• Journal of Plant Biotechnology
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• v.45 no.1
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• pp.71-76
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• 2018

The Arabidopsis SHL1 (${\underline{Sh}}ort$ ${\underline{L}}ife$ 1) gene encodes a small nuclear protein that is critical for the proper expression of the developmental programs that are responsible for controlling plant stature, senescence, flowering and seed formation. The SHL1 contains a single PHD finger domain that works in conjunction with a bromo-adjacent homology (BAH) motif that is thought to function significantly in protein-protein interactions. The TCH4 gene of the Arabidopsis encodes a xylogluclan endotransglucosylase/hydrolase that is transcriptionally regulated by a variety of hormonal and environmental stimuli. We report here in this study that the SHL1 exhibits sequence specific DNA binding properties, recognizing a 14 bp region of the TCH4 promoter in vitro, spanning nucleotides -262 to -275 (GGAAAAAACTCCCA). Chiefly, the nuclear extracts of Arabidopsis contain a protein with similar binding properties as recombinant SHL1, which is absent in identified transgenic plants that are noted as expressing antisense SHL1 RNA. Interestingly, the SHL1 gene expression with a BL treatment in characteristically wild types of seedlings showed that the transcript level of SHL1 is significantly down regulated by the BL treatment. The SHL1 may play a subtle role in regulating the kinetics of induction of the TCH4 in response to several stimuli in vivo.

• Interdisciplinary Bio Central
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• v.3 no.2
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• pp.8.1-8.6
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• 2011

Background: Thanks to the development of the mathematical/statistical reverse engineering and the high-throughput measuring biotechnology, lots of biologically meaningful genegene interaction networks have been revealed. Steady-state analysis of these systems provides an important clue to understand and to predict the systematic behaviours of the biological system. However, modeling such a complex and large-scale system is one of the challenging difficulties in systems biology. Results: We introduce a new stochastic modeling approach that can describe gene regulatory mechanisms by dividing two (DNA and protein) layers. Simple queuing system is employed to explain the DNA layer and the protein layer is modeled using G-networks which enable us to account for the post-translational protein interactions. Our method is applied to a transcription repression system and an active protein degradation system. The steady-state results suggest that the active protein degradation system is more sensitive but the transcription repression system might be more reliable than the transcription repression system. Conclusions: Our two layer stochastic model successfully describes the long-run behaviour of gene regulatory networks which consist of various mRNA/protein processes. The analytic solution of the G-networks enables us to extend our model to a large-scale system. A more reliable modeling approach could be achieved by cooperating with a real experimental study in synthetic biology.

• Transactions of the Society of Information Storage Systems
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• v.9 no.1
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• pp.28-31
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• 2013

We proposed a method to fabricate label-free protein sensor with sub-wavelength nanograting structures to be used for diagnosing acute myocardial infarction. A nickel stamp for the injection molding of nanograting integrated protein sensor was fabricated by electroforming process with high fidelity. By using metallic stamp, we replicated label-free protein sensor via injection molding, which is an outstanding method for low-cost and mass production of polymer products. Finally, we performed a feasibility test, examining cardiac troponin T (cTnT) and anti-cTnT interactions. From the results, we demonstrated that the fabricated protein sensor can provide information for the early and accurate detection of cardiac diseases such as acute myocardial infarction.

• Journal of Microbiology and Biotechnology
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• v.32 no.9
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• pp.1209-1216
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• 2022

To better understand the effects of PEGylation and biotinylation on the delivery efficiency of proteins, the cationic protein lysozyme (LZ) and anionic protein bovine serum albumin (BSA) were chemically conjugated with poly(ethylene glycol) (PEG) and biotin-PEG to primary amine groups of proteins using N-hydroxysuccinimide reactions. Four types of protein conjugates were successfully prepared: PEGylated LZ (PEG-LZ), PEGylated BSA (PEG-BSA), biotin-PEG-conjugated LZ (Bio-PEG-LZ), and biotin-PEG-conjugated BSA (Bio-PEG-BSA). PEG-LZ and Bio-PEG-LZ exhibited a lower intracellular uptake than that of LZ in A549 human lung cancer cells (in a two-dimensional culture). However, Bio-PEG-BSA showed significantly improved intracellular delivery as compared to that of PEG-BSA and BSA, probably because of favorable interactions with cells via biotin receptors. For A549/fibroblast coculture spheroids, PEG-LZ and PEG-BSA exhibited significantly decreased tissue penetration as compared with that of unmodified proteins. However, Bio-PEG-BSA showed tissue penetration comparable to that of unmodified BSA. In addition, citraconlyated LZ (Cit-LZ) showed reduced spheroid penetration as compared to that of LZ, probably owing to a decrease in protein charge. Taken together, chemical conjugation of targeting ligands-PEG to anionic proteins could be a promising strategy to improve intracellular delivery and in vivo activity, whereas modifications of cationic proteins should be more delicately designed.

• Food Science of Animal Resources
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• v.43 no.3
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• pp.540-551
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• 2023

Milk protein concentrate (MPC) is widely used to enhance the stability and texture of fermented dairy products. However, most research has focused on yogurt products, and the effects of MPC on sour cream characteristics remain unknown. Therefore, we investigated the effects of different MPC levels (0%, 1%, 2%, and 3% w/w) on the rheological, physicochemical, microbiological, and aroma characteristics of sour creams in this study. We found that MPC supplementation stimulated the growth of lactic acid bacteria (LAB) in sour creams, resulting in higher acidity than that in the control sample due to the lactic acid produced by LAB. Three aroma compounds, acetaldehyde, diacetyl, and acetoin, were detected in all sour cream samples. All sour creams showed shear-thinning behavior (n=0.41-0.50), and the addition of MPC led to an increase in the rheological parameters (η_a,50, K, G', and G"). In particular, sour cream with 3% MPC showed the best elastic property owing to the interaction between denatured whey protein and caseins. In addition, these protein interactions resulted in the formation of a gel network, which enhanced the water-holding capacity and improved the whey separation. These findings revealed that MPC can be used as a supplementary protein to improve the rheological and physicochemical characteristics of sour cream.

• Journal of Life Science
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• v.22 no.12
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• pp.1608-1613
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• 2012

A conventional kinesin, KIF5/Kinesin-I, transports various cargoes along the microtubule through interaction between its light chain subunit and the cargoes. Kinesin light chains (KLCs) interact with many different cargoes using their tetratricopeptide repeat (TPR) domain, but the mechanism underlying recognition and binding of a specific cargo has not yet been completely elucidated. We used the yeast two-hybrid assay to identify proteins that interact with the TPR domain of KLC1. We found an interaction between the TPR domain of KLC1 and an amyloid precursor protein (APP)-binding protein PAT1 (protein interacting with APP tail 1). The yeast two-hybrid assay demonstrated that the TPR domain-containing region of KLC1 mediated binding to the C-terminal tail region of PAT1. PAT1 also bound to KLC2 but not to kinesin heavy chains (KIF5A, KIF5B, and KIF5C) in the yeast two-hybrid assay. These protein-protein interactions were also observed in the glutathione S-transferase (GST) pull-down assay and by co-immunoprecipitation. Anti-PAT1 antibody as well as anti-APP anti-body co-immunoprecipitated KLC and KHCs associated with PAT1 from mouse brain extracts. These results suggest that PAT1 could mediate interactions between Kinesin-I and APP containing vesicles.

• Biotechnology and Bioprocess Engineering:BBE
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• v.11 no.5
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• pp.455-461
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• 2006

In this study, we have described a method for the fabrication of a protein chip on silicon substrate using hydrophobic thin film and microfluidic channels, for the simultaneous detection of multiple targets in samples. The use of hydrophobic thin film provides for a physical, chemical, and biological barrier for protein patterning. The microfluidic channels create four protein patterned strips on the silicon surfaces with a high signal-to-noise ratio. The feasibility of the protein chips was determined in order to discriminate between each protein interaction in a mixture sample that included biotin, ovalbumin, hepatitis B antigen, and hepatitis C antigen. In the fabrication of the multiplexed assay system, the utilization of the hydrophobic thin film and the microfluidic networks constitutes a more convenient method for the development of biosensors or biochips. This technique may be applicable to the simultaneous evaluation of multiple protein-protein interactions.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.5
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• pp.267-281
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• 2006

PPI(Protein-Protein Interaction) data has information about the organism has maintained a life with some kind of mechanism. So, it is used in study about cure research back, cause of disease, and new medicine development. This PPI data has been increased by geometric progression because high throughput methods are developed such as Yeast-two-hybrid, Mass spectrometry, and Correlated mRNA expression. So, it is impossible that a person directly manage and analyze PPI data. Fortunately, PPI data is able to abstract the graph which has proteins as nodes, interactions as edges. Consequently, Graph theory plentifully researched from the computer science until now is able to be applied to PPI data successfully. In this paper, we introduce Proteinca(PROTEin INteraction CAbaret) workbench system for easily managing, analyzing and visualizing PPI data. Proteinca assists the user understand PPI data intuitively as visualizing a PPI data in graph and provide various analytical function on graph theory. And Protenica provides a simplified visualization with gravity-rule.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1003-1008
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• 2016

Breast cancer is now the leading cause of cancer death in women worldwide. Cancer progression is driven not only by cancer cell intrinsic alterations and interactions with tumor microenvironment, but also by systemic effects. Integration of multiple profiling data may provide insights into the underlying molecular mechanisms of complex systemic processes. We performed a bioinformatic analysis of two public available microarray datasets for breast tumor stroma and peripheral blood mononuclear cells, featuring integrated transcriptomics data, protein-protein interactions (PPIs) and protein subcellular localization, to identify genes and biological pathways that contribute to dialogue between tumor stroma and the peripheral circulation. Genes of the integrin family as well as CXCR4 proved to be hub nodes of the crosstalk network and may play an important role in response to stroma-derived chemoattractants. This study pointed to potential for development of therapeutic strategies that target systemic signals travelling through the circulation and interdict tumor cell recruitment.

• Genomics & Informatics
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• v.12 no.2
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• pp.64-70
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• 2014

Human papillomavirus (HPV) infection is the leading cause of cancer mortality among women worldwide. The life-threatening infection caused by HPV demands the need for designing anticancerous drugs. In the recent years, different compounds from natural origins, such as carrageenan, curcumin, epigallocatechin gallate, indole-3-carbinol, jaceosidin, and withaferin, have been used as a hopeful source of anticancer therapy. These compounds have been shown to suppress HPV infection by different researchers. In the present study, we explored these natural inhibitors against E6 oncoprotein of high-risk HPV-16, which is known to inactivate the p53 tumor suppressor protein. A robust homology model of HPV-16 E6 was built to anticipate the interaction mechanism of E6 oncoprotein with natural inhibitory molecules using a structure-based drug designing approach. Docking analysis showed the interaction of these natural compounds with the p53-binding site of E6 protein residues 113-122 (CQKPLCPEEK) and helped the restoration of p53 functioning. Docking analysis, besides helping in silico validation of natural compounds, also helps understand molecular mechanisms of protein-ligand interactions.