RESUMEN
Hepatitis B virus (HBV) infection is the leading cause for liver disorders and can lead to hepatocellular carcinoma, cirrhosis and liver damage which in turn can cause death of patients. HBV DNA Polymerase is essential for HBV replication in the host and hence is used as one of the most potent pharmacological target for the inhibition of HBV. Chronic hepatitis B is currently treated with nucleotide analogues that suppress viral reverse transcriptase activity and most of them are reported to have viral resistance. Therefore, it is of interest to model HBV DNA polymerase to dock known phytochemicals. The present study focuses on homology modeling and molecular docking analysis of phytocompounds from the traditional antidote Phyllanthus niruri and other nucleoside analogues against HBV DNA Polymerase using the software Discovery studio 4.0. 3D structure of HBV DNA Polymerase was predicted based on previously reported alignment. Docking studies revealed that a few phytochemicals from Phyllanthus niruri had good interactions with HBV DNA Polymerase. These compounds had acceptable binding properties for further in vitro validation. Thus the study puts forth experimental validation for traditional antidote and these phytocompounds could be further promoted as potential lead molecule.
RESUMEN
Inspite of the large body of genomic data obtained from the transcriptome of Zingiber officinale, very few studies have focused on the identification and characterization of miRNAs in gingerol biosynthesis. Zingiber officinale transcriptome was analyzed using EST dataset (38169 total) deposited in public domains. In this paper computational functional annotation of the available ESTs and identification of genes which play a significant role in gingerol biosynthesis are described. Zingiber officinale transcriptome was analyzed using EST dataset (38169 total) from ncbi. ESTs were clustered and assembled, resulting in 8624 contigs and 8821 singletons. Assembled dataset was then submitted to the EST functional annotation workflow including blast, gene ontology (go) analysis, and pathway enrichment by kyoto encyclopedia of genes and genomes (kegg) and interproscan. The unigene datasets were further exploited to identify simple sequence repeats that enable linkage mapping. A total of 409 simple sequence repeats were identified from the contigs. Furthermore we examined the existence of novel miRNAs from the ESTs in rhizome, root and leaf tissues. EST analysis revealed the presence of single hypothetical miRNA in rhizome tissue. The hypothetical miRNA is warranted to play an important role in controlling genes involved in gingerol biosynthesis and hence demands experimental validation. The assembly and associated information of transcriptome data provides a comprehensive functional and evolutionary characterization of genomics of Zingiber officinale. As an effort to make the genomic and transcriptomic data widely available to the public domain, the results were integrated into a web-based Ginger EST database which is freely accessible at http://www.kaubic.in/gingerest/.
RESUMEN
UNLABELLED: Medicinal plants and plant derived molecules are widely used in traditional cultures all over the world and they are becoming large popular among biomedical researchers and pharmaceutical companies as a natural alternative to synthetic medicine. Information related to medicinal plants and herbal drugs accumulated over the ages are scattered and unstructured which make it prudent to develop a curated database for medicinal plants. The Antidiabetic and Anticancer Medicinal Plants Database (DIACAN) aims to collect and provide an integrated platform for plants and phytochemiclas having antidiabetic or anticancer activity. AVAILABILITY: http://www.kaubic.in/diacan.
RESUMEN
UNLABELLED: DNA methylation, the highly studied epigenetic mechanism which is involved in the regulatory events of various cellular processes like chromatin structure modifications, chromosomal inactivation, gene expressional patterns, embriyonic developments and transcriptional modification etc. Various high throughput techniques evolved for direct detection of methylation actions as well as information across the entire region. However, despite high throughput technological advances in experimental field, the development of software tools that has been dedicated to the prediction of epigenetic information from specific genome sequences is warranted. To this end we developed a tissue specific classifier MethFinder based on the frequency of novel sequence patterns across nine human tissues that was capable of discriminating methylation prone and methylation resistant CpG islands with an overall accuracy of 93%. AVAILABILITY: MethFinder is freely available at www.rgcb.res.in/methfinder.
