• Asian Pacific Journal of Cancer Prevention
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• 제15권10호
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• pp.4301-4305
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• 2014

Tanshinone IIA is a pharmacologically active ingredient extracted from Danshen, a Chinese traditional medicine. Its molecular mechanisms are still unclear. The present study utilized computational approaches to uncover the potential targets of this compound. In this research, PharmMapper server was used as the inverse docking tool andnd the results were verified by Autodock vina in PyRx 0.8, and by DRAR-CPI, a server for drug repositioning via the chemical-protein interactome. Results showed that the retinoic acid receptor alpha ($RAR{\alpha}$), a target protein in acute promyelocytic leukemia (APL), was in the top rank, with a pharmacophore model matching well the molecular features of Tanshinone IIA. Moreover, molecular docking and drug repurposing results showed that the complex was also matched in terms of structure and chemical-protein interactions. These results indicated that $RAR{\alpha}$ may be a potential target of Tanshinone IIA for APL. The study can provide useful information for further biological and biochemical research on natural compounds.

• 셀메드
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• 제3권2호
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• pp.12.1-12.4
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• 2013

Identification of target protein is an important procedure in the course of drug discovery. Because of complexity, action mechanisms of herbal medicine are rather obscure, unlike small-molecular drugs. Inverse docking simulation is a reverse use of molecular docking involving multiple target searches for known chemical structure. This methodology can be applied in the field of target fishing and toxicity prediction for herbal compounds as well as known drug molecules. The aim of this review is to introduce a series of in silico works for predicting potential drug targets and side-effects based on inverse docking simulations.

• Biomolecules & Therapeutics
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• 제21권6호
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• pp.423-434
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• 2013

The adoption of oligonucleotide aptamer is well on the rise, serving an ever increasing demand for versatility in biomedical field. Through the SELEX (Systematic Evolution of Ligands by EXponential enrichment), aptamer that can bind to specific target with high affinity and specificity can be obtained. Aptamers are single-stranded nucleic acid molecules that can fold into complex three-dimensional structures, forming binding pockets and clefts for the specific recognition and tight binding of any given molecular target. Recently, aptamers have attracted much attention because they not only have all of the advantages of antibodies, but also have unique merits such as thermal stability, ease of synthesis, reversibility, and little immunogenicity. The advent of novel technologies is revolutionizing aptamer applications. Aptamers can be easily modified by various chemical reactions to introduce functional groups and/or nucleotide extensions. They can also be conjugated to therapeutic molecules such as drugs, drug containing carriers, toxins, or photosensitizers. Here, we discuss new SELEX strategies and stabilization methods as well as applications in drug delivery and molecular imaging.

• 통합자연과학논문집
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• 제5권4호
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• pp.216-219
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• 2012

Structure-based drug design possibly benefit from in silico methods that precisely predict the binding affinity of small molecules to target macromolecules. There are many limitations arise from the difficulty of predicting the binding affinity of a small molecule to a biological target with the current scoring functions. There is thus a strong interest in novel methodologies based on MD simulations that claim predictions of greater accuracy than current scoring functions, helpful for a regular use designed for drug discovery in the pharmaceutical industry. Herein, we report a short review on free energy calculations using MMPBSA method a useful method in structure based drug discovery.

• 셀메드
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• 제6권4호
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• pp.24.1-24.4
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• 2016

The emergence of influenza virus and antigenic drift are potential cause of world-wide pandemic. There are some commercially available drugs in the market to treat influenza. During past decade, however, critical resistances have been raised for biological targets. Because of structural complexity and flexibility of target proteins, applying a computational modeling tool is very beneficial for developing alternative anti-influenza drugs. In this review, we introduced molecular dynamics (MD) simulations approach to reflect full conformational flexibility of proteins during molecular modeling works. Case studies of MD works were summarized for the drug discovery and drug resistance mechanism of anti-influenza pharmaceuticals.

• Bulletin of the Korean Chemical Society
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• 제35권1호
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• pp.250-252
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• 2014

Lipoprotein-associated phospholipase A2 (Lp-$PLA_2$) is a crucial enzyme in atherosclerosis as a potential drug target. The most remarkable Lp-$PLA_2$ inhibitory drug is Darapladib. We determined the binding pose of Darapladib to Lp-$PLA_2$ through docking study. Darapladib formed two hydrogen bonding interactions with the side chain of Tyr160 and Gln352 and several pi-pi interactions with aromatic and aliphatic hydrophobic residues of Lp-$PLA_2$. It is known that the dietylpropan-amine moiety of Darapladib has influence on the improvement of its oral bioavailability and we supposed this in our docking results.

• 통합자연과학논문집
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• 제6권3호
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• pp.138-142
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• 2013

The HIV-1 envelope glycoprotein gp120 plays a vital role in the entry of the virus into the host cells. The crucial role of the glycoprotein suggests gp120 as potential drug target for the future antiviral therapies. Identification of the binding mode of small drug like compounds has been an important goal in drug design. In the current study we attempt to propose binding mode of indole derivatives in the binding pocket of gp120. These derivatives are reported to inhibit HIV-1 by acting as attachment inhibitors that bind to gp120 and prevent the gp120-CD4 interaction and thus inhibit the infectivity of HIV-1. To elucidate the molecular basis of the small molecules interactions to inhibit the glycoprotein function we employed the molecular docking simulation approach. This study provides insights to elucidate the binding pattern of indole-based gp120 inhibitors and may help in the rational design of novel HIV-1 inhibitors with improved potency.

• 유전체소식지
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• 제3권3호
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• pp.8-10
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• 2003

• Genomics & Informatics
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• 제18권4호
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• pp.43.1-43.13
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• 2020

The coronavirus disease 2019 is a contagious disease and had caused havoc throughout the world by creating widespread mortality and morbidity. The unavailability of vaccines and proper antiviral drugs encourages the researchers to identify potential antiviral drugs to be used against the virus. The presence of RNA binding domain in the nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could be a potential drug target, which serves multiple critical functions during the viral life cycle, especially the viral replication. Since vaccine development might take some time, the identification of a drug compound targeting viral replication might offer a solution for treatment. The study analyzed the phylogenetic relationship of N protein sequence divergence with other 49 coronavirus species and also identified the conserved regions according to protein families through conserved domain search. Good structural binding affinities of a few natural and/or synthetic phytocompounds or drugs against N protein were determined using the molecular docking approaches. The analyzed compounds presented the higher numbers of hydrogen bonds of selected chemicals supporting the drug-ability of these compounds. Among them, the established antiviral drug glycyrrhizic acid and the phytochemical theaflavin can be considered as possible drug compounds against target N protein of SARS-CoV-2 as they showed lower binding affinities. The findings of this study might lead to the development of a drug for the SARS-CoV-2 mediated disease and offer solution to treatment of SARS-CoV-2 infection.

• Molecules and Cells
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• 제42권3호
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• pp.237-244
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• 2019

Understanding the mechanisms of cancer drug resistance is a critical challenge in cancer therapy. For many cancer drugs, various resistance mechanisms have been identified such as target alteration, alternative signaling pathways, epithelial-mesenchymal transition, and epigenetic modulation. Resistance may arise via multiple mechanisms even for a single drug, making it necessary to investigate multiple independent models for comprehensive understanding and therapeutic application. In particular, we hypothesize that different resistance processes result in distinct gene expression changes. Here, we present a web-based database, CDRgator (Cancer Drug Resistance navigator) for comparative analysis of gene expression signatures of cancer drug resistance. Resistance signatures were extracted from two different types of datasets. First, resistance signatures were extracted from transcriptomic profiles of cancer cells or patient samples and their resistance-induced counterparts for >30 cancer drugs. Second, drug resistance group signatures were also extracted from two large-scale drug sensitivity datasets representing ~1,000 cancer cell lines. All the datasets are available for download, and are conveniently accessible based on drug class and cancer type, along with analytic features such as clustering analysis, multidimensional scaling, and pathway analysis. CDRgator allows meta-analysis of independent resistance models for more comprehensive understanding of drug-resistance mechanisms that is difficult to accomplish with individual datasets alone (database URL: http://cdrgator.ewha.ac.kr).