• Korean Journal of Cognitive Science
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• v.28 no.4
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• pp.299-314
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• 2017

Predicting compound-protein interactions in-silico is significant for the drug discovery. In this paper, we propose an scalable machine learning model to predict compound-protein interaction. The key idea of this scalable machine learning model is the architecture of pairwise neural network model and feature embedding method from the raw data, especially for protein. This method automatically extracts the features without additional knowledge of compound and protein. Also, the pairwise architecture elevate the expressiveness and compact dimension of feature by preventing biased learning from occurring due to the dimension and type of features. Through the 5-fold cross validation results on large scale database show that pairwise neural network improves the performance of predicting compound-protein interaction compared to previous prediction models.

• Genomics & Informatics
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• v.15 no.4
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• pp.142-146
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• 2017

More effective production of human insulin is important, because insulin is the main medication that is used to treat multiple types of diabetes and because many people are suffering from diabetes. The current system of insulin production is based on recombinant DNA technology, and the expression vector is composed of a preproinsulin sequence that is a fused form of an artificial leader peptide and the native proinsulin. It has been reported that the sequence of the leader peptide affects the production of insulin. To analyze how the leader peptide affects the maturation of insulin structurally, we adapted several in silico simulations using 13 artificial proinsulin sequences. Three-dimensional structures of models were predicted and compared. Although their sequences had few differences, the predicted structures were somewhat different. The structures were refined by molecular dynamics simulation, and the energy of each model was estimated. Then, protein-protein docking between the models and trypsin was carried out to compare how efficiently the protease could access the cleavage sites of the proinsulin models. The results showed some concordance with experimental results that have been reported; so, we expect our analysis will be used to predict the optimized sequence of artificial proinsulin for more effective production.

• Genomics & Informatics
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• v.20 no.4
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• pp.45.1-45.7
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• 2022

Food security will be affected by climate change worldwide, particularly in the developing world, where the most important food products originate from plants. Plants are often exposed to environmental stresses that may affect their growth, development, yield, and food quality. Auxin is a hormone that plays a critical role in improving plants' tolerance of environmental conditions. Auxin controls the expression of many stress-responsive genes in plants by interacting with specific cis-regulatory elements called auxin-responsive elements (AuxREs). In this work, we performed an in silico prediction of AuxREs in promoters of five auxin-responsive genes in Zea mays. We applied a data fusion approach based on the combined use of Dempster-Shafer evidence theory and fuzzy sets. Auxin has a direct impact on cell membrane proteins. The short-term auxin response may be represented by the regulation of transmembrane gene expression. The detection of an AuxRE in the promoter of prolyl oligopeptidase (POP) in Z. mays and the 3-fold overexpression of this gene under auxin treatment for 30 min indicated the role of POP in maize auxin response. POP is regulated by auxin to perform stress adaptation. In addition, the detection of two AuxRE TGTCTC motifs in the upstream sequence of the bx1 gene suggests that bx1 can be regulated by auxin. Auxin may also be involved in the regulation of dehydration-responsive element-binding and some members of the protein kinase superfamily.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.10
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• pp.5973-5981
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• 2013

At present, the most common cause of cancer-related death in women is breast cancer. In a large proportion of breast cancers, there is the overexpression of human epidermal growth factor receptor 2 (HER2). This receptor is a 185 KDa growth factor glycoprotein, also known as the first tumor-associated antigen for different types of breast cancers. Moreover, HER2 is an appropriate cell-surface specific antigen for passive immunotherapy, which relies on the repeated application of monoclonal antibodies that are transferred to the patient. However, vaccination is preferable because it would stimulate a patient's own immune system to actively respond to a disease. In the current study, several bioinformatics tools were used for designing synthetic peptide vaccines. PEPOP was used to predict peptides from HER2 ECD subdomain III in the form of discontinuous-continuous B-cell epitopes. Then, T-cell epitope prediction web servers MHCPred, SYFPEITHI, HLA peptide motif search, Propred, and SVMHC were used to identify class-I and II MHC peptides. In this way, PEPOP selected 12 discontinuous peptides from the 3D structure of the HER2 ECD subdomain III. Furthermore, T-cell epitope prediction analyses identified four peptides containing the segments 77 (384-391) and 99 (495-503) for both B and T-cell epitopes. This work is the only study to our knowledge focusing on design of in silico potential novel cancer peptide vaccines of the HER2 ECD subdomain III that contain epitopes for both B and T-cells. These findings based on bioinformatics analyses may be used in vaccine design and cancer therapy; saving time and minimizing the number of tests needed to select the best possible epitopes.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.7
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• pp.3053-3059
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• 2012

Human epidermal growth factor receptor 2 (HER2) is a member of the epidermal growth factor receptor family of receptor tyrosine kinases that plays important roles in all processes of cell development. Their overexpression is related to many cancers, including examples in the breast, ovaries and stomach. Anticancer therapies targeting the HER2 receptor have shown promise, and monoclonal antibodies against subdomains II and IV of the HER2 extra-cellular domain (ECD), Pertuzumab and Herceptin, are currently used in treatments for some types of breast cancers. Since anti HER2 antibodies targeting distinct epitopes have different biological effects on cancer cells; in this research linear and conformational B cell epitopes of HER2 ECD, subdomain III, were identified by bioinformatics analyses using a combination of linear B cell epitope prediction web servers such as ABCpred, BCPREDs, Bepired, Bcepred and Elliprro. Then, Discotope, CBtope and SUPERFICIAL software tools were employed for conformational B cell epitope prediction. In contrast to previously reported epitopes of HER2 ECD we predicted conformational B cell epitopes $P1_C$: 378-393 (PESFDGDPASNTAPLQ) and $P2_C$: 500-510 (PEDECVGEGLA) by the integrated strategy and P4: PESFDGD-X-TAPLQ; P5: PESFDGDP X TAPLQ; P6: ESFDGDP X NTAPLQP; P7: PESFDGDP-X-NTAPLQ; P8: ESFDG-XX-TAPLQPEQL and P9: ESFDGDP-X-NTAPLQP by SUPERFICIAL software. These epitopes could be further used as peptide antigens to actively immune mice for development of new monoclonal antibodies and peptide cancer vaccines that target different epitopes or structural domains of HER2 ECD.

• Genomics & Informatics
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• v.15 no.2
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• pp.69-80
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• 2017

In this study, cytolethal distending toxin (CDT) producer isolates genome were compared with genome of pathogenic and commensal Escherichia coli strains. Conserved genomic signatures among different types of CDT producer E. coli strains were assessed. It was shown that they could be used as biomarkers for research purposes and clinical diagnosis by polymerase chain reaction, or in vaccine development. cdt genes and several other genetic biomarkers were identified as signature sequences in CDT producer strains. The identified signatures include several individual phage proteins (holins, nucleases, and terminases, and transferases) and multiple members of different protein families (the lambda family, phage-integrase family, phage-tail tape protein family, putative membrane proteins, regulatory proteins, restriction-modification system proteins, tail fiber-assembly proteins, base plate-assembly proteins, and other prophage tail-related proteins). In this study, a sporadic phylogenic pattern was demonstrated in the CDT-producing strains. In conclusion, conserved signature proteins in a wide range of pathogenic bacterial strains can potentially be used in modern vaccine-design strategies.

• Current Research on Agriculture and Life Sciences
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• v.32 no.1
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• pp.43-52
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• 2014

Reactive oxygen and nitrogen species (ROS and RNS, respectively) are messengers that carry signals to alter the redox state in order to activate plant responses and other physiological processes, such as differentiation, aging, senescence, and pathogen defense. Quite a large number of genes are involved in this signaling and lead to oxidative stress in plants. Although the role of ROS/RNS during stress conditions is well documented, a comprehensive list of genes and comparative study of these genes has not yet been completed. Accordingly, the in silico identification of oxidative stress-related genes was performed for soybeans and Arabidopsis. These genes were also studied in relation to multiple domain prediction. The presence of domains like dehydogenase and ATPase suggests that these genes are involved in various metabolic processes, as well as the transportation of ions under optimal environmental conditions. In addition to a sequence analysis, a phylogenetic analysis was also performed to identify orthologous pairs among the soybean and Arabidopsis oxidative stress-related genes based on neighbor joining. This study was also conducted with the objective of further understanding the complex molecular signaling mechanism in plants under various stress conditions.

• Toxicological Research
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• v.33 no.3
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• pp.191-203
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• 2017

Human eyes and skin are frequently exposed to chemicals accidentally or on purpose due to their external location. Therefore, chemicals are required to undergo the evaluation of the ocular and dermal irritancy for their safe handling and use before release into the market. Draize rabbit eye and skin irritation test developed in 1944, has been a gold standard test which was enlisted as OECD TG 404 and OECD TG 405 but it has been criticized with respect to animal welfare due to invasive and cruel procedure. To replace it, diverse alternatives have been developed: (i) For Draize eye irritation test, organotypic assay, in vitro cytotoxicity-based method, in chemico tests, in silico prediction model, and 3D reconstructed human cornealike epithelium (RhCE); (ii) For Draize skin irritation test, in vitro cytotoxicity-based cell model, and 3D reconstructed human epidermis models (RhE). Of these, RhCE and RhE models are getting spotlight as a promising alternative with a wide applicability domain covering cosmetics and personal care products. In this review, we overviewed the current alternatives to Draize test with a focus on 3D human epithelium models to provide an insight into advancing and widening their utility.

• Molecules and Cells
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• v.26 no.3
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• pp.228-235
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• 2008

Thiol-dependent redox systems are involved in regulation of diverse biological processes, such as response to stress, signal transduction, and protein folding. The thiol-based redox control is provided by mechanistically similar, but structurally distinct families of enzymes known as thiol oxidoreductases. Many such enzymes have been characterized, but identities and functions of the entire sets of thiol oxidoreductases in organisms are not known. Extreme sequence and structural divergence makes identification of these proteins difficult. Thiol oxidoreductases contain a redox-active cysteine residue, or its functional analog selenocysteine, in their active sites. Here, we describe computational methods for in silico prediction of thiol oxidoreductases in nucleotide and protein sequence databases and identification of their redox-active cysteines. We discuss different functional categories of cysteine residues, describe methods for discrimination between catalytic and noncatalytic and between redox and non-redox cysteine residues and highlight unique properties of the redox-active cysteines based on evolutionary conservation, secondary and three-dimensional structures, and sporadic replacement of cysteines with catalytically superior selenocysteine residues.

• Clinical and Experimental Pediatrics
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• v.59 no.sup1
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• pp.103-106
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• 2016

Bartter syndrome (BS) is an inherited renal tubular disorder characterized by low or normal blood pressure, hypokalemic metabolic alkalosis, and hyperreninemic hyperaldosteronism. Type III BS is caused by loss-of-function mutations in CLCNKB encoding basolateral ClC-Kb. The clinical phenotype of patients with CLCNKB mutations has been known to be highly variable, and cases that are difficult to categorize as type III BS or other hereditary tubulopathies, such as Gitelman syndrome, have been rarely reported. We report a case of a 10-year-old Korean boy with atypical clinical findings caused by a novel CLCNKB mutation. The boy showed intermittent muscle cramps with laboratory findings of hypokalemia, severe hypomagnesemia, and nephrocalcinosis. These findings were not fully compatible with those observed in cases of BS or Gitelman syndrome. The CLCNKB mutation analysis revealed a heterozygous c.139G>A transition in exon 13 [p.Gly(GGG)465Glu(GAG)]. This change is not a known mutation; however, the clinical findings and in silico prediction results indicated that it is the underlying cause of his presentation.