PvaxDB: a comprehensive structural repository of Plasmodium vivax proteome.

Database URL: http://www.scfbio-iitd.res.in/PvaxDB.

TPMT Polymorphism: When Shield Becomes Weakness.

Thiopurine methyltransferase (TPMT) is a cytoplasmic transmethylase present in both prokaryotes and eukaryotes. In humans, it shows its presence in almost all of the tissues, predominantly in liver and kidney. TPMT is one of the important metabolic enzymes of phase II metabolic pathway and catalyzes methylation of thiopurine drugs such as azathioprine, 6-thioguanine and 6-mercaptopurine, which are used to treat patients with neoplasia and autoimmune disease as well as transplant recipients. In this sense, TPMT acts as shield against toxic effect of these drugs. Pharmacogenomic studies revealed that genetic polymorphism in TPMT is responsible for variable and, in some cases, adverse drug reaction. Those human groups who carry variants of TPMT (i.e., [Formula: see text], [Formula: see text], [Formula: see text]) are at high risk, because they are unable to metabolize thiopurine drugs thus becoming a weakness of patients against these drugs. Keeping in the mind the importance of TPMT, this review discusses the existence and distribution of various TPMT variants throughout different ethnic groups and risk of adverse drug reactions to them, and how they can avoid this risk of side effects. The review also highlighted factors responsible for variable reactions of TPMT, how this TPMT polymorphism can be considered in drug designing process to avoid toxic effects, designing precautions against them and more importantly designing personalized medicine.

Microsatellite analysis in organelle genomes of Chlorophyta.

Simple Sequence Repeats (SSRs) or microsatellites constitute a significant portion of genomes however; their significance in organellar genomes has not been completely understood. The availability of organelle genome sequences allows us to understand the organization of SSRs in their genic and intergenic regions. In the present work, SSRs were identified and categorized in 14 mitochondrial and 22 chloroplast genomes of algal species belonging to Chlorophyta. Based on the study, it was observed that number of SSRs in non-coding region were more as compared to coding region and frequency of mononucleotides repeats were highest followed by dinucleotides in both mitochondrial and chloroplast genomes. It was also observed that maximum number of SSRs was found in genes encoding for beta subunit of RNA polymerase in chloroplast genomes and NADH dehydrogenase in mitochondrial genomes. This is the first and original report on whole genomes sequence analysis of organellar genomes of green algae.

In silico analysis of SSRs in mitochondrial genomes of plants.

Simple sequence repeats (SSRs) or microsatellites constitute a countable portion of genomes. However, the significance of SSRs in organelle genomes has not been completely understood. The availability of organelle genome sequences allows us to understand the organization of SSRs in their genic and intergenic regions. In the current study we surveyed the patterns of SSRs in mitochondrial genomes of different taxa of plants. A total of 16 mitochondrial genomes, from algae to angiosperms, have been considered to analyze the pattern of simple sequence repeats present in them. Based on study, the mononucleotide repeats of A/T were found to be more prevalent in mitochondrial genomes over other repeat types. The dinucleotides repeats, TA/AT, were the second most numerous, whereas tri-, tetra-, and pentanucleotide repeats were in less number and present in intronic or intergenic portions only. Mononucleotide repeats prevailed in protein-coding exonic portions of all organisms. These results indicates that microsatellite pattern in mitochondrial genomes is different from nuclear genomes and also focuses on organization and diversity at SSR locuses in mitochondrial genomes. This is the novel report of microsatellite polymorphism in plant mitochondrion on whole genome level.

In silico prediction of drug targets in Vibrio cholerae.

Identification of potential drug targets is the first step in the process of modern drug discovery, subjected to their validation and drug development. Whole genome sequences of a number of organisms allow prediction of potential drug targets using sequence comparison approaches. Here, we present a subtractive approach exploiting the knowledge of global gene expression along with sequence comparisons to predict the potential drug targets more efficiently. Based on the knowledge of 155 known virulence and their coexpressed genes mined from microarray database in the public domain, 357 coexpressed probable virulence genes for Vibrio cholerae were predicted. Based on screening of Database of Essential Genes using blastn, a total of 102 genes out of these 357 were enlisted as vitally essential genes, and hence good putative drug targets. As the effective drug target is a protein which is only present in the pathogen, similarity search of these 102 essential genes against human genome sequence led to subtraction of 66 genes, thus leaving behind a subset of 36 genes whose products have been called as potential drug targets. The gene ontology analysis using Blast2GO of these 36 genes revealed their roles in important metabolic pathways of V. cholerae or on the surface of the pathogen. Thus, we propose that the products of these genes be evaluated as target sites of drugs against V. cholerae in future investigations.

Prediction of miRNA targets, affected proteins and their homologs in Glycine max.

microRNAs are small noncoding RNA gene products about 20-24nt long that are processed by Dicer from precursors with a characteristic hairpin secondary structure. As miRNAs affect the morphology of plants and animals by the posttranscriptional regulation of genes involved in critical developmental events, it has been proposed that precise regulation of miRNAs activity during various stages of growth and in specific cell types is of central importance for normal plant development. In our work we focus on the plant miRNAs and predict the miRNA targets, affected proteins by miRNA and miRNA homologs of Glycine max. Our analyses were based on sequence complementarities between miRNAs and mRNAs. As a result, we predicted 573 targets for 44 mature miRNAs sequences among 69 mature miRNAs sequences were published in database. Study of affected proteins revealed that for very less number of miRNAs, protein products are known and they mostly involved in diverse physiological process like as element of photosynthesis system. Homology analyses for miRNAs suggested that 22 miRNAs of Glycine max show 418 miRNA homologs for different plant species.