• Bulletin of the Korean Chemical Society
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• 제33권7호
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• pp.2365-2368
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• 2012

The $11{\beta}$-hydroxysteroid dehydrogenase type 1 ($11{\beta}$-HSD1) enzyme is involved in modulation of glucocorticoid activity within target tissues. This enzyme may contribute to obesity and/or metabolic disease through its action in adipose or liver tissue. Inhibition of $11{\beta}$-HSD1 has major therapeutic potential for glucocorticoid-associated diseases, including obesity, diabetes (wound healing), and muscle atrophy. To develop such therapeutics, we performed a pharmacophore-based virtual screening (VS) for identification of novel $11{\beta}$-HSD1 inhibitors and found that the VS hit compounds show potent inhibition of $11{\beta}$-HSD1 enzyme activity. Further, we present a binding model for active compounds. The proposed pharmacophore may serve as a useful guideline for future design of new chemical entities as $11{\beta}$-HSD1-targeted antidiabetic agents.

• Journal of Microbiology and Biotechnology
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• 제32권6호
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• pp.718-729
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• 2022

Esophageal squamous cell carcinoma (ESCC) is the most common primary esophageal malignancy with poor prognosis. Here, due to the necessity for exploring potential therapies against ESCC, we obtained the gene expression data on ESCC from the TCGA and GEO databases. Venn diagram analysis was applied to identify common targets. The protein-protein interaction network was constructed by Cytoscape software, and the hub targets were extracted from the network via cytoHubba. The potential hub nodes as drug targets were found by pharmacophore-based virtual screening and molecular modeling, and the antitumor activity was evaluated through in vitro studies. A total of 364 differentially expressed genes (DEGs) in ESCC were identified. Pathway enrichment analyses suggested that most DEGs were mainly involved in the cell cycle. Three hub targets were retrieved, including CENPF, CCNA2 (cyclin A), and CCNB1 (cyclin B1), which were highly expressed in esophageal cancer and associated with prognosis. Moreover, amentoflavone, a promising drug candidate found by pharmacophore-based virtual screening, showed antiproliferative and proapoptotic effects and induced G1 in esophageal squamous carcinoma cells. Taken together, our findings suggested that amentoflavone could be a potential cell cycle inhibitor targeting cyclin B1, and is therefore expected to serve as a great therapeutic agent for treating esophageal squamous cell carcinoma.

• Genomics & Informatics
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• 제15권4호
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• pp.147-155
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• 2017

Apurinic/apyrimidinic endonuclease 1 (APE1) is an enzyme responsible for the initial step in the base excision repair pathway and is known to be a potential drug target for treating cancers, because its expression is associated with resistance to DNA-damaging anticancer agents. Although several inhibitors already have been identified, the identification of novel kinds of potential inhibitors of APE1 could provide a seed for the development of improved anticancer drugs. For this purpose, we first classified known inhibitors of APE1. According to the classification, we constructed two distinct pharmacophore models. We screened more than 3 million lead-like compounds using the pharmacophores. Hits that fulfilled the features of the pharmacophore models were identified. In addition to the pharmacophore screen, we carried out molecular docking to prioritize hits. Based on these processes, we ultimately identified 1,338 potential inhibitors of APE1 with predicted binding affinities to the enzyme.

• Bulletin of the Korean Chemical Society
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• 제33권3호
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• pp.869-880
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• 2012

Identification of the selective chemical features for Aurora-B inhibitors gained much attraction in drug discovery for the treatment of cancer. Hence to identify the Aurora-B critical features various techniques were utilized such as pharmacophore generation, virtual screening, homology modeling, molecular dynamics, and docking. Top ten hypotheses were generated for Aurora-B and Aurora-A. Among ten hypotheses, HypoB1 and HypoA1 were selected as a best hypothesis for Aurora-B and Aurora-A based on cluster analysis and ranking score, respectively. Test set result revealed that ring aromatic (RA) group in HypoB1 plays an essential role in differentiates Aurora-B from Aurora-A inhibitors. Hence, HypoB1 used as 3D query in virtual screening of databases and the hits were sorted out by applying drug-like properties and molecular docking. The molecular docking result revealed that 15 hits have shown strong hydrogen bond interactions with Ala157, Glu155, and Lys106. Hence, we proposed that HypoB1 might be a reasonable hypothesis to retrieve the structurally diverse and selective leads from various databases to inhibit Aurora-B.

• Bulletin of the Korean Chemical Society
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• 제35권7호
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• pp.2097-2108
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• 2014

Chemical feature based quantitative pharmacophore models were generated using the HypoGen module implemented in DS2.5. The best hypothesis, Hypo1, which was characterized by the highest correlation coefficient (0.96), the highest cost difference (61.60) and the lowest RMSD (0.74), consisted of one hydrogen bond acceptor, one hydrogen bond donor, one hydrophobic and one ring aromatic. The reliability of Hypo1 was validated on the basis of cost analysis, test set, Fischer's randomization method and GH test method. The validated Hypo1 was used as a 3D search query to identify novel inhibitors. The screened molecules were further refined by employing ADMET, docking studies and visual inspection. Three compounds with novel scaffolds were selected as the most promising candidates for the designing of Mcl-1 antagonists. Finally, a 10 ns molecular dynamics simulation was carried out on the complex of receptor and the retrieved ligand to demonstrate that the binding mode was stable during the MD simulation.

• The Plant Pathology Journal
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• 제33권6호
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• pp.529-542
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• 2017

Control of plant diseases is largely dependent on use of agrochemicals. However, there are widening gaps between our knowledge on plant diseases gained from genetic/mechanistic studies and rapid translation of the knowledge into target-oriented development of effective agrochemicals. Here we propose that the time is ripe for computer-aided drug discovery/design (CADD) in molecular plant pathology. CADD has played a pivotal role in development of medically important molecules over the last three decades. Now, explosive increase in information on genome sequences and three dimensional structures of biological molecules, in combination with advances in computational and informational technologies, opens up exciting possibilities for application of CADD in discovery and development of agrochemicals. In this review, we outline two categories of the drug discovery strategies: structure- and ligand-based CADD, and relevant computational approaches that are being employed in modern drug discovery. In order to help readers to dive into CADD, we explain concepts of homology modelling, molecular docking, virtual screening, and de novo ligand design in structure-based CADD, and pharmacophore modelling, ligand-based virtual screening, quantitative structure activity relationship modelling and de novo ligand design for ligand-based CADD. We also provide the important resources available to carry out CADD. Finally, we present a case study showing how CADD approach can be implemented in reality for identification of potent chemical compounds against the important plant pathogens, Pseudomonas syringae and Colletotrichum gloeosporioides.

• Journal of Microbiology and Biotechnology
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• 제32권10호
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• pp.1262-1274
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• 2022

Cholangiocarcinoma (CCA) is a complex and refractor type of cancer with global prevalence. Several barriers remain in CCA diagnosis, treatment, and prognosis. Therefore, exploring more biomarkers and therapeutic drugs for CCA management is necessary. CCA gene expression data was downloaded from the TCGA and GEO databases. KEGG enrichment, GO analysis, and protein-protein interaction network were used for hub gene identification. miRNA were predicted using Targetscan and validated according to several GEO databases. The relative RNA and miRNA expression levels and prognostic information were obtained from the GEPIA. The candidate drug was screened using pharmacophore-based virtual screening and validated by molecular modeling and through several in vitro studies. 301 differentially expressed genes (DEGs) were screened out. Complement and coagulation cascades-related genes (including AHSG, F2, TTR, and KNG1), and cell cycle-related genes (including CDK1, CCNB1, and KIAA0101) were considered as the hub genes in CCA progression. AHSG, F2, TTR, and KNG1 were found to be significantly decreased and the eight predicted miRNA targeting AHSG, F2, and TTR were increased in CCA patients. CDK1, CCNB1, and KIAA0101 were found to be significantly abundant in CCA patients. In addition, Molport-003-703-800, which is a compound that is derived from pharmacophores-based virtual screening, could directly bind to CDK1 and exhibited anti-tumor activity in cholangiocarcinoma cells. AHSG, F2, TTR, and KNG1 could be novel biomarkers for CCA. Molport-003-703-800 targets CDK1 and work as potential cell cycle inhibitors, thereby having potential for consideration for new chemotherapeutics for CCA.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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• pp.139-143
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• 2005

Cytochrome P450 14${\alpha}$-sterol demethylase enzyme (CYP51) is the target a of azole type antifungals. The azole blocks the ergosterol synthesis and thereby inhibits fungal growth. A three-dimensional (3D) homology model of CYP51 from Candida albicans was constructed based on the X-ray crystal structure of CYP51 from Mycobacterium tuberculosis. Using this model, the binding modes for the substrate (24-methylene-24, 25-dihydrolanosterol) and the known inhibitors (fluconazole, voriconazole, oxiconazole, miconazole) were predicted from docking. Virtual screening was performed employing Structure Based Focusing (SBF). In this procedure, the pharmacophore models for database search were generated from the protein-ligands interactions each other. The initial structure-based virtual screening selected 15 compounds from a commercial available 3D database of approximately 50,000 molecule library, Being evaluated by a cell-based assay, 5 compounds were further identified as the potent inhibitors of Candida albicans CYP51 (CACYP51) with low minimal inhibitory concentration (MIC) range. BMD-09-01${\sim}$BMD-09-04 MIC range was 0.5 ${\mu}$g/ml and BMD-09-05 was 1 ${\mu}$g/ml. These new inhibitors provide a basis for some non-azole antifungal rational design of new, and more efficacious antifungal agents.

• Bulletin of the Korean Chemical Society
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• 제33권5호
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• pp.1707-1714
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• 2012

Grb2 is an adapter protein involved in the signal transduction and cell communication. The Grb2 is responsible for initiation of kinase signaling by Ras activation which leads to the modification in transcription. Ligand based pharmacophore approach was applied to built the suitable pharmacophore model for Grb2. The best pharmacophore model was selected based on the statistical values and then validated by Fischer's randomization method and test set. Hypo1 was selected as a best pharmacophore model based on its statistical values like high cost difference (182.22), lowest RMSD (1.273), and total cost (80.68). It contains four chemical features, one hydrogen bond acceptor (HBA), two hydrophobic (HY), and one ring aromatic (RA). Fischer's randomization results also shows that Hypo1 have a 95% significant level. The correlation coefficient of test set was 0.97 which was close to the training set value (0.94). Thus Hypo1 was used for virtual screening to find the potent inhibitors from various chemical databases. The screened compounds were filtered by Lipinski's rule of five, ADMET and subjected to molecular docking studies. Totally, 11 compounds were selected as a best potent leads from docking studies based on the consensus scoring function and critical interactions with the amino acids in Grb2 active site.

• Bulletin of the Korean Chemical Society
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• 제32권1호
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• pp.201-207
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• 2011

Peroxisome proliferator-activated receptors (PPARs) are members of nuclear receptors and their activation induces regulation of fatty acid storage and glucose metabolism. Therefore, the $PPAR\gamma$ is a major target for the treatment of type 2 diabetes mellitus. In order to generate pharmacophore model, 1080 known agonists database was constructed and a training set was selected. The Hypo7, selected from 10 hypotheses, contains four features: three hydrogen-bond acceptors (HBA) and one general hydrophobic (HY). This pharmacophore model was validated by using 862 test set compounds with a correlation coefficient of 0.903 between actual and estimated activity. Secondly, CatScramble method was used to verify the model. Hence, the validated Hypo7 was utilized for searching new lead compounds over 238,819 and 54,620 chemical structures in NCI and Maybridge database, respectively. Then the leads were selected by screening based on the pharmacophore model, predictive activity, and Lipinski's rules. Candidates were obtained and subsequently the binding affinities to $PPAR\gamma$ were investigated by the molecular docking simulations. Finally the best two compounds were presented and would be useful to treat type 2 diabetes.