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.

Intrinsic Limit for Contact Resistance in Exfoliated Multilayered MoS2 FET

A new method for the separation of contact resistance (R-contact) into Schottky barrier resistance (R-SB) and interlayer resistance (R-IL) is proposed for multilayered MoS2 FETs. While R-SB varies exponentially with Schottky barrier height (Phi(bn)), R-IL essentially remains unchanged. An empirical model utilizing this dependence of R-contact versus Phi(bn) is proposed and fits to the experimental data. The results, on comparison with the existing reports of lowest R-contact, suggest that the extracted R-IL (1.53 k Omega.mu m) for an unaltered channel would determine the lower limit of intrinsic R-contact even for barrierless contacts for multilayered exfoliated MoS2 FETs.

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.

Reply to Discussion on ``Bearing capacity of circular footings over rock mass by using axisymmetric quasi lower bound finite element limit analysis'' Comput. Geotech. 70 (2015) 138-149]

A discussion has been provided for the comments raised by the discusser (Clausen, 2015)1] on the article recently published by the authors (Chakraborty and Kumar, 2015). The effect of exponent alpha for values of GSI approximately smaller than 30 becomes more critical. On the other hand, for greater values of GSI, the results obtained by the authors earlier remain primarily independent of alpha and can be easily used. (C) 2015 Elsevier Ltd. All rights reserved.

Doping dependence of fluctuation diamagnetism in high T-c superconductors

Using a recently proposed Ginzburg-Landau-like lattice free energy functional due to Banerjee et al. (2011) we calculate the fluctuation diamagnetism of high -T-c superconductors as a function of doping, magnetic field and temperature. We analyse the pairing fluctuations above the superconducting transition temperature in the cuprates, ranging from the strong phase fluctuation dominated underdoped limit to the more conventional amplitude fluctuation dominated overdoped regime. We show that a model where the pairing scale increases and the superfluid density decreases with underdoping produces features of the observed magnetization in the pseudogap region, in good qualitative and reasonable quantitative agreement with the experimental data. In particular, we explicitly show that even when the pseudogap has a pairing origin the magnetization actually tracks the superconducting dome instead of the pseudogap temperature, as seen in experiment. We discuss the doping dependence of the `onset' temperature for fluctuation diamagnetism and comment on the role of vortex core -energy jn our model. (C) 2015 Elsevier Inc. All rights reserved.

Complex patterns arise through spontaneous symmetry breaking in dense homogeneous networks of neural oscillators

There has been much interest in understanding collective dynamics in networks of brain regions due to their role in behavior and cognitive function. Here we show that a simple, homogeneous system of densely connected oscillators, representing the aggregate activity of local brain regions, can exhibit a rich variety of dynamical patterns emerging via spontaneous breaking of permutation or translational symmetries. Upon removing just a few connections, we observe a striking departure from the mean-field limit in terms of the collective dynamics, which implies that the sparsity of these networks may have very important consequences. Our results suggest that the origins of some of the complicated activity patterns seen in the brain may be understood even with simple connection topologies.

Combustion and heat transfer characteristics of nanofluid fuel droplets: A short review

With the pressing need to meet an ever-increasing energy demand, the combustion systems utilizing fossil fuels have been the major contributors to carbon footprint. As the combustion of conventional energy resources continue to produce significant Green House gas (GHG) emissions, there is a strong emphasis to either upgrade or find an energy-efficient eco-friendly alternative to the traditional hydrocarbon fuels. With recent developments in nanotechnology, the ability to manufacture materials with custom tailored properties at nanoscale has led to the discovery of a new class of high energy density fuels containing reactive metallic nanoparticles (NPs). Due to the high reactive interfacial area and enhanced thermal and mass transport properties of nanomaterials, the high heat of formation of these metallic fuels can now be released rapidly, thereby saving on specific fuel consumption and hence reducing GHG emissions. In order to examine the efficacy of nanofuels in energetic formulations, it is imperative to first study their combustion characteristics at the droplet scale that form the fundamental building block for any combustion system utilizing liquid fuel spray. During combustion of such multiphase, multicomponent droplets, the phenomenon of diffusional entrapment of high volatility species leads to its explosive boiling (at the superheat limit) thereby leading to an intense internal pressure build-up. This pressure upsurge causes droplet fragmentation either in form of a microexplosion or droplet puffing followed by atomization (with formation of daughter droplets) featuring disruptive burning. Both these atomization modes represent primary mechanisms for extracting the high oxidation energies of metal NP additives by exposing them to the droplet flame (with daughter droplets acting as carriers of NPs). Atomization also serves as a natural mechanism for uniform distribution and mixing of the base fuel and enhancing burning rates (due to increase in specific surface area through formation of smaller daughter droplets). However, the efficiency of atomization depends on the thermo-physical properties of the base fuel, NP concentration and type. For instance, at dense loading NP agglomeration may lead to shell formation which would sustain the pressure upsurge and hence suppress atomization thereby reducing droplet gasification rate. Contrarily, the NPs may act as nucleation sites and aid boiling and the radiation absorption by NPs (from the flame) may lead to enhanced burning rates. Thus, nanoadditives may have opposing effects on the burning rate depending on the relative dominance of processes occurring at the droplet scale. The fundamental idea in this study is to: First, review different thermo-physical processes that occur globally at the droplet and sub-droplet scale such as surface regression, shell formation due to NP agglomeration, internal boiling, atomization/NP transport to flame zone and flame acoustic interaction that occur at the droplet scale and second, understand how their interaction changes as a function of droplet size, NP type, NP concentration and the type of base fuel. This understanding is crucial for obtaining phenomenological insights on the combustion behavior of novel nanofluid fuels that show great promise for becoming the next-generation fuels. (C) 2016 Elsevier Ltd. All rights reserved.

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.

Strain gradient theory with couple stress for crystalline solids

A new phenomenological strain gradient theory for crystalline solid is proposed. It fits within the framework of general couple stress theory and involves a single material length scale Ics. In the present theory three rotational degrees of freedom omega (i) are introduced, which denote part of the material angular displacement theta (i) and are induced accompanying the plastic deformation. omega (i) has no direct dependence upon u(i) while theta = (1 /2) curl u. The strain energy density omega is assumed to consist of two parts: one is a function of the strain tensor epsilon (ij) and the curvature tensor chi (ij), where chi (ij) = omega (i,j); the other is a function of the relative rotation tensor alpha (ij). alpha (ij) = e(ijk) (omega (k) - theta (k)) plays the role of elastic rotation reason The anti-symmetric part of Cauchy stress tau (ij) is only the function of alpha (ij) and alpha (ij) has no effect on the symmetric part of Cauchy stress sigma (ij) and the couple stress m(ij). A minimum potential principle is developed for the strain gradient deformation theory. In the limit of vanishing l(cs), it reduces to the conventional counterparts: J(2) deformation theory. Equilibrium equations, constitutive relations and boundary conditions are given in detail. For simplicity, the elastic relation between the anti-symmetric part of Cauchy stress tau (ij), and alpha (ij) is established and only one elastic constant exists between the two tensors. Combining the same hardening law as that used in previously by other groups, the present theory is used to investigate two typical examples, i.e., thin metallic wire torsion and ultra-thin metallic beam bend, the analytical results agree well with the experiment results. While considering the, stretching gradient, a new hardening law is presented and used to analyze the two typical problems. The flow theory version of the present theory is also given.

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.

A generalized self-consistent method accounting for fiber section shape

A three-phase confocal elliptical cylinder model is proposed for fiber-reinforced composites, in terms of which a generalized self-consistent method is developed for fiber-reinforced composites accounting for variations in fiber section shapes and randomness in fiber section orientation. The reasonableness of the fiber distribution function in the present model is shown. The dilute, self-consistent, differential and Mori-Tanaka methods are also extended to consider randomness in fiber section orientation in a statistical sense. A full comparison is made between various micromechanics methods and with the Hashin and Shtrikman's bounds. The present method provides convergent and reasonable results for a full range of variations in fiber section shapes (from circular fibers to ribbons), for a complete spectrum of the fiber volume fraction (from 0 to 1, and the latter limit shows the correct asymptotic behavior in the fully packed case) and for extreme types of the inclusion phases (from voids to rigid inclusions). A very different dependence of the five effective moduli on fiber section shapes is theoretically predicted, and it provides a reasonable explanation on the poor correlation between previous theory and experiment in the case of longitudinal shear modulus.

Dynamic function of damage and its implications

Dynamic function of damage is the key to the problem of damage evolution of solids. In order to understand it, one must understand its mesoscopic mechanisms and macroscopic formulation. In terms of evolution equation of microdamage and damage moment, a dynamic function of damage is strictly defined. The mesoscopic mechanism underlying self-closed damage evolution law is investigated by means of double damage moments. Numerical results of damage evolution demonstrate some common features for various microdamage dynamics. Then, the dynamic function of damage is applied to inhomogeneous damage field. In this case, damage evolution rate is no longer equal to the dynamic function of damage. It is found that the criterion for damage localization is closely related to compound damage. Finally, an inversion of damage evolution to the dynamic function of damage is proposed.