• Genomics & Informatics
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• v.14 no.3
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• pp.96-103
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• 2016

The influenza A (H1N1) virus, also known as swine flu is a leading cause of morbidity and mortality since 2009. There is a need to explore novel anti-viral drugs for overcoming the epidemics. Traditionally, different plant extracts of garlic, ginger, kalmegh, ajwain, green tea, turmeric, menthe, tulsi, etc. have been used as hopeful source of prevention and treatment of human influenza. The H1N1 virus contains an important glycoprotein, known as neuraminidase (NA) that is mainly responsible for initiation of viral infection and is essential for the life cycle of H1N1. It is responsible for sialic acid cleavage from glycans of the infected cell. We employed amino acid sequence of H1N1 NA to predict the tertiary structure using Phyre2 server and validated using ProCheck, ProSA, ProQ, and ERRAT server. Further, the modelled structure was docked with thirteen natural compounds of plant origin using AutoDock4.2. Most of the natural compounds showed effective inhibitory activity against H1N1 NA in binding condition. This study also highlights interaction of these natural inhibitors with amino residues of NA protein. Furthermore, among 13 natural compounds, theaflavin, found in green tea, was observed to inhibit H1N1 NA proteins strongly supported by lowest docking energy. Hence, it may be of interest to consider theaflavin for further in vitro and in vivo evaluation.

• Journal of Ginseng Research
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• v.36 no.4
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• pp.375-382
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• 2012

Ginsenoside Rp1 (G-Rp1) is a saponin derivate that provides anti-metastatic activities through inhibition of the NF-${\kappa}B$ pathway. In this study, we examined the effects of G-Rp1 on regulatory T cell (Treg) activation. After treatment of splenocytes with G-Rp1, Tregs exhibited upregulation of IL-10 expression, and along with dendritic cells (DCs), these Tregs showed increased cell number compared to other cell populations. The effect of G-Rp1 on Treg number was augmented in the presence of lipopolysaccharide (LPS), which mimics pathological changes that occur during inflammation. However, depletion of DCs prevented the increase in Treg number in the presence of G-Rp1 and/or LPS. In addition, G-Rp1 promoted the differentiation of the memory types of $CD4^+Foxp3^+CD62L^{low}$ Tregs rather than the generation of new Tregs. In vivo experiments also demonstrated that Tregs and DCs from mice that were fed G-Rp1 for 7 d and then injected with LPS exhibited increased activation compared with those from mice that were injected with LPS alone. Expression of TGF-${\beta}$ and CTLA4 in Tregs was increased, and upregulation of IL-2 and CD80/CD86 expression by DCs affected the suppressive function of Tregs through IL-2 receptors and CTLA4. These data demonstrate that G-Rp1 exerts anti-inflammatory effects by activating Tregs in vitro and in vivo.

• Genomics & Informatics
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• v.14 no.2
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• pp.53-61
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• 2016

Toxoplasma gondii is an intracellular Apicomplexan parasite and a causative agent of toxoplasmosis in human. It causes encephalitis, uveitis, chorioretinitis, and congenital infection. T. gondii invades the host cell by forming a moving junction (MJ) complex. This complex formation is initiated by intermolecular interactions between the two secretory parasitic proteins-namely, apical membrane antigen 1 (AMA1) and rhoptry neck protein 2 (RON2) and is critically essential for the host invasion process. By this study, we propose two potential leads, NSC95522 and NSC179676 that can efficiently target the AMA1 hydrophobic cleft, which is a hotspot for targeting MJ complex formation. The proposed leads are the result of an exhaustive conformational search-based virtual screen with multilevel precision scoring of the docking affinities. These two compounds surpassed all the precision levels of docking and also the stringent post docking and cumulative molecular dynamics evaluations. Moreover, the backbone flexibility of hotspot residues in the hydrophobic cleft, which has been previously reported to be essential for accommodative binding of RON2 to AMA1, was also highly perturbed by these compounds. Furthermore, binding free energy calculations of these two compounds also revealed a significant affinity to AMA1. Machine learning approaches also predicted these two compounds to possess more relevant activities. Hence, these two leads, NSC95522 and NSC179676, may prove to be potential inhibitors targeting AMA1-RON2 complex formation towards combating toxoplasmosis.

• Analytical Science and Technology
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• v.28 no.4
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• pp.270-277
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• 2015

Boiling point (BP) is one of the most fundamental physicochemical properties of organic compounds to characterize and identify the thermal characteristics of target compounds. Previously developed QSPR equations, however, still had some limitation for the specific compounds, like high-energy molecules, mainly because of the lack of experimental data and less coverage. A large BP dataset of 5,923 solid organic compounds was finally secured in this study, after dedicated pre-filtration of experimental data from different sources, mostly consisting of compounds not only from common organic molecules but also from some specially used molecules, and those dataset was used to build the new BP prediction model. Various machine learning methods were performed for newly collected data based on meaningful 2D descriptor set. Results of combined check showed acceptable validity and robustness of our models, and consensus approaches of each model were also performed. Applicability domain of BP prediction model was shown based on descriptor of training set.

• Genomics & Informatics
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• v.19 no.2
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• pp.17.1-17.13
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• 2021

Breast cancer is one of the leading causes of cancer in women all over the world and accounts for ~25% of newly observed cancers in women. Epigenetic modifications influence differential expression of genes through non-coding RNA and play a crucial role in cancer regulation. In the present study, epigenetic regulation of gene expression by in-silico analysis of histone modifications using chromatin immunoprecipitation sequencing (ChIP-Seq) has been carried out. Histone modification data of H3K4me3 from one normal-like and four breast cancer cell lines were used to predict miRNA expression at the promoter level. Predicted miRNA promoters (based on ChIP-Seq) were used as a probe to identify gene targets. Five triple-negative breast cancer (TNBC)-specific miRNAs (miR153-1, miR4767, miR4487, miR6720, and miR-LET7I) were identified and corresponding 13 gene targets were predicted. Eight miRNA promoter peaks were predicted to be differentially expressed in at least three breast cancer cell lines (miR4512, miR6791, miR330, miR3180-3, miR6080, miR5787, miR6733, and miR3613). A total of 44 gene targets were identified based on the 3'-untranslated regions of downregulated mRNA genes that contain putative binding targets to these eight miRNAs. These include 17 and 15 genes in luminal-A type and TNBC respectively, that have been reported to be associated with breast cancer regulation. Of the remaining 12 genes, seven (A4GALT, C2ORF74, HRCT1, ZC4H2, ZNF512, ZNF655, and ZNF608) show similar relative expression profiles in large patient samples and other breast cancer cell lines thereby giving insight into predicted role of H3K4me3 mediated gene regulation via the miRNA-mRNA axis.

• The Plant Pathology Journal
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• v.40 no.1
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• pp.59-72
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• 2024

A comprehensive survey of mungbean-growing areas was conducted to observe leaf spot disease caused by Alternaria alternata. Alternaria leaf spot symptoms were observed on the leaves. Diversity of 50 genotypes of mungbean was assessed against A. alternata and data on pathological traits was subjected to cluster analysis. The results showed that genotypes of mungbean were grouped into four clusters based on resistance parameters under the influence of disease. The principal component biplot demonstrated that all the disease-related parameters (% disease incidence, % disease intensity, lesion area, and % of infection) were strongly correlated with each other. Alt a 1 gene that is precisely found in Alternaria species and is responsible for virulence and pathogenicity. Alt a 1 gene was amplified using gene specific primers. The isolated pathogen produced similar symptoms when inoculated on mungbean and tobacco. The sequence analysis of the internal transcribed spacer (ITS) region, a 600 bp fragment amplified using specific primers, ITS1 and ITS2 showed 100% identity with A. alternata. Potato virus X (PVX) -based silencing vector expressing Alt a 1 gene was constructed to control this pathogen through RNA interference in tobacco. Out of 50 inoculated plants, 9 showed delayed onset of disease. Furthermore, to confirm our findings at molecular level semi-quantitative reverse transcriptase polymerase chain reaction was used. Both phenotypic and molecular investigation indicated that RNAi induced through the VIGS vector was efficacious in resisting the pathogen in the model host, Tobacco (Nicotiana tabacum). To the best of our knowledge, this study has been reported for the first time.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.11
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• pp.1521-1525
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• 2014

This study investigated heritability for bovine growth estimated with genomewide single nucleotide polymorphism (SNP) information obtained from a DNA microarray chip. Three hundred sixty seven Korean cattle were genotyped with the Illumina BovineSNP50 BeadChip, and 39,112 SNPs of 364 animals filtered by quality assurance were analyzed to estimate heritability of body weights at 6, 9, 12, 15, 18, 21, and 24 months of age. Restricted maximum likelihood estimate of heritability was obtained using covariance structure of genomic relationships among animals in a mixed model framework. Heritability estimates ranged from 0.58 to 0.76 for body weights at different ages. The heritability estimates using genomic information in this study were larger than those which had been estimated previously using pedigree information. The results revealed a trend that the heritability for body weight increased at a younger age (6 months). This suggests an early genetic evaluation for bovine growth using genomic information to increase genetic merits of animals.

• Journal of Integrative Natural Science
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• v.8 no.1
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• pp.13-18
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• 2015

Cysteinyl leukotrienes are inflammatory mediators having important role in pathophysiological conditions such as asthma, allergic rhinitis and have been implicated in a number of inflammatory conditions including cardiovascular and gastrointestinal diseases. Most of the disease regulatory actions of the CysLTs are mediated through CysLT1 receptor. Hence in the present study, homology modeling of CysLT1 was performed because the availability of 3D structure would enhance the development of new drugs for inflammatory diseases. However the templates identified have low sequence identity which increases the complexity of modeling. Hence, homology modeling was performed using single template, multiple templates and also using threading I-TASSER server. The best model was selected based on the validation of the generated models using Ramachandran and ERRAT plot. The model developed could be useful for identifying crucial residues and docking study.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.1-5
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• 2008

Generally the analytical tools of data mining have two learning types which are supervised and unsupervised learning algorithms. Classification and prediction are main analysis tools for supervised learning. In this paper, we perform a comparison study of classification algorithms in data mining. We make comparative studies between popular classification algorithms which are LDA, QDA, kernel method, K-nearest neighbor, naive Bayesian, SVM, and CART. Also, we use almost all classification data sets of UCI machine learning repository for our experiments. According to our results, we are able to select proper algorithms for given classification data sets.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.263-266
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• 2005

We made a stepping stone for asthma study by analyzing an asthma-specific protein-protein interaction network. It follows the power-law degree distribution and its hub nodes and skeleton frame of the network agreed with the prior knowledge about asthma pathway. This study is providing a systematic approach to analyze the complex effect of genes or to represent the frame of their relations associated with specific disease.