Endonuclease Active Site Plasticity Allows DNA Cleavage with Diverse Alkaline Earth and Transition Metal Ions

A majority of enzymes show a high degree of specificity toward a particular metal ion in their catalytic reaction. However, Type II restriction endonuclease (REase) R.KpnI, which is the first member of the HNH superfamily of REases, exhibits extraordinary diversity in metal ion dependent DNA cleavage. Several alkaline earth and transition group metal ions induce high fidelity and promiscuous cleavage or inhibition depending upon their concentration. The metal ions having different ionic radii and co-ordination geometries readily replace each other from the enzyme's active site, revealing its plasticity. Ability of R KpnI to cleave DNA with both alkaline earth and transition group metal ions having varied ionic radii could imply utilization of different catalytic site(s). However, mutation of the invariant His residue of the HNH motif caused abolition of the enzyme activity with all of the cofactors, indicating that the enzyme follows a single metal ion catalytic mechanism for DNA cleavage. Indispensability of His in nucleophile activation together with broad cofactor tolerance of the enzyme indicates electrostatic stabilization function of metal ions during catalysis. Nevertheless, a second metal ion is recruited at higher concentrations to either induce promiscuity or inhibit the DNA cleavage. Regulation of the endonuclease activity and fidelity by a second metal ion binding is a unique feature of R.KpnI among REases and HNH nucleases. The active site plasticity of R.KpnI opens up avenues for redesigning cofactor specificities and generation of mutants specific to a particular metal ion.

Power Efficient Redundant Execution for Chip Multiprocessor

This paper describes the design of a power efficient microarchitecture for transient fault detection in chip multiprocessors (CMPs) We introduce a new per-core dynamic voltage and frequency scaling (DVFS) algorithm for our architecture that significantly reduces power dissipation for redundant execution with a minimal performance overhead. Using cycle accurate simulation combined with a simple first order power model, we estimate that our architecture reduces dynamic power dissipation in the redundant core by an mean value of 79% and a maximum of 85% with an associated mean performance overhead of only 1:2%

Cojoined Irregular Topology and Routing Table Generation for Network-on-Chip

Scalable Networks on Chips (NoCs) are needed to match the ever-increasing communication demands of large-scale Multi-Processor Systems-on-chip (MPSoCs) for multi media communication applications. The heterogeneous nature of application specific on-chip cores along with the specific communication requirements among the cores calls for the design of application-specific NoCs for improved performance in terms of communication energy, latency, and throughput. In this work, we propose a methodology for the design of customized irregular networks-on-chip. The proposed method exploits a priori knowledge of the applications communication characteristic to generate an optimized network topology and corresponding routing tables.

Structural Rigidity of Paranemic Crossover and Juxtapose DNA Nanostructures

Crossover motifs are integral components for designing DNA-based nanostructures and nanomechanical devices due to their enhanced rigidity compared to the normal B-DNA. Although the structural rigidity of the double helix B-DNA has been investigated extensively using both experimental and theoretical tools, to date there is no quantitative information about structural rigidity and the mechanical strength of parallel crossover DNA motifs. We have used fully atomistic molecular dynamics simulations in explicit solvent to get the force-extension curve of parallel DNA nanostructures to characterize their mechanical rigidity. In the presence of monovalent Na(+) ions, we find that the stretch modulus (gamma(1)) of the paranemic crossover and its topoisomer JX DNA structure is significantly higher (similar to 30%) compared to normal B-DNA of the same sequence and length. However, this is in contrast to the original expectation that these motifs are almost twice as rigid compared to the double-stranded B-DNA. When the DNA motif is surrounded by a solvent with Mg(2+) counterions, we find an enhanced rigidity compared to Na(+) environment due to the electrostatic screening effects arising from the divalent nature of Mg(2+) ions. To our knowledge, this is the first direct determination of the mechanical strength of these crossover motifs, which can be useful for the design of suitable DNA for DNA-based nanostructures and nanomechanical devices with improved structural rigidity.

MODLEX: A Multi Objective Data Layout EXploration Framework for Embedded Systems-on-Chip

The memory subsystem is a major contributor to the performance, power, and area of complex SoCs used in feature rich multimedia products. Hence, memory architecture of the embedded DSP is complex and usually custom designed with multiple banks of single-ported or dual ported on-chip scratch pad memory and multiple banks of off-chip memory. Building software for such large complex memories with many of the software components as individually optimized software IPs is a big challenge. In order to obtain good performance and a reduction in memory stalls, the data buffers of the application need to be placed carefully in different types of memory. In this paper we present a unified framework (MODLEX) that combines different data layout optimizations to address the complex DSP memory architectures. Our method models the data layout problem as multi-objective genetic algorithm (GA) with performance and power being the objectives and presents a set of solution points which is attractive from a platform design viewpoint. While most of the work in the literature assumes that performance and power are non-conflicting objectives, our work demonstrates that there is significant trade-off (up to 70%) that is possible between power and performance.

MAX: A Multi Objective Memory Architecture eXploration Framework for Embedded Systems-on-Chip

Today's feature-rich multimedia products require embedded system solution with complex System-on-Chip (SoC) to meet market expectations of high performance at a low cost and lower energy consumption. The memory architecture of the embedded system strongly influences these parameters. Hence the embedded system designer performs a complete memory architecture exploration. This problem is a multi-objective optimization problem and can be tackled as a two-level optimization problem. The outer level explores various memory architecture while the inner level explores placement of data sections (data layout problem) to minimize memory stalls. Further, the designer would be interested in multiple optimal design points to address various market segments. However, tight time-to-market constraints enforces short design cycle time. In this paper we address the multi-level multi-objective memory architecture exploration problem through a combination of Multi-objective Genetic Algorithm (Memory Architecture exploration) and an efficient heuristic data placement algorithm. At the outer level the memory architecture exploration is done by picking memory modules directly from a ASIC memory Library. This helps in performing the memory architecture exploration in a integrated framework, where the memory allocation, memory exploration and data layout works in a tightly coupled way to yield optimal design points with respect to area, power and performance. We experimented our approach for 3 embedded applications and our approach explores several thousand memory architecture for each application, yielding a few hundred optimal design points in a few hours of computation time on a standard desktop.

Exploring the spectral enantiodiscrimination potential of a DNA-based orienting medium using deuterium NMR spectroscopy

(2)H-{(1)H} 1D and 2D-NMR spectroscopy is used to evaluate the enantiodiscrimination potential of DNA-based, lyotropic chiral mesophases on a series of (pro) chiral amino acids.

Dynamic and thermodynamic anomalies of water at low temperatures: from bulk water to reverse micelles and DNA hydration layer

Liquid water is known to exhibit remarkable thermodynamic and dynamic anomalies, ranging from solvation properties in supercritical state to an apparent divergence of the linear response functions at a low temperature. Anomalies in various dynamic properties of water have also been observed in the hydration layer of proteins, DNA grooves and inside the nanocavity, such as reverse micelles and nanotubes. Here we report studies on the molecular origin of these anomalies in supercooled water, in the grooves of DNA double helix and reverse micelles. The anomalies have been discussed in terms of growing correlation length and intermittent population fluctuation of 4- and 5-coordinated species. We establish correlation between thermodynamic response functions and mean squared species number fluctuation. Lifetime analysis of 4- and 5-coordinated species reveals interesting differences between the role of the two species in supercooled and constrained water. The nature and manifestations of the apparent and much discussed liquid-liquid transition under confinement are found to be markedly different from that in the bulk. We find an interesting `faster than bulk' relaxation in reverse micelles which we attribute to frustration effects created by competition between the correlations imposed by surface interactions and that imposed by hydrogen bond network of water.