The goal in the whisper activity detection (WAD) is to find the whispered speech segments in a given noisy recording of whispered speech. Since whispering lacks the periodic glottal excitation, it resembles an unvoiced speech. This noise-like nature of the whispered speech makes WAD a more challenging task compared to a typical voice activity detection (VAD) problem. In this paper, we propose a feature based on the long term variation of the logarithm of the short-time sub-band signal energy for WAD. We also propose an automatic sub-band selection algorithm to maximally discriminate noisy whisper from noise. Experiments with eight noise types in four different signal-to-noise ratio (SNR) conditions show that, for most of the noises, the performance of the proposed WAD scheme is significantly better than that of the existing VAD schemes and whisper detection schemes when used for WAD.

Event-triggered sampling using signal extrema for instantaneous amplitude and instantaneous frequency estimation

Event-triggered sampling (ETS) is a new approach towards efficient signal analysis. The goal of ETS need not be only signal reconstruction, but also direct estimation of desired information in the signal by skillful design of event. We show a promise of ETS approach towards better analysis of oscillatory non-stationary signals modeled by a time-varying sinusoid, when compared to existing uniform Nyquist-rate sampling based signal processing. We examine samples drawn using ETS, with events as zero-crossing (ZC), level-crossing (LC), and extrema, for additive in-band noise and jitter in detection instant. We find that extrema samples are robust, and also facilitate instantaneous amplitude (IA), and instantaneous frequency (IF) estimation in a time-varying sinusoid. The estimation is proposed solely using extrema samples, and a local polynomial regression based least-squares fitting approach. The proposed approach shows improvement, for noisy signals, over widely used analytic signal, energy separation, and ZC based approaches (which are based on uniform Nyquist-rate sampling based data-acquisition and processing). Further, extrema based ETS in general gives a sub-sampled representation (relative to Nyquistrate) of a time-varying sinusoid. For the same data-set size captured with extrema based ETS, and uniform sampling, the former gives much better IA and IF estimation. (C) 2015 Elsevier B.V. All rights reserved.

Deciphering complex patterns of class-I HLA-peptide cross-reactivity via hierarchical grouping

T-cell responses in humans are initiated by the binding of a peptide antigen to a human leukocyte antigen (HLA) molecule. The peptide-HLA complex then recruits an appropriate T cell, leading to cell-mediated immunity. More than 2000 HLA class-I alleles are known in humans, and they vary only in their peptide-binding grooves. The polymorphism they exhibit enables them to bind a wide range of peptide antigens from diverse sources. HLA molecules and peptides present a complex molecular recognition pattern, as many peptides bind to a given allele and a given peptide can be recognized by many alleles. A powerful grouping scheme that not only provides an insightful classification, but is also capable of dissecting the physicochemical basis of recognition specificity is necessary to address this complexity. We present a hierarchical classification of 2010 class-I alleles by using a systematic divisive clustering method. All-pair distances of alleles were obtained by comparing binding pockets in the structural models. By varying the similarity thresholds, a multilevel classification was obtained, with 7 supergroups, each further subclassifying to yield 72 groups. An independent clustering performed based only on similarities in their epitope pools correlated highly with pocket-based clustering. Physicochemical feature combinations that best explain the basis of clustering are identified. Mutual information calculated for the set of peptide ligands enables identification of binding site residues contributing to peptide specificity. The grouping of HLA molecules achieved here will be useful for rational vaccine design, understanding disease susceptibilities and predicting risk of organ transplants.

Multi-agent Reinforcement Learning for Traffic Signal Control

Optimal control of traffic lights at junctions or traffic signal control (TSC) is essential for reducing the average delay experienced by the road users amidst the rapid increase in the usage of vehicles. In this paper, we formulate the TSC problem as a discounted cost Markov decision process (MDP) and apply multi-agent reinforcement learning (MARL) algorithms to obtain dynamic TSC policies. We model each traffic signal junction as an independent agent. An agent decides the signal duration of its phases in a round-robin (RR) manner using multi-agent Q-learning with either is an element of-greedy or UCB 3] based exploration strategies. It updates its Q-factors based on the cost feedback signal received from its neighbouring agents. This feedback signal can be easily constructed and is shown to be effective in minimizing the average delay of the vehicles in the network. We show through simulations over VISSIM that our algorithms perform significantly better than both the standard fixed signal timing (FST) algorithm and the saturation balancing (SAT) algorithm 15] over two real road networks.

Physical Layer Data Fusion Via Distributed Co-Phasing With General Signal Constellations

This paper studies a pilot-assisted physical layer data fusion technique known as Distributed Co-Phasing (DCP). In this two-phase scheme, the sensors first estimate the channel to the fusion center (FC) using pilots sent by the latter; and then they simultaneously transmit their common data by pre-rotating them by the estimated channel phase, thereby achieving physical layer data fusion. First, by analyzing the symmetric mutual information of the system, it is shown that the use of higher order constellations (HOC) can improve the throughput of DCP compared to the binary signaling considered heretofore. Using an HOC in the DCP setting requires the estimation of the composite DCP channel at the FC for data decoding. To this end, two blind algorithms are proposed: 1) power method, and 2) modified K-means algorithm. The latter algorithm is shown to be computationally efficient and converges significantly faster than the conventional K-means algorithm. Analytical expressions for the probability of error are derived, and it is found that even at moderate to low SNRs, the modified K-means algorithm achieves a probability of error comparable to that achievable with a perfect channel estimate at the FC, while requiring no pilot symbols to be transmitted from the sensor nodes. Also, the problem of signal corruption due to imperfect DCP is investigated, and constellation shaping to minimize the probability of signal corruption is proposed and analyzed. The analysis is validated, and the promising performance of DCP for energy-efficient physical layer data fusion is illustrated, using Monte Carlo simulations.

A sleep-inducing peptide from the venom of the Indian cone snail Conus araneosus

The marine snail Conus araneosus has unusual significance due to its confined distribution to coastal regions of southeast India and Sri Lanka. Due to its relative scarceness, this species has been poorly studied. In this work, we characterized the venom of C. araneosus to identify new venom peptides. We identified 14 novel compounds. We determined amino acid sequences from chemically-modified and unmodified crude venom using liquid chromatography-electrospray ionization mass spectrometry and matrix assisted laser desorption ionization time-of-flight mass spectrometry. Ten sequences showed six Cys residues arranged in a pattern that is most commonly associated with the M-superfamily of conotoxins. Four other sequences had four Cys residues in a pattern that is most commonly associated with the T-superfamily of conotoxins. The post-translationally modified residue (pyroglutamate) was determined at the N-terminus of two sequences, ar3h and ar3i respectively. In addition, two sequences, ar3g and ar3h were C-terminally amidated. At a dose of 2 nmol, peptide ar3j elicited sleep when injected intraperitoneally into mice. To our knowledge, this is the first report of a peptide from a molluscivorous cone snail with sleep-inducing effects in mice. The novel peptides characterized herein extend the repertoire of unique peptides derived from cone snails and may add value to the therapeutic promise of conotoxins. (C) 2015 Elsevier Ltd. All rights reserved.

An Unbiased Risk Estimator for Multiplicative Noise - Application to 1-D Signal Denoising

The effect of multiplicative noise on a signal when compared with that of additive noise is very large. In this paper, we address the problem of suppressing multiplicative noise in one-dimensional signals. To deal with signals that are corrupted with multiplicative noise, we propose a denoising algorithm based on minimization of an unbiased estimator (MURE) of meansquare error (MSE). We derive an expression for an unbiased estimate of the MSE. The proposed denoising is carried out in wavelet domain (soft thresholding) by considering time-domain MURE. The parameters of thresholding function are obtained by minimizing the unbiased estimator MURE. We show that the parameters for optimal MURE are very close to the optimal parameters considering the oracle MSE. Experiments show that the SNR improvement for the proposed denoising algorithm is competitive with a state-of-the-art method.