CancerLectinDB: a database of lectins relevant to cancer

The role of lectins in mediating cancer metastasis, apoptosis as well as various other signaling events has been well established in the past few years. Data on various aspects of the role of lectins in cancer is being accumulated at a rapid pace. The data on lectins available in the literature is so diverse, that it becomes difficult and time-consuming, if not impossible to comprehend the advances in various areas and obtain the maximum benefit. Not only do the lectins vary significantly in their individual functional roles, but they are also diverse in their sequences, structures, binding site architectures, quaternary structures, carbohydrate affinities and specificities as well as their potential applications. An organization of these seemingly independent data into a common framework is essential in order to achieve effective use of all the data towards understanding the roles of different lectins in different aspects of cancer and any resulting applications. An integrated knowledge base (CancerLectinDB) together with appropriate analytical tools has therefore been developed for lectins relevant for any aspect of cancer, by collating and integrating diverse data. This database is unique in terms of providing sequence, structural, and functional annotations for lectins from all known sources in cancer and is expected to be a useful addition to the number of glycan related resources now available to the community. The database has been implemented using MySQL on a Linux platform and web-enabled using Perl-CGI and Java tools. Data for individual lectins pertain to taxonomic, biochemical, domain architecture, molecular sequence and structural details as well as carbohydrate specificities. Extensive links have also been provided for relevant bioinformatics resources and analytical tools. Availability of diverse data integrated into a common framework is expected to be of high value for various studies on lectin cancer biology.

Off-axis field approximations for ion traps with apertures

In recent work (Int. J. Mass Spec., vol. 282, pp. 112���122) we have considered the effect of apertures on the fields inside rf traps at points on the trap axis. We now complement and complete that work by considering off-axis fields in axially symmetric (referred to as ���3D���) and in two dimensional (���2D���) ion traps whose electrodes have apertures, i.e., holes in 3D and slits in 2D. Our approximation has two parts. The first, EnoAperture, is the field obtained numerically for the trap under study with apertures artificially closed. We have used the boundary element method (BEM) for obtaining this field. The second part, EdueToAperture, is an analytical expression for the field contribution of the aperture. In EdueToAperture, aperture size is a free parameter. A key element in our approximation is the electrostatic field near an infinite thin plate with an aperture, and with different constant-valued far field intensities on either side. Compact expressions for this field can be found using separation of variables, wherein the choice of coordinate system is crucial. This field is, in turn, used four times within our trap-specific approximation. The off-axis field expressions for the 3D geometries were tested on the quadrupole ion trap (QIT) and the cylindrical ion trap (CIT), and the corresponding expressions for the 2D geometries were tested on the linear ion trap (LIT) and the rectilinear ion trap (RIT). For each geometry, we have considered apertures which are 10%, 30%, and 50% of the trap dimension. We have found that our analytical correction term EdueToAperture, though based on a classical small-aperture approximation, gives good results even for relatively large apertures.

Conformationally locked thiosugars alpha-mannosidase inhibitors: Synthesis, and docking studies as potent biochemical

series of thiosugar derivatives (thiolevomannosans) derived from mannose were synthesized and their inhibitory activity was tested against alpha-mannosidase (jack bean). These inhibitors were found to be more potent than the well-known inhibitors like kifunensine and deoxymannojirimycin based on docking and biochemical studies. The sulfone derivative 10 was shown to be the best inhibitor of alpha-mannosidase with the K-i value of 350 nM. (c) 2007 Elsevier Ltd. All rights reserved.

Ion pairs in non-redundant protein structures

Ion pairs contribute to several functions including the activity of catalytic triads, fusion of viral membranes, stability in thermophilic proteins and solvent-protein interactions. Furthermore, they have the ability to affect the stability of protein structures and are also a part of the forces that act to hold monomers together. This paper deals with the possible ion pair combinations and networks in 25% and 90% non-redundant protein chains. Different types of ion pairs present in various secondary structural elements are analysed. The ion pairs existing between different subunits of multisubunit protein structures are also computed and the results of various analyses are presented in detail. The protein structures used in the analysis are solved using X-ray crystallography, whose resolution is better than or equal to 1.5 angstrom and R-factor better than or equal to 20%. This study can, therefore, be useful for analyses of many protein functions. It also provides insights into the better understanding of the architecture of protein structure.

Inferring molecular function: contributions from functional linkages

In the current era of high-throughput sequencing and structure determination, functional annotation has become a bottleneck in biomedical science. Here, we show that automated inference of molecular function using functional linkages among genes increases the accuracy of functional assignments by >= 8% and enriches functional descriptions in >= 34% of top assignments. Furthermore, biochemical literature supports >80% of automated inferences for previously unannotated proteins. These results emphasize the benefit of incorporating functional linkages in protein annotation.

Memory-efficient spatial prediction image compression scheme

In prediction phase, the hierarchical tree structure obtained from the test image is used to predict every central pixel of an image by its four neighboring pixels. The prediction scheme generates the predicted error image, to which the wavelet/sub-band coding algorithm can be applied to obtain efficient compression. In quantization phase, we used a modified SPIHT algorithm to achieve efficiency in memory requirements. The memory constraint plays a vital role in wireless and bandwidth-limited applications. A single reusable list is used instead of three continuously growing linked lists as in case of SPIHT. This method is error resilient. The performance is measured in terms of PSNR and memory requirements. The algorithm shows good compression performance and significant savings in memory. (C) 2006 Elsevier B.V. All rights reserved.

Leveraging Partially Enhanced Scan for Improved Observability in Delay Fault Testing

Enhanced Scan design can significantly improve the fault coverage for two pattern delay tests at the cost of exorbitantly high area overhead. The redundant flip-flops introduced in the scan chains have traditionally only been used to launch the two-pattern delay test inputs, not to capture tests results. This paper presents a new, much lower cost partial Enhanced Scan methodology with both improved controllability and observability. Facilitating observation of some hard to observe internal nodes by capturing their response in the already available and underutilized redundant flip-flops improves delay fault coverage with minimal or almost negligible cost. Experimental results on ISCAS'89 benchmark circuits show significant improvement in TDF fault coverage for this new partial enhance scan methodology.

RECONNECT: A NoC for polymorphic ASICs using a low overhead single cycle router

A polymorphic ASIC is a runtime reconfigurable hardware substrate comprising compute and communication elements. It is a ldquofuture proofrdquo custom hardware solution for multiple applications and their derivatives in a domain. Interoperability between application derivatives at runtime is achieved through hardware reconfiguration. In this paper we present the design of a single cycle Network on Chip (NoC) router that is responsible for effecting runtime reconfiguration of the hardware substrate. The router design is optimized to avoid FIFO buffers at the input port and loop back at output crossbar. It provides virtual channels to emulate a non-blocking network and supports a simple X-Y relative addressing scheme to limit the control overhead to 9 bits per packet. The 8times8 honeycomb NoC (RECONNECT) implemented in 130 nm UMC CMOS standard cell library operates at 500 MHz and has a bisection bandwidth of 28.5 GBps. The network is characterized for random, self-similar and application specific traffic patterns that model the execution of multimedia and DSP kernels with varying network loads and virtual channels. Our implementation with 4 virtual channels has an average network latency of 24 clock cycles and throughput of 62.5% of the network capacity for random traffic. For application specific traffic the latency is 6 clock cycles and throughput is 87% of the network capacity.

Structures and molecular-dynamics studies of three active-site mutants of bovine pancreatic phospholipase A(2)

Phospholipase A(2) hydrolyzes phospholipids at the sn-2 position to cleave the fatty-acid ester bond of L-glycerophospholipids. The catalytic dyad (Asp99 and His48) along with a nucleophilic water molecule is responsible for enzyme hydrolysis. Furthermore, the residue Asp49 in the calcium-binding loop is essential for controlling the binding of the calcium ion and the catalytic action of phospholipase A2. To elucidate the structural role of His48 and Asp49, the crystal structures of three active-site single mutants H48N, D49N and D49K have been determined at 1.9 angstrom resolution. Although the catalytically important calcium ion is present in the H48N mutant, the crystal structure shows that proton transfer is not possible from the catalytic water to the mutated residue. In the case of the Asp49 mutants, no calcium ion was found in the active site. However, the tertiary structures of the three active-site mutants are similar to that of the trigonal recombinant enzyme. Molecular-dynamics simulation studies provide a good explanation for the crystallographic results.

Parallel implementation of AutoDock

Computational docking of ligands to protein structures is a key step in structure-based drug design. Currently, the time required for each docking run is high and thus limits the use of docking in a high-throughput manner, warranting parallelization of docking algorithms. AutoDock, a widely used tool, has been chosen for parallelization. Near-linear increases in speed were observed with 96 processors, reducing the time required for docking ligands to HIV-protease from 81 min, as an example, on a single IBM Power-5 processor ( 1.65 GHz), to about 1 min on an IBM cluster, with 96 such processors. This implementation would make it feasible to perform virtual ligand screening using AutoDock.

Usefulness of DARPA dataset for intrusion detection system evaluation

The MIT Lincoln Laboratory IDS evaluation methodology is a practical solution in terms of evaluating the performance of Intrusion Detection Systems, which has contributed tremendously to the research progress in that field. The DARPA IDS evaluation dataset has been criticized and considered by many as a very outdated dataset, unable to accommodate the latest trend in attacks. Then naturally the question arises as to whether the detection systems have improved beyond detecting these old level of attacks. If not, is it worth thinking of this dataset as obsolete? The paper presented here tries to provide supporting facts for the use of the DARPA IDS evaluation dataset. The two commonly used signature-based IDSs, Snort and Cisco IDS, and two anomaly detectors, the PHAD and the ALAD, are made use of for this evaluation purpose and the results support the usefulness of DARPA dataset for IDS evaluation.

Visibility volumes for interactive path optimization

We describe a real-time system that supports design of optimal flight paths over terrains. These paths either maximize view coverage or minimize vehicle exposure to ground. A volume-rendered display of multi-viewpoint visibility and a haptic interface assists the user in selecting, assessing, and refining the computed flight path. We design a three-dimensional scalar field representing the visibility of a point above the terrain, describe an efficient algorithm to compute the visibility field, and develop visual and haptic schemes to interact with the visibility field. Given the origin and destination, the desired flight path is computed using an efficient simulation of an articulated rope under the influence of the visibility gradient. The simulation framework also accepts user input, via the haptic interface, thereby allowing manual refinement of the flight path.

Visual Analysis of Biomolecular Surfaces

Surface models of biomolecules have become crucially important for the study and understanding of interaction between biomolecules and their environment. We argue for the need for a detailed understanding of biomolecular surfaces by describing several applications in computational and structural biology. We review methods used to model, represent, characterize, and visualize biomolecular surfaces focusing on the role that geometry and topology play in identifying features on the surface. These methods enable the development of efficient computational and visualization tools for studying the function of biomolecules.

New measures for estimating surface complementarity and packing at protein-protein interfaces

A number of methods exist that use different approaches to assess geometric properties like the surface complementarity and atom packing at the protein-protein interface. We have developed two new and conceptually different measures using the Delaunay tessellation and interface slice selection to compute the surface complementarity and atom packing at the protein-protein interface in a straightforward manner. Our measures show a strong correlation among themselves and with other existing measures, and can be calculated in a highly time-efficient manner. The measures are discriminative for evaluating biological, as well as non-biological protein-protein contacts, especially from large protein complexes and large-scale structural studies(http://pallab.serc. iisc.ernet.in/nip_nsc). (C) 201 Federation of European Biochemical Societies. Published by Elsevier B. V. All rights reserved.

A model based factorization approach for dense 3D recovery from monocular video

Feature track matrix factorization based methods have been attractive solutions to the Structure-front-motion (Sfnl) problem. Group motion of the feature points is analyzed to get the 3D information. It is well known that the factorization formulations give rise to rank deficient system of equations. Even when enough constraints exist, the extracted models are sparse due the unavailability of pixel level tracks. Pixel level tracking of 3D surfaces is a difficult problem, particularly when the surface has very little texture as in a human face. Only sparsely located feature points can be tracked and tracking error arc inevitable along rotating lose texture surfaces. However, the 3D models of an object class lie in a subspace of the set of all possible 3D models. We propose a novel solution to the Structure-from-motion problem which utilizes the high-resolution 3D obtained from range scanner to compute a basis for this desired subspace. Adding subspace constraints during factorization also facilitates removal of tracking noise which causes distortions outside the subspace. We demonstrate the effectiveness of our formulation by extracting dense 3D structure of a human face and comparing it with a well known Structure-front-motion algorithm due to Brand.