DNA topoisomerase I from mycobacteria - A potential drug target

DNA topoisomerases are ubiquitous group of enzymes altering the topology of DNA by concerted breakage and rejoining of the phosphodiester backbone of DNA. The enzymes are classified based on the pattern of DNA cleavage. Type IA enzymes found in all bacteria nick the DNA and attach themselves covalently to the 5' side of the nick during the first transesterification reaction. Most of the information on this group of enzymes comes from studies with E. coli topoisomerase I and III. Members of type IA group are single subunit Zn++ metalloenzymes recognizing single stranded DNA without high degree of sequence specificity during relaxation reaction of negatively super coiled DNA. So far no inhibitors are known for this group of enzymes inspite of their important role in maintaining homeostasis of DNA topology. Molecular characterization of DNA topoisomerase I from mycobacteria has revealed some of the important features of type IA enzymes hitherto unknown and provide scope for identifying novel inhibitors. The present review describes the recent developments in the area summarizing the distinctive features of mycobacterial topoisomerase I. The enzyme has several properties not shared by either type IA or 113 enzymes with respect to DNA binding, recognition, sequence specificity and interaction pattern. The physiological basis of the unusual features is discussed. The unique properties described would aid in developing the enzyme as a target molecule in pharmaceutical design. In addition, the findings lead to address some fundamental questions on the intracellular role of topoisomerase I in the biology of mycobacteria which are one of the most formidable group of pathogenic organisms.

Pruned Universal Symbol Sequences for LZW based Language identification

We present a improved language modeling technique for Lempel-Ziv-Welch (LZW) based LID scheme. The previous approach to LID using LZW algorithm prepares the language pattern table using LZW algorithm. Because of the sequential nature of the LZW algorithm, several language specific patterns of the language were missing in the pattern table. To overcome this, we build a universal pattern table, which contains all patterns of different length. For each language it's corresponding language specific pattern table is constructed by retaining the patterns of the universal table whose frequency of appearance in the training data is above the threshold.This approach reduces the classification score (Compression Ratio [LZW-CR] or the weighted discriminant score[LZW-WDS]) for non native languages and increases the LID performance considerably.

LZW Based Distance Measures for Spoken Language Identification

We present a new approach to spoken language modeling for language identification (LID) using the Lempel-Ziv-Welch (LZW) algorithm. The LZW technique is applicable to any kind of tokenization of the speech signal. Because of the efficiency of LZW algorithm to obtain variable length symbol strings in the training data, the LZW codebook captures the essentials of a language effectively. We develop two new deterministic measures for LID based on the LZW algorithm namely: (i) Compression ratio score (LZW-CR) and (ii) weighted discriminant score (LZW-WDS). To assess these measures, we consider error-free tokenization of speech as well as artificially induced noise in the tokenization. It is shown that for a 6 language LID task of OGI-TS database with clean tokenization, the new model (LZW-WDS) performs slightly better than the conventional bigram model. For noisy tokenization, which is the more realistic case, LZW-WDS significantly outperforms the bigram technique

Auxin-Responsive OsMGH3, a Common Downstream Target of OsMADS1 and OsMADS6, Controls Rice Floret Fertility

GH3 proteins control auxin homeostasis by inactivating excess auxin as conjugates of amino acids and sugars and thereby controlling cellular bioactive auxin. Since auxin regulates many aspects of plant growth and development, regulated expression of these genes offers a mechanism to control various developmental processes. OsMGH3/OsGH3-8 is expressed abundantly in rice florets and is regulated by two related and redundant transcription factors, OsMADS1 and OsMADS6, but its contribution to flower development is not known. We functionally characterize OsMGH3 by overexpression and knock-down analysis and show a partial overlap in these phenotypes with that of mutants in OsMADS1 and OsMADS6. The overexpression of OsMGH3 during the vegetative phase affects the overall plant architecture, whereas its inflorescence-specific overexpression creates short panicles with reduced branching, resembling in part the effects of OsMADS1 overexpression. In contrast, the down-regulation of endogenous OsMGH3 caused phenotypes consistent with auxin overproduction or activated signaling, such as ectopic rooting from aerial nodes. Florets in OsMGH3 knock-down plants were affected in carpel development and pollen viability, both of which reduced fertility. Some of these floret phenotypes are similar to osmads6 mutants. Taken together, we provide evidence for the functional significance of auxin homeostasis and its transcriptional regulation during rice panicle branching and floret organ development.

RAD51 as a potential biomarker and therapeutic target for pancreatic cancer

Chemotherapy is a very important therapeutic strategy for cancer treatment. The failure of conventional and molecularly targeted chemotherapeutic regimes for the treatment of pancreatic cancer highlights a desperate need for novel therapeutic interventions. Chemotherapy often fails to eliminate all tumor cells because of intrinsic or acquired drug resistance, which is the most common cause of tumor recurrence. Overexpression of RAD51 protein, a key player in DNA repair/recombination has been observed in many cancer cells and its hyperexpression is implicated in drug resistance. Recent studies suggest that RAD51 overexpression contributes to the development, progression and drug resistance of pancreatic cancer cells. Here we provide a brief overview of the available pieces of evidence in support of the role of RAD51 in pancreatic tumorigenesis and drug resistance, and hypothesize that RAD51 could serve as a potential biomarker for diagnosis of pancreatic cancer. We discuss the possible involvement of RAD51 in the drug resistance associated with epithelial to mesenchymal transition and with cancer stem cells. Finally, we speculate that targeting RAD51 in pancreatic cancer cells may be a novel approach for the treatment of pancreatic cancer. (C) 2011 Elsevier B.V. All rights reserved.

Computational Biology and Language

Current scientific research is characterized by increasing specialization, accumulating knowledge at a high speed due to parallel advances in a multitude of sub-disciplines. Recent estimates suggest that human knowledge doubles every two to three years – and with the advances in information and communication technologies, this wide body of scientific knowledge is available to anyone, anywhere, anytime. This may also be referred to as ambient intelligence – an environment characterized by plentiful and available knowledge. The bottleneck in utilizing this knowledge for specific applications is not accessing but assimilating the information and transforming it to suit the needs for a specific application. The increasingly specialized areas of scientific research often have the common goal of converting data into insight allowing the identification of solutions to scientific problems. Due to this common goal, there are strong parallels between different areas of applications that can be exploited and used to cross-fertilize different disciplines. For example, the same fundamental statistical methods are used extensively in speech and language processing, in materials science applications, in visual processing and in biomedicine. Each sub-discipline has found its own specialized methodologies making these statistical methods successful to the given application. The unification of specialized areas is possible because many different problems can share strong analogies, making the theories developed for one problem applicable to other areas of research. It is the goal of this paper to demonstrate the utility of merging two disparate areas of applications to advance scientific research. The merging process requires cross-disciplinary collaboration to allow maximal exploitation of advances in one sub-discipline for that of another. We will demonstrate this general concept with the specific example of merging language technologies and computational biology.

Language identification using parallel sub-word recognition

Parallel sub-word recognition (PSWR) is a new model that has been proposed for language identification (LID) which does not need elaborate phonetic labeling of the speech data in a foreign language. The new approach performs a front-end tokenization in terms of sub-word units which are designed by automatic segmentation, segment clustering and segment HMM modeling. We develop PSWR based LID in a framework similar to the parallel phone recognition (PPR) approach in the literature. This includes a front-end tokenizer and a back-end language model, for each language to be identified. Considering various combinations of the statistical evaluation scores, it is found that PSWR can perform as well as PPR, even with broad acoustic sub-word tokenization, thus making it an efficient alternative to the PPR system.

Ribosome-RNA interaction: a potential target for developing antiviral against hepatitis C virus

Hepatitis C virus (HCV), a member of Flaviviridae, encoding a positive-sense single-stranded RNA translates by cap-independent mechanism using the internal ribosome entry site (IRES) present in the 5' UTR of the virus. The IRES has complex stem loop structures and is capable of recruiting the 40S ribosomal subunit in a factor-independent fashion. As the IRES sequence is highly conserved throughout the HCV genotypes and the translation is the first obligatory step of the HCV life cycle, the IRE'S-mediated translation, or more specifically, the ribosome HCV RNA interaction is an attractive target to design effective antivirals. This article will focus on the mechanism of the HCV IRES translation and the various ways in which the interaction of ribosome and IRES has been targeted.

Deorphanization of Malonyl CoA:ACP Transacylase Drug Target in Plasmodium falciparum (PfFabD) Using Bacterial Antagonists: A Piggyback' Approach for Antimalarial Drug Discovery

Quest for new drug targets in Plasmodium sp. has underscored malonyl CoA:ACP transacylase (PfFabD) of fatty acid biosynthetic pathway in apicoplast. In this study, a piggyback approach was employed for the receptor deorphanization using inhibitors of bacterial FabD enzymes. Due to the lack of crystal structure, theoretical model was constructed using the structural details of homologous enzymes. Sequence and structure analysis has localized the presence of two conserved pentapeptide motifs: GQGXG and GXSXG and five key invariant residues viz., Gln109, Ser193, Arg218, His305 and Gln354 characteristic of FabD enzyme. Active site mapping of PfFabD using substrate molecules has disclosed the spatial arrangement of key residues in the cavity. As structurally similar molecules exhibit similar biological activities, signature pharmacophore fingerprints of FabD antagonists were generated using 0D-3D descriptors for molecular similarity-based cluster analysis and to correlate with their binding profiles. It was observed that antagonists showing good geometrical fitness score were grouped in cluster-1, whereas those exhibiting high binding affinities in cluster-2. This study proves important to shed light on the active site environment to reveal the hotspot for binding with higher affinity and to narrow down the virtual screening process by searching for close neighbors of the active compounds.

Reactive biased target ion beam deposited W-DLC nanocomposite thin films - Microstructure and its mechanical properties

Tungsten incorporated diamond like carbon (W-DLC) nanocomposite thin films with variable fractions of tungsten were deposited by using reactive biased target ion beam deposition technique. The influence of tungsten incorporation on the microstructure, surface topography, mechanical and tribological properties of the DLC were studied using X-ray photoelectron spectroscopy (XPS), Raman spectroscopy. Atomic force microscope (AFM), transmission electron microscopy (TEM), nano-indentation and nano-scratch tests. The amount of W in films gets increases with increasing target bias voltage and most of the incorporated W reacts with carbon to form WC nanoclusters. Using TEM and FFT pattern, it was found that spherical shaped WC nanoclusters were uniformly dispersed in the DLC matrix and attains hexagonal (W2C) crystalline structure at higher W concentration. On the other hand, the incorporation of tungsten led to increase the formation of C-sp(2) hybridized bonding in DLC network and which is reflected in the hardness and elastic modulus of W-DLC films. Moreover, W-DLC films show very low friction coefficient and increased adhesion to the substrate than the DLC film, which could be closely related to its unique nanostructure of the W incorporated thin films. (C) 2011 Elsevier B.V. All rights reserved.