• Journal of Biomedical Engineering Research
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• v.44 no.4
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• pp.275-283
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• 2023

The demand for skincare has increased due to the end of the COVID-19 pandemic, leading to a focus on skincare devices and technologies designed to improve the delivery of cosmetics. Among these technologies, skincare medical devices that utilize plasma therapy (Plasma) and sonophoresis (Sono) are commonly used in dermatology clinics. However, there is still a lack of quantitative analysis for transdermal absorption effects of Plasma and Sono skincare medical devices. In this study, we quantified enhanced transdermal absorption effects of Plasma and Sono devices through in-silico and ex-vivo studies. The Sono treatment demonstrated an increased transdermal absorption effect, showing a 10~13% difference in penetration compared to the control group in the in-silico experiment, and 159% and 184% increase in the ex-vivo experiment. The Plasma treatment revealed increased transdermal absorption effects, with a 1.0~2.5% penetration difference in the in-silico experiment, and a 124% increase in the ex-vivo experiment compared to the control group. We also observed a synergistic effect from the combined treatment of Plasma and Sono, as indicated by the highest increases of 197% and 242% in penetration. Furthermore, we have determined the optimal device settings and treatment conditions for Plasma-Sono skincare medical devices. Notably, higher on/off durations (Intensity levels) and longer Sono treatments resulted in greater transdermal absorption effects.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.7663-7670
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• 2015

DNA methyltransferase 1 (DNMT1) is a relatively large protein family responsible for maintenance of normal methylation, cell growth and survival in mammals. Toxic industrial chemical exposure associated methylation misregulation has been shown to have epigenetic influence. Such misregulation could effectively contribute to cancer development and progression. Methyl isocyanate (MIC) is a noxious industrial chemical used extensively in the production of carbamate pesticides. We here applied an in silico molecular docking approach to study the interaction of MIC with diverse domains of DNMT1, to predict cancer risk in the Bhopal population exposed to MIC during 1984. For the first time, we investigated the interaction of MIC and its hydrolytic product (1,3-dimethylurea) with DNMT1 interacting (such as DMAP1, RFTS, and CXXC) and catalytic (SAM, SAH, and Sinefungin) domains using computer simulations. The results of the present study showed a potential interaction of MIC and 1,3-dimethylurea with these domains. Obviously, strong binding of MIC with DNMT1 interrupting normal methylation will lead to epigenetic alterations in the exposed humans. We suggest therefore that the MIC-exposed individuals surviving after 1984 disaster have excess risk of cancer, which can be attributed to alterations in their epigenome. Our findings will help in better understanding the underlying epigenetic mechanisms in humans exposed to MIC.

• Bulletin of the Korean Chemical Society
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• v.32 no.4
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• pp.1237-1240
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• 2011

In this study, we have developed a ligand-based in-silico prediction model to classify chemical structures into hERG blockers using Bayesian and random forest modeling methods. These models were built based on patch clamp experimental results. The findings presented in this work indicate that Laplacian-modified naive Bayesian classification with diverse selection is useful for predicting hERG inhibitors when a large data set is not obtained.

• Genomics & Informatics
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• v.6 no.3
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• pp.153-156
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• 2008

Complex diseases such as stroke and cancer have two or more genetic loci and are affected by environmental factors that contribute to the diseases. Due to the complex characteristics of these diseases, identifying candidate genes requires a system-level analysis of the following: gene ontology, pathway, and interactions. A database and user interface, termed StrokeBase, was developed; StrokeBase provides queries that search for pathways, candidate genes, candidate SNPs, and gene networks. The database was developed by using in silico data mining of HGNC, ENSEMBL, STRING, RefSeq, UCSC, GO, HPRD, KEGG, GAD, and OMIM. Forty candidate genes that are associated with cerebrovascular disease were selected by human experts and public databases. The networked cerebrovascular disease gene maps also were developed; these maps describe genegene interactions and biological pathways. We identified 1127 genes, related indirectly to cerebrovascular disease but directly to the etiology of cerebrovascular disease. We found that a protein-protein interaction (PPI) network that was associated with cerebrovascular disease follows the power-law degree distribution that is evident in other biological networks. Not only was in silico data mining utilized, but also 250K Affymetrix SNP chips were utilized in the 320 control/disease association study to generate associated markers that were pertinent to the cerebrovascular disease as a genome-wide search. The associated genes and the genes that were retrieved from the in silico data mining system were compared and analyzed. We developed a well-curated cerebrovascular disease-associated gene network and provided bioinformatic resources to cerebrovascular disease researchers. This cerebrovascular disease network can be used as a frame of systematic genomic research, applicable to other complex diseases. Therefore, the ongoing database efficiently supports medical and genetic research in order to overcome cerebrovascular disease.

• Biomolecules & Therapeutics
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• v.32 no.3
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• pp.390-398
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• 2024

FoxO1, a member of the Forkhead transcription factor family subgroup O (FoxO), is expressed in a range of cell types and is crucial for various pathophysiological processes, such as apoptosis and inflammation. While FoxO1's roles in multiple diseases have been recognized, the target has remained largely unexplored due to the absence of cost-effective and efficient inhibitors. Therefore, there is a need for natural FoxO1 inhibitors with minimal adverse effects. In this study, docking, MMGBSA, and ADMET analyses were performed to identify natural compounds that exhibit strong binding affinity to FoxO1. The top candidates were then subjected to molecular dynamics (MD) simulations. A natural product library was screened for interaction with FoxO1 (PDB ID-3CO6) using the Glide module of the Schrödinger suite. In silico ADMET profiling was conducted using SwissADME and pkCSM web servers. Binding free energies of the selected compounds were assessed with the Prime-MMGBSA module, while the dynamics of the top hits were analyzed using the Desmond module of the Schrödinger suite. Several natural products demonstrated high docking scores with FoxO1, indicating their potential as FoxO1 inhibitors. Specifically, the docking scores of neochlorogenic acid and fraxin were both below -6.0. These compounds also exhibit favorable drug-like properties, and a 25 ns MD study revealed a stable interaction between fraxin and FoxO1. Our findings highlight the potential of various natural products, particularly fraxin, as effective FoxO1 inhibitors with strong binding affinity, dynamic stability, and suitable ADMET profiles.

• Journal of the Korean Chemical Society
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• v.68 no.3
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• pp.151-159
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• 2024

Indian spices are well known for their numerous health benefits, flavour, taste, and colour. Recent Advancements in chemical technology have led to better extraction and identification of bioactive molecules (phytochemicals) from spices. The therapeutic effects of spices against diabetes, cardiac problems, and various cancers has been well established. The present in silico study aims to investigate the binding affinity of 29 phytochemicals from 11 Indian spices with two prominent proteins, BCL3 and CXCL10 involved in invasiveness and bone metastasis of breast cancer. The three-dimensional structures of 29 phytochemicals were extracted from PubChem database. Protein Data Bank was used to retrieve the 3D structures of BCL3 and CXCL10 proteins. The drug-likeness and other properties of compounds were analysed by ADME and Lipinski rule of five (RO5). All computational simulations were carried out using Autodock 4.0 on Windows platform. The proteins were set to be rigid and compounds were kept free to rotate. In-silico study demonstrated a strong complex formation (positive binding constants and negative binding energy ΔG) between all phytochemicals and target proteins. However, piperine and sesamolin demonstrated high binding constants with BCL3 (50.681 × 10³ mol^-1, 137.76 × 10³ mol^-1) and CXCL10 (98.71 × 10³ mol^-1, 861.7 × 10³ mol^-1), respectively. The potential of these two phytochemicals as a drug candidate was highlighted by their binding energy of -6.5 kcal mol^-1, -7.1 kcal mol^-1 with BCL3 and -6.9 kcal mol^-1, -8.2 kcal mol^-1 with CXCL10, respectively coupled with their favourable drug likeliness and pharmacokinetics properties. These findings underscore the potential of piperine and sesamolin as drug candidates for inhibiting invasiveness and regulating breast cancer metastasis. However, further validation through in vitro and in vivo studies is necessary to confirm the in silico results and evaluate their clinical potential.

• Bulletin of the Korean Chemical Society
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• v.29 no.8
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• pp.1479-1484
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• 2008

Protein tyrosine phosphatase (PTP) 1B is the superfamily of PTPs and a negative regulator of multiple receptor tyrosine kinases (RTKs). Inhibition of protein tyrosine phosphatase 1B (PTP1B) has been proposed as a strategy for the treatment of type 2 diabetes and obesity. Recently, it has been reported that amentoflavone, a biflavonoid extracted from Selaginella tamariscina, inhibited PTP1B. In the present study, docking model between amentoflavone and PTP1B was determined using automated docking study. Based on this docking model and the interactions between the known inhibitors and PTP1B, we determined multiple pharmacophore maps which consisted of five features, two hydrogen bonding acceptors, two hydrogen bonding donors, and one lipophilic. Using receptor-oriented pharmacophore-based in silico screening, we searched the biflavonoid database including 40 naturally occurring biflavonoids. From these results, it can be proposed that two biflavonoids, sumaflavone and tetrahydroamentoflavone can be potent allosteric inhibitors, and the linkage at 5',8''-position of two flavones and a hydroxyl group at 4'-position are the critical factors for their allosteric inhibition. This study will be helpful to understand the mechanism of allosteric inhibition of PTP1B by biflavonoids and give insights to develop potent inhibitors of PTP1B.

• Journal of Life Science
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• v.12 no.5
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• pp.610-621
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• 2002

Conserved genes are importantly used to understand the major function in survival and replication of living organism. This study was focused on identification of conserved genes in microbial species and measuring the degree of conservation. For this purpose, in silico analysis was performed to search conserved genes based on the conservation level within microbial species. The ortholog list of COGs (Clusters of Orthologous Groups of proteins) in NCBI was used and whole genomes of 43 microbial species were included in that list. The distance value, derived from CLUSTALW multiple alignment program, was used as a descriptor of the conservation level of orthologs. It was revealed that 43 microbial genomes hold 72 conserved orthologs in common. The majority(72.2%) of the conserved genes was related to "translation, ribosomal structure and biogenesis" functional category. A GTPase-translation elogation factor(COG0050) was the best conserved gene from the distance value analysis. The 72 conserved genes, found in this research, would be useful not only to study minimal function genes but also new drug target among pathogens and to make a model of the virtual cell.tual cell.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.2
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• pp.170-178
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• 2005

An in silico approach was developed to survey the genes expressed in four internal organs of pig: liver, kidney, spleen and small intestine. The major procedures of the approach included: (1) BLAST searching against GenBank "est_others" database using human cDNA sequences as queries to screen the porcine orthologous expressed sequence tags (ESTs), (2) classifying the porcine ESTs records by resources according to certain criteria and (3) analyzing data for ESTs specifically expressed in each organ. In order to do so, four Java programs were developed. Based on the ESTs available in the GenBank database, it was found that there were at least 2,100 genes expressed in these four organs, including 128 in the liver, 81 in the kidney, 780 in the spleen, and 1,423 in the small intestine respectively (a few genes co-expressed in these tissues). Gene expression patterns, such as co-expressed genes, preferentially expressed genes and basic active genes were also compared and characterized among these organs. This study provides a comprehensive model on how to use the bioinformatics approach and Genbank databases to facilitate the discovery of new genes in livestock species.

• The Korean Journal of Physiology and Pharmacology
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• v.20 no.1
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• pp.111-117
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• 2016

Vagal nerve activity has been known to play a crucial role in the induction and maintenance of atrial fibrillation (AF). However, it is unclear how the distribution and concentration of local acetylcholine (ACh) promotes AF. In this study, we investigated the effect of the spatial distribution and concentration of ACh on fibrillation patterns in an in silico human atrial model. A human atrial action potential model with an ACh-dependent $K^+$ current ($I_{KAch}$) was used to examine the effect of vagal activation. A simulation of cardiac wave dynamics was performed in a realistic 3D model of the atrium. A model of the ganglionated plexus (GP) and nerve was developed based on the "octopus hypothesis". The pattern of cardiac wave dynamics was examined by applying vagal activation to the GP areas or randomly. AF inducibility in the octopus hypothesis-based GP and nerve model was tested. The effect of the ACh concentration level was also examined. In the single cell simulation, an increase in the ACh concentration shortened $APD_{90}$ and increased the maximal slope of the restitution curve. In the 3D simulation, a random distribution of vagal activation promoted wavebreaks while ACh secretion limited to the GP areas did not induce a noticeable change in wave dynamics. The octopus hypothesis-based model of the GP and nerve exhibited AF inducibility at higher ACh concentrations. In conclusion, a 3D in silico model of the GP and parasympathetic nerve based on the octopus model exhibited higher AF inducibility with higher ACh concentrations.