Insight into trichomonas vaginalis genome evolution through metabolic pathways comparison

Trichomonas vaginalis causes the trichomoniasis, in women and urethritis and prostate cancer in men. Its genome draft published by TIGR in 2007 presents many unusual genomic and biochemical features like, exceptionally large genome size, the presence of hydrogenosome, gene duplication, lateral gene transfer mechanism and the presence of miRNA. To understand some of genomic features we have performed a comparative analysis of metabolic pathways of the T. vaginalis with other 22 significant common organisms. Enzymes from the biochemical pathways of T. vaginalis and other selected organisms were retrieved from the KEGG metabolic pathway database. The metabolic pathways of T. vaginalis common in other selected organisms were identified. Total 101 enzymes present in different metabolic pathways of T. vaginalis were found to be orthologous by using BLASTP program against the selected organisms. Except two enzymes all identified orthologous enzymes were also identified as paralogous enzymes. Seventy-five of identified enzymes were also identified as essential for the survival of T. vaginalis, while 26 as non-essential. The identified essential enzymes also represent as good candidate for novel drug targets. Interestingly, some of the identified orthologous and paralogous enzymes were found playing significant role in the key metabolic activities while others were found playing active role in the process of pathogenesis. The N-acetylneuraminate lyase was analyzed as the candidate of lateral genes transfer. These findings clearly suggest the active participation of lateral gene transfer and gene duplication during evolution of T. vaginalis from the enteric to the pathogenic urogenital environment

<span style="font-size:11.0pt;font-family: "Times New Roman";mso-fareast-font-family:"Times New Roman";mso-bidi-font-family: Mangal;mso-ansi-language:EN-GB;mso-fareast-language:EN-US;mso-bidi-language: HI" lang="EN-GB">Analyzing time course microarray data of <i style="mso-bidi-font-style: normal">Toxoplasma gondii</i> and study the impact on host transcript levels using Bioconductor</span>

46-51Toxoplasma gondii is an obligate, intracellular, apicomplexan parasite that can infect a wide range of warm-blooded animals including humans. In humans and other intermediate hosts, Toxoplasma develops into chronic infection that cannot be eliminated by host’s immune response or by currently used drugs. The ability of the parasite to convert to the bradyzoite stage and to live inside slow-growing cysts that can go unnoticed by the host immune system allows for the persistence of parasite throughout the life of the infected host. Little is known, however, about how bradyzoites manipulate their host cell. Large scale microarray experiments are becoming increasingly routine, particularly those which track a number of different cell lines through time. This time course information provides valuable insight into dynamics of various biological processes. The proper statistical analysis, however, requires the use of more sophisticated tools and complex statistical models. In the current study, the open-source R programming environment in conjunction with the open-source Bioconductor software was used to analyze microarray data of T. gondii. Several statistical analysis procedures like (log) fold changes in conjunction with ordinary and moderated t-statistics were used to determine differentially expressed genes. The differentially expressed genes were subjected to cluster analysis, followed by the annotation of the up and down regulated genes based on the gene ontology. The findings in the present study suggest the overall effect of the gene expression changes is to modulate the key metabolic pathways leading to compromised host immune response, enhancement in programmed cell death, depression in cell proliferation process and induction of various diseases

Statistical analysis of differential gene expression profile for colon cancer

396-403To analyze differentially expressed genes in colon cancer, we compared expression profiles of colorectal cancer cells from normal colonic cells using data of DNA microarray consisting of 6584 human genes. Each probe set on the array consisted of EST (expressed sequence tag) sequence of 20 feature pairs of 25 bp sequence. The data set comprised of 61 samples, divided into two groups of 40 samples for tumor cells (Group 1) and 21 samples for normal cells (Group 2). In order to do background adjustments for the negative expression values, the data was transformed into log base 2 and estimation of missing values was performed by K-nearest neighbor method, followed by normalization using ‘minimum mean ratio’ among arrays. The basic statistics used for the significance analysis was J5 test, which was computed for each probe and for each contrast with a threshold value of 4.0 and mean as the measure of central tendency. The differentially expressed genes were expressed at high frequency in tumour samples. The Naive Bayes Classifier Algorithm was used to test defined classification of samples of genes. Correlation distance was measured with the help of Pearson’s correlation distance. On the basis of J5 test scores, top 5 upregulated genes, viz., vasopressin-neurophysin 2-copeptin preproprotein, cytochrome, P450 2A7 isoform, major centromere autoantigen B, myelin associated glycoprotein and bone morphogenetic protein 1 isoform 3 precursor, were selected for further analysis. The above said genes have not yet been reported to be differentially overexpressed in colon cancer cells, while their overexpression was reported in other cancers, such as, lung and breast cancer, etc. These genes can be used for prediction and analyses of the gene products, which will help in designing new diagnostic and treatment strategies for the colon cancer

MOLECULAR MODELING AND DRUG DISCOVERY OF POTENTIAL INHIBITORS FOR ANTI CANCER TARGET GENE PLK- POLO LIKE KINASE1

published quarterly. The aim of IJPBS is to publish. peer reviewed research and review articles rapidly without delay in the developing field of pharmaceutical and biological science

Computer-Aided Drug Design for cancer-causing H-Ras p21 mutant protein

Abstract: GTP-bound mutant form H-Ras (Harvey-Ras) proteins are found in 30% of human tumors. Activation of H-Ras is due to point mutation at positions 12, 13, 59 and/or 61 codon. Mutant form of H-Ras proteins is continuously involved in signal transduction for cell growth and proliferation through interaction of downstream-regulated protein Raf. In this paper, we have reported the virtual screening of lead compounds for H-Ras P 21 mutant protein from ChemBank and DrugBank databases using LigandFit and DrugBank-BLAST. The analysis resulted in 13 hits which were docked and scored to identify structurally active leads that make similar interaction to those of bound complex of H-Ras P 21 mutantRaf. This approach produced two different leads, 3-Aminopropanesulphonic acid (docked energy -3.014 kcal/mol) and Hydroxyurea (docked energy -0.009 kcal/mol) with finest Lipinski&apos;s rule-of-five. Their docked energy scores were better than the complex structure of H-Ras P 21 mutant protein bound with Raf (1.18 kcal/mol). All the leads were docked into effector region forming interaction with ILE36, GLU37, ASP38 and SER39