Sensitivity of polarization fluctuations to the nature of protein-water interactions: Study of biological water in four different protein-water systems

Since the time of Kirkwood, observed deviations in magnitude of the dielectric constant of aqueous protein solution from that of neat water (similar to 80) and slower decay of polarization have been subjects of enormous interest, controversy, and debate. Most of the common proteins have large permanent dipole moments (often more than 100 D) that can influence structure and dynamics of even distant water molecules, thereby affecting collective polarization fluctuation of the solution, which in turn can significantly alter solution's dielectric constant. Therefore, distance dependence of polarization fluctuation can provide important insight into the nature of biological water. We explore these aspects by studying aqueous solutions of four different proteins of different characteristics and varying sizes, chicken villin headpiece subdomain (HP-36), immunoglobulin binding domain protein G (GB1), hen-egg white lysozyme (LYS), and Myoglobin (MYO). We simulate fairly large systems consisting of single protein molecule and 20000-30000 water molecules (varied according to the protein size), providing a concentration in the range of similar to 2-3 mM. We find that the calculated dielectric constant of the system shows a noticeable increment in all the cases compared to that of neat water. Total dipole moment auto time correlation function of water < dM(W) (0)delta M-W (t) > is found to be sensitive to the nature of the protein. Surprisingly, dipole moment of the protein and total dipole moment of the water molecules are found to be only weakly coupled. Shellwise decomposition of water molecules around protein reveals higher density of first layer compared to the succeeding ones. We also calculate heuristic effective dielectric constant of successive layers and find that the layer adjacent to protein has much lower value (similar to 50). However, progressive layers exhibit successive increment of dielectric constant, finally reaching a value close to that of bulk 4-5 layers away. We also calculate shellwise orientational correlation function and tetrahedral order parameter to understand the local dynamics and structural re-arrangement of water. Theoretical analysis providing simple method for calculation of shellwise local dielectric constant and implication of these findings are elaborately discussed in the present work. (C) 2014 AIP Publishing LLC.

Finite Element Analysis of Stress Evolution in Al-Si Alloy

A 2D multi-particle model is carried out to understand the effect of microstructural variations and loading conditions on the stress evolution in Al-Si alloy under compression. A total of six parameters are varied to create 26 idealized microstructures: particle size, shape, orientation, matrix temper, strain rate, and temperature. The effect of these parameters is investigated to understand the fracture of Si particles and the yielding of Al matrix. The Si particles are modeled as a linear elastic solid and the Al matrix is modeled as an elasto-plastic solid. The results of the study demonstrate that the increase in particle size decreases the yield strength of the alloy. The particles with high aspect ratio and oriented at 0A degrees and 90A degrees to the loading axis show higher stress values. This implies that the particle shape and orientation are dominant factors in controlling particle fracture. The heat treatment of the alloy is found to increase the stress levels of both particles and matrix. Stress calculations also show that higher particle fracture and matrix yielding is expected at higher strain rate deformation. Particle fracture decreases with increase in temperature and the Al matrix plays an important role in controlling the properties of the alloy at higher temperatures. Further, this strain rate and temperature dependence is more pronounced in the heat-treated microstructure. These predictions are consistent with the experimentally observed Si particle fracture in real microstructure.

Study of Microstructure Evolution during Semi-Solid Processing of an In-Situ Al Alloy Composite

In the present work, effect of pouring temperature (650 degrees C, 655 degrees C, and 660 degrees C) on semi-solid microstructure evolution of in-situ magnesium silicide (Mg2Si) reinforced aluminum (Al) alloy composite has been studied. The shear force exerted by the cooling slope during gravity driven flow of the melt facilitates the formation of near spherical primary Mg2Si and primary Al grains. Shear driven melt flow along the cooling slope and grain fragmentation have been identified as the responsible mechanisms for refinement of primary Mg2Si and Al grains with improved sphericity. Results show that, while flowing down the cooling slope, morphology of primary Mg2Si and primary Al transformed gradually from coarse dendritic to mixture of near spherical particles, rosettes, and degenerated dendrites. In terms of minimum grain size and maximum sphericity, 650 degrees C has been identified as the ideal pouring temperature for the cooling slope semi-solid processing of present Al alloy composite. Formation of spheroidal grains with homogeneous distribution of reinforcing phase (Mg2Si) improves the isotropic property of the said composite, which is desirable in most of the engineering applications.

A literature survey on the real-time computational simulation of biological organs

This paper lists some references that could in some way be relevant in the context of the real-time computational simulation of biological organs, the research area being defined in a very broad sense. This paper contains 198 references.

Evolution of domain combinations in protein kinases and its implications for functional diversity

Protein kinases phosphorylating Ser/Thr/Tyr residues in several cellular proteins exert tight control over their biological functions. They constitute the largest protein family in most eukaryotic species. Protein kinases classified based on sequence similarity in their catalytic domains, cluster into subfamilies, which share gross functional properties. Many protein kinases are associated or tethered covalently to domains that serve as adapter or regulatory modules,naiding substrate recruitment, specificity, and also serve as scaffolds. Hence the modular organisation of the protein kinases serves as guidelines to their functional and molecular properties. Analysis of genomic repertoires of protein kinases in eukaryotes have revealed wide spectrum of domain organisation across various subfamilies of kinases. Occurrence of organism-specific novel domain combinations suggests functional diversity achieved by protein kinases in order to regulate variety of biological processes. In addition, domain architecture of protein kinases revealed existence of hybrid protein kinase subfamilies and their emerging roles in the signaling of eukaryotic organisms. In this review we discuss the repertoire of non-kinase domains tethered to multi-domain kinases in the metazoans. Similarities and differences in the domain architectures of protein kinases in these organisms indicate conserved and unique features that are critical to functional specialization. (C) 2009 Elsevier Ltd. All rights reserved.

Microstructure evolution during solidification of DRMMCs (discontinuously reinforced metal matrix composites): State of art

Distribution of particle reinforcements in cast composites is determined by the morphology of the solidification front. Interestingly, during solidification, the morphology of the interface is intrinsically affected by the presence of dispersed reinforcements. Thus the dispersoid distribution and length scale of matrix microstructure is a result of the interplay between these two. A proper combination of material and process parameters can be used to obtain composites with tailored microstructures. This requires the generation of a broad data base and optimization of the complete solidification process. The length scale of soldification microtructure has a large influence on the mechanical properties of the composites. This presentation addresses the concept of a particle distribution map which can help in predicting particle distribution under different solidification conditions Future research directions have also been indicated.

Computational algorithms inspired by biological processes and evolution

In recent times computational algorithms inspired by biological processes and evolution are gaining much popularity for solving science and engineering problems. These algorithms are broadly classified into evolutionary computation and swarm intelligence algorithms, which are derived based on the analogy of natural evolution and biological activities. These include genetic algorithms, genetic programming, differential evolution, particle swarm optimization, ant colony optimization, artificial neural networks, etc. The algorithms being random-search techniques, use some heuristics to guide the search towards optimal solution and speed-up the convergence to obtain the global optimal solutions. The bio-inspired methods have several attractive features and advantages compared to conventional optimization solvers. They also facilitate the advantage of simulation and optimization environment simultaneously to solve hard-to-define (in simple expressions), real-world problems. These biologically inspired methods have provided novel ways of problem-solving for practical problems in traffic routing, networking, games, industry, robotics, economics, mechanical, chemical, electrical, civil, water resources and others fields. This article discusses the key features and development of bio-inspired computational algorithms, and their scope for application in science and engineering fields.