The origins of the evolutionary signal used to predict protein-protein interactions

Background: The correlation of genetic distances between pairs of protein sequence alignments has been used to infer protein-protein interactions. It has been suggested that these correlations are based on the signal of co-evolution between interacting proteins. However, although mutations in different proteins associated with maintaining an interaction clearly occur (particularly in binding interfaces and neighbourhoods), many other factors contribute to correlated rates of sequence evolution. Proteins in the same genome are usually linked by shared evolutionary history and so it would be expected that there would be topological similarities in their phylogenetic trees, whether they are interacting or not. For this reason the underlying species tree is often corrected for. Moreover processes such as expression level, are known to effect evolutionary rates. However, it has been argued that the correlated rates of evolution used to predict protein interaction explicitly includes shared evolutionary history; here we test this hypothesis. Results: In order to identify the evolutionary mechanisms giving rise to the correlations between interaction proteins, we use phylogenetic methods to distinguish similarities in tree topologies from similarities in genetic distances. We use a range of datasets of interacting and non-interacting proteins from Saccharomyces cerevisiae. We find that the signal of correlated evolution between interacting proteins is predominantly a result of shared evolutionary rates, rather than similarities in tree topology, independent of evolutionary divergence. Conclusions: Since interacting proteins do not have tree topologies that are more similar than the control group of non-interacting proteins, it is likely that coevolution does not contribute much to, if any, of the observed correlations.

Evolution of Texture and Microstructure in Commercially Pure Titanium with Change in Strain Path During Rolling

The evolution of microstructure and texture in commercially pure titanium has been studied as a function of strain path during rolling using experimental techniques and viscoplastic self-consistent simulations. Four different strain paths, namely unidirectional rolling, two-step cross rolling, multistep cross rolling, and reverse rolling, have been employed to decipher the effect of strain path change on the evolution of deformation texture and microstructure. The cross-rolled samples show higher hardness with lower microstrain and intragranular misorientation compared to the unidirectional rolled sample as determined from X-ray diffraction and electron backscatter diffraction, respectively. The higher hardness of the cross-rolled samples is attributed to orientation hardening due to the near basal texture. Viscoplastic self-consistent simulations are able to successfully predict the texture evolution of the differently rolled samples. Simulation results indicate the higher contribution of basal slip in the formation of near basal texture and as well as lower intragranular misorientation in the cross-rolled samples.

A POSSIBLE EVOLUTIONARY SCENARIO OF HIGHLY MAGNETIZED SUPER-CHANDRASEKHAR WHITE DWARFS: PROGENITORS OF PECULIAR TYPE Ia SUPERNOVAE

Several recently discovered peculiar Type Ia supernovae seem to demand an altogether new formation theory that might help explain the puzzling dissimilarities between them and the standard Type Ia supernovae. The most striking aspect of the observational analysis is the necessity of invoking super-Chandrasekhar white dwarfs having masses similar to 2.1-2.8 M-circle dot, M-circle dot being the mass of Sun, as their most probable progenitors. Strongly magnetized white dwarfs having super-Chandrasekhar masses have already been established as potential candidates for the progenitors of peculiar Type Ia supernovae. Owing to the Landau quantization of the underlying electron degenerate gas, theoretical results yielded the observationally inferred mass range. Here, we sketch a possible evolutionary scenario by which super-Chandrasekhar white dwarfs could be formed by accretion on to a commonly observed magnetized white dwarf, invoking the phenomenon of flux freezing. This opens multiple possible evolution scenarios ending in supernova explosions of super-Chandrasekhar white dwarfs having masses within the range stated above. We point out that our proposal has observational support, such as the recent discovery of a large number of magnetized white dwarfs by the Sloan Digital Sky Survey.

DMT of parallel-path and layered networks under the half-duplex constraint

In this paper, we study the diversity-multiplexing-gain tradeoff (DMT) of wireless relay networks under the half-duplex constraint. It is often unclear what penalty if any, is imposed by the half-duplex constraint on the DMT of such networks. We study two classes of networks; the first class, called KPP(I) networks, is the class of networks with the relays organized in K parallel paths between the source and the destination. While we assume that there is no direct source-destination path, the K relaying paths can interfere with each other. The second class, termed as layered networks, is comprised of relays organized in layers, where links exist only between adjacent layers. We present a communication scheme based on static schedules and amplify-and-forward relaying for these networks. We also show that for KPP(I) networks with K >= 3, the proposed schemes can achieve full-duplex DMT performance, thus demonstrating that there is no performance hit on the DMT due to the half-duplex constraint. We also show that, for layered networks, a linear DMT of d(max)(1 - r)(+) between the maximum diversity d(max) and the maximum MG, r(max) = 1 is achievable. We adapt existing DMT optimal coding schemes to these networks, thus specifying the end-to-end communication strategy explicitly.

Optimal synthesis of adjustable planar four-bar crank-rocker type mechanisms for approximate multi-path generation

This paper deals with an optimization based method for synthesis of adjustable planar four-bar, crank-rocker mechanisms. For multiple different and desired paths to be traced by a point on the coupler, a two stage method first determines the parameters of the possible driving dyads. Then the remaining mechanism parameters are determined in the second stage where a least-squares based circle-fitting procedure is used. Compared to existing formulations, the optimization method uses less number of design variables. Two numerical examples demonstrate the effectiveness of the proposed synthesis method. (C) 2013 Elsevier Ltd. All rights reserved.

Sustaining cooperation on networks: an analytical study based on evolutionary game theory

We analytically study the role played by the network topology in sustaining cooperation in a society of myopic agents in an evolutionary setting. In our model, each agent plays the Prisoner's Dilemma (PD) game with its neighbors, as specified by a network. Cooperation is the incumbent strategy, whereas defectors are the mutants. Starting with a population of cooperators, some agents are switched to defection. The agents then play the PD game with their neighbors and compute their fitness. After this, an evolutionary rule, or imitation dynamic is used to update the agent strategy. A defector switches back to cooperation if it has a cooperator neighbor with higher fitness. The network is said to sustain cooperation if almost all defectors switch to cooperation. Earlier work on the sustenance of cooperation has largely consisted of simulation studies, and we seek to complement this body of work by providing analytical insight for the same. We find that in order to sustain cooperation, a network should satisfy some properties such as small average diameter, densification, and irregularity. Real-world networks have been empirically shown to exhibit these properties, and are thus candidates for the sustenance of cooperation. We also analyze some specific graphs to determine whether or not they sustain cooperation. In particular, we find that scale-free graphs belonging to a certain family sustain cooperation, whereas Erdos-Renyi random graphs do not. To the best of our knowledge, ours is the first analytical attempt to determine which networks sustain cooperation in a population of myopic agents in an evolutionary setting.

Reaction dynamics under confinement: an exact path integral treatment of a two-stage model of stochastic gene expression

Gene expression in living systems is inherently stochastic, and tends to produce varying numbers of proteins over repeated cycles of transcription and translation. In this paper, an expression is derived for the steady-state protein number distribution starting from a two-stage kinetic model of the gene expression process involving p proteins and r mRNAs. The derivation is based on an exact path integral evaluation of the joint distribution, P(p, r, t), of p and r at time t, which can be expressed in terms of the coupled Langevin equations for p and r that represent the two-stage model in continuum form. The steady-state distribution of p alone, P(p), is obtained from P(p, r, t) (a bivariate Gaussian) by integrating out the r degrees of freedom and taking the limit t -> infinity. P(p) is found to be proportional to the product of a Gaussian and a complementary error function. It provides a generally satisfactory fit to simulation data on the same two-stage process when the translational efficiency (a measure of intrinsic noise levels in the system) is relatively low; it is less successful as a model of the data when the translational efficiency (and noise levels) are high.

Optimum steering input determination and path-tracking of all-wheel steer vehicles on uneven terrains based on constrained optimization

In this paper we propose a framework for optimum steering input determination of all-wheel steer vehicles (AWSV) on rough terrains. The framework computes the steering input which minimizes the tracking error for a given trajectory. Unlike previous methodologies of computing steering inputs of car-like vehicles, the proposed methodology depends explicitly on the vehicle dynamics and can be extended to vehicle having arbitrary number of steering inputs. A fully generic framework has been used to derive the vehicle dynamics and a non-linear programming based constrained optimization approach has been used to compute the steering input considering the instantaneous vehicle dynamics, no-slip and contact constraints of the vehicle. All Wheel steer Vehicles have a special parallel steering ability where the instantaneous centre of rotation (ICR) is at infinity. The proposed framework automatically enables the vehicle to choose between parallel steer and normal operation depending on the error with respect to the desired trajectory. The efficacy of the proposed framework is proved by extensive uneven terrain simulations, for trajectories with continuous or discontinuous velocity profile.

Optimal trajectory planning for path convergence in three-dimensional space

This article addresses the problem of determining the shortest path that connects a given initial configuration (position, heading angle, and flight path angle) to a given rectilinear or a circular path in three-dimensional space for a constant speed and turn-rate constrained aerial vehicle. The final path is assumed to be located relatively far from the starting point. Due to its simplicity and low computational requirements the algorithm can be implemented on a fixed-wing type unmanned air vehicle in real time in missions where the final path may change dynamically. As wind has a very significant effect on the flight of small aerial vehicles, the method of optimal path planning is extended to meet the same objective in the presence of wind comparable to the speed of the aerial vehicles. But, if the path to be followed is closer to the initial point, an off-line method based on multiple shooting, in combination with a direct transcription technique, is used to obtain the optimal solution. Optimal paths are generated for a variety of cases to show the efficiency of the algorithm. Simulations are presented to demonstrate tracking results using a 6-degrees-of-freedom model of an unmanned air vehicle.

Correlation between local structural dynamics of proteins inferred from NMR ensembles and evolutionary dynamics of homologues of known structure

Conformational changes in proteins are extremely important for their biochemical functions. Correlation between inherent conformational variations in a protein and conformational differences in its homologues of known structure is still unclear. In this study, we have used a structural alphabet called Protein Blocks (PBs). PBs are used to perform abstraction of protein 3-D structures into a 1-D strings of 16 alphabets (a-p) based on dihedral angles of overlapping pentapeptides. We have analyzed the variations in local conformations in terms of PBs represented in the ensembles of 801 protein structures determined using NMR spectroscopy. In the analysis of concatenated data over all the residues in all the NMR ensembles, we observe that the overall nature of inherent local structural variations in NMR ensembles is similar to the nature of local structural differences in homologous proteins with a high correlation coefficient of .94. High correlation at the alignment positions corresponding to helical and beta-sheet regions is only expected. However, the correlation coefficient by considering only the loop regions is also quite high (.91). Surprisingly, segregated position-wise analysis shows that this high correlation does not hold true to loop regions at the structurally equivalent positions in NMR ensembles and their homologues of known structure. This suggests that the general nature of local structural changes is unique; however most of the local structural variations in loop regions of NMR ensembles do not correlate to their local structural differences at structurally equivalent positions in homologues.

Diffraction tomography from intensity measurements: an evolutionary stochastic search to invert experimental data

We develop iterative diffraction tomography algorithms, which are similar to the distorted Born algorithms, for inverting scattered intensity data. Within the Born approximation, the unknown scattered field is expressed as a multiplicative perturbation to the incident field. With this, the forward equation becomes stable, which helps us compute nearly oscillation-free solutions that have immediate bearing on the accuracy of the Jacobian computed for use in a deterministic Gauss-Newton (GN) reconstruction. However, since the data are inherently noisy and the sensitivity of measurement to refractive index away from the detectors is poor, we report a derivative-free evolutionary stochastic scheme, providing strictly additive updates in order to bridge the measurement-prediction misfit, to arrive at the refractive index distribution from intensity transport data. The superiority of the stochastic algorithm over the GN scheme for similar settings is demonstrated by the reconstruction of the refractive index profile from simulated and experimentally acquired intensity data. (C) 2014 Optical Society of America

A fractional order proportional integral controller for path following and trajectory tracking of miniature air vehicles

In this paper, a fractional order proportional-integral controller is developed for a miniature air vehicle for rectilinear path following and trajectory tracking. The controller is implemented by constructing a vector field surrounding the path to be followed, which is then used to generate course commands for the miniature air vehicle. The fractional order proportional-integral controller is simulated using the fundamentals of fractional calculus, and the results for this controller are compared with those obtained for a proportional controller and a proportional integral controller. In order to analyze the performance of the controllers, four performance metrics, namely (maximum) overshoot, control effort, settling time and integral of the timed absolute error cost, have been selected. A comparison of the nominal as well as the robust performances of these controllers indicates that the fractional order proportional-integral controller exhibits the best performance in terms of ITAE while showing comparable performances in all other aspects.

Time-Optimal Convergence to a Rectilinear Path in the Presence of Wind

This paper considers the problem of determining the time-optimal path of a fixed-wing Miniature Air Vehicle (MAV), in the presence of wind. The MAV, which is subject to a bounded turn rate, is required to eventually converge to a straight line starting from a known initial position and orientation. Earlier work in the literature uses Pontryagin's Minimum Principle (PMP) to solve this problem only for the no-wind case. In contrast, the present work uses a geometric approach to solve the problem completely in the presence of wind. In addition, it also shows how PMP can be used to partially solve the problem. Using a 6-DOF model of a MAV the generated optimal path is tracked by an autopilot consisting of proportional-integral-derivative (PID) controllers. The simulation results show the path generation and tracking for cases with steady and time-varying wind. Some issues on real-time path planning are also addressed.

Bi-Domain Protein Tyrosine Phosphatases Reveal an Evolutionary Adaptation to Optimize Signal Transduction

Significance: The bi-domain protein tyrosine phosphatases (PTPs) exemplify functional evolution in signaling proteins for optimal spatiotemporal signal transduction. Bi-domain PTPs are products of gene duplication. The catalytic activity, however, is often localized to one PTP domain. The inactive PTP domain adopts multiple functional roles. These include modulation of catalytic activity, substrate specificity, and stability of the bi-domain enzyme. In some cases, the inactive PTP domain is a receptor for redox stimuli. Since multiple bi-domain PTPs are concurrently active in related cellular pathways, a stringent regulatory mechanism and selective cross-talk is essential to ensure fidelity in signal transduction. Recent Advances: The inactive PTP domain is an activator for the catalytic PTP domain in some cases, whereas it reduces catalytic activity in other bi-domain PTPs. The relative orientation of the two domains provides a conformational rationale for this regulatory mechanism. Recent structural and biochemical data reveal that these PTP domains participate in substrate recruitment. The inactive PTP domain has also been demonstrated to undergo substantial conformational rearrangement and oligomerization under oxidative stress. Critical Issues and Future Directions: The role of the inactive PTP domain in coupling environmental stimuli with catalytic activity needs to be further examined. Another aspect that merits attention is the role of this domain in substrate recruitment. These aspects have been poorly characterized in vivo. These lacunae currently restrict our understanding of neo-functionalization of the inactive PTP domain in the bi-domain enzyme. It appears likely that more data from these research themes could form the basis for understanding the fidelity in intracellular signal transduction.

Accurate prediction of interfacial residues in two-domain proteins using evolutionary information: Implications for three-dimensional modeling

With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naive Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (approximate to 85%) and specific (approximate to 95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions. Proteins 2014; 82:1219-1234. (c) 2013 Wiley Periodicals, Inc.