Coconut phytocompounds inhibits polyol pathway enzymes: Implication in prevention of microvascular diabetic complications.

Coconut oil (CO), the primary choice of cooking purposes in the south Asian countries, is rich in medium chain saturated fatty acids, especially lauric acid (50-52%). The oil has high medicinal use in Ayurvedic system and known to contain polyphenolic antioxidants. Studies have reported that CO improves insulin sensitivity and shows hypoglycemic effect. However, there is no information regarding its effect on chronic diabetic complications including retinopathy and nephropathy is available. The secondary diabetic complications are mediated by the activation of polyol pathway, where aldose reductase (AR) plays crucial role. In this study, in silico analysis has been used to screen the effect of CO as well as its constituents, MCFAs and phenolic compounds, for targeting the molecules in polyol pathway. The study revealed that lauric acid (LA) interacts with AR and DPP-IV of polyol pathway and inhibits the activity of these enzymes. Validation studies using animal models confirmed the inhibition of AR and SDH in wistar rats. Further, the LA dose dependently reduced the expression of AR in HCT-15 cells. Together, the study suggests the possible role of CO, particularly LA in reducing secondary diabetic complications.

In Silico and Wet Lab Studies Reveal the Cholesterol Lowering Efficacy of Lauric Acid, a Medium Chain Fat of Coconut Oil.

The coconut oil (CO) contains 91 % of saturated fatty acids in which 72 % are medium chain fatty acids (MCFAs) like lauric, capric and caprylic acids. In contrast to animal fat, coconut oil has no cholesterol. Despite this fact, CO is sidelined among other vegetable oils due to the health hazards attributed to the saturated fatty acids. Though various medicinal effects of CO have been reported including the hypolipidemic activity, people are still confused in the consumption of this natural oil. In silico analyses and wet lab experiments have been carried out to identify the hypolipidemic properties of MCFAs and phenolic acids in CO by using different protein targets involved in cholesterol synthesis. The molecular docking studies were carried out using CDOCKER protocol in Accelery's Discovery Studio, by taking different proteins like HMG- CoA reductase and cholesterol esterase as targets and the different phytocompounds in coconut as ligands. Molecular docking highlighted the potential of lauric acid in inhibiting the protein targets involved in hyperlipidemics. Further, validation of in silico results was carried out through in vivo studies. The activity of key enzymes HMG- CoA reductase and lipoprotein lipase were found reduced in animals fed with lauric acid and CO.

Molecular docking studies of phytochemicals from Phyllanthus niruri against Hepatitis B DNA Polymerase.

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.

Computer aided gene mining for gingerol biosynthesis.

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/.

DIACAN: Integrated Database for Antidiabetic and Anticancer Medicinal Plants.

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.